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All modules for which code is available

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+ + + \ No newline at end of file diff --git a/_modules/pathsimanalysis/psa.html b/_modules/pathsimanalysis/psa.html new file mode 100644 index 0000000..9f47eff --- /dev/null +++ b/_modules/pathsimanalysis/psa.html @@ -0,0 +1,2353 @@ + + + + + + + + + + + + + + + + + + + + + + pathsimanalysis.psa — PathSimAnalysis documentation + + + + + + + + + + + + + + + + +
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Source code for pathsimanalysis.psa

+# -*- Mode: python; tab-width: 4; indent-tabs-mode:nil; coding:utf-8 -*-
+# vim: tabstop=4 expandtab shiftwidth=4 softtabstop=4
+#
+# MDAnalysis --- https://www.mdanalysis.org
+# Copyright (c) 2006-2017 The MDAnalysis Development Team and contributors
+# (see the file AUTHORS for the full list of names)
+#
+# Released under the GNU Public Licence, v2 or any higher version
+#
+# Please cite your use of MDAnalysis in published work:
+#
+# R. J. Gowers, M. Linke, J. Barnoud, T. J. E. Reddy, M. N. Melo, S. L. Seyler,
+# D. L. Dotson, J. Domanski, S. Buchoux, I. M. Kenney, and O. Beckstein.
+# MDAnalysis: A Python package for the rapid analysis of molecular dynamics
+# simulations. In S. Benthall and S. Rostrup editors, Proceedings of the 15th
+# Python in Science Conference, pages 102-109, Austin, TX, 2016. SciPy.
+# doi: 10.25080/majora-629e541a-00e
+#
+# N. Michaud-Agrawal, E. J. Denning, T. B. Woolf, and O. Beckstein.
+# MDAnalysis: A Toolkit for the Analysis of Molecular Dynamics Simulations.
+# J. Comput. Chem. 32 (2011), 2319--2327, doi:10.1002/jcc.21787
+#
+
+r"""
+Calculating path similarity --- :mod:`pathsimanalysis.psa`
+==========================================================================
+
+.. versionadded:: 0.10.0
+
+The module contains code to calculate the geometric similarity of trajectories
+using path metrics such as the Hausdorff or Fréchet distances
+:footcite:p:`Seyler2015`. The path metrics are functions of two paths and return a
+nonnegative number, i.e., a distance. Two paths are identical if their distance
+is zero, and large distances indicate dissimilarity. Each path metric is a
+function of the individual points (e.g., coordinate snapshots) that comprise
+each path and, loosely speaking, identify the two points, one per path of a
+pair of paths, where the paths deviate the most.  The distance between these
+points of maximal deviation is measured by the root mean square deviation
+(RMSD), i.e., to compute structural similarity.
+
+One typically computes the pairwise similarity for an ensemble of paths to
+produce a symmetric distance matrix, which can be clustered to, at a glance,
+identify patterns in the trajectory data. To properly analyze a path ensemble,
+one must select a suitable reference structure to which all paths (each
+conformer in each path) will be universally aligned using the rotations
+determined by the best-fit rmsds. Distances between paths and their structures
+are then computed directly with no further alignment. This pre-processing step
+is necessary to preserve the metric properties of the Hausdorff and Fréchet
+metrics; using the best-fit rmsd on a pairwise basis does not generally
+preserve the triangle inequality.
+
+Note
+----
+The `PSAnalysisTutorial`_ outlines a typical application of PSA to
+a set of trajectories, including doing proper alignment,
+performing distance comparisons, and generating heat
+map-dendrogram plots from hierarchical clustering.
+
+.. _`PSAnalysisTutorial`: https://github.com/Becksteinlab/PSAnalysisTutorial
+
+
+Helper functions and variables
+------------------------------
+The following convenience functions are used by other functions in this module.
+
+.. autofunction:: sqnorm
+.. autofunction:: get_msd_matrix
+.. autofunction:: get_coord_axes
+
+
+Classes, methods, and functions
+-------------------------------
+
+.. autofunction:: get_path_metric_func
+.. autofunction:: hausdorff
+.. autofunction:: hausdorff_wavg
+.. autofunction:: hausdorff_avg
+.. autofunction:: hausdorff_neighbors
+.. autofunction:: discrete_frechet
+.. autofunction:: dist_mat_to_vec
+
+.. autoclass:: Path
+   :members:
+
+   .. attribute:: u_original
+
+      :class:`~MDAnalysis.Universe` object with a trajectory
+
+   .. attribute:: u_reference
+
+      :class:`~MDAnalysis.Universe` object containing a reference structure
+
+   .. attribute:: select
+
+      string, selection for
+      :meth:`~MDAnalysis.core.groups.AtomGroup.select_atoms` to select frame
+      from :attr:`Path.u_reference`
+
+   .. attribute:: path_select
+
+      string, selection for
+      :meth:`~MDAnalysis.core.groups.AtomGroup.select_atoms` to select atoms
+      to compose :attr:`Path.path`
+
+   .. attribute:: ref_frame
+
+      int, frame index to select frame from :attr:`Path.u_reference`
+
+   .. attribute:: u_fitted
+
+      :class:`~MDAnalysis.Universe` object with the fitted trajectory
+
+   .. attribute:: path
+
+      :class:`numpy.ndarray` object representation of the fitted trajectory
+
+.. autoclass:: PSAPair
+
+   .. attribute:: npaths
+
+      int, total number of paths in the comparison in which *this*
+      :class:`PSAPair` was generated
+
+   .. attribute:: matrix_id
+
+      (int, int), (row, column) indices of the location of *this*
+      :class:`PSAPair` in the corresponding pairwise distance matrix
+
+   .. attribute:: pair_id
+
+      int, ID of *this* :class:`PSAPair` (the pair_id:math:`^\text{th}`
+      comparison) in the distance vector corresponding to the pairwise distance
+      matrix
+
+   .. attribute:: nearest_neighbors
+
+      dict, contains the nearest neighbors by frame index and the
+      nearest neighbor distances for each path in *this* :class:`PSAPair`
+
+   .. attribute:: hausdorff_pair
+
+      dict, contains the frame indices of the Hausdorff pair for each path in
+      *this* :class:`PSAPair` and the corresponding (Hausdorff) distance
+
+.. autoclass:: PSAnalysis
+   :members:
+
+   .. attribute:: universes
+
+      list of :class:`MDAnalysis.Universe` objects containing trajectories
+
+   .. attribute:: u_reference
+
+      :class:`MDAnalysis.Universe` object containing a reference structure
+
+   .. attribute:: select
+
+      string, selection for
+      :meth:`~MDAnalysis.core.groups.AtomGroup.select_atoms` to select frame
+      from :attr:`PSAnalysis.u_reference`
+
+   .. attribute:: path_select
+
+      string, selection for
+      :meth:`~MDAnalysis.core.groups.AtomGroup.select_atoms` to select atoms
+      to compose :attr:`Path.path`
+
+   .. attribute:: ref_frame
+
+      int, frame index to select frame from :attr:`Path.u_reference`
+
+   .. attribute:: paths
+
+      list of :class:`numpy.ndarray` objects representing the set/ensemble of
+      fitted trajectories
+
+   .. attribute:: D
+
+      :class:`numpy.ndarray` which stores the calculated distance matrix
+
+
+.. Markup definitions
+.. ------------------
+..
+.. |3Dp| replace:: :math:`N_p \times N \times 3`
+.. |2Dp| replace:: :math:`N_p \times (3N)`
+.. |3Dq| replace:: :math:`N_q \times N \times 3`
+.. |2Dq| replace:: :math:`N_q \times (3N)`
+.. |3D| replace:: :math:`N_p\times N\times 3`
+.. |2D| replace:: :math:`N_p\times 3N`
+.. |Np| replace:: :math:`N_p`
+
+
+.. Rubric:: References
+
+.. footbibliography::
+"""
+import pickle
+import os
+import warnings
+import numbers
+
+import numpy as np
+from scipy import spatial, cluster
+from scipy.spatial.distance import directed_hausdorff
+import matplotlib
+
+import MDAnalysis
+import MDAnalysis.analysis.align
+from MDAnalysis import NoDataError
+from MDAnalysis.lib.util import deprecate
+
+import logging
+logger = logging.getLogger('MDAnalysis.analysis.psa')
+
+
[docs]def get_path_metric_func(name):
+    """Selects a path metric function by name.
+
+    Parameters
+    ----------
+    name : str
+        name of path metric
+
+    Returns
+    -------
+    path_metric : function
+        The path metric function specified by *name* (if found).
+    """
+    path_metrics = {
+            'hausdorff' : hausdorff,
+            'weighted_average_hausdorff' : hausdorff_wavg,
+            'average_hausdorff' : hausdorff_avg,
+            'hausdorff_neighbors' : hausdorff_neighbors,
+            'discrete_frechet' : discrete_frechet
+    }
+    try:
+        return path_metrics[name]
+    except KeyError as key:
+        errmsg = (f'Path metric "{key}" not found. Valid selections: '
+                  f'{" ".join(n for n in path_metrics.keys())}')
+        raise KeyError(errmsg) from None

+
+
+
[docs]def sqnorm(v, axis=None):
+    """Compute the sum of squares of elements along specified axes.
+
+    Parameters
+    ----------
+    v :  numpy.ndarray
+         coordinates
+    axes : None / int / tuple (optional)
+         Axes or axes along which a sum is performed. The default
+         (*axes* = ``None``) performs a sum over all the dimensions of
+         the input array.  The value of *axes* may be negative, in
+         which case it counts from the last axis to the zeroth axis.
+
+    Returns
+    -------
+    float
+          the sum of the squares of the elements of `v` along `axes`
+
+    """
+    return np.sum(v*v, axis=axis)

+
+
+
[docs]def get_msd_matrix(P, Q, axis=None):
+    r"""Generate the matrix of pairwise mean-squared deviations between paths.
+
+    The MSDs between all pairs of points in `P` and `Q` are
+    calculated, each pair having a point from `P` and a point from
+    `Q`.
+
+    `P` (`Q`) is a :class:`numpy.ndarray` of :math:`N_p` (:math:`N_q`) time
+    steps, :math:`N` atoms, and :math:`3N` coordinates (e.g.,
+    :attr:`MDAnalysis.core.groups.AtomGroup.positions`). The pairwise MSD
+    matrix has dimensions :math:`N_p` by :math:`N_q`.
+
+    Parameters
+    ----------
+    P : numpy.ndarray
+        the points in the first path
+    Q : numpy.ndarray
+        the points in the second path
+
+    Returns
+    -------
+    msd_matrix : numpy.ndarray
+         matrix of pairwise MSDs between points in `P` and points
+         in `Q`
+
+    Notes
+    -----
+    We calculate the MSD matrix
+
+    .. math::
+       M_{ij} = ||p_i - q_j||^2
+
+    where :math:`p_i \in P` and :math:`q_j \in Q`.
+    """
+    return np.asarray([sqnorm(p - Q, axis=axis) for p in P])

+
+
+def reshaper(path, axis):
+    """Flatten path when appropriate to facilitate calculations
+    requiring two dimensional input.
+    """
+    if len(axis) > 1:
+        path = path.reshape(len(path), -1)
+    return path
+
+
[docs]def get_coord_axes(path):
+    """Return the number of atoms and the axes corresponding to atoms
+    and coordinates for a given path.
+
+    The `path` is assumed to be a :class:`numpy.ndarray` where the 0th axis
+    corresponds to a frame (a snapshot of coordinates). The :math:`3N`
+    (Cartesian) coordinates are assumed to be either:
+
+    1. all in the 1st axis, starting with the x,y,z coordinates of the
+       first atom, followed by the *x*,*y*,*z* coordinates of the 2nd, etc.
+    2. in the 1st *and* 2nd axis, where the 1st axis indexes the atom
+       number and the 2nd axis contains the *x*,*y*,*z* coordinates of
+       each atom.
+
+    Parameters
+    ----------
+    path : numpy.ndarray
+         representing a path
+
+    Returns
+    -------
+    (int, (int, ...))
+         the number of atoms and the axes containing coordinates
+
+    """
+    path_dimensions = len(path.shape)
+    if path_dimensions == 3:
+        N = path.shape[1]
+        axis = (1,2) # 1st axis: atoms, 2nd axis: x,y,z coords
+    elif path_dimensions == 2:
+        # can use mod to check if total # coords divisible by 3
+        N = path.shape[1] / 3
+        axis = (1,) # 1st axis: 3N structural coords (x1,y1,z1,...,xN,xN,zN)
+    else:
+        raise ValueError("Path must have 2 or 3 dimensions; the first "
+                         "dimensions (axis 0) must correspond to frames, "
+                         "axis 1 (and axis 2, if present) must contain atomic "
+                         "coordinates.")
+    return N, axis

+
+
+
[docs]def hausdorff(P, Q):
+    r"""Calculate the symmetric Hausdorff distance between two paths.
+
+    The metric used is RMSD, as opposed to the more conventional L2
+    (Euclidean) norm, because this is convenient for i.e., comparing
+    protein configurations.
+
+    *P* (*Q*) is a :class:`numpy.ndarray` of :math:`N_p` (:math:`N_q`) time
+    steps, :math:`N` atoms, and :math:`3N` coordinates (e.g.,
+    :attr:`MDAnalysis.core.groups.AtomGroup.positions`). *P* (*Q*) has
+    either shape |3Dp| (|3Dq|), or |2Dp| (|2Dq|) in flattened form.
+
+    Note that reversing the path does not change the Hausdorff distance.
+
+    Parameters
+    ----------
+    P : numpy.ndarray
+        the points in the first path
+    Q : numpy.ndarray
+        the points in the second path
+
+    Returns
+    -------
+    float
+        the Hausdorff distance between paths `P` and `Q`
+
+    Example
+    -------
+    Calculate the Hausdorff distance between two halves of a trajectory:
+
+     >>> import MDAnalysis as mda
+     >>> import numpy
+     >>> from MDAnalysis.tests.datafiles import PSF, DCD
+     >>> import pathsimanalysis as psa
+     >>> u = mda.Universe(PSF,DCD)
+     >>> mid = int(len(u.trajectory)/2)
+     >>> ca = u.select_atoms('name CA')
+     >>> P = numpy.array([
+     ...                ca.positions for _ in u.trajectory[:mid:]
+     ...              ]) # first half of trajectory
+     >>> Q = numpy.array([
+     ...                ca.positions for _ in u.trajectory[mid::]
+     ...              ]) # second half of trajectory
+     >>> psa.hausdorff(P,Q)
+     4.778663899862152
+     >>> psa.hausdorff(P,Q[::-1]) # hausdorff distance w/ reversed 2nd trajectory
+     4.778663899862152
+
+
+    Notes
+    -----
+    :func:`scipy.spatial.distance.directed_hausdorff` is an optimized
+    implementation of the early break algorithm of :footcite:p:`Taha2015`; the
+    latter code is used here to calculate the symmetric Hausdorff
+    distance with an RMSD metric
+
+    """
+    N_p, axis_p = get_coord_axes(P)
+    N_q, axis_q = get_coord_axes(Q)
+
+    if N_p != N_q:
+        raise ValueError("P and Q must have matching sizes")
+
+    P = reshaper(P, axis_p)
+    Q = reshaper(Q, axis_q)
+
+    return max(directed_hausdorff(P, Q)[0],
+               directed_hausdorff(Q, P)[0]) / np.sqrt(N_p)

+
+
+
[docs]def hausdorff_wavg(P, Q):
+    r"""Calculate the weighted average Hausdorff distance between two paths.
+
+    *P* (*Q*) is a :class:`numpy.ndarray` of :math:`N_p` (:math:`N_q`) time
+    steps, :math:`N` atoms, and :math:`3N` coordinates (e.g.,
+    :attr:`MDAnalysis.core.groups.AtomGroup.positions`). *P* (*Q*) has
+    either shape |3Dp| (|3Dq|), or |2Dp| (|2Dq|) in flattened form. The nearest
+    neighbor distances for *P* (to *Q*) and those of *Q* (to *P*) are averaged
+    individually to get the average nearest neighbor distance for *P* and
+    likewise for *Q*. These averages are then summed and divided by 2 to get a
+    measure that gives equal weight to *P* and *Q*.
+
+    Parameters
+    ----------
+    P : numpy.ndarray
+        the points in the first path
+    Q : numpy.ndarray
+        the points in the second path
+
+    Returns
+    -------
+    float
+        the weighted average Hausdorff distance between paths `P` and `Q`
+
+    Example
+    -------
+
+     >>> import MDAnalysis as mda
+     >>> from MDAnalysis import Universe
+     >>> from MDAnalysis.tests.datafiles import PSF, DCD
+     >>> import pathsimanalysis as psa
+     >>> u = mda.Universe(PSF,DCD)
+     >>> mid = int(len(u.trajectory)/2)
+     >>> ca = u.select_atoms('name CA')
+     >>> P = numpy.array([
+     ...                ca.positions for _ in u.trajectory[:mid:]
+     ...              ]) # first half of trajectory
+     >>> Q = numpy.array([
+     ...                ca.positions for _ in u.trajectory[mid::]
+     ...              ]) # second half of trajectory
+     >>> psa.hausdorff_wavg(P,Q)
+     2.5669644353703447
+     >>> psa.hausdorff_wavg(P,Q[::-1]) # weighted avg hausdorff dist w/ Q reversed
+     2.5669644353703447
+
+    Notes
+    -----
+    The weighted average Hausdorff distance is not a true metric (it does not
+    obey the triangle inequality); see :footcite:p:`Seyler2015` for further
+    details.
+
+
+    """
+    N, axis = get_coord_axes(P)
+    d = get_msd_matrix(P, Q, axis=axis)
+    out = 0.5*( np.mean(np.amin(d,axis=0)) + np.mean(np.amin(d,axis=1)) )
+    return ( out / N )**0.5

+
+
+
[docs]def hausdorff_avg(P, Q):
+    r"""Calculate the average Hausdorff distance between two paths.
+
+    *P* (*Q*) is a :class:`numpy.ndarray` of :math:`N_p` (:math:`N_q`) time
+    steps, :math:`N` atoms, and :math:`3N` coordinates (e.g.,
+    :attr:`MDAnalysis.core.groups.AtomGroup.positions`). *P* (*Q*) has
+    either shape |3Dp| (|3Dq|), or |2Dp| (|2Dq|) in flattened form. The nearest
+    neighbor distances for *P* (to *Q*) and those of *Q* (to *P*) are all
+    averaged together to get a mean nearest neighbor distance. This measure
+    biases the average toward the path that has more snapshots, whereas weighted
+    average Hausdorff gives equal weight to both paths.
+
+    Parameters
+    ----------
+    P : numpy.ndarray
+        the points in the first path
+    Q : numpy.ndarray
+        the points in the second path
+
+    Returns
+    -------
+    float
+        the average Hausdorff distance between paths `P` and `Q`
+
+    Example
+    -------
+
+     >>> import MDAnalysis as mda
+     >>> from MDAnalysis.tests.datafiles import PSF, DCD
+     >>> import pathsimanalysis as psa
+     >>> u = mda.Universe(PSF,DCD)
+     >>> mid = int(len(u.trajectory)/2)
+     >>> ca = u.select_atoms('name CA')
+     >>> P = numpy.array([
+     ...                ca.positions for _ in u.trajectory[:mid:]
+     ...              ]) # first half of trajectory
+     >>> Q = numpy.array([
+     ...                ca.positions for _ in u.trajectory[mid::]
+     ...              ]) # second half of trajectory
+     >>> psa.hausdorff_avg(P,Q)
+     2.5669646575869005
+     >>> psa.hausdorff_avg(P,Q[::-1]) # hausdorff distance w/ reversed 2nd trajectory
+     2.5669646575869005
+
+
+    Notes
+    -----
+    The average Hausdorff distance is not a true metric (it does not obey the
+    triangle inequality); see :footcite:p:`Seyler2015` for further details.
+
+    """
+    N, axis = get_coord_axes(P)
+    d = get_msd_matrix(P, Q, axis=axis)
+    out = np.mean( np.append( np.amin(d,axis=0), np.amin(d,axis=1) ) )
+    return ( out / N )**0.5

+
+
+
[docs]def hausdorff_neighbors(P, Q):
+    r"""Find the Hausdorff neighbors of two paths.
+
+    *P* (*Q*) is a :class:`numpy.ndarray` of :math:`N_p` (:math:`N_q`) time
+    steps, :math:`N` atoms, and :math:`3N` coordinates (e.g.,
+    :attr:`MDAnalysis.core.groups.AtomGroup.positions`). *P* (*Q*) has
+    either shape |3Dp| (|3Dq|), or |2Dp| (|2Dq|) in flattened form.
+
+    Parameters
+    ----------
+    P : numpy.ndarray
+        the points in the first path
+    Q : numpy.ndarray
+        the points in the second path
+
+    Returns
+    -------
+    dict
+        dictionary of two pairs of numpy arrays, the first pair (key
+        "frames") containing the indices of (Hausdorff) nearest
+        neighbors for `P` and `Q`, respectively, the second (key
+        "distances") containing (corresponding) nearest neighbor
+        distances for `P` and `Q`, respectively
+
+    Notes
+    -----
+    - Hausdorff neighbors are those points on the two paths that are separated by
+      the Hausdorff distance. They are the farthest nearest neighbors and are
+      maximally different in the sense of the Hausdorff distance
+      :footcite:p:`Seyler2015`.
+    - :func:`scipy.spatial.distance.directed_hausdorff` can also provide the
+      hausdorff neighbors.
+
+    """
+    N, axis = get_coord_axes(P)
+    d = get_msd_matrix(P, Q, axis=axis)
+    nearest_neighbors = {
+        'frames' : (np.argmin(d, axis=1), np.argmin(d, axis=0)),
+        'distances' : ((np.amin(d,axis=1)/N)**0.5, (np.amin(d, axis=0)/N)**0.5)
+    }
+    return nearest_neighbors

+
+
+
[docs]def discrete_frechet(P, Q):
+    r"""Calculate the discrete Fréchet distance between two paths.
+
+    *P* (*Q*) is a :class:`numpy.ndarray` of :math:`N_p` (:math:`N_q`) time
+    steps, :math:`N` atoms, and :math:`3N` coordinates (e.g.,
+    :attr:`MDAnalysis.core.groups.AtomGroup.positions`). *P* (*Q*) has
+    either shape |3Dp| (|3Dq|), or :|2Dp| (|2Dq|) in flattened form.
+
+    Parameters
+    ----------
+    P : numpy.ndarray
+        the points in the first path
+    Q : numpy.ndarray
+        the points in the second path
+
+    Returns
+    -------
+    float
+        the discrete Fréchet distance between paths *P* and *Q*
+
+    Example
+    -------
+    Calculate the discrete Fréchet distance between two halves of a
+    trajectory.
+
+     >>> import MDAnalysis as mda
+     >>> import numpy as np
+     >>> from MDAnalysis.tests.datafiles import PSF, DCD
+     >>> import pathsimanalysis as psa
+     >>> u = mda.Universe(PSF,DCD)
+     >>> mid = int(len(u.trajectory)/2)
+     >>> ca = u.select_atoms('name CA')
+     >>> P = np.array([
+     ...                ca.positions for _ in u.trajectory[:mid:]
+     ...              ]) # first half of trajectory
+     >>> Q = np.array([
+     ...                ca.positions for _ in u.trajectory[mid::]
+     ...              ]) # second half of trajectory
+     >>> psa.discrete_frechet(P,Q)
+     4.778663984013591
+     >>> psa.discrete_frechet(P,Q[::-1]) # frechet distance w/ 2nd trj reversed 2nd
+     6.842901117711383
+
+    Note that reversing the direction increased the Fréchet distance:
+    it is sensitive to the direction of the path.
+
+    Notes
+    -----
+
+    The discrete Fréchet metric is an approximation to the continuous Fréchet
+    metric :footcite:p:`Frechet1906,Alt1995`. The calculation of the continuous
+    Fréchet distance is implemented with the dynamic programming algorithm of
+    :footcite:p:`EiterMannila1994,EiterMannila1997`.
+
+    """
+
+    N, axis = get_coord_axes(P)
+    Np, Nq = len(P), len(Q)
+    d = get_msd_matrix(P, Q, axis=axis)
+    ca = -np.ones((Np, Nq))
+
+    def c(i, j):
+        """Compute the coupling distance for two partial paths formed by *P* and
+        *Q*, where both begin at frame 0 and end (inclusive) at the respective
+        frame indices :math:`i-1` and :math:`j-1`. The partial path of *P* (*Q*)
+        up to frame *i* (*j*) is formed by the slicing ``P[0:i]`` (``Q[0:j]``).
+
+        :func:`c` is called recursively to compute the coupling distance
+        between the two full paths *P* and *Q*  (i.e., the discrete Frechet
+        distance) in terms of coupling distances between their partial paths.
+
+        Parameters
+        ----------
+        i : int
+            partial path of *P* through final frame *i-1*
+        j : int
+            partial path of *Q* through final frame *j-1*
+
+        Returns
+        -------
+        dist : float
+            the coupling distance between partial paths `P[0:i]` and `Q[0:j]`
+        """
+        if ca[i,j] != -1 :
+            return ca[i,j]
+        if i > 0:
+            if j > 0:
+                ca[i,j] = max( min(c(i-1,j),c(i,j-1),c(i-1,j-1)), d[i,j] )
+            else:
+                ca[i,j] = max( c(i-1,0), d[i,0] )
+        elif j > 0:
+            ca[i,j] = max( c(0,j-1), d[0,j] )
+        else:
+            ca[i,j] = d[0,0]
+        return ca[i,j]
+
+    return (c(Np-1, Nq-1) / N)**0.5

+
+
+
[docs]def dist_mat_to_vec(N, i, j):
+    """Convert distance matrix indices (in the upper triangle) to the index of
+    the corresponding distance vector.
+
+    This is a convenience function to locate distance matrix elements (and the
+    pair generating it) in the corresponding distance vector. The row index *j*
+    should be greater than *i+1*, corresponding to the upper triangle of the
+    distance matrix.
+
+    Parameters
+    ----------
+    N : int
+        size of the distance matrix (of shape *N*-by-*N*)
+    i : int
+        row index (starting at 0) of the distance matrix
+    j : int
+        column index (starting at 0) of the distance matrix
+
+    Returns
+    -------
+    int
+        index (of the matrix element) in the corresponding distance vector
+
+    """
+
+    if not (isinstance(N, numbers.Integral) and isinstance(i, numbers.Integral)
+            and isinstance(j, numbers.Integral)):
+        raise ValueError("N, i, j all must be of type int")
+
+    if i < 0 or j < 0 or N < 2:
+        raise ValueError("Matrix indices are invalid; i and j must be greater "
+                         "than 0 and N must be greater the 2")
+
+    if (j > i and (i > N - 1 or j > N)) or (j < i and (i > N or j > N - 1)):
+        raise ValueError("Matrix indices are out of range; i and j must be "
+                         "less than N = {0:d}".format(N))
+    if j > i:
+        return (N*i) + j - (i+2)*(i+1) // 2  # old-style division for int output
+    elif j < i:
+        warnings.warn("Column index entered (j = {:d} is smaller than row "
+                      "index (i = {:d}). Using symmetric element in upper "
+                      "triangle of distance matrix instead: i --> j, "
+                      "j --> i".format(j, i))
+        return (N*j) + i - (j+2)*(j+1) // 2  # old-style division for int output
+    else:
+        raise ValueError("Error in processing matrix indices; i and j must "
+                         "be integers less than integer N = {0:d} such that"
+                         " j >= i+1.".format(N))

+
+
+
[docs]class Path(object):
+    """Represent a path based on a :class:`~MDAnalysis.core.universe.Universe`.
+
+    Pre-process a :class:`Universe` object: (1) fit the trajectory to a
+    reference structure, (2) convert fitted time series to a
+    :class:`numpy.ndarray` representation of :attr:`Path.path`.
+
+    The analysis is performed with :meth:`PSAnalysis.run` and stores the result
+    in the :class:`numpy.ndarray` distance matrix :attr:`PSAnalysis.D`.
+    :meth:`PSAnalysis.run` also generates a fitted trajectory and path from
+    alignment of the original trajectories to a reference structure.
+
+    .. versionadded:: 0.9.1
+
+    """
+
+    def __init__(self, universe, reference, select='name CA',
+                 path_select='all', ref_frame=0):
+        """Setting up trajectory alignment and fitted path generation.
+
+        Parameters
+        ----------
+        universe : Universe
+             :class:`MDAnalysis.Universe` object containing a trajectory
+        reference : Universe
+             reference structure (uses `ref_frame` from the trajectory)
+        select : str or dict or tuple (optional)
+             The selection to operate on for rms fitting; can be one of:
+
+             1. any valid selection string for
+                :meth:`~MDAnalysis.core.groups.AtomGroup.select_atoms` that
+                produces identical selections in *mobile* and *reference*; or
+             2. a dictionary ``{'mobile':sel1, 'reference':sel2}`` (the
+                :func:`MDAnalysis.analysis.align.fasta2select` function returns
+                such a dictionary based on a ClustalW_ or STAMP_ sequence
+                alignment); or
+             3. a tuple ``(sel1, sel2)``
+
+             When using 2. or 3. with *sel1* and *sel2* then these selections
+             can also each be a list of selection strings (to generate an
+             AtomGroup with defined atom order as described under
+             :ref:`ordered-selections-label`).
+        ref_frame : int
+             frame index to select the coordinate frame from
+             `select.trajectory`
+        path_select : selection_string
+             atom selection composing coordinates of (fitted) path; if ``None``
+             then `path_select` is set to `select` [``None``]
+
+        """
+        self.u_original = universe
+        self.u_reference = reference
+        self.select = select
+        self.ref_frame = ref_frame
+        self.path_select = path_select
+
+        self.top_name = self.u_original.filename
+        self.trj_name = self.u_original.trajectory.filename
+        self.newtrj_name = None
+        self.u_fitted = None
+        self.path = None
+        self.natoms = None
+
+
[docs]    def fit_to_reference(self, filename=None, prefix='', postfix='_fit',
+                         rmsdfile=None, targetdir=os.path.curdir,
+                         weights=None, tol_mass=0.1):
+        """Align each trajectory frame to the reference structure
+
+        Parameters
+        ----------
+        filename : str (optional)
+             file name for the RMS-fitted trajectory or pdb; defaults to the
+             original trajectory filename (from :attr:`Path.u_original`) with
+             `prefix` prepended
+        prefix : str (optional)
+             prefix for auto-generating the new output filename
+        rmsdfile : str (optional)
+             file name for writing the RMSD time series [``None``]
+        weights : {"mass", ``None``} or array_like (optional)
+             choose weights. With ``"mass"`` uses masses as weights; with
+             ``None`` weigh each atom equally. If a float array of the same
+             length as the selected AtomGroup is provided, use each element of
+             the `array_like` as a weight for the corresponding atom in the
+             AtomGroup.
+        tol_mass : float (optional)
+             Reject match if the atomic masses for matched atoms differ by more
+             than `tol_mass` [0.1]
+
+        Returns
+        -------
+        Universe
+            :class:`MDAnalysis.Universe` object containing a fitted trajectory
+
+        Notes
+        -----
+        Uses :class:`MDAnalysis.analysis.align.AlignTraj` for the fitting.
+
+
+        .. deprecated:: 0.16.1
+           Instead of ``mass_weighted=True`` use new ``weights='mass'``;
+           refactored to fit with AnalysisBase API
+
+        .. versionchanged:: 0.17.0
+           Deprecated keyword `mass_weighted` was removed.
+        """
+        head, tail = os.path.split(self.trj_name)
+        oldname, ext = os.path.splitext(tail)
+        filename = filename or oldname
+        self.newtrj_name = os.path.join(targetdir, filename + postfix + ext)
+        self.u_reference.trajectory[self.ref_frame] # select frame from ref traj
+        aligntrj = MDAnalysis.analysis.align.AlignTraj(self.u_original,
+                                                       self.u_reference,
+                                                       select=self.select,
+                                                       filename=self.newtrj_name,
+                                                       prefix=prefix,
+                                                       weights=weights,
+                                                       tol_mass=tol_mass).run()
+        if rmsdfile is not None:
+            aligntrj.save(rmsdfile)
+        return MDAnalysis.Universe(self.top_name, self.newtrj_name)

+
+
[docs]    def to_path(self, fitted=False, select=None, flat=False):
+        r"""Generates a coordinate time series from the fitted universe
+        trajectory.
+
+        Given a selection of *N* atoms from *select*, the atomic positions for
+        each frame in the fitted universe (:attr:`Path.u_fitted`) trajectory
+        (with |Np| total frames) are appended sequentially to form a 3D or 2D
+        (if *flat* is ``True``) :class:`numpy.ndarray` representation of the
+        fitted trajectory (with dimensions |3D| or |2D|, respectively).
+
+        Parameters
+        ----------
+        fitted : bool (optional)
+             construct a :attr:`Path.path` from the :attr:`Path.u_fitted`
+             trajectory; if ``False`` then :attr:`Path.path` is generated with
+             the trajectory from :attr:`Path.u_original` [``False``]
+        select : str (optional)
+             the selection for constructing the coordinates of each frame in
+             :attr:`Path.path`; if ``None`` then :attr:`Path.path_select`
+             is used, else it is overridden by *select* [``None``]
+        flat : bool (optional)
+             represent :attr:`Path.path` as a 2D (|2D|) :class:`numpy.ndarray`;
+             if ``False`` then :attr:`Path.path` is a 3D (|3D|)
+             :class:`numpy.ndarray` [``False``]
+
+        Returns
+        -------
+        numpy.ndarray
+              representing a time series of atomic positions of an
+              :class:`MDAnalysis.core.groups.AtomGroup` selection from
+              :attr:`Path.u_fitted.trajectory`
+
+        """
+        select = select if select is not None else self.path_select
+        if fitted:
+            if not isinstance(self.u_fitted, MDAnalysis.Universe):
+                raise TypeError("Fitted universe not found. Generate a fitted " +
+                        "universe with fit_to_reference() first, or explicitly "+
+                        "set argument \"fitted\" to \"False\" to generate a "   +
+                        "path from the original universe.")
+            u = self.u_fitted
+        else:
+            u = self.u_original
+        frames = u.trajectory
+        atoms = u.select_atoms(select)
+        self.natoms = len(atoms)
+        frames.rewind()
+        if flat:
+            return np.array([atoms.positions.flatten() for _ in frames])
+        else:
+            return np.array([atoms.positions for _ in frames])

+
+
[docs]    def run(self, align=False, filename=None, postfix='_fit', rmsdfile=None,
+            targetdir=os.path.curdir, weights=None, tol_mass=0.1,
+            flat=False):
+        r"""Generate a path from a trajectory and reference structure.
+
+        As part of the path generation, the trajectory can be superimposed
+        ("aligned") to a reference structure if specified.
+
+        This is a convenience method to generate a fitted trajectory from an
+        inputted universe (:attr:`Path.u_original`) and reference structure
+        (:attr:`Path.u_reference`). :meth:`Path.fit_to_reference` and
+        :meth:`Path.to_path` are used consecutively to generate a new universe
+        (:attr:`Path.u_fitted`) containing the fitted trajectory along with the
+        corresponding :attr:`Path.path` represented as an
+        :class:`numpy.ndarray`. The method returns a tuple of the topology name
+        and new trajectory name, which can be fed directly into an
+        :class:`MDAnalysis.Universe` object after unpacking the tuple using the
+        ``*`` operator, as in
+        ``MDAnalysis.Universe(*(top_name, newtraj_name))``.
+
+        Parameters
+        ----------
+        align : bool (optional)
+             Align trajectory to atom selection :attr:`Path.select` of
+             :attr:`Path.u_reference`. If ``True``, a universe containing an
+             aligned trajectory is produced with :meth:`Path.fit_to_reference`
+             [``False``]
+        filename : str (optional)
+             filename for the RMS-fitted trajectory or pdb; defaults to the
+             original trajectory filename (from :attr:`Path.u_original`) with
+             *prefix* prepended
+        postfix : str (optional)
+             prefix for auto-generating the new output filename
+        rmsdfile : str (optional)
+             file name for writing the RMSD time series [``None``]
+        weights : {"mass", ``None``} or array_like (optional)
+             choose weights. With ``"mass"`` uses masses as weights; with
+             ``None`` weigh each atom equally. If a float array of the same
+             length as the selected AtomGroup is provided, use each element of
+             the `array_like` as a weight for the corresponding atom in the
+             AtomGroup.
+        tol_mass : float (optional)
+             Reject match if the atomic masses for matched atoms differ by more
+             than *tol_mass* [0.1]
+        flat : bool (optional)
+             represent :attr:`Path.path` with 2D (|2D|) :class:`numpy.ndarray`;
+             if ``False`` then :attr:`Path.path` is a 3D (|3D|)
+             :class:`numpy.ndarray` [``False``]
+
+        Returns
+        -------
+        topology_trajectory : tuple
+             A tuple of the topology name and new trajectory name.
+
+
+        .. deprecated:: 0.16.1
+           Instead of ``mass_weighted=True`` use new ``weights='mass'``;
+           refactored to fit with AnalysisBase API
+
+        .. versionchanged:: 0.17.0
+           Deprecated keyword `mass_weighted` was removed.
+        """
+        if align:
+            self.u_fitted = self.fit_to_reference(
+                                filename=filename, postfix=postfix,
+                                rmsdfile=rmsdfile, targetdir=targetdir,
+                                weights=weights, tol_mass=0.1)
+        self.path = self.to_path(fitted=align, flat=flat)
+        return self.top_name, self.newtrj_name

+
+
[docs]    def get_num_atoms(self):
+        """Return the number of atoms used to construct the :class:`Path`.
+
+        Must run :meth:`Path.to_path` prior to calling this method.
+
+        Returns
+        -------
+        int
+            the number of atoms in the :class:`Path`
+
+
+        """
+        if self.natoms is None:
+            raise ValueError("No path data; do 'Path.to_path()' first.")
+        return self.natoms

+
+
+
[docs]class PSAPair(object):
+    """Generate nearest neighbor and Hausdorff pair information between a pair
+    of paths from an all-pairs comparison generated by :class:`PSA`.
+
+    The nearest neighbors for each path of a pair of paths is generated by
+    :meth:`PSAPair.compute_nearest_neighbors` and stores the result
+    in a dictionary (:attr:`nearest_neighbors`): each path has a
+    :class:`numpy.ndarray` of the frames of its nearest neighbors, and a
+    :class:`numpy.ndarray` of its nearest neighbor distances
+    :attr:`PSAnalysis.D`. For example, *nearest_neighbors['frames']* is a pair
+    of :class:`numpy.ndarray`, the first being the frames of the nearest
+    neighbors of the first path, *i*, the second being those of the second path,
+    *j*.
+
+    The Hausdorff pair for the pair of paths is found by calling
+    :meth:`find_hausdorff_pair` (locates the nearest neighbor pair having the
+    largest overall distance separating them), which stores the result in a
+    dictionary (:attr:`hausdorff_pair`) containing the frames (indices) of the
+    pair along with the corresponding (Hausdorff) distance.
+    *hausdorff_pair['frame']* contains a pair of frames in the first path, *i*,
+    and the second path, *j*, respectively, that correspond to the Hausdorff
+    distance between them.
+
+    .. versionadded:: 0.11
+    """
+
+    def __init__(self, npaths, i, j):
+        """Set up a :class:`PSAPair` for a pair of paths that are part of a
+        :class:`PSA` comparison of *npaths* total paths.
+
+        Each unique pair of paths compared using :class:`PSA` is related by
+        their nearest neighbors (and corresponding distances) and the Hausdorff
+        pair and distance. :class:`PSAPair` is a convenience class for
+        calculating and encapsulating nearest neighbor and Hausdorff pair
+        information for one pair of paths.
+
+        Given *npaths*, :class:`PSA` performs and all-pairs comparison among all
+        paths for a total of :math:`\text{npaths}*(\text{npaths}-1)/2` unique
+        comparisons. If distances between paths are computed, the all-pairs
+        comparison can be summarized in a symmetric distance matrix whose upper
+        triangle can be mapped to a corresponding distance vector form in a
+        one-to-one manner. A particular comparison of a pair of paths in a
+        given instance of :class:`PSAPair` is thus unique identified by the row
+        and column indices in the distance matrix representation (whether or not
+        distances are actually computed), or a single ID (index) in the
+        corresponding distance vector.
+
+        Parameters
+        ----------
+        npaths : int
+            total number of paths in :class:`PSA` used to generate *this*
+            :class:`PSAPair`
+        i : int
+             row index (starting at 0) of the distance matrix
+        j : int
+             column index (starting at 0) of the distance matrix
+        """
+        self.npaths = npaths
+        self.matrix_idx = (i,j)
+        self.pair_idx = self._dvec_idx(i,j)
+
+        # Set by calling hausdorff_nn
+        self.nearest_neighbors = {'frames' : None, 'distances' : None}
+
+        # Set by self.getHausdorffPair
+        self.hausdorff_pair = {'frames' : (None, None), 'distance' : None}
+
+    def _dvec_idx(self, i, j):
+        """Convert distance matrix indices (in the upper triangle) to the index
+        of the corresponding distance vector.
+
+        This is a convenience function to locate distance matrix elements (and
+        the pair generating it) in the corresponding distance vector. The row
+        index *j* should be greater than *i+1*, corresponding to the upper
+        triangle of the distance matrix.
+
+        Parameters
+        ----------
+        i : int
+            row index (starting at 0) of the distance matrix
+        j : int
+            column index (starting at 0) of the distance matrix
+
+        Returns
+        -------
+        int
+             (matrix element) index in the corresponding distance vector
+        """
+        return (self.npaths*i) + j - (i+2)*(i+1)/2
+
+    def compute_nearest_neighbors(self, P,Q, N=None):
+        """Generates Hausdorff nearest neighbor lists of *frames* (by index) and
+        *distances* for *this* pair of paths corresponding to distance matrix
+        indices (*i*,*j*).
+
+        :meth:`PSAPair.compute_nearest_neighbors` calls
+        :func:`hausdorff_neighbors` to populate the dictionary of the nearest
+        neighbor lists of frames (by index) and distances
+        (:attr:`PSAPair.nearest_neighbors`). This method must explicitly take as
+        arguments a pair of paths, *P* and *Q*, where *P* is the
+        :math:`i^\text{th}` path and *Q* is the :math:`j^\text{th}` path among
+        the set of *N* total paths in the comparison.
+
+        Parameters
+        ----------
+        P : numpy.ndarray
+            representing a path
+        Q : numpy.ndarray
+            representing a path
+        N : int
+            size of the distance matrix (of shape *N*-by-*N*) [``None``]
+
+        """
+        hn = hausdorff_neighbors(P, Q)
+        self.nearest_neighbors['frames'] = hn['frames']
+        self.nearest_neighbors['distances'] = hn['distances']
+
+    def find_hausdorff_pair(self):
+        r"""Find the Hausdorff pair (of frames) for *this* pair of paths.
+
+        :meth:`PSAPair.find_hausdorff_pair` requires that
+        `:meth:`PSAPair.compute_nearest_neighbors` be called first to
+        generate the nearest neighbors (and corresponding distances) for each
+        path in *this* :class:`PSAPair`. The Hausdorff pair is the nearest
+        neighbor pair (of snapshots/frames), one in the first path and one in
+        the second, with the largest separation distance.
+        """
+        if self.nearest_neighbors['distances'] is None:
+            raise NoDataError("Nearest neighbors have not been calculated yet;"
+                              " run compute_nearest_neighbors() first.")
+
+        nn_idx_P, nn_idx_Q = self.nearest_neighbors['frames']
+        nn_dist_P, nn_dist_Q = self.nearest_neighbors['distances']
+        max_nn_dist_P = max(nn_dist_P)
+        max_nn_dist_Q = max(nn_dist_Q)
+        if max_nn_dist_P > max_nn_dist_Q:
+            max_nn_idx_P = np.argmax(nn_dist_P)
+            self.hausdorff_pair['frames'] = max_nn_idx_P, nn_idx_P[max_nn_idx_P]
+            self.hausdorff_pair['distance']  = max_nn_dist_P
+        else:
+            max_nn_idx_Q = np.argmax(nn_dist_Q)
+            self.hausdorff_pair['frames'] = nn_idx_Q[max_nn_idx_Q], max_nn_idx_Q
+            self.hausdorff_pair['distance'] = max_nn_dist_Q
+
+    def get_nearest_neighbors(self, frames=True, distances=True):
+        """Returns the nearest neighbor frame indices, distances, or both, for
+        each path in *this* :class:`PSAPair`.
+
+        :meth:`PSAPair.get_nearest_neighbors` requires that the nearest
+        neighbors (:attr:`nearest_neighbors`) be initially computed by first
+        calling :meth:`compute_nearest_neighbors`. At least one of *frames*
+        or *distances* must be ``True``, or else a ``NoDataError`` is raised.
+
+        Parameters
+        ----------
+        frames :  bool
+             if ``True``, return nearest neighbor frame indices
+             [``True``]
+         distances : bool
+             if ``True``, return nearest neighbor distances [``True``]
+
+        Returns
+        -------
+        dict or tuple
+             If both *frames* and *distances* are ``True``, return the entire
+             dictionary (:attr:`nearest_neighbors`); if only *frames* is
+             ``True``, return a pair of :class:`numpy.ndarray` containing the
+             indices of the frames (for the pair of paths) of the nearest
+             neighbors; if only *distances* is ``True``, return a pair of
+             :class:`numpy.ndarray` of the nearest neighbor distances (for the
+             pair of paths).
+
+        """
+        if self.nearest_neighbors['distances'] is None:
+            raise NoDataError("Nearest neighbors have not been calculated yet;"
+                              " run compute_nearest_neighbors() first.")
+
+        if frames:
+            if distances:
+                return self.nearest_neighbors
+            else:
+                return self.nearest_neighbors['frames']
+        elif distances:
+            return self.nearest_neighbors['distances']
+        else:
+            raise NoDataError('Need to select Hausdorff pair "frames" or'
+                              ' "distances" or both. "frames" and "distances"'
+                              ' cannot both be set to False.')
+
+    def get_hausdorff_pair(self, frames=True, distance=True):
+        """Returns the Hausdorff pair of frames indices, the Hausdorff distance,
+        or both, for the paths in *this* :class:`PSAPair`.
+
+        :meth:`PSAPair.get_hausdorff_pair` requires that the Hausdorff pair
+        (and distance) be initially found by first calling
+        :meth:`find_hausdorff_pair`. At least one of *frames* or *distance*
+        must be ``True``, or else a ``NoDataError`` is raised.
+
+        Parameters
+        ----------
+        frames : bool
+             if ``True``, return the indices of the frames
+             of the Hausdorff pair [``True``]
+        distances : bool
+             if ``True``, return Hausdorff distance [``True``]
+
+        Returns
+        -------
+        dict or tuple
+             If both *frames* and *distance* are ``True``, return the entire
+             dictionary (:attr:`hausdorff_pair`); if only *frames* is
+             ``True``, return a pair of ``int`` containing the indices of the
+             frames (one index per path) of the Hausdorff pair; if only *distance*
+             is ``True``, return the Hausdorff distance for this path pair.
+        """
+        if self.hausdorff_pair['distance'] is None:
+            raise NoDataError("Hausdorff pair has not been calculated yet;"
+                              " run find_hausdorff_pair() first.")
+
+        if frames:
+            if distance:
+                return self.hausdorff_pair
+            else:
+                return self.hausdorff_pair['frames']
+        elif distance:
+            return self.hausdorff_pair['distance']
+        else:
+            raise NoDataError('Need to select Hausdorff pair "frames" or'
+                              ' "distance" or both. "frames" and "distance"'
+                              ' cannot both be set to False.')

+
+
+
[docs]class PSAnalysis(object):
+    """Perform Path Similarity Analysis (PSA) on a set of trajectories.
+
+    The analysis is performed with :meth:`PSAnalysis.run` and stores the result
+    in the :class:`numpy.ndarray` distance matrix :attr:`PSAnalysis.D`.
+    :meth:`PSAnalysis.run` also generates a fitted trajectory and path from
+    alignment of the original trajectories to a reference structure.
+
+    .. versionadded:: 0.8
+
+    .. versionchanged:: 1.0.0
+       ``save_result()`` method has been removed. You can use ``np.save()`` on
+       :attr:`PSAnalysis.D` instead.
+    """
+    def __init__(self, universes, reference=None, select='name CA',
+                 ref_frame=0, path_select=None, labels=None,
+                 targetdir=os.path.curdir):
+        """Setting up Path Similarity Analysis.
+
+        The mutual similarity between all unique pairs of trajectories
+        are computed using a selected path metric.
+
+        Parameters
+        ----------
+        universes : list
+             a list of universes (:class:`MDAnalysis.Universe` object), each
+             containing a trajectory
+        reference : Universe
+             reference coordinates; :class:`MDAnalysis.Universe` object; if
+             ``None`` the first time step of the first item in `universes` is used
+             [``None``]
+        select : str or dict or tuple
+             The selection to operate on; can be one of:
+
+             1. any valid selection string for
+                :meth:`~MDAnalysis.core.groups.AtomGroup.select_atoms` that
+                produces identical selections in *mobile* and *reference*; or
+             2. a dictionary ``{'mobile':sel1, 'reference':sel2}`` (the
+                :func:`MDAnalysis.analysis.align.fasta2select` function returns
+                such a dictionary based on a ClustalW_ or STAMP_ sequence
+                alignment); or
+             3. a tuple ``(sel1, sel2)``
+
+             When using 2. or 3. with *sel1* and *sel2* then these selections
+             can also each be a list of selection strings (to generate an
+             AtomGroup with defined atom order as described under
+             :ref:`ordered-selections-label`).
+        tol_mass : float
+             Reject match if the atomic masses for matched atoms differ by more
+             than *tol_mass* [0.1]
+        ref_frame : int
+             frame index to select frame from *reference* [0]
+        path_select : str
+             atom selection composing coordinates of (fitted) path; if ``None``
+             then *path_select* is set to *select* [``None``]
+        targetdir : str
+            output files are saved there; if ``None`` then "./psadata" is
+            created and used [.]
+        labels : list
+             list of strings, names of trajectories to be analyzed
+             (:class:`MDAnalysis.Universe`); if ``None``, defaults to trajectory
+             names [``None``]
+
+
+        .. _ClustalW: http://www.clustal.org/
+        .. _STAMP: http://www.compbio.dundee.ac.uk/manuals/stamp.4.2/
+
+        """
+        self.universes = universes
+        self.u_reference = self.universes[0] if reference is None else reference
+        self.select = select
+        self.ref_frame = ref_frame
+        self.path_select = self.select if path_select is None else path_select
+        if targetdir is None:
+            try:
+                targetdir = os.path.join(os.path.curdir, 'psadata')
+                os.makedirs(targetdir)
+            except OSError:
+                if not os.path.isdir(targetdir):
+                    raise
+        self.targetdir = os.path.realpath(targetdir)
+
+        # Set default directory names for storing topology/reference structures,
+        # fitted trajectories, paths, distance matrices, and plots
+        self.datadirs = {'fitted_trajs' : 'fitted_trajs',
+                         'paths' : 'paths',
+                         'distance_matrices' : 'distance_matrices',
+                         'plots' : 'plots'}
+        for dir_name, directory in self.datadirs.items():
+            try:
+                full_dir_name = os.path.join(self.targetdir, dir_name)
+                os.makedirs(full_dir_name)
+            except OSError:
+                if not os.path.isdir(full_dir_name):
+                    raise
+
+        # Keep track of topology, trajectory, and related files
+        trj_names = []
+        for i, u in enumerate(self.universes):
+            head, tail = os.path.split(u.trajectory.filename)
+            filename, ext = os.path.splitext(tail)
+            trj_names.append(filename)
+        self.trj_names = trj_names
+        self.fit_trj_names = None
+        self.path_names = None
+        self.top_name = self.universes[0].filename if len(universes) != 0 else None
+        self.labels = labels or self.trj_names
+
+        # Names of persistence (pickle) files where topology and trajectory
+        # filenames are stored--should not be modified by user
+        self._top_pkl = os.path.join(self.targetdir, "psa_top-name.pkl")
+        self._trjs_pkl = os.path.join(self.targetdir, "psa_orig-traj-names.pkl")
+        self._fit_trjs_pkl = os.path.join(self.targetdir, "psa_fitted-traj-names.pkl")
+        self._paths_pkl = os.path.join(self.targetdir, "psa_path-names.pkl")
+        self._labels_pkl = os.path.join(self.targetdir, "psa_labels.pkl")
+        # Pickle topology and trajectory filenames for this analysis to curdir
+        with open(self._top_pkl, 'wb') as output:
+            pickle.dump(self.top_name, output)
+        with open(self._trjs_pkl, 'wb') as output:
+            pickle.dump(self.trj_names, output)
+        with open(self._labels_pkl, 'wb') as output:
+            pickle.dump(self.labels, output)
+
+        self.natoms = None
+        self.npaths = None
+        self.paths = None
+        self.D = None   # pairwise distances
+        self._HP = None # (distance vector order) list of all Hausdorff pairs
+        self._NN = None # (distance vector order) list of all nearest neighbors
+        self._psa_pairs = None # (distance vector order) list of all PSAPairs
+
+
[docs]    def generate_paths(self, align=False, filename=None, infix='', weights=None,
+                       tol_mass=False, ref_frame=None, flat=False, save=True, store=False):
+        """Generate paths, aligning each to reference structure if necessary.
+
+        Parameters
+        ----------
+        align : bool
+             Align trajectories to atom selection :attr:`PSAnalysis.select`
+             of :attr:`PSAnalysis.u_reference` [``False``]
+        filename : str
+             strings representing base filename for fitted trajectories and
+             paths [``None``]
+        infix : str
+             additional tag string that is inserted into the output filename of
+             the fitted trajectory files ['']
+        weights : {"mass", ``None``} or array_like (optional)
+             choose weights. With ``"mass"`` uses masses as weights; with
+             ``None`` weigh each atom equally. If a float array of the same
+             length as the selected AtomGroup is provided, use each element of
+             the `array_like` as a weight for the corresponding atom in the
+             AtomGroup [``None``]
+        tol_mass : float
+             Reject match if the atomic masses for matched atoms differ by more
+             than *tol_mass* [``False``]
+        ref_frame : int
+             frame index to select frame from *reference* [``None``]
+        flat : bool
+             represent :attr:`Path.path` as a 2D (|2D|) :class:`numpy.ndarray`;
+             if ``False`` then :attr:`Path.path` is a 3D (|3D|)
+             :class:`numpy.ndarray` [``False``]
+        save : bool
+             if ``True``, pickle list of names for fitted trajectories
+             [``True``]
+        store : bool
+             if ``True`` then writes each path (:class:`numpy.ndarray`)
+             in :attr:`PSAnalysis.paths` to compressed npz (numpy) files
+             [``False``]
+
+
+        The fitted trajectories are written to new files in the
+        "/trj_fit" subdirectory in :attr:`PSAnalysis.targetdir` named
+        "filename(*trajectory*)XXX*infix*_psa", where "XXX" is a number between
+        000 and 999; the extension of each file is the same as its original.
+        Optionally, the trajectories can also be saved in numpy compressed npz
+        format in the "/paths" subdirectory in :attr:`PSAnalysis.targetdir` for
+        persistence and can be accessed as the attribute
+        :attr:`PSAnalysis.paths`.
+
+
+        .. deprecated:: 0.16.1
+           Instead of ``mass_weighted=True`` use new ``weights='mass'``;
+           refactored to fit with AnalysisBase API
+
+        .. versionchanged:: 0.17.0
+           Deprecated keyword `mass_weighted` was removed.
+
+        .. versionchanged:: 1.0.0
+           Defaults for the `store` and `filename` keywords have been changed
+           from `True` and `fitted` to `False` and `None` respectively. These
+           now match the docstring documented defaults.
+        """
+        if ref_frame is None:
+            ref_frame = self.ref_frame
+
+        paths = []
+        fit_trj_names = []
+        for i, u in enumerate(self.universes):
+            p = Path(u, self.u_reference, select=self.select,
+                     path_select=self.path_select, ref_frame=ref_frame)
+            trj_dir = os.path.join(self.targetdir, self.datadirs['fitted_trajs'])
+            postfix = '{0}{1}{2:03n}'.format(infix, '_psa', i+1)
+            top_name, fit_trj_name = p.run(align=align, filename=filename,
+                                           postfix=postfix,
+                                           targetdir=trj_dir,
+                                           weights=weights,
+                                           tol_mass=tol_mass, flat=flat)
+            paths.append(p.path)
+            fit_trj_names.append(fit_trj_name)
+        self.natoms, axis = get_coord_axes(paths[0])
+        self.paths = paths
+        self.npaths = len(paths)
+        self.fit_trj_names = fit_trj_names
+        if save:
+            with open(self._fit_trjs_pkl, 'wb') as output:
+                pickle.dump(self.fit_trj_names, output)
+        if store:
+            self.save_paths(filename=filename)

+
+
[docs]    def run(self, **kwargs):
+        """Perform path similarity analysis on the trajectories to compute
+        the distance matrix.
+
+        A number of parameters can be changed from the defaults. The
+        result is stored as the array :attr:`PSAnalysis.D`.
+
+        Parameters
+        ----------
+        metric : str or callable
+             selection string specifying the path metric to measure pairwise
+             distances among :attr:`PSAnalysis.paths` or a callable with the
+             same call signature as :func:`hausdorff`
+             [``'hausdorff'``]
+        start : int
+             `start` and `stop` frame index with `step` size: analyze
+             ``trajectory[start:stop:step]`` [``None``]
+        stop : int
+        step : int
+
+        .. versionchanged:: 1.0.0
+           `store` and `filename` have been removed.
+
+        """
+        metric = kwargs.pop('metric', 'hausdorff')
+        start = kwargs.pop('start', None)
+        stop = kwargs.pop('stop', None)
+        step = kwargs.pop('step', None)
+
+        if isinstance(metric, str):
+            metric_func = get_path_metric_func(str(metric))
+        else:
+            metric_func = metric
+        numpaths = self.npaths
+        D = np.zeros((numpaths,numpaths))
+
+        for i in range(0, numpaths-1):
+            for j in range(i+1, numpaths):
+                P = self.paths[i][start:stop:step]
+                Q = self.paths[j][start:stop:step]
+                D[i,j] = metric_func(P, Q)
+                D[j,i] = D[i,j]
+        self.D = D

+
+
[docs]    def run_pairs_analysis(self, **kwargs):
+        """Perform PSA Hausdorff (nearest neighbor) pairs analysis on all unique
+        pairs of paths in :attr:`PSAnalysis.paths`.
+
+        Partial results can be stored in separate lists, where each list is
+        indexed according to distance vector convention (i.e., element *(i,j)*
+        in distance matrix representation corresponds to element
+        :math:`s=N*i+j-(i+1)*(i+2)` in distance vector representation, which is
+        the :math:`s`:sup:`th` comparison). For each unique pair of paths, the
+        nearest neighbors for that pair can be stored in :attr:`NN` and the
+        Hausdorff pair in :attr:`HP`. :attr:`PP` stores the full information
+        of Hausdorff pairs analysis that is available for each pair of path,
+        including nearest neighbors lists and the Hausdorff pairs.
+
+        The pairwise distances are stored as the array :attr:`PSAnalysis.D`.
+
+        Parameters
+        ----------
+        start : int
+             `start` and `stop` frame index with `step` size: analyze
+             ``trajectory[start:stop:step]`` [``None``]
+        stop : int
+        step : int
+        neighbors : bool
+             if ``True``, then stores dictionary of nearest neighbor
+             frames/distances in :attr:`PSAnalysis.NN` [``False``]
+        hausdorff_pairs : bool
+             if ``True``, then stores dictionary of Hausdorff pair
+             frames/distances in :attr:`PSAnalysis.HP` [``False``]
+        """
+        start = kwargs.pop('start', None)
+        stop = kwargs.pop('stop', None)
+        step = kwargs.pop('step', None)
+        neighbors = kwargs.pop('neighbors', False)
+        hausdorff_pairs = kwargs.pop('hausdorff_pairs', False)
+
+        numpaths = self.npaths
+        D = np.zeros((numpaths,numpaths))
+        self._NN = [] # list of nearest neighbors pairs
+        self._HP = [] # list of Hausdorff pairs
+        self._psa_pairs = [] # list of PSAPairs
+
+        for i in range(0, numpaths-1):
+            for j in range(i+1, numpaths):
+                pp = PSAPair(i, j, numpaths)
+                P = self.paths[i][start:stop:step]
+                Q = self.paths[j][start:stop:step]
+                pp.compute_nearest_neighbors(P, Q, self.natoms)
+                pp.find_hausdorff_pair()
+                D[i,j] = pp.hausdorff_pair['distance']
+                D[j,i] = D[i,j]
+                self._psa_pairs.append(pp)
+                if neighbors:
+                    self._NN.append(pp.get_nearest_neighbors())
+                if hausdorff_pairs:
+                    self._HP.append(pp.get_hausdorff_pair())
+        self.D = D

+
+
[docs]    def save_paths(self, filename=None):
+        """Save fitted :attr:`PSAnalysis.paths` to numpy compressed npz files.
+
+        The data are saved with :func:`numpy.savez_compressed` in the directory
+        specified by :attr:`PSAnalysis.targetdir`.
+
+        Parameters
+        ----------
+        filename : str
+             specifies filename [``None``]
+
+        Returns
+        -------
+        filename : str
+
+        See Also
+        --------
+        load
+
+        """
+        filename = filename or 'path_psa'
+        head = os.path.join(self.targetdir, self.datadirs['paths'])
+        outfile = os.path.join(head, filename)
+        if self.paths is None:
+            raise NoDataError("Paths have not been calculated yet")
+        path_names = []
+        for i, path in enumerate(self.paths):
+            current_outfile = "{0}{1:03n}.npy".format(outfile, i+1)
+            np.save(current_outfile, self.paths[i])
+            path_names.append(current_outfile)
+            logger.info("Wrote path to file %r", current_outfile)
+        self.path_names = path_names
+        with open(self._paths_pkl, 'wb') as output:
+            pickle.dump(self.path_names, output)
+        return filename

+
+
[docs]    def load(self):
+        """Load fitted paths specified by 'psa_path-names.pkl' in
+        :attr:`PSAnalysis.targetdir`.
+
+        All filenames are determined by :class:`PSAnalysis`.
+
+        See Also
+        --------
+        save_paths
+
+        """
+        if not os.path.exists(self._paths_pkl):
+            raise NoDataError("Fitted trajectories cannot be loaded; save file" +
+                              "{0} does not exist.".format(self._paths_pkl))
+        self.path_names = np.load(self._paths_pkl, allow_pickle=True)
+        self.paths = [np.load(pname) for pname in self.path_names]
+        if os.path.exists(self._labels_pkl):
+            self.labels = np.load(self._labels_pkl, allow_pickle=True)
+        logger.info("Loaded paths from %r", self._paths_pkl)

+
+
[docs]    def plot(self, filename=None, linkage='ward', count_sort=False,
+             distance_sort=False, figsize=4.5, labelsize=12):
+        """Plot a clustered distance matrix.
+
+        Usese method *linkage* and plots the corresponding dendrogram. Rows
+        (and columns) are identified using the list of strings specified by
+        :attr:`PSAnalysis.labels`.
+
+        If `filename` is supplied then the figure is also written to file (the
+        suffix determines the file type, e.g. pdf, png, eps, ...). All other
+        keyword arguments are passed on to :func:`matplotlib.pyplot.matshow`.
+
+
+        Parameters
+        ----------
+        filename : str
+             save figure to *filename* [``None``]
+        linkage : str
+             name of linkage criterion for clustering [``'ward'``]
+        count_sort : bool
+             see :func:`scipy.cluster.hierarchy.dendrogram` [``False``]
+        distance_sort : bool
+             see :func:`scipy.cluster.hierarchy.dendrogram` [``False``]
+        figsize : float
+             set the vertical size of plot in inches [``4.5``]
+        labelsize : float
+             set the font size for colorbar labels; font size for path labels on
+             dendrogram default to 3 points smaller [``12``]
+
+        Returns
+        -------
+        Z
+          `Z` from :meth:`cluster`
+        dgram
+          `dgram` from :meth:`cluster`
+        dist_matrix_clus
+          clustered distance matrix (reordered)
+
+        .. versionchanged:: 1.0.0
+            :attr:`tick1On`, :attr:`tick2On`, :attr:`label1On` and :attr:`label2On`
+            changed to :attr:`tick1line`, :attr:`tick2line`, :attr:`label1` and
+            :attr:`label2` due to upstream deprecation (see #2493)
+        """
+        from matplotlib.pyplot import figure, colorbar, cm, savefig, clf
+
+        if self.D is None:
+            raise ValueError(
+                "No distance data; do 'PSAnalysis.run()' first.")
+        npaths = len(self.D)
+        dist_matrix = self.D
+
+        dgram_loc, hmap_loc, cbar_loc = self._get_plot_obj_locs()
+        aspect_ratio = 1.25
+        clf()
+        fig = figure(figsize=(figsize*aspect_ratio, figsize))
+        ax_hmap = fig.add_axes(hmap_loc)
+        ax_dgram = fig.add_axes(dgram_loc)
+
+        Z, dgram = self.cluster(method=linkage,                                 \
+                                count_sort=count_sort,                          \
+                                distance_sort=distance_sort)
+        rowidx = colidx = dgram['leaves'] # get row-wise ordering from clustering
+        ax_dgram.invert_yaxis() # Place origin at up left (from low left)
+
+        minDist, maxDist = 0, np.max(dist_matrix)
+        dist_matrix_clus = dist_matrix[rowidx,:]
+        dist_matrix_clus = dist_matrix_clus[:,colidx]
+        im = ax_hmap.matshow(dist_matrix_clus, aspect='auto', origin='lower',   \
+                    cmap=cm.YlGn, vmin=minDist, vmax=maxDist)
+        ax_hmap.invert_yaxis() # Place origin at upper left (from lower left)
+        ax_hmap.locator_params(nbins=npaths)
+        ax_hmap.set_xticks(np.arange(npaths), minor=True)
+        ax_hmap.set_yticks(np.arange(npaths), minor=True)
+        ax_hmap.tick_params(axis='x', which='both', labelleft='off',            \
+                        labelright='off', labeltop='on', labelsize=0)
+        ax_hmap.tick_params(axis='y', which='both', labelleft='on',             \
+                labelright='off', labeltop='off', labelsize=0)
+        rowlabels = [self.labels[i] for i in rowidx]
+        collabels = [self.labels[i] for i in colidx]
+        ax_hmap.set_xticklabels(collabels, rotation='vertical',                 \
+                size=(labelsize-4), multialignment='center', minor=True)
+        ax_hmap.set_yticklabels(rowlabels, rotation='horizontal',               \
+                size=(labelsize-4), multialignment='left', ha='right',          \
+                minor=True)
+
+        ax_color = fig.add_axes(cbar_loc)
+        colorbar(im, cax=ax_color, ticks=np.linspace(minDist, maxDist, 10),  \
+                format="%0.1f")
+        ax_color.tick_params(labelsize=labelsize)
+
+        # Remove major ticks and labels from both heat map axes
+        for tic in ax_hmap.xaxis.get_major_ticks():
+            tic.tick1line.set_visible(False)
+            tic.tick2line.set_visible(False)
+            tic.label1.set_visible(False)
+            tic.label2.set_visible(False)
+        for tic in ax_hmap.yaxis.get_major_ticks():
+            tic.tick1line.set_visible(False)
+            tic.tick2line.set_visible(False)
+            tic.label1.set_visible(False)
+            tic.label2.set_visible(False)
+        # Remove minor ticks from both heat map axes
+        for tic in ax_hmap.xaxis.get_minor_ticks():
+            tic.tick1line.set_visible(False)
+            tic.tick2line.set_visible(False)
+        for tic in ax_hmap.yaxis.get_minor_ticks():
+            tic.tick1line.set_visible(False)
+            tic.tick2line.set_visible(False)
+        # Remove tickmarks from colorbar
+        for tic in ax_color.yaxis.get_major_ticks():
+            tic.tick1line.set_visible(False)
+            tic.tick2line.set_visible(False)
+
+        if filename is not None:
+            head = os.path.join(self.targetdir, self.datadirs['plots'])
+            outfile = os.path.join(head, filename)
+            savefig(outfile, dpi=300, bbox_inches='tight')
+
+        return Z, dgram, dist_matrix_clus

+
+
[docs]    def plot_annotated_heatmap(self, filename=None, linkage='ward',             \
+                               count_sort=False, distance_sort=False,           \
+                               figsize=8, annot_size=6.5):
+        """Plot a clustered distance matrix.
+
+        Uses method `linkage` and plots annotated distances in the matrix. Rows
+        (and columns) are identified using the list of strings specified by
+        :attr:`PSAnalysis.labels`.
+
+        If `filename` is supplied then the figure is also written to file (the
+        suffix determines the file type, e.g. pdf, png, eps, ...). All other
+        keyword arguments are passed on to :func:`matplotlib.pyplot.imshow`.
+
+        Parameters
+        ----------
+        filename : str
+             save figure to *filename* [``None``]
+        linkage : str
+             name of linkage criterion for clustering [``'ward'``]
+        count_sort : bool
+             see :func:`scipy.cluster.hierarchy.dendrogram` [``False``]
+        distance_sort : bool
+             see :func:`scipy.cluster.hierarchy.dendrogram` [``False``]
+        figsize : float
+             set the vertical size of plot in inches [``4.5``]
+        annot_size : float
+             font size of annotation labels on heat map [``6.5``]
+
+        Returns
+        -------
+        Z
+          `Z` from :meth:`cluster`
+        dgram
+          `dgram` from :meth:`cluster`
+        dist_matrix_clus
+          clustered distance matrix (reordered)
+
+
+        Note
+        ----
+        This function requires the seaborn_ package, which can be installed
+        with `pip install seaborn` or `conda install seaborn`.
+
+        .. _seaborn: https://seaborn.pydata.org/
+
+        .. versionchanged:: 1.0.0
+            :attr:`tick1On`, :attr:`tick2On`, :attr:`label1On` and :attr:`label2On`
+            changed to :attr:`tick1line`, :attr:`tick2line`, :attr:`label1` and
+            :attr:`label2` due to upstream deprecation (see #2493)
+
+        """
+        from matplotlib.pyplot import figure, colorbar, cm, savefig, clf
+
+        try:
+            import seaborn as sns
+        except ImportError:
+            raise ImportError(
+                """ERROR --- The seaborn package cannot be found!
+
+                The seaborn API could not be imported. Please install it first.
+                You can try installing with pip directly from the
+                internet:
+
+                  pip install seaborn
+
+                Alternatively, download the package from
+
+                  http://pypi.python.org/pypi/seaborn/
+
+                and install in the usual manner.
+                """
+                ) from None
+
+        if self.D is None:
+            raise ValueError(
+                "No distance data; do 'PSAnalysis.run()' first.")
+        dist_matrix = self.D
+
+        Z, dgram = self.cluster(method=linkage,                                 \
+                                count_sort=count_sort,                          \
+                                distance_sort=distance_sort,                    \
+                                no_plot=True)
+        rowidx = colidx = dgram['leaves'] # get row-wise ordering from clustering
+        dist_matrix_clus = dist_matrix[rowidx,:]
+        dist_matrix_clus = dist_matrix_clus[:,colidx]
+
+        clf()
+        aspect_ratio = 1.25
+        fig = figure(figsize=(figsize*aspect_ratio, figsize))
+        ax_hmap = fig.add_subplot(111)
+        ax_hmap = sns.heatmap(dist_matrix_clus,                                 \
+                         linewidths=0.25, cmap=cm.YlGn, annot=True, fmt='3.1f', \
+                         square=True, xticklabels=rowidx, yticklabels=colidx,   \
+                         annot_kws={"size": 7}, ax=ax_hmap)
+
+        # Remove major ticks from both heat map axes
+        for tic in ax_hmap.xaxis.get_major_ticks():
+            tic.tick1line.set_visible(False)
+            tic.tick2line.set_visible(False)
+            tic.label1.set_visible(False)
+            tic.label2.set_visible(False)
+        for tic in ax_hmap.yaxis.get_major_ticks():
+            tic.tick1line.set_visible(False)
+            tic.tick2line.set_visible(False)
+            tic.label1.set_visible(False)
+            tic.label2.set_visible(False)
+        # Remove minor ticks from both heat map axes
+        for tic in ax_hmap.xaxis.get_minor_ticks():
+            tic.tick1line.set_visible(False)
+            tic.tick2line.set_visible(False)
+        for tic in ax_hmap.yaxis.get_minor_ticks():
+            tic.tick1line.set_visible(False)
+            tic.tick2line.set_visible(False)
+
+        if filename is not None:
+            head = os.path.join(self.targetdir, self.datadirs['plots'])
+            outfile = os.path.join(head, filename)
+            savefig(outfile, dpi=600, bbox_inches='tight')
+
+        return Z, dgram, dist_matrix_clus

+
+
[docs]    def plot_nearest_neighbors(self, filename=None, idx=0,                      \
+                               labels=('Path 1', 'Path 2'), figsize=4.5,        \
+                               multiplot=False, aspect_ratio=1.75,              \
+                               labelsize=12):
+        """Plot nearest neighbor distances as a function of normalized frame
+        number.
+
+        The frame number is mapped to the interval *[0, 1]*.
+
+        If `filename` is supplied then the figure is also written to file (the
+        suffix determines the file type, e.g. pdf, png, eps, ...). All other
+        keyword arguments are passed on to :func:`matplotlib.pyplot.imshow`.
+
+        Parameters
+        ----------
+        filename : str
+             save figure to *filename* [``None``]
+        idx : int
+             index of path (pair) comparison to plot [``0``]
+        labels : (str, str)
+             pair of names to label nearest neighbor distance
+             curves [``('Path 1', 'Path 2')``]
+        figsize : float
+             set the vertical size of plot in inches [``4.5``]
+        multiplot : bool
+             set to ``True`` to enable plotting multiple nearest
+             neighbor distances on the same figure [``False``]
+        aspect_ratio : float
+             set the ratio of width to height of the plot [``1.75``]
+        labelsize : float
+             set the font size for colorbar labels; font size for path labels on
+             dendrogram default to 3 points smaller [``12``]
+
+        Returns
+        -------
+        ax : axes
+
+        Note
+        ----
+        This function requires the seaborn_ package, which can be installed
+        with `pip install seaborn` or `conda install seaborn`.
+
+        .. _seaborn: https://seaborn.pydata.org/
+
+        """
+        from matplotlib.pyplot import figure, savefig, tight_layout, clf, show
+        try:
+            import seaborn as sns
+        except ImportError:
+            raise ImportError(
+                """ERROR --- The seaborn package cannot be found!
+
+                The seaborn API could not be imported. Please install it first.
+                You can try installing with pip directly from the
+                internet:
+
+                  pip install seaborn
+
+                Alternatively, download the package from
+
+                  http://pypi.python.org/pypi/seaborn/
+
+                and install in the usual manner.
+                """
+                ) from None
+
+        colors = sns.xkcd_palette(["cherry", "windows blue"])
+
+        if self._NN is None:
+            raise ValueError("No nearest neighbor data; run "
+                             "'PSAnalysis.run_pairs_analysis(neighbors=True)' first.")
+
+        sns.set_style('whitegrid')
+
+        if not multiplot:
+            clf()
+        fig = figure(figsize=(figsize*aspect_ratio, figsize))
+        ax = fig.add_subplot(111)
+
+        nn_dist_P, nn_dist_Q = self._NN[idx]['distances']
+        frames_P = len(nn_dist_P)
+        frames_Q = len(nn_dist_Q)
+        progress_P = np.asarray(range(frames_P))/(1.0*frames_P)
+        progress_Q = np.asarray(range(frames_Q))/(1.0*frames_Q)
+
+        ax.plot(progress_P, nn_dist_P, color=colors[0], lw=1.5, label=labels[0])
+        ax.plot(progress_Q, nn_dist_Q, color=colors[1], lw=1.5, label=labels[1])
+
+        ax.legend()
+        ax.set_xlabel(r'(normalized) progress by frame number', fontsize=12)
+        ax.set_ylabel(r'nearest neighbor rmsd ($\AA$)', fontsize=12)
+        ax.tick_params(axis='both', which='major', labelsize=12, pad=4)
+
+        sns.despine(bottom=True, left=True, ax=ax)
+        tight_layout()
+
+        if filename is not None:
+            head = os.path.join(self.targetdir, self.datadirs['plots'])
+            outfile = os.path.join(head, filename)
+            savefig(outfile, dpi=300, bbox_inches='tight')
+
+        return ax

+
+
[docs]    def cluster(self, dist_mat=None, method='ward', count_sort=False,           \
+                distance_sort=False, no_plot=False, no_labels=True,             \
+                color_threshold=4):
+        """Cluster trajectories and optionally plot the dendrogram.
+
+        This method is used by :meth:`PSAnalysis.plot` to generate a heatmap-
+        dendrogram combination plot. By default, the distance matrix,
+        :attr:`PSAnalysis.D`, is assumed to exist, converted to
+        distance-vector form, and inputted to :func:`cluster.hierarchy.linkage`
+        to generate a clustering. For convenience in plotting arbitrary
+        distance matrices, one can also be specify `dist_mat`, which will be
+        checked for proper distance matrix form by
+        :func:`spatial.distance.squareform`
+
+        Parameters
+        ----------
+        dist_mat : numpy.ndarray
+            user-specified distance matrix to be clustered [``None``]
+        method : str
+            name of linkage criterion for clustering [``'ward'``]
+        no_plot : bool
+            if ``True``, do not render the dendrogram [``False``]
+        no_labels : bool
+            if ``True`` then do not label dendrogram [``True``]
+        color_threshold : float
+            For brevity, let t be the color_threshold. Colors all the
+            descendent links below a cluster node k the same color if k is
+            the first node below the cut threshold t. All links connecting
+            nodes with distances greater than or equal to the threshold are
+            colored blue. If t is less than or equal to zero, all nodes are
+            colored blue. If color_threshold is None or ‘default’,
+            corresponding with MATLAB(TM) behavior, the threshold is set to
+            0.7*max(Z[:,2]). [``4``]]
+
+        Returns
+        -------
+        Z
+            output from :func:`scipy.cluster.hierarchy.linkage`;
+            list of indices representing the row-wise order of the objects
+            after clustering
+        dgram
+            output from :func:`scipy.cluster.hierarchy.dendrogram`
+        """
+        # perhaps there is a better way to manipulate the plot... or perhaps it
+        # is not even necessary? In any case, the try/finally makes sure that
+        # we are not permanently changing the user's global state
+        orig_linewidth = matplotlib.rcParams['lines.linewidth']
+        matplotlib.rcParams['lines.linewidth'] = 0.5
+        try:
+            if dist_mat:
+                dist_vec = spatial.distance.squareform(dist_mat,
+                                                       force='tovector',
+                                                       checks=True)
+            else:
+                dist_vec = self.get_pairwise_distances(vectorform=True)
+            Z = cluster.hierarchy.linkage(dist_vec, method=method)
+            dgram = cluster.hierarchy.dendrogram(
+                Z, no_labels=no_labels, orientation='left',
+                count_sort=count_sort, distance_sort=distance_sort,
+                no_plot=no_plot, color_threshold=color_threshold)
+        finally:
+            matplotlib.rcParams['lines.linewidth'] = orig_linewidth
+        return Z, dgram

+
+    def _get_plot_obj_locs(self):
+        """Find and return coordinates for dendrogram, heat map, and colorbar.
+
+        Returns
+        -------
+        tuple
+          tuple of coordinates for placing the dendrogram, heat map, and
+          colorbar in the plot.
+        """
+        plot_xstart = 0.04
+        plot_ystart = 0.04
+        label_margin = 0.155
+
+        dgram_height = 0.2 # dendrogram heights(s)
+        hmap_xstart = plot_xstart + dgram_height + label_margin
+
+        # Set locations for dendrogram(s), matrix, and colorbar
+        hmap_height = 0.8
+        hmap_width = 0.6
+        dgram_loc = [plot_xstart, plot_ystart, dgram_height, hmap_height]
+        cbar_width = 0.02
+        cbar_xstart = hmap_xstart + hmap_width + 0.01
+        cbar_loc = [cbar_xstart, plot_ystart, cbar_width, hmap_height]
+        hmap_loc =  [hmap_xstart, plot_ystart, hmap_width, hmap_height]
+
+        return dgram_loc, hmap_loc, cbar_loc
+
+
[docs]    def get_num_atoms(self):
+        """Return the number of atoms used to construct the :class:`Path` instances in
+        :class:`PSA`.
+
+        Returns
+        -------
+        int
+            the number of atoms in any path
+
+        Note
+        ----
+        Must run :meth:`PSAnalysis.generate_paths` prior to calling this
+        method.
+        """
+        if self.natoms is None:
+            raise ValueError(
+                "No path data; do 'PSAnalysis.generate_paths()' first.")
+        return self.natoms

+
+
[docs]    def get_num_paths(self):
+        """Return the number of paths in :class:`PSA`.
+
+        Note
+        ----
+        Must run :meth:`PSAnalysis.generate_paths` prior to calling this method.
+
+        Returns
+        -------
+        int
+           the number of paths in :class:`PSA`
+        """
+        if self.npaths is None:
+            raise ValueError(
+                "No path data; do 'PSAnalysis.generate_paths()' first.")
+        return self.npaths

+
+
[docs]    def get_paths(self):
+        """Return the paths in :class:`PSA`.
+
+        Note
+        ----
+        Must run :meth:`PSAnalysis.generate_paths` prior to calling this
+        method.
+
+        Returns
+        -------
+        list
+            list of :class:`numpy.ndarray` representations of paths in
+            :class:`PSA`
+        """
+        if self.paths is None:
+            raise ValueError(
+                "No path data; do 'PSAnalysis.generate_paths()' first.")
+        return self.paths

+
+
[docs]    def get_pairwise_distances(self, vectorform=False, checks=False):
+        """Return the distance matrix (or vector) of pairwise path distances.
+
+        Note
+        ----
+        Must run :meth:`PSAnalysis.run` prior to calling this method.
+
+        Parameters
+        ----------
+        vectorform : bool
+             if ``True``, return the distance vector instead [``False``]
+        checks : bool
+             if ``True``, check that :attr:`PSAnalysis.D` is a proper distance
+             matrix [``False``]
+
+        Returns
+        -------
+        numpy.ndarray
+             representation of the distance matrix (or vector)
+
+        """
+        if self.D is None:
+            raise ValueError(
+                "No distance data; do 'PSAnalysis.run()' first.")
+        if vectorform:
+            return spatial.distance.squareform(self.D, force='tovector',
+                                               checks=checks)
+        else:
+            return self.D

+
+    @property
+    def psa_pairs(self):
+        """The list of :class:`PSAPair` instances for each pair of paths.
+
+        :attr:`psa_pairs` is a list of all :class:`PSAPair` objects (in
+        distance vector order). The elements of a :class:`PSAPair` are pairs of
+        paths that have been compared using
+        :meth:`PSAnalysis.run_pairs_analysis`. Each :class:`PSAPair` contains
+        nearest neighbor and Hausdorff pair information specific to a pair of
+        paths. The nearest neighbor frames and distances for a :class:`PSAPair`
+        can be accessed in the nearest neighbor dictionary using the keys
+        'frames' and 'distances', respectively. E.g.,
+        :attr:`PSAPair.nearest_neighbors['distances']` returns a *pair* of
+        :class:`numpy.ndarray` corresponding to the nearest neighbor distances
+        for each path. Similarly, Hausdorff pair information can be accessed
+        using :attr:`PSAPair.hausdorff_pair` with the keys 'frames' and
+        'distance'.
+
+        Note
+        ----
+        Must run :meth:`PSAnalysis.run_pairs_analysis` prior to calling this
+        method.
+
+        """
+        if self._psa_pairs is None:
+            raise ValueError("No nearest neighbors data; do"
+                             " 'PSAnalysis.run_pairs_analysis()' first.")
+        return self._psa_pairs
+
+    @property
+    def hausdorff_pairs(self):
+        """The Hausdorff pair for each (unique) pairs of paths.
+
+        This attribute contains a list of Hausdorff pair information (in
+        distance vector order), where each element is a dictionary containing
+        the pair of frames and the (Hausdorff) distance between a pair of
+        paths. See :meth:`PSAnalysis.psa_pairs` and
+        :attr:`PSAPair.hausdorff_pair` for more information about accessing
+        Hausdorff pair data.
+
+        Note
+        ----
+        Must run :meth:`PSAnalysis.run_pairs_analysis` with
+        ``hausdorff_pairs=True`` prior to calling this method.
+
+        """
+        if self._HP is None:
+            raise ValueError("No Hausdorff pairs data; do "
+                             "'PSAnalysis.run_pairs_analysis(hausdorff_pairs=True)' "
+                             "first.")
+        return self._HP
+
+    @property
+    def nearest_neighbors(self):
+        """The nearest neighbors for each (unique) pair of paths.
+
+        This attribute contains a list of nearest neighbor information (in
+        distance vector order), where each element is a dictionary containing
+        the nearest neighbor frames and distances between a pair of paths. See
+        :meth:`PSAnalysis.psa_pairs` and :attr:`PSAPair.nearest_neighbors` for
+        more information about accessing nearest neighbor data.
+
+        Note
+        ----
+        Must run :meth:`PSAnalysis.run_pairs_analysis` with
+        ``neighbors=True`` prior to calling this method.
+
+        """
+        if self._NN is None:
+            raise ValueError("No nearest neighbors data; do"
+                             " 'PSAnalysis.run_pairs_analysis(neighbors=True)'"
+                             " first.")
+        return self._NN

+
+ +
+
+ +
+
+
+
+ + +
+ + + + + + +
+
+
Other Versions
+
+ +
+
+ + + \ No newline at end of file diff --git a/_sources/api.rst.txt b/_sources/api.rst.txt new file mode 100644 index 0000000..a60c504 --- /dev/null +++ b/_sources/api.rst.txt @@ -0,0 +1,4 @@ +API Documentation +================= + +.. automodule:: pathsimanalysis.psa diff --git a/_sources/getting_started.rst.txt b/_sources/getting_started.rst.txt new file mode 100644 index 0000000..dfd56bb --- /dev/null +++ b/_sources/getting_started.rst.txt @@ -0,0 +1,15 @@ +Getting Started +=============== + +This page details how to get started with PathSimAnalysis. + +Installation +------------ + +PathSimAnalysis is currently only installable from source. + +.. code-block:: bash + + git clone --depth=1 https://github.com/MDAnalysis/PathSimAnalysis + cd PathSimAnalysis + pip install . \ No newline at end of file diff --git a/_sources/index.rst.txt b/_sources/index.rst.txt new file mode 100644 index 0000000..bcec6b7 --- /dev/null +++ b/_sources/index.rst.txt @@ -0,0 +1,25 @@ +.. pathsimanalysis documentation master file, created by + sphinx-quickstart on Thu Mar 15 13:55:56 2018. + You can adapt this file completely to your liking, but it should at least + contain the root `toctree` directive. + +Welcome to PathSimAnalysis's documentation! +========================================================= + +PathSimAnalysis is an MDAnalysis based analysis package for calculating the similarity between molecular dynamics trajectories. + +.. toctree:: + :maxdepth: 2 + :caption: Contents: + + getting_started + api + + + +Indices and tables +================== + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` diff --git a/_static/README.md b/_static/README.md new file mode 100644 index 0000000..8d30b2b --- /dev/null +++ b/_static/README.md @@ -0,0 +1,16 @@ +# Static Doc Directory + +Add any paths that contain custom static files (such as style sheets) here, +relative to the `conf.py` file's directory. +They are copied after the builtin static files, +so a file named "default.css" will overwrite the builtin "default.css". + +The path to this folder is set in the Sphinx `conf.py` file in the line: +```python +html_static_path = ['_static'] +``` + +## Examples of file to add to this directory +* Custom Cascading Style Sheets +* Custom JavaScript code +* Static logo images diff --git a/_static/_sphinx_javascript_frameworks_compat.js b/_static/_sphinx_javascript_frameworks_compat.js new file mode 100644 index 0000000..8141580 --- /dev/null +++ b/_static/_sphinx_javascript_frameworks_compat.js @@ -0,0 +1,123 @@ +/* Compatability shim for jQuery and underscores.js. + * + * Copyright Sphinx contributors + * Released under the two clause BSD licence + */ + +/** + * small helper function to urldecode strings + * + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL + */ +jQuery.urldecode = function(x) { + if (!x) { + return x + } + return decodeURIComponent(x.replace(/\+/g, ' ')); +}; + +/** + * small helper function to urlencode strings + */ +jQuery.urlencode = encodeURIComponent; + +/** + * This function returns the parsed url parameters of the + * current request. 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+div.sphinxsidebar { + float: left; + width: 230px; + margin-left: -100%; + font-size: 90%; + word-wrap: break-word; + overflow-wrap : break-word; +} + +div.sphinxsidebar ul { + list-style: none; +} + +div.sphinxsidebar ul ul, +div.sphinxsidebar ul.want-points { + margin-left: 20px; + list-style: square; +} + +div.sphinxsidebar ul ul { + margin-top: 0; + margin-bottom: 0; +} + +div.sphinxsidebar form { + margin-top: 10px; +} + +div.sphinxsidebar input { + border: 1px solid #98dbcc; + font-family: sans-serif; + font-size: 1em; +} + +div.sphinxsidebar #searchbox form.search { + overflow: hidden; +} + +div.sphinxsidebar #searchbox input[type="text"] { + float: left; + width: 80%; + padding: 0.25em; + box-sizing: border-box; +} + +div.sphinxsidebar #searchbox input[type="submit"] { + float: left; + width: 20%; + border-left: none; + padding: 0.25em; + box-sizing: border-box; +} + + +img { + border: 0; + max-width: 100%; +} + +/* -- search page ----------------------------------------------------------- */ + +ul.search { + margin: 10px 0 0 20px; + padding: 0; +} + +ul.search li { + padding: 5px 0 5px 20px; + background-image: url(file.png); + background-repeat: no-repeat; + background-position: 0 7px; +} + +ul.search li a { + font-weight: bold; +} + +ul.search li p.context { + color: #888; + margin: 2px 0 0 30px; + text-align: left; +} + +ul.keywordmatches li.goodmatch a { + font-weight: bold; +} + +/* -- index page ------------------------------------------------------------ */ + +table.contentstable { + width: 90%; + margin-left: auto; + margin-right: auto; +} + +table.contentstable p.biglink { + line-height: 150%; +} + +a.biglink { + font-size: 1.3em; +} + +span.linkdescr { + font-style: italic; + padding-top: 5px; + font-size: 90%; +} + +/* -- general index --------------------------------------------------------- */ + +table.indextable { + width: 100%; +} + +table.indextable td { + text-align: left; + vertical-align: 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+ + +/* Non-minified version is copied as a separate JS file, is available */ + +/** + * Porter Stemmer + */ +var Stemmer = function() { + + var step2list = { + ational: 'ate', + tional: 'tion', + enci: 'ence', + anci: 'ance', + izer: 'ize', + bli: 'ble', + alli: 'al', + entli: 'ent', + eli: 'e', + ousli: 'ous', + ization: 'ize', + ation: 'ate', + ator: 'ate', + alism: 'al', + iveness: 'ive', + fulness: 'ful', + ousness: 'ous', + aliti: 'al', + iviti: 'ive', + biliti: 'ble', + logi: 'log' + }; + + var step3list = { + icate: 'ic', + ative: '', + alize: 'al', + iciti: 'ic', + ical: 'ic', + ful: '', + ness: '' + }; + + var c = "[^aeiou]"; // consonant + var v = "[aeiouy]"; // vowel + var C = c + "[^aeiouy]*"; // consonant sequence + var V = v + "[aeiou]*"; // vowel sequence + + var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0 + var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1 + var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1 + var s_v = "^(" + C + ")?" + v; // vowel in stem + + this.stemWord = function (w) { + var stem; + var suffix; + var firstch; + var origword = w; + + if (w.length < 3) + return w; + + var re; + var re2; + var re3; + var re4; + + firstch = w.substr(0,1); + if (firstch == "y") + w = firstch.toUpperCase() + w.substr(1); + + // Step 1a + re = /^(.+?)(ss|i)es$/; + re2 = /^(.+?)([^s])s$/; + + if (re.test(w)) + w = w.replace(re,"$1$2"); + else if (re2.test(w)) + w = w.replace(re2,"$1$2"); + + // Step 1b + re = /^(.+?)eed$/; + re2 = /^(.+?)(ed|ing)$/; + if (re.test(w)) { + var fp = re.exec(w); + re = new RegExp(mgr0); + if (re.test(fp[1])) { + re = /.$/; + w = w.replace(re,""); + } + } + else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1]; + re2 = new RegExp(s_v); + if (re2.test(stem)) { + w = stem; + re2 = /(at|bl|iz)$/; + re3 = new RegExp("([^aeiouylsz])\\1$"); + re4 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + if (re2.test(w)) + w = w + "e"; + else if (re3.test(w)) { + re = /.$/; + w = w.replace(re,""); + } + else if (re4.test(w)) + w = w + "e"; + } + } + + // Step 1c + re = /^(.+?)y$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(s_v); + if (re.test(stem)) + w = stem + "i"; + } + + // Step 2 + re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = new RegExp(mgr0); + if (re.test(stem)) + w = stem + step2list[suffix]; + } + + // Step 3 + re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = new RegExp(mgr0); + if (re.test(stem)) + w = stem + step3list[suffix]; + } + + // Step 4 + re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; + re2 = /^(.+?)(s|t)(ion)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(mgr1); + if (re.test(stem)) + w = stem; + } + else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1] + fp[2]; + re2 = new RegExp(mgr1); + if (re2.test(stem)) + w = stem; + } + + // Step 5 + re = /^(.+?)e$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(mgr1); + re2 = new RegExp(meq1); + re3 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) + w = stem; + } + re = /ll$/; + re2 = new RegExp(mgr1); + if (re.test(w) && re2.test(w)) { + re = /.$/; + w = w.replace(re,""); + } + + // and turn initial Y back to y + if (firstch == "y") + w = firstch.toLowerCase() + w.substr(1); + return w; + } +} + diff --git a/_static/logo/mda_favicon.ico b/_static/logo/mda_favicon.ico new file mode 100644 index 0000000..3c102d0 Binary files /dev/null and b/_static/logo/mda_favicon.ico differ diff --git a/_static/logo/mda_logo.png b/_static/logo/mda_logo.png new file mode 100644 index 0000000..6553570 Binary files /dev/null and b/_static/logo/mda_logo.png differ diff --git a/_static/logo/placeholder_favicon.svg b/_static/logo/placeholder_favicon.svg new file mode 100644 index 0000000..cf62228 --- /dev/null +++ b/_static/logo/placeholder_favicon.svg @@ -0,0 +1,46 @@ + + + + + + + + + + + + + + + diff --git a/_static/logo/placeholder_logo.png b/_static/logo/placeholder_logo.png new file mode 100644 index 0000000..77e9056 Binary files /dev/null and b/_static/logo/placeholder_logo.png differ diff --git a/_static/minus.png b/_static/minus.png new file mode 100644 index 0000000..d96755f Binary files /dev/null and b/_static/minus.png differ diff --git a/_static/plus.png b/_static/plus.png new file mode 100644 index 0000000..7107cec Binary files /dev/null and b/_static/plus.png differ diff --git a/_static/pygments.css b/_static/pygments.css new file mode 100644 index 0000000..84ab303 --- /dev/null +++ b/_static/pygments.css @@ -0,0 +1,75 @@ +pre { line-height: 125%; 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+ +/** + * Simple result scoring code. + */ +if (typeof Scorer === "undefined") { + var Scorer = { + // Implement the following function to further tweak the score for each result + // The function takes a result array [docname, title, anchor, descr, score, filename] + // and returns the new score. + /* + score: result => { + const [docname, title, anchor, descr, score, filename] = result + return score + }, + */ + + // query matches the full name of an object + objNameMatch: 11, + // or matches in the last dotted part of the object name + objPartialMatch: 6, + // Additive scores depending on the priority of the object + objPrio: { + 0: 15, // used to be importantResults + 1: 5, // used to be objectResults + 2: -5, // used to be unimportantResults + }, + // Used when the priority is not in the mapping. + objPrioDefault: 0, + + // query found in title + title: 15, + partialTitle: 7, + // query found in terms + term: 5, + partialTerm: 2, + }; +} + +const _removeChildren = (element) => { + while (element && element.lastChild) element.removeChild(element.lastChild); +}; + +/** + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping + */ +const _escapeRegExp = (string) => + string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string + +const _displayItem = (item, searchTerms) => { + const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; + const docUrlRoot = DOCUMENTATION_OPTIONS.URL_ROOT; + const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; + const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; + const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; + + const [docName, title, anchor, descr, score, _filename] = item; + + let listItem = document.createElement("li"); + let requestUrl; + let linkUrl; + if (docBuilder === "dirhtml") { + // dirhtml builder + let dirname = docName + "/"; + if (dirname.match(/\/index\/$/)) + dirname = dirname.substring(0, dirname.length - 6); + else if (dirname === "index/") dirname = ""; + requestUrl = docUrlRoot + dirname; + linkUrl = requestUrl; + } else { + // normal html builders + requestUrl = docUrlRoot + docName + docFileSuffix; + linkUrl = docName + docLinkSuffix; + } + let linkEl = listItem.appendChild(document.createElement("a")); + linkEl.href = linkUrl + anchor; + linkEl.dataset.score = score; + linkEl.innerHTML = title; + if (descr) + listItem.appendChild(document.createElement("span")).innerHTML = + " (" + descr + ")"; + else if (showSearchSummary) + fetch(requestUrl) + .then((responseData) => responseData.text()) + .then((data) => { + if (data) + listItem.appendChild( + Search.makeSearchSummary(data, searchTerms) + ); + }); + Search.output.appendChild(listItem); +}; +const _finishSearch = (resultCount) => { + Search.stopPulse(); + Search.title.innerText = _("Search Results"); + if (!resultCount) + Search.status.innerText = Documentation.gettext( + "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories." + ); + else + Search.status.innerText = _( + `Search finished, found ${resultCount} page(s) matching the search query.` + ); +}; +const _displayNextItem = ( + results, + resultCount, + searchTerms +) => { + // results left, load the summary and display it + // this is intended to be dynamic (don't sub resultsCount) + if (results.length) { + _displayItem(results.pop(), searchTerms); + setTimeout( + () => _displayNextItem(results, resultCount, searchTerms), + 5 + ); + } + // search finished, update title and status message + else _finishSearch(resultCount); +}; + +/** + * Default splitQuery function. Can be overridden in ``sphinx.search`` with a + * custom function per language. + * + * The regular expression works by splitting the string on consecutive characters + * that are not Unicode letters, numbers, underscores, or emoji characters. + * This is the same as ``\W+`` in Python, preserving the surrogate pair area. + */ +if (typeof splitQuery === "undefined") { + var splitQuery = (query) => query + .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu) + .filter(term => term) // remove remaining empty strings +} + +/** + * Search Module + */ +const Search = { + _index: null, + _queued_query: null, + _pulse_status: -1, + + htmlToText: (htmlString) => { + const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html'); + htmlElement.querySelectorAll(".headerlink").forEach((el) => { el.remove() }); + const docContent = htmlElement.querySelector('[role="main"]'); + if (docContent !== undefined) return docContent.textContent; + console.warn( + "Content block not found. Sphinx search tries to obtain it via '[role=main]'. Could you check your theme or template." + ); + return ""; + }, + + init: () => { + const query = new URLSearchParams(window.location.search).get("q"); + document + .querySelectorAll('input[name="q"]') + .forEach((el) => (el.value = query)); + if (query) Search.performSearch(query); + }, + + loadIndex: (url) => + (document.body.appendChild(document.createElement("script")).src = url), + + setIndex: (index) => { + Search._index = index; + if (Search._queued_query !== null) { + const query = Search._queued_query; + Search._queued_query = null; + Search.query(query); + } + }, + + hasIndex: () => Search._index !== null, + + deferQuery: (query) => (Search._queued_query = query), + + stopPulse: () => (Search._pulse_status = -1), + + startPulse: () => { + if (Search._pulse_status >= 0) return; + + const pulse = () => { + Search._pulse_status = (Search._pulse_status + 1) % 4; + Search.dots.innerText = ".".repeat(Search._pulse_status); + if (Search._pulse_status >= 0) window.setTimeout(pulse, 500); + }; + pulse(); + }, + + /** + * perform a search for something (or wait until index is loaded) + */ + performSearch: (query) => { + // create the required interface elements + const searchText = document.createElement("h2"); + searchText.textContent = _("Searching"); + const searchSummary = document.createElement("p"); + searchSummary.classList.add("search-summary"); + searchSummary.innerText = ""; + const searchList = document.createElement("ul"); + searchList.classList.add("search"); + + const out = document.getElementById("search-results"); + Search.title = out.appendChild(searchText); + Search.dots = Search.title.appendChild(document.createElement("span")); + Search.status = out.appendChild(searchSummary); + Search.output = out.appendChild(searchList); + + const searchProgress = document.getElementById("search-progress"); + // Some themes don't use the search progress node + if (searchProgress) { + searchProgress.innerText = _("Preparing search..."); + } + Search.startPulse(); + + // index already loaded, the browser was quick! + if (Search.hasIndex()) Search.query(query); + else Search.deferQuery(query); + }, + + /** + * execute search (requires search index to be loaded) + */ + query: (query) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + const allTitles = Search._index.alltitles; + const indexEntries = Search._index.indexentries; + + // stem the search terms and add them to the correct list + const stemmer = new Stemmer(); + const searchTerms = new Set(); + const excludedTerms = new Set(); + const highlightTerms = new Set(); + const objectTerms = new Set(splitQuery(query.toLowerCase().trim())); + splitQuery(query.trim()).forEach((queryTerm) => { + const queryTermLower = queryTerm.toLowerCase(); + + // maybe skip this "word" + // stopwords array is from language_data.js + if ( + stopwords.indexOf(queryTermLower) !== -1 || + queryTerm.match(/^\d+$/) + ) + return; + + // stem the word + let word = stemmer.stemWord(queryTermLower); + // select the correct list + if (word[0] === "-") excludedTerms.add(word.substr(1)); + else { + searchTerms.add(word); + highlightTerms.add(queryTermLower); + } + }); + + if (SPHINX_HIGHLIGHT_ENABLED) { // set in sphinx_highlight.js + localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" ")) + } + + // console.debug("SEARCH: searching for:"); + // console.info("required: ", [...searchTerms]); + // console.info("excluded: ", [...excludedTerms]); + + // array of [docname, title, anchor, descr, score, filename] + let results = []; + _removeChildren(document.getElementById("search-progress")); + + const queryLower = query.toLowerCase(); + for (const [title, foundTitles] of Object.entries(allTitles)) { + if (title.toLowerCase().includes(queryLower) && (queryLower.length >= title.length/2)) { + for (const [file, id] of foundTitles) { + let score = Math.round(100 * queryLower.length / title.length) + results.push([ + docNames[file], + titles[file] !== title ? `${titles[file]} > ${title}` : title, + id !== null ? "#" + id : "", + null, + score, + filenames[file], + ]); + } + } + } + + // search for explicit entries in index directives + for (const [entry, foundEntries] of Object.entries(indexEntries)) { + if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) { + for (const [file, id] of foundEntries) { + let score = Math.round(100 * queryLower.length / entry.length) + results.push([ + docNames[file], + titles[file], + id ? "#" + id : "", + null, + score, + filenames[file], + ]); + } + } + } + + // lookup as object + objectTerms.forEach((term) => + results.push(...Search.performObjectSearch(term, objectTerms)) + ); + + // lookup as search terms in fulltext + results.push(...Search.performTermsSearch(searchTerms, excludedTerms)); + + // let the scorer override scores with a custom scoring function + if (Scorer.score) results.forEach((item) => (item[4] = Scorer.score(item))); + + // now sort the results by score (in opposite order of appearance, since the + // display function below uses pop() to retrieve items) and then + // alphabetically + results.sort((a, b) => { + const leftScore = a[4]; + const rightScore = b[4]; + if (leftScore === rightScore) { + // same score: sort alphabetically + const leftTitle = a[1].toLowerCase(); + const rightTitle = b[1].toLowerCase(); + if (leftTitle === rightTitle) return 0; + return leftTitle > rightTitle ? -1 : 1; // inverted is intentional + } + return leftScore > rightScore ? 1 : -1; + }); + + // remove duplicate search results + // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept + let seen = new Set(); + results = results.reverse().reduce((acc, result) => { + let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(','); + if (!seen.has(resultStr)) { + acc.push(result); + seen.add(resultStr); + } + return acc; + }, []); + + results = results.reverse(); + + // for debugging + //Search.lastresults = results.slice(); // a copy + // console.info("search results:", Search.lastresults); + + // print the results + _displayNextItem(results, results.length, searchTerms); + }, + + /** + * search for object names + */ + performObjectSearch: (object, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const objects = Search._index.objects; + const objNames = Search._index.objnames; + const titles = Search._index.titles; + + const results = []; + + const objectSearchCallback = (prefix, match) => { + const name = match[4] + const fullname = (prefix ? prefix + "." : "") + name; + const fullnameLower = fullname.toLowerCase(); + if (fullnameLower.indexOf(object) < 0) return; + + let score = 0; + const parts = fullnameLower.split("."); + + // check for different match types: exact matches of full name or + // "last name" (i.e. last dotted part) + if (fullnameLower === object || parts.slice(-1)[0] === object) + score += Scorer.objNameMatch; + else if (parts.slice(-1)[0].indexOf(object) > -1) + score += Scorer.objPartialMatch; // matches in last name + + const objName = objNames[match[1]][2]; + const title = titles[match[0]]; + + // If more than one term searched for, we require other words to be + // found in the name/title/description + const otherTerms = new Set(objectTerms); + otherTerms.delete(object); + if (otherTerms.size > 0) { + const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase(); + if ( + [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0) + ) + return; + } + + let anchor = match[3]; + if (anchor === "") anchor = fullname; + else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname; + + const descr = objName + _(", in ") + title; + + // add custom score for some objects according to scorer + if (Scorer.objPrio.hasOwnProperty(match[2])) + score += Scorer.objPrio[match[2]]; + else score += Scorer.objPrioDefault; + + results.push([ + docNames[match[0]], + fullname, + "#" + anchor, + descr, + score, + filenames[match[0]], + ]); + }; + Object.keys(objects).forEach((prefix) => + objects[prefix].forEach((array) => + objectSearchCallback(prefix, array) + ) + ); + return results; + }, + + /** + * search for full-text terms in the index + */ + performTermsSearch: (searchTerms, excludedTerms) => { + // prepare search + const terms = Search._index.terms; + const titleTerms = Search._index.titleterms; + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + + const scoreMap = new Map(); + const fileMap = new Map(); + + // perform the search on the required terms + searchTerms.forEach((word) => { + const files = []; + const arr = [ + { files: terms[word], score: Scorer.term }, + { files: titleTerms[word], score: Scorer.title }, + ]; + // add support for partial matches + if (word.length > 2) { + const escapedWord = _escapeRegExp(word); + Object.keys(terms).forEach((term) => { + if (term.match(escapedWord) && !terms[word]) + arr.push({ files: terms[term], score: Scorer.partialTerm }); + }); + Object.keys(titleTerms).forEach((term) => { + if (term.match(escapedWord) && !titleTerms[word]) + arr.push({ files: titleTerms[word], score: Scorer.partialTitle }); + }); + } + + // no match but word was a required one + if (arr.every((record) => record.files === undefined)) return; + + // found search word in contents + arr.forEach((record) => { + if (record.files === undefined) return; + + let recordFiles = record.files; + if (recordFiles.length === undefined) recordFiles = [recordFiles]; + files.push(...recordFiles); + + // set score for the word in each file + recordFiles.forEach((file) => { + if (!scoreMap.has(file)) scoreMap.set(file, {}); + scoreMap.get(file)[word] = record.score; + }); + }); + + // create the mapping + files.forEach((file) => { + if (fileMap.has(file) && fileMap.get(file).indexOf(word) === -1) + fileMap.get(file).push(word); + else fileMap.set(file, [word]); + }); + }); + + // now check if the files don't contain excluded terms + const results = []; + for (const [file, wordList] of fileMap) { + // check if all requirements are matched + + // as search terms with length < 3 are discarded + const filteredTermCount = [...searchTerms].filter( + (term) => term.length > 2 + ).length; + if ( + wordList.length !== searchTerms.size && + wordList.length !== filteredTermCount + ) + continue; + + // ensure that none of the excluded terms is in the search result + if ( + [...excludedTerms].some( + (term) => + terms[term] === file || + titleTerms[term] === file || + (terms[term] || []).includes(file) || + (titleTerms[term] || []).includes(file) + ) + ) + break; + + // select one (max) score for the file. + const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w])); + // add result to the result list + results.push([ + docNames[file], + titles[file], + "", + null, + score, + filenames[file], + ]); + } + return results; + }, + + /** + * helper function to return a node containing the + * search summary for a given text. keywords is a list + * of stemmed words. + */ + makeSearchSummary: (htmlText, keywords) => { + const text = Search.htmlToText(htmlText); + if (text === "") return null; + + const textLower = text.toLowerCase(); + const actualStartPosition = [...keywords] + .map((k) => textLower.indexOf(k.toLowerCase())) + .filter((i) => i > -1) + .slice(-1)[0]; + const startWithContext = Math.max(actualStartPosition - 120, 0); + + const top = startWithContext === 0 ? "" : "..."; + const tail = startWithContext + 240 < text.length ? "..." : ""; + + let summary = document.createElement("p"); + summary.classList.add("context"); + summary.textContent = top + text.substr(startWithContext, 240).trim() + tail; + + return summary; + }, +}; + +_ready(Search.init); diff --git a/_static/site.css b/_static/site.css new file mode 100644 index 0000000..6da5916 --- /dev/null +++ b/_static/site.css @@ -0,0 +1,10256 @@ +@charset "UTF-8"; +@import url(css/theme.css); +@font-face { + font-family: 'PT Sans', Helvetica, Arial, 'sans-serif'; +} + +@use "sass:math"; +/* Bulma Utilities */ +.file-cta, +.file-name, .select select, .textarea, .input { + -moz-appearance: none; + -webkit-appearance: none; + align-items: center; + border: 1px solid transparent; + border-radius: 4px; + box-shadow: none; + display: inline-flex; + font-size: 1rem; + height: 2.5em; + justify-content: flex-start; + line-height: 1.5; + padding-bottom: calc(0.5em - 1px); + padding-left: calc(0.75em - 1px); + padding-right: calc(0.75em - 1px); + padding-top: calc(0.5em - 1px); + position: relative; + vertical-align: top; +} + +.file-cta:focus, +.file-name:focus, .select select:focus, .textarea:focus, .input:focus, .is-focused.file-cta, +.is-focused.file-name, .select select.is-focused, .is-focused.textarea, .is-focused.input, .file-cta:active, +.file-name:active, .select select:active, .textarea:active, .input:active, .is-active.file-cta, +.is-active.file-name, .select select.is-active, .is-active.textarea, .is-active.input { + outline: none; +} + +[disabled].file-cta, +[disabled].file-name, .select select[disabled], [disabled].textarea, [disabled].input, fieldset[disabled] .file-cta, +fieldset[disabled] .file-name, fieldset[disabled] .select select, .select fieldset[disabled] select, fieldset[disabled] .textarea, fieldset[disabled] .input { + cursor: not-allowed; +} + +.is-unselectable, .file, .tabs, .breadcrumb { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + +.select:not(.is-multiple):not(.is-loading)::after, .navbar-link:not(.is-arrowless)::after { + border: 3px solid transparent; + border-radius: 2px; + border-right: 0; + border-top: 0; + content: " "; + display: block; + height: 0.625em; + margin-top: -0.4375em; + pointer-events: none; + position: absolute; + top: 50%; + transform: rotate(-45deg); + transform-origin: center; + width: 0.625em; +} + +.tabs:not(:last-child), .level:not(:last-child), .breadcrumb:not(:last-child) { + margin-bottom: 1.5rem; +} + +.control.is-loading::after, .select.is-loading::after { + animation: spinAround 500ms infinite linear; + border: 2px solid #dbdbdb; + border-radius: 290486px; + border-right-color: transparent; + border-top-color: transparent; + content: ""; + display: block; + height: 1em; + position: relative; + width: 1em; +} + +.hero-video, .is-overlay, .image.is-square img, +.image.is-square .has-ratio, .image.is-1by1 img, +.image.is-1by1 .has-ratio, .image.is-5by4 img, +.image.is-5by4 .has-ratio, .image.is-4by3 img, +.image.is-4by3 .has-ratio, .image.is-3by2 img, +.image.is-3by2 .has-ratio, .image.is-5by3 img, +.image.is-5by3 .has-ratio, .image.is-16by9 img, +.image.is-16by9 .has-ratio, .image.is-2by1 img, +.image.is-2by1 .has-ratio, .image.is-3by1 img, +.image.is-3by1 .has-ratio, .image.is-4by5 img, +.image.is-4by5 .has-ratio, .image.is-3by4 img, +.image.is-3by4 .has-ratio, .image.is-2by3 img, +.image.is-2by3 .has-ratio, .image.is-3by5 img, +.image.is-3by5 .has-ratio, .image.is-9by16 img, +.image.is-9by16 .has-ratio, .image.is-1by2 img, +.image.is-1by2 .has-ratio, .image.is-1by3 img, +.image.is-1by3 .has-ratio { + bottom: 0; + left: 0; + position: absolute; + right: 0; + top: 0; +} + +/* Bulma Base */ +/*! minireset.css v0.0.6 | MIT License | github.com/jgthms/minireset.css */ +html, +body, +p, +ol, +ul, +li, +dl, +dt, +dd, +blockquote, +figure, +fieldset, +legend, +textarea, +pre, +iframe, +hr, +h1, +h2, +.rst-content #index h3, +.rst-content .toctree-wrapper .caption, +h3, +h4, +h5, +h6 { + margin: 0; + padding: 0; +} + +h1, +h2, +.rst-content #index h3, +.rst-content .toctree-wrapper .caption, +h3, +h4, +h5, +h6 { + font-size: 100%; + font-weight: normal; +} + +ul { + list-style: none; +} + +button, +input, +select, +textarea { + margin: 0; +} + +html { + box-sizing: border-box; +} + +*, *::before, *::after { + box-sizing: inherit; +} + +img, +video { + height: auto; + max-width: 100%; +} + +iframe { + border: 0; +} + +table { + border-collapse: collapse; + border-spacing: 0; +} + +td, +th { + padding: 0; +} + +td:not([align]), +th:not([align]) { + text-align: inherit; +} + +html { + background-color: #FFFFFF; + font-size: 16px; + -moz-osx-font-smoothing: grayscale; + -webkit-font-smoothing: antialiased; + min-width: 300px; + overflow-x: hidden; + overflow-y: scroll; + text-rendering: optimizeLegibility; + text-size-adjust: 100%; +} + +article, +aside, +figure, +footer, +header, +hgroup, +section { + display: block; +} + +body, +button, +input, +optgroup, +select, +textarea { + font-family: "PT Sans", Helvetica, Arial, "sans-serif"; +} + +code, +pre { + -moz-osx-font-smoothing: auto; + -webkit-font-smoothing: auto; + font-family: Menlo, Monaco, "Courier New", monospace; +} + +body { + color: rgba(0, 0, 0, 0.87); + font-size: 1em; + font-weight: 400; + line-height: 1.5; +} + +a { + color: #FF9200; + cursor: pointer; + text-decoration: none; +} + +a strong { + color: currentColor; +} + +a:hover { + color: #ca6500; +} + +code { + background-color: #f8f8f8; + color: rgba(0, 0, 0, 0.87); + font-size: 1em; + font-weight: normal; + padding: 0.25em; +} + +hr { + background-color: #FFFFFF; + border: none; + display: block; + height: 2px; + margin: 1.5rem 0; +} + +img { + height: auto; + max-width: 100%; +} + +input[type="checkbox"], +input[type="radio"] { + vertical-align: baseline; +} + +small { + font-size: 0.875em; +} + +span { + font-style: inherit; + font-weight: inherit; +} + +strong { + color: #363636; + font-weight: 700; +} + +fieldset { + border: none; +} + +pre { + -webkit-overflow-scrolling: touch; + background-color: #f8f8f8; + color: rgba(0, 0, 0, 0.87); + font-size: 0.825em; + overflow-x: auto; + padding: 0.75em; + white-space: pre; + word-wrap: normal; +} + +pre code { + background-color: transparent; + color: currentColor; + font-size: 1em; + padding: 0; +} + +table td, +table th { + vertical-align: top; +} + +table td:not([align]), +table th:not([align]) { + text-align: inherit; +} + +table th { + color: #363636; +} + +@keyframes spinAround { + from { + transform: rotate(0deg); + } + to { + transform: rotate(359deg); + } +} + +.column { + display: block; + flex-basis: 0; + flex-grow: 1; + flex-shrink: 1; + padding: 0.75rem; +} + +.columns.is-mobile > .column.is-narrow { + flex: none; + width: unset; +} + +.columns.is-mobile > .column.is-full { + flex: none; + width: 100%; +} + +.columns.is-mobile > .column.is-three-quarters { + flex: none; + width: 75%; +} + +.columns.is-mobile > .column.is-two-thirds { + flex: none; + width: 66.6666%; +} + +.columns.is-mobile > .column.is-half { + flex: none; + width: 50%; +} + +.columns.is-mobile > .column.is-one-third { + flex: none; + width: 33.3333%; +} + +.columns.is-mobile > .column.is-one-quarter { + flex: none; + width: 25%; +} + +.columns.is-mobile > .column.is-one-fifth { + flex: none; + width: 20%; +} + +.columns.is-mobile > .column.is-two-fifths { + flex: none; + width: 40%; +} + +.columns.is-mobile > .column.is-three-fifths { + flex: none; + width: 60%; +} + +.columns.is-mobile > .column.is-four-fifths { + flex: none; + width: 80%; +} + +.columns.is-mobile > .column.is-offset-three-quarters { + margin-left: 75%; +} + +.columns.is-mobile > .column.is-offset-two-thirds { + margin-left: 66.6666%; +} + +.columns.is-mobile > .column.is-offset-half { + margin-left: 50%; +} + +.columns.is-mobile > .column.is-offset-one-third { + margin-left: 33.3333%; +} + +.columns.is-mobile > .column.is-offset-one-quarter { + margin-left: 25%; +} + +.columns.is-mobile > .column.is-offset-one-fifth { + margin-left: 20%; +} + +.columns.is-mobile > .column.is-offset-two-fifths { + margin-left: 40%; +} + +.columns.is-mobile > .column.is-offset-three-fifths { + margin-left: 60%; +} + +.columns.is-mobile > .column.is-offset-four-fifths { + margin-left: 80%; +} + +.columns.is-mobile > .column.is-0 { + flex: none; + width: 0%; +} + +.columns.is-mobile > .column.is-offset-0 { + margin-left: 0%; +} + +.columns.is-mobile > .column.is-1 { + flex: none; + width: 8.33333%; +} + +.columns.is-mobile > .column.is-offset-1 { + margin-left: 8.33333%; +} + +.columns.is-mobile > .column.is-2 { + flex: none; + width: 16.66667%; +} + +.columns.is-mobile > .column.is-offset-2 { + margin-left: 16.66667%; +} + +.columns.is-mobile > .column.is-3 { + flex: none; + width: 25%; +} + +.columns.is-mobile > .column.is-offset-3 { + margin-left: 25%; +} + +.columns.is-mobile > .column.is-4 { + flex: none; + width: 33.33333%; +} + +.columns.is-mobile > .column.is-offset-4 { + margin-left: 33.33333%; +} + +.columns.is-mobile > .column.is-5 { + flex: none; + width: 41.66667%; +} + +.columns.is-mobile > .column.is-offset-5 { + margin-left: 41.66667%; +} + +.columns.is-mobile > .column.is-6 { + flex: none; + width: 50%; +} + +.columns.is-mobile > .column.is-offset-6 { + margin-left: 50%; +} + +.columns.is-mobile > .column.is-7 { + flex: none; + width: 58.33333%; +} + +.columns.is-mobile > .column.is-offset-7 { + margin-left: 58.33333%; +} + +.columns.is-mobile > .column.is-8 { + flex: none; + width: 66.66667%; +} + +.columns.is-mobile > .column.is-offset-8 { + margin-left: 66.66667%; +} + +.columns.is-mobile > .column.is-9 { + flex: none; + width: 75%; +} + +.columns.is-mobile > .column.is-offset-9 { + margin-left: 75%; +} + +.columns.is-mobile > .column.is-10 { + flex: none; + width: 83.33333%; +} + +.columns.is-mobile > .column.is-offset-10 { + margin-left: 83.33333%; +} + +.columns.is-mobile > .column.is-11 { + flex: none; + width: 91.66667%; +} + +.columns.is-mobile > .column.is-offset-11 { + margin-left: 91.66667%; +} + +.columns.is-mobile > .column.is-12 { + flex: none; + width: 100%; +} + +.columns.is-mobile > .column.is-offset-12 { + margin-left: 100%; +} + +@media screen and (max-width: 768px) { + .column.is-narrow-mobile { + flex: none; + width: unset; + } + .column.is-full-mobile { + flex: none; + width: 100%; + } + .column.is-three-quarters-mobile { + flex: none; + width: 75%; + } + .column.is-two-thirds-mobile { + flex: none; + width: 66.6666%; + } + .column.is-half-mobile { + flex: none; + width: 50%; + } + .column.is-one-third-mobile { + flex: none; + width: 33.3333%; + } + .column.is-one-quarter-mobile { + flex: none; + width: 25%; + } + .column.is-one-fifth-mobile { + flex: none; + width: 20%; + } + .column.is-two-fifths-mobile { + flex: none; + width: 40%; + } + .column.is-three-fifths-mobile { + flex: none; + width: 60%; + } + .column.is-four-fifths-mobile { + flex: none; + width: 80%; + } + .column.is-offset-three-quarters-mobile { + margin-left: 75%; + } + .column.is-offset-two-thirds-mobile { + margin-left: 66.6666%; + } + .column.is-offset-half-mobile { + margin-left: 50%; + } + .column.is-offset-one-third-mobile { + margin-left: 33.3333%; + } + .column.is-offset-one-quarter-mobile { + margin-left: 25%; + } + .column.is-offset-one-fifth-mobile { + margin-left: 20%; + } + .column.is-offset-two-fifths-mobile { + margin-left: 40%; + } + .column.is-offset-three-fifths-mobile { + margin-left: 60%; + } + .column.is-offset-four-fifths-mobile { + margin-left: 80%; + } + .column.is-0-mobile { + flex: none; + width: 0%; + } + .column.is-offset-0-mobile { + margin-left: 0%; + } + .column.is-1-mobile { + flex: none; + width: 8.33333%; + } + .column.is-offset-1-mobile { + margin-left: 8.33333%; + } + .column.is-2-mobile { + flex: none; + width: 16.66667%; + } + .column.is-offset-2-mobile { + margin-left: 16.66667%; + } + .column.is-3-mobile { + flex: none; + width: 25%; + } + .column.is-offset-3-mobile { + margin-left: 25%; + } + .column.is-4-mobile { + flex: none; + width: 33.33333%; + } + .column.is-offset-4-mobile { + margin-left: 33.33333%; + } + .column.is-5-mobile { + flex: none; + width: 41.66667%; + } + .column.is-offset-5-mobile { + margin-left: 41.66667%; + } + .column.is-6-mobile { + flex: none; + width: 50%; + } + .column.is-offset-6-mobile { + margin-left: 50%; + } + .column.is-7-mobile { + flex: none; + width: 58.33333%; + } + .column.is-offset-7-mobile { + margin-left: 58.33333%; + } + .column.is-8-mobile { + flex: none; + width: 66.66667%; + } + .column.is-offset-8-mobile { + margin-left: 66.66667%; + } + .column.is-9-mobile { + flex: none; + width: 75%; + } + .column.is-offset-9-mobile { + margin-left: 75%; + } + .column.is-10-mobile { + flex: none; + width: 83.33333%; + } + .column.is-offset-10-mobile { + margin-left: 83.33333%; + } + .column.is-11-mobile { + flex: none; + width: 91.66667%; + } + .column.is-offset-11-mobile { + margin-left: 91.66667%; + } + .column.is-12-mobile { + flex: none; + width: 100%; + } + .column.is-offset-12-mobile { + margin-left: 100%; + } +} + +@media screen and (min-width: 769px), print { + .column.is-narrow, .column.is-narrow-tablet { + flex: none; + width: unset; + } + .column.is-full, .column.is-full-tablet { + flex: none; + width: 100%; + } + .column.is-three-quarters, .column.is-three-quarters-tablet { + flex: none; + width: 75%; + } + .column.is-two-thirds, .column.is-two-thirds-tablet { + flex: none; + width: 66.6666%; + } + .column.is-half, .column.is-half-tablet { + flex: none; + width: 50%; + } + .column.is-one-third, .column.is-one-third-tablet { + flex: none; + width: 33.3333%; + } + .column.is-one-quarter, .column.is-one-quarter-tablet { + flex: none; + width: 25%; + } + .column.is-one-fifth, .column.is-one-fifth-tablet { + flex: none; + width: 20%; + } + .column.is-two-fifths, .column.is-two-fifths-tablet { + flex: none; + width: 40%; + } + .column.is-three-fifths, .column.is-three-fifths-tablet { + flex: none; + width: 60%; + } + .column.is-four-fifths, .column.is-four-fifths-tablet { + flex: none; + width: 80%; + } + .column.is-offset-three-quarters, .column.is-offset-three-quarters-tablet { + margin-left: 75%; + } + .column.is-offset-two-thirds, .column.is-offset-two-thirds-tablet { + margin-left: 66.6666%; + } + .column.is-offset-half, .column.is-offset-half-tablet { + margin-left: 50%; + } + .column.is-offset-one-third, .column.is-offset-one-third-tablet { + margin-left: 33.3333%; + } + .column.is-offset-one-quarter, .column.is-offset-one-quarter-tablet { + margin-left: 25%; + } + .column.is-offset-one-fifth, .column.is-offset-one-fifth-tablet { + margin-left: 20%; + } + .column.is-offset-two-fifths, .column.is-offset-two-fifths-tablet { + margin-left: 40%; + } + .column.is-offset-three-fifths, .column.is-offset-three-fifths-tablet { + margin-left: 60%; + } + .column.is-offset-four-fifths, .column.is-offset-four-fifths-tablet { + margin-left: 80%; + } + .column.is-0, .column.is-0-tablet { + flex: none; + width: 0%; + } + .column.is-offset-0, .column.is-offset-0-tablet { + margin-left: 0%; + } + .column.is-1, .column.is-1-tablet { + flex: none; + width: 8.33333%; + } + .column.is-offset-1, .column.is-offset-1-tablet { + margin-left: 8.33333%; + } + .column.is-2, .column.is-2-tablet { + flex: none; + width: 16.66667%; + } + .column.is-offset-2, .column.is-offset-2-tablet { + margin-left: 16.66667%; + } + .column.is-3, .column.is-3-tablet { + flex: none; + width: 25%; + } + .column.is-offset-3, .column.is-offset-3-tablet { + margin-left: 25%; + } + .column.is-4, .column.is-4-tablet { + flex: none; + width: 33.33333%; + } + .column.is-offset-4, .column.is-offset-4-tablet { + margin-left: 33.33333%; + } + .column.is-5, .column.is-5-tablet { + flex: none; + width: 41.66667%; + } + .column.is-offset-5, .column.is-offset-5-tablet { + margin-left: 41.66667%; + } + .column.is-6, .column.is-6-tablet { + flex: none; + width: 50%; + } + .column.is-offset-6, .column.is-offset-6-tablet { + margin-left: 50%; + } + .column.is-7, .column.is-7-tablet { + flex: none; + width: 58.33333%; + } + .column.is-offset-7, .column.is-offset-7-tablet { + margin-left: 58.33333%; + } + .column.is-8, .column.is-8-tablet { + flex: none; + width: 66.66667%; + } + .column.is-offset-8, .column.is-offset-8-tablet { + margin-left: 66.66667%; + } + .column.is-9, .column.is-9-tablet { + flex: none; + width: 75%; + } + .column.is-offset-9, .column.is-offset-9-tablet { + margin-left: 75%; + } + .column.is-10, .column.is-10-tablet { + flex: none; + width: 83.33333%; + } + .column.is-offset-10, .column.is-offset-10-tablet { + margin-left: 83.33333%; + } + .column.is-11, .column.is-11-tablet { + flex: none; + width: 91.66667%; + } + .column.is-offset-11, .column.is-offset-11-tablet { + margin-left: 91.66667%; + } + .column.is-12, .column.is-12-tablet { + flex: none; + width: 100%; + } + .column.is-offset-12, .column.is-offset-12-tablet { + margin-left: 100%; + } +} + +@media screen and (max-width: 1023px) { + .column.is-narrow-touch { + flex: none; + width: unset; + } + .column.is-full-touch { + flex: none; + width: 100%; + } + .column.is-three-quarters-touch { + flex: none; + width: 75%; + } + .column.is-two-thirds-touch { + flex: none; + width: 66.6666%; + } + .column.is-half-touch { + flex: none; + width: 50%; + } + .column.is-one-third-touch { + flex: none; + width: 33.3333%; + } + .column.is-one-quarter-touch { + flex: none; + width: 25%; + } + .column.is-one-fifth-touch { + flex: none; + width: 20%; + } + .column.is-two-fifths-touch { + flex: none; + width: 40%; + } + .column.is-three-fifths-touch { + flex: none; + width: 60%; + } + .column.is-four-fifths-touch { + flex: none; + width: 80%; + } + .column.is-offset-three-quarters-touch { + margin-left: 75%; + } + .column.is-offset-two-thirds-touch { + margin-left: 66.6666%; + } + .column.is-offset-half-touch { + margin-left: 50%; + } + .column.is-offset-one-third-touch { + margin-left: 33.3333%; + } + .column.is-offset-one-quarter-touch { + margin-left: 25%; + } + .column.is-offset-one-fifth-touch { + margin-left: 20%; + } + .column.is-offset-two-fifths-touch { + margin-left: 40%; + } + .column.is-offset-three-fifths-touch { + margin-left: 60%; + } + .column.is-offset-four-fifths-touch { + margin-left: 80%; + } + .column.is-0-touch { + flex: none; + width: 0%; + } + .column.is-offset-0-touch { + margin-left: 0%; + } + .column.is-1-touch { + flex: none; + width: 8.33333%; + } + .column.is-offset-1-touch { + margin-left: 8.33333%; + } + .column.is-2-touch { + flex: none; + width: 16.66667%; + } + .column.is-offset-2-touch { + margin-left: 16.66667%; + } + .column.is-3-touch { + flex: none; + width: 25%; + } + .column.is-offset-3-touch { + margin-left: 25%; + } + .column.is-4-touch { + flex: none; + width: 33.33333%; + } + .column.is-offset-4-touch { + margin-left: 33.33333%; + } + .column.is-5-touch { + flex: none; + width: 41.66667%; + } + .column.is-offset-5-touch { + margin-left: 41.66667%; + } + .column.is-6-touch { + flex: none; + width: 50%; + } + .column.is-offset-6-touch { + margin-left: 50%; + } + .column.is-7-touch { + flex: none; + width: 58.33333%; + } + .column.is-offset-7-touch { + margin-left: 58.33333%; + } + .column.is-8-touch { + flex: none; + width: 66.66667%; + } + .column.is-offset-8-touch { + margin-left: 66.66667%; + } + .column.is-9-touch { + flex: none; + width: 75%; + } + .column.is-offset-9-touch { + margin-left: 75%; + } + .column.is-10-touch { + flex: none; + width: 83.33333%; + } + .column.is-offset-10-touch { + margin-left: 83.33333%; + } + .column.is-11-touch { + flex: none; + width: 91.66667%; + } + .column.is-offset-11-touch { + margin-left: 91.66667%; + } + .column.is-12-touch { + flex: none; + width: 100%; + } + .column.is-offset-12-touch { + margin-left: 100%; + } +} + +@media screen and (min-width: 1024px) { + .column.is-narrow-desktop { + flex: none; + width: unset; + } + .column.is-full-desktop { + flex: none; + width: 100%; + } + .column.is-three-quarters-desktop { + flex: none; + width: 75%; + } + .column.is-two-thirds-desktop { + flex: none; + width: 66.6666%; + } + .column.is-half-desktop { + flex: none; + width: 50%; + } + .column.is-one-third-desktop { + flex: none; + width: 33.3333%; + } + .column.is-one-quarter-desktop { + flex: none; + width: 25%; + } + .column.is-one-fifth-desktop { + flex: none; + width: 20%; + } + .column.is-two-fifths-desktop { + flex: none; + width: 40%; + } + .column.is-three-fifths-desktop { + flex: none; + width: 60%; + } + .column.is-four-fifths-desktop { + flex: none; + width: 80%; + } + .column.is-offset-three-quarters-desktop { + margin-left: 75%; + } + .column.is-offset-two-thirds-desktop { + margin-left: 66.6666%; + } + .column.is-offset-half-desktop { + margin-left: 50%; + } + .column.is-offset-one-third-desktop { + margin-left: 33.3333%; + } + .column.is-offset-one-quarter-desktop { + margin-left: 25%; + } + .column.is-offset-one-fifth-desktop { + margin-left: 20%; + } + .column.is-offset-two-fifths-desktop { + margin-left: 40%; + } + .column.is-offset-three-fifths-desktop { + margin-left: 60%; + } + .column.is-offset-four-fifths-desktop { + margin-left: 80%; + } + .column.is-0-desktop { + flex: none; + width: 0%; + } + .column.is-offset-0-desktop { + margin-left: 0%; + } + .column.is-1-desktop { + flex: none; + width: 8.33333%; + } + .column.is-offset-1-desktop { + margin-left: 8.33333%; + } + .column.is-2-desktop { + flex: none; + width: 16.66667%; + } + .column.is-offset-2-desktop { + margin-left: 16.66667%; + } + .column.is-3-desktop { + flex: none; + width: 25%; + } + .column.is-offset-3-desktop { + margin-left: 25%; + } + .column.is-4-desktop { + flex: none; + width: 33.33333%; + } + .column.is-offset-4-desktop { + margin-left: 33.33333%; + } + .column.is-5-desktop { + flex: none; + width: 41.66667%; + } + .column.is-offset-5-desktop { + margin-left: 41.66667%; + } + .column.is-6-desktop { + flex: none; + width: 50%; + } + .column.is-offset-6-desktop { + margin-left: 50%; + } + .column.is-7-desktop { + flex: none; + width: 58.33333%; + } + .column.is-offset-7-desktop { + margin-left: 58.33333%; + } + .column.is-8-desktop { + flex: none; + width: 66.66667%; + } + .column.is-offset-8-desktop { + margin-left: 66.66667%; + } + .column.is-9-desktop { + flex: none; + width: 75%; + } + .column.is-offset-9-desktop { + margin-left: 75%; + } + .column.is-10-desktop { + flex: none; + width: 83.33333%; + } + .column.is-offset-10-desktop { + margin-left: 83.33333%; + } + .column.is-11-desktop { + flex: none; + width: 91.66667%; + } + .column.is-offset-11-desktop { + margin-left: 91.66667%; + } + .column.is-12-desktop { + flex: none; + width: 100%; + } + .column.is-offset-12-desktop { + margin-left: 100%; + } +} + +@media screen and (min-width: 1216px) { + .column.is-narrow-widescreen { + flex: none; + width: unset; + } + .column.is-full-widescreen { + flex: none; + width: 100%; + } + .column.is-three-quarters-widescreen { + flex: none; + width: 75%; + } + .column.is-two-thirds-widescreen { + flex: none; + width: 66.6666%; + } + .column.is-half-widescreen { + flex: none; + width: 50%; + } + .column.is-one-third-widescreen { + flex: none; + width: 33.3333%; + } + .column.is-one-quarter-widescreen { + flex: none; + width: 25%; + } + .column.is-one-fifth-widescreen { + flex: none; + width: 20%; + } + .column.is-two-fifths-widescreen { + flex: none; + width: 40%; + } + .column.is-three-fifths-widescreen { + flex: none; + width: 60%; + } + .column.is-four-fifths-widescreen { + flex: none; + width: 80%; + } + .column.is-offset-three-quarters-widescreen { + margin-left: 75%; + } + .column.is-offset-two-thirds-widescreen { + margin-left: 66.6666%; + } + .column.is-offset-half-widescreen { + margin-left: 50%; + } + .column.is-offset-one-third-widescreen { + margin-left: 33.3333%; + } + .column.is-offset-one-quarter-widescreen { + margin-left: 25%; + } + .column.is-offset-one-fifth-widescreen { + margin-left: 20%; + } + .column.is-offset-two-fifths-widescreen { + margin-left: 40%; + } + .column.is-offset-three-fifths-widescreen { + margin-left: 60%; + } + .column.is-offset-four-fifths-widescreen { + margin-left: 80%; + } + .column.is-0-widescreen { + flex: none; + width: 0%; + } + .column.is-offset-0-widescreen { + margin-left: 0%; + } + .column.is-1-widescreen { + flex: none; + width: 8.33333%; + } + .column.is-offset-1-widescreen { + margin-left: 8.33333%; + } + .column.is-2-widescreen { + flex: none; + width: 16.66667%; + } + .column.is-offset-2-widescreen { + margin-left: 16.66667%; + } + .column.is-3-widescreen { + flex: none; + width: 25%; + } + .column.is-offset-3-widescreen { + margin-left: 25%; + } + .column.is-4-widescreen { + flex: none; + width: 33.33333%; + } + .column.is-offset-4-widescreen { + margin-left: 33.33333%; + } + .column.is-5-widescreen { + flex: none; + width: 41.66667%; + } + .column.is-offset-5-widescreen { + margin-left: 41.66667%; + } + .column.is-6-widescreen { + flex: none; + width: 50%; + } + .column.is-offset-6-widescreen { + margin-left: 50%; + } + .column.is-7-widescreen { + flex: none; + width: 58.33333%; + } + .column.is-offset-7-widescreen { + margin-left: 58.33333%; + } + .column.is-8-widescreen { + flex: none; + width: 66.66667%; + } + .column.is-offset-8-widescreen { + margin-left: 66.66667%; + } + .column.is-9-widescreen { + flex: none; + width: 75%; + } + .column.is-offset-9-widescreen { + margin-left: 75%; + } + .column.is-10-widescreen { + flex: none; + width: 83.33333%; + } + .column.is-offset-10-widescreen { + margin-left: 83.33333%; + } + .column.is-11-widescreen { + flex: none; + width: 91.66667%; + } + .column.is-offset-11-widescreen { + margin-left: 91.66667%; + } + .column.is-12-widescreen { + flex: none; + width: 100%; + } + .column.is-offset-12-widescreen { + margin-left: 100%; + } +} + +@media screen and (min-width: 1408px) { + .column.is-narrow-fullhd { + flex: none; + width: unset; + } + .column.is-full-fullhd { + flex: none; + width: 100%; + } + .column.is-three-quarters-fullhd { + flex: none; + width: 75%; + } + .column.is-two-thirds-fullhd { + flex: none; + width: 66.6666%; + } + .column.is-half-fullhd { + flex: none; + width: 50%; + } + .column.is-one-third-fullhd { + flex: none; + width: 33.3333%; + } + .column.is-one-quarter-fullhd { + flex: none; + width: 25%; + } + .column.is-one-fifth-fullhd { + flex: none; + width: 20%; + } + .column.is-two-fifths-fullhd { + flex: none; + width: 40%; + } + .column.is-three-fifths-fullhd { + flex: none; + width: 60%; + } + .column.is-four-fifths-fullhd { + flex: none; + width: 80%; + } + .column.is-offset-three-quarters-fullhd { + margin-left: 75%; + } + .column.is-offset-two-thirds-fullhd { + margin-left: 66.6666%; + } + .column.is-offset-half-fullhd { + margin-left: 50%; + } + .column.is-offset-one-third-fullhd { + margin-left: 33.3333%; + } + .column.is-offset-one-quarter-fullhd { + margin-left: 25%; + } + .column.is-offset-one-fifth-fullhd { + margin-left: 20%; + } + .column.is-offset-two-fifths-fullhd { + margin-left: 40%; + } + .column.is-offset-three-fifths-fullhd { + margin-left: 60%; + } + .column.is-offset-four-fifths-fullhd { + margin-left: 80%; + } + .column.is-0-fullhd { + flex: none; + width: 0%; + } + .column.is-offset-0-fullhd { + margin-left: 0%; + } + .column.is-1-fullhd { + flex: none; + width: 8.33333%; + } + .column.is-offset-1-fullhd { + margin-left: 8.33333%; + } + .column.is-2-fullhd { + flex: none; + width: 16.66667%; + } + .column.is-offset-2-fullhd { + margin-left: 16.66667%; + } + .column.is-3-fullhd { + flex: none; + width: 25%; + } + .column.is-offset-3-fullhd { + margin-left: 25%; + } + .column.is-4-fullhd { + flex: none; + width: 33.33333%; + } + .column.is-offset-4-fullhd { + margin-left: 33.33333%; + } + .column.is-5-fullhd { + flex: none; + width: 41.66667%; + } + .column.is-offset-5-fullhd { + margin-left: 41.66667%; + } + .column.is-6-fullhd { + flex: none; + width: 50%; + } + .column.is-offset-6-fullhd { + margin-left: 50%; + } + .column.is-7-fullhd { + flex: none; + width: 58.33333%; + } + .column.is-offset-7-fullhd { + margin-left: 58.33333%; + } + .column.is-8-fullhd { + flex: none; + width: 66.66667%; + } + .column.is-offset-8-fullhd { + margin-left: 66.66667%; + } + .column.is-9-fullhd { + flex: none; + width: 75%; + } + .column.is-offset-9-fullhd { + margin-left: 75%; + } + .column.is-10-fullhd { + flex: none; + width: 83.33333%; + } + .column.is-offset-10-fullhd { + margin-left: 83.33333%; + } + .column.is-11-fullhd { + flex: none; + width: 91.66667%; + } + .column.is-offset-11-fullhd { + margin-left: 91.66667%; + } + .column.is-12-fullhd { + flex: none; + width: 100%; + } + .column.is-offset-12-fullhd { + margin-left: 100%; + } +} + +.columns { + margin-left: -0.75rem; + margin-right: -0.75rem; + margin-top: -0.75rem; +} + +.columns:last-child { + margin-bottom: -0.75rem; +} + +.columns:not(:last-child) { + margin-bottom: calc(1.5rem - 0.75rem); +} + +.columns.is-centered { + justify-content: center; +} + +.columns.is-gapless { + margin-left: 0; + margin-right: 0; + margin-top: 0; +} + +.columns.is-gapless > .column { + margin: 0; + padding: 0 !important; +} + +.columns.is-gapless:not(:last-child) { + margin-bottom: 1.5rem; +} + +.columns.is-gapless:last-child { + margin-bottom: 0; +} + +.columns.is-mobile { + display: flex; +} + +.columns.is-multiline { + flex-wrap: wrap; +} + +.columns.is-vcentered { + align-items: center; +} + +@media screen and (min-width: 769px), print { + .columns:not(.is-desktop) { + display: flex; + } +} + +@media screen and (min-width: 1024px) { + .columns.is-desktop { + display: flex; + } +} + +.columns.is-variable { + --columnGap: 0.75rem; + margin-left: calc(-1 * var(--columnGap)); + margin-right: calc(-1 * var(--columnGap)); +} + +.columns.is-variable > .column { + padding-left: var(--columnGap); + padding-right: var(--columnGap); +} + +.columns.is-variable.is-0 { + --columnGap: 0rem; +} + +@media screen and (max-width: 768px) { + .columns.is-variable.is-0-mobile { + --columnGap: 0rem; + } +} + +@media screen and (min-width: 769px), print { + .columns.is-variable.is-0-tablet { + --columnGap: 0rem; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .columns.is-variable.is-0-tablet-only { + --columnGap: 0rem; + } +} + +@media screen and (max-width: 1023px) { + .columns.is-variable.is-0-touch { + --columnGap: 0rem; + } +} + +@media screen and (min-width: 1024px) { + .columns.is-variable.is-0-desktop { + --columnGap: 0rem; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .columns.is-variable.is-0-desktop-only { + --columnGap: 0rem; + } +} + +@media screen and (min-width: 1216px) { + .columns.is-variable.is-0-widescreen { + --columnGap: 0rem; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .columns.is-variable.is-0-widescreen-only { + --columnGap: 0rem; + } +} + +@media screen and (min-width: 1408px) { + .columns.is-variable.is-0-fullhd { + --columnGap: 0rem; + } +} + +.columns.is-variable.is-1 { + --columnGap: 0.25rem; +} + +@media screen and (max-width: 768px) { + .columns.is-variable.is-1-mobile { + --columnGap: 0.25rem; + } +} + +@media screen and (min-width: 769px), print { + .columns.is-variable.is-1-tablet { + --columnGap: 0.25rem; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .columns.is-variable.is-1-tablet-only { + --columnGap: 0.25rem; + } +} + +@media screen and (max-width: 1023px) { + .columns.is-variable.is-1-touch { + --columnGap: 0.25rem; + } +} + +@media screen and (min-width: 1024px) { + .columns.is-variable.is-1-desktop { + --columnGap: 0.25rem; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .columns.is-variable.is-1-desktop-only { + --columnGap: 0.25rem; + } +} + +@media screen and (min-width: 1216px) { + .columns.is-variable.is-1-widescreen { + --columnGap: 0.25rem; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .columns.is-variable.is-1-widescreen-only { + --columnGap: 0.25rem; + } +} + +@media screen and (min-width: 1408px) { + .columns.is-variable.is-1-fullhd { + --columnGap: 0.25rem; + } +} + +.columns.is-variable.is-2 { + --columnGap: 0.5rem; +} + +@media screen and (max-width: 768px) { + .columns.is-variable.is-2-mobile { + --columnGap: 0.5rem; + } +} + +@media screen and (min-width: 769px), print { + .columns.is-variable.is-2-tablet { + --columnGap: 0.5rem; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .columns.is-variable.is-2-tablet-only { + --columnGap: 0.5rem; + } +} + +@media screen and (max-width: 1023px) { + .columns.is-variable.is-2-touch { + --columnGap: 0.5rem; + } +} + +@media screen and (min-width: 1024px) { + .columns.is-variable.is-2-desktop { + --columnGap: 0.5rem; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .columns.is-variable.is-2-desktop-only { + --columnGap: 0.5rem; + } +} + +@media screen and (min-width: 1216px) { + .columns.is-variable.is-2-widescreen { + --columnGap: 0.5rem; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .columns.is-variable.is-2-widescreen-only { + --columnGap: 0.5rem; + } +} + +@media screen and (min-width: 1408px) { + .columns.is-variable.is-2-fullhd { + --columnGap: 0.5rem; + } +} + +.columns.is-variable.is-3 { + --columnGap: 0.75rem; +} + +@media screen and (max-width: 768px) { + .columns.is-variable.is-3-mobile { + --columnGap: 0.75rem; + } +} + +@media screen and (min-width: 769px), print { + .columns.is-variable.is-3-tablet { + --columnGap: 0.75rem; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .columns.is-variable.is-3-tablet-only { + --columnGap: 0.75rem; + } +} + +@media screen and (max-width: 1023px) { + .columns.is-variable.is-3-touch { + --columnGap: 0.75rem; + } +} + +@media screen and (min-width: 1024px) { + .columns.is-variable.is-3-desktop { + --columnGap: 0.75rem; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .columns.is-variable.is-3-desktop-only { + --columnGap: 0.75rem; + } +} + +@media screen and (min-width: 1216px) { + .columns.is-variable.is-3-widescreen { + --columnGap: 0.75rem; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .columns.is-variable.is-3-widescreen-only { + --columnGap: 0.75rem; + } +} + +@media screen and (min-width: 1408px) { + .columns.is-variable.is-3-fullhd { + --columnGap: 0.75rem; + } +} + +.columns.is-variable.is-4 { + --columnGap: 1rem; +} + +@media screen and (max-width: 768px) { + .columns.is-variable.is-4-mobile { + --columnGap: 1rem; + } +} + +@media screen and (min-width: 769px), print { + .columns.is-variable.is-4-tablet { + --columnGap: 1rem; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .columns.is-variable.is-4-tablet-only { + --columnGap: 1rem; + } +} + +@media screen and (max-width: 1023px) { + .columns.is-variable.is-4-touch { + --columnGap: 1rem; + } +} + +@media screen and (min-width: 1024px) { + .columns.is-variable.is-4-desktop { + --columnGap: 1rem; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .columns.is-variable.is-4-desktop-only { + --columnGap: 1rem; + } +} + +@media screen and (min-width: 1216px) { + .columns.is-variable.is-4-widescreen { + --columnGap: 1rem; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .columns.is-variable.is-4-widescreen-only { + --columnGap: 1rem; + } +} + +@media screen and (min-width: 1408px) { + .columns.is-variable.is-4-fullhd { + --columnGap: 1rem; + } +} + +.columns.is-variable.is-5 { + --columnGap: 1.25rem; +} + +@media screen and (max-width: 768px) { + .columns.is-variable.is-5-mobile { + --columnGap: 1.25rem; + } +} + +@media screen and (min-width: 769px), print { + .columns.is-variable.is-5-tablet { + --columnGap: 1.25rem; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .columns.is-variable.is-5-tablet-only { + --columnGap: 1.25rem; + } +} + +@media screen and (max-width: 1023px) { + .columns.is-variable.is-5-touch { + --columnGap: 1.25rem; + } +} + +@media screen and (min-width: 1024px) { + .columns.is-variable.is-5-desktop { + --columnGap: 1.25rem; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .columns.is-variable.is-5-desktop-only { + --columnGap: 1.25rem; + } +} + +@media screen and (min-width: 1216px) { + .columns.is-variable.is-5-widescreen { + --columnGap: 1.25rem; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .columns.is-variable.is-5-widescreen-only { + --columnGap: 1.25rem; + } +} + +@media screen and (min-width: 1408px) { + .columns.is-variable.is-5-fullhd { + --columnGap: 1.25rem; + } +} + +.columns.is-variable.is-6 { + --columnGap: 1.5rem; +} + +@media screen and (max-width: 768px) { + .columns.is-variable.is-6-mobile { + --columnGap: 1.5rem; + } +} + +@media screen and (min-width: 769px), print { + .columns.is-variable.is-6-tablet { + --columnGap: 1.5rem; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .columns.is-variable.is-6-tablet-only { + --columnGap: 1.5rem; + } +} + +@media screen and (max-width: 1023px) { + .columns.is-variable.is-6-touch { + --columnGap: 1.5rem; + } +} + +@media screen and (min-width: 1024px) { + .columns.is-variable.is-6-desktop { + --columnGap: 1.5rem; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .columns.is-variable.is-6-desktop-only { + --columnGap: 1.5rem; + } +} + +@media screen and (min-width: 1216px) { + .columns.is-variable.is-6-widescreen { + --columnGap: 1.5rem; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .columns.is-variable.is-6-widescreen-only { + --columnGap: 1.5rem; + } +} + +@media screen and (min-width: 1408px) { + .columns.is-variable.is-6-fullhd { + --columnGap: 1.5rem; + } +} + +.columns.is-variable.is-7 { + --columnGap: 1.75rem; +} + +@media screen and (max-width: 768px) { + .columns.is-variable.is-7-mobile { + --columnGap: 1.75rem; + } +} + +@media screen and (min-width: 769px), print { + .columns.is-variable.is-7-tablet { + --columnGap: 1.75rem; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .columns.is-variable.is-7-tablet-only { + --columnGap: 1.75rem; + } +} + +@media screen and (max-width: 1023px) { + .columns.is-variable.is-7-touch { + --columnGap: 1.75rem; + } +} + +@media screen and (min-width: 1024px) { + .columns.is-variable.is-7-desktop { + --columnGap: 1.75rem; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .columns.is-variable.is-7-desktop-only { + --columnGap: 1.75rem; + } +} + +@media screen and (min-width: 1216px) { + .columns.is-variable.is-7-widescreen { + --columnGap: 1.75rem; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .columns.is-variable.is-7-widescreen-only { + --columnGap: 1.75rem; + } +} + +@media screen and (min-width: 1408px) { + .columns.is-variable.is-7-fullhd { + --columnGap: 1.75rem; + } +} + +.columns.is-variable.is-8 { + --columnGap: 2rem; +} + +@media screen and (max-width: 768px) { + .columns.is-variable.is-8-mobile { + --columnGap: 2rem; + } +} + +@media screen and (min-width: 769px), print { + .columns.is-variable.is-8-tablet { + --columnGap: 2rem; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .columns.is-variable.is-8-tablet-only { + --columnGap: 2rem; + } +} + +@media screen and (max-width: 1023px) { + .columns.is-variable.is-8-touch { + --columnGap: 2rem; + } +} + +@media screen and (min-width: 1024px) { + .columns.is-variable.is-8-desktop { + --columnGap: 2rem; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .columns.is-variable.is-8-desktop-only { + --columnGap: 2rem; + } +} + +@media screen and (min-width: 1216px) { + .columns.is-variable.is-8-widescreen { + --columnGap: 2rem; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .columns.is-variable.is-8-widescreen-only { + --columnGap: 2rem; + } +} + +@media screen and (min-width: 1408px) { + .columns.is-variable.is-8-fullhd { + --columnGap: 2rem; + } +} + +.breadcrumb { + font-size: 1rem; + white-space: nowrap; +} + +.breadcrumb a { + align-items: center; + color: #FF9200; + display: flex; + justify-content: center; + padding: 0 0.75em; +} + +.breadcrumb a:hover { + color: #ca6500; +} + +.breadcrumb li { + align-items: center; + display: flex; +} + +.breadcrumb li:first-child a { + padding-left: 0; +} + +.breadcrumb li.is-active a { + color: #363636; + cursor: default; + pointer-events: none; +} + +.breadcrumb li + li::before { + color: #b5b5b5; + content: "\0002f"; +} + +.breadcrumb ul, +.breadcrumb ol { + align-items: flex-start; + display: flex; + flex-wrap: wrap; + justify-content: flex-start; +} + +.breadcrumb .icon:first-child { + margin-right: 0.5em; +} + +.breadcrumb .icon:last-child { + margin-left: 0.5em; +} + +.breadcrumb.is-centered ol, +.breadcrumb.is-centered ul { + justify-content: center; +} + +.breadcrumb.is-right ol, +.breadcrumb.is-right ul { + justify-content: flex-end; +} + +.breadcrumb.is-small { + font-size: 0.75rem; +} + +.breadcrumb.is-medium { + font-size: 1.25rem; +} + +.breadcrumb.is-large { + font-size: 1.5rem; +} + +.breadcrumb.has-arrow-separator li + li::before { + content: "\02192"; +} + +.breadcrumb.has-bullet-separator li + li::before { + content: "\02022"; +} + +.breadcrumb.has-dot-separator li + li::before { + content: "\000b7"; +} + +.breadcrumb.has-succeeds-separator li + li::before { + content: "\0227B"; +} + +.level { + align-items: center; + justify-content: space-between; +} + +.level code { + border-radius: 4px; +} + +.level img { + display: inline-block; + vertical-align: top; +} + +.level.is-mobile { + display: flex; +} + +.level.is-mobile .level-left, +.level.is-mobile .level-right { + display: flex; +} + +.level.is-mobile .level-left + .level-right { + margin-top: 0; +} + +.level.is-mobile .level-item:not(:last-child) { + margin-bottom: 0; + margin-right: 0.75rem; +} + +.level.is-mobile .level-item:not(.is-narrow) { + flex-grow: 1; +} + +@media screen and (min-width: 769px), print { + .level { + display: flex; + } + .level > .level-item:not(.is-narrow) { + flex-grow: 1; + } +} + +.level-item { + align-items: center; + display: flex; + flex-basis: auto; + flex-grow: 0; + flex-shrink: 0; + justify-content: center; +} + +.level-item .title, +.level-item .subtitle { + margin-bottom: 0; +} + +@media screen and (max-width: 768px) { + .level-item:not(:last-child) { + margin-bottom: 0.75rem; + } +} + +.level-left, +.level-right { + flex-basis: auto; + flex-grow: 0; + flex-shrink: 0; +} + +.level-left .level-item.is-flexible, +.level-right .level-item.is-flexible { + flex-grow: 1; +} + +@media screen and (min-width: 769px), print { + .level-left .level-item:not(:last-child), +.level-right .level-item:not(:last-child) { + margin-right: 0.75rem; + } +} + +.level-left { + align-items: center; + justify-content: flex-start; +} + +@media screen and (max-width: 768px) { + .level-left + .level-right { + margin-top: 1.5rem; + } +} + +@media screen and (min-width: 769px), print { + .level-left { + display: flex; + } +} + +.level-right { + align-items: center; + justify-content: flex-end; +} + +@media screen and (min-width: 769px), print { + .level-right { + display: flex; + } +} + +.navbar { + background-color: white; + min-height: 4rem; + position: relative; + z-index: 30; +} + +.navbar.is-white { + background-color: white; + color: #0a0a0a; +} + +.navbar.is-white .navbar-brand > .navbar-item, +.navbar.is-white .navbar-brand .navbar-link { + color: #0a0a0a; +} + +.navbar.is-white .navbar-brand > a.navbar-item:focus, .navbar.is-white .navbar-brand > a.navbar-item:hover, .navbar.is-white .navbar-brand > a.navbar-item.is-active, +.navbar.is-white .navbar-brand .navbar-link:focus, +.navbar.is-white .navbar-brand .navbar-link:hover, +.navbar.is-white .navbar-brand .navbar-link.is-active { + background-color: #f2f2f2; + color: #0a0a0a; +} + +.navbar.is-white .navbar-brand .navbar-link::after { + border-color: #0a0a0a; +} + +.navbar.is-white .navbar-burger { + color: #0a0a0a; +} + +@media screen and (min-width: 1024px) { + .navbar.is-white .navbar-start > .navbar-item, +.navbar.is-white .navbar-start .navbar-link, +.navbar.is-white .navbar-end > .navbar-item, +.navbar.is-white .navbar-end .navbar-link { + color: #0a0a0a; + } + .navbar.is-white .navbar-start > a.navbar-item:focus, .navbar.is-white .navbar-start > a.navbar-item:hover, .navbar.is-white .navbar-start > a.navbar-item.is-active, +.navbar.is-white .navbar-start .navbar-link:focus, +.navbar.is-white .navbar-start .navbar-link:hover, +.navbar.is-white .navbar-start .navbar-link.is-active, +.navbar.is-white .navbar-end > a.navbar-item:focus, +.navbar.is-white .navbar-end > a.navbar-item:hover, +.navbar.is-white .navbar-end > a.navbar-item.is-active, +.navbar.is-white .navbar-end .navbar-link:focus, +.navbar.is-white .navbar-end .navbar-link:hover, +.navbar.is-white .navbar-end .navbar-link.is-active { + background-color: #f2f2f2; + color: #0a0a0a; + } + .navbar.is-white .navbar-start .navbar-link::after, +.navbar.is-white .navbar-end .navbar-link::after { + border-color: #0a0a0a; + } + .navbar.is-white .navbar-item.has-dropdown:focus .navbar-link, +.navbar.is-white .navbar-item.has-dropdown:hover .navbar-link, +.navbar.is-white .navbar-item.has-dropdown.is-active .navbar-link { + background-color: #f2f2f2; + color: #0a0a0a; + } + .navbar.is-white .navbar-dropdown a.navbar-item.is-active { + background-color: white; + color: #0a0a0a; + } +} + +.navbar.is-black { + background-color: #0a0a0a; + color: white; +} + +.navbar.is-black .navbar-brand > .navbar-item, +.navbar.is-black .navbar-brand .navbar-link { + color: white; +} + +.navbar.is-black .navbar-brand > a.navbar-item:focus, .navbar.is-black .navbar-brand > a.navbar-item:hover, .navbar.is-black .navbar-brand > a.navbar-item.is-active, +.navbar.is-black .navbar-brand .navbar-link:focus, +.navbar.is-black .navbar-brand .navbar-link:hover, +.navbar.is-black .navbar-brand .navbar-link.is-active { + background-color: black; + color: white; +} + +.navbar.is-black .navbar-brand .navbar-link::after { + border-color: white; +} + +.navbar.is-black .navbar-burger { + color: white; +} + +@media screen and (min-width: 1024px) { + .navbar.is-black .navbar-start > .navbar-item, +.navbar.is-black .navbar-start .navbar-link, +.navbar.is-black .navbar-end > .navbar-item, +.navbar.is-black .navbar-end .navbar-link { + color: white; + } + .navbar.is-black .navbar-start > a.navbar-item:focus, .navbar.is-black .navbar-start > a.navbar-item:hover, .navbar.is-black .navbar-start > a.navbar-item.is-active, +.navbar.is-black .navbar-start .navbar-link:focus, +.navbar.is-black .navbar-start .navbar-link:hover, +.navbar.is-black .navbar-start .navbar-link.is-active, +.navbar.is-black .navbar-end > a.navbar-item:focus, +.navbar.is-black .navbar-end > a.navbar-item:hover, +.navbar.is-black .navbar-end > a.navbar-item.is-active, +.navbar.is-black .navbar-end .navbar-link:focus, +.navbar.is-black .navbar-end .navbar-link:hover, +.navbar.is-black .navbar-end .navbar-link.is-active { + background-color: black; + color: white; + } + .navbar.is-black .navbar-start .navbar-link::after, +.navbar.is-black .navbar-end .navbar-link::after { + border-color: white; + } + .navbar.is-black .navbar-item.has-dropdown:focus .navbar-link, +.navbar.is-black .navbar-item.has-dropdown:hover .navbar-link, +.navbar.is-black .navbar-item.has-dropdown.is-active .navbar-link { + background-color: black; + color: white; + } + .navbar.is-black .navbar-dropdown a.navbar-item.is-active { + background-color: #0a0a0a; + color: white; + } +} + +.navbar.is-light { + background-color: whitesmoke; + color: rgba(0, 0, 0, 0.7); +} + +.navbar.is-light .navbar-brand > .navbar-item, +.navbar.is-light .navbar-brand .navbar-link { + color: rgba(0, 0, 0, 0.7); +} + +.navbar.is-light .navbar-brand > a.navbar-item:focus, .navbar.is-light .navbar-brand > a.navbar-item:hover, .navbar.is-light .navbar-brand > a.navbar-item.is-active, +.navbar.is-light .navbar-brand .navbar-link:focus, +.navbar.is-light .navbar-brand .navbar-link:hover, +.navbar.is-light .navbar-brand .navbar-link.is-active { + background-color: #e8e8e8; + color: rgba(0, 0, 0, 0.7); +} + +.navbar.is-light .navbar-brand .navbar-link::after { + border-color: rgba(0, 0, 0, 0.7); +} + +.navbar.is-light .navbar-burger { + color: rgba(0, 0, 0, 0.7); +} + +@media screen and (min-width: 1024px) { + .navbar.is-light .navbar-start > .navbar-item, +.navbar.is-light .navbar-start .navbar-link, +.navbar.is-light .navbar-end > .navbar-item, +.navbar.is-light .navbar-end .navbar-link { + color: rgba(0, 0, 0, 0.7); + } + .navbar.is-light .navbar-start > a.navbar-item:focus, .navbar.is-light .navbar-start > a.navbar-item:hover, .navbar.is-light .navbar-start > a.navbar-item.is-active, +.navbar.is-light .navbar-start .navbar-link:focus, +.navbar.is-light .navbar-start .navbar-link:hover, +.navbar.is-light .navbar-start .navbar-link.is-active, +.navbar.is-light .navbar-end > a.navbar-item:focus, +.navbar.is-light .navbar-end > a.navbar-item:hover, +.navbar.is-light .navbar-end > a.navbar-item.is-active, +.navbar.is-light .navbar-end .navbar-link:focus, +.navbar.is-light .navbar-end .navbar-link:hover, +.navbar.is-light .navbar-end .navbar-link.is-active { + background-color: #e8e8e8; + color: rgba(0, 0, 0, 0.7); + } + .navbar.is-light .navbar-start .navbar-link::after, +.navbar.is-light .navbar-end .navbar-link::after { + border-color: rgba(0, 0, 0, 0.7); + } + .navbar.is-light .navbar-item.has-dropdown:focus .navbar-link, +.navbar.is-light .navbar-item.has-dropdown:hover .navbar-link, +.navbar.is-light .navbar-item.has-dropdown.is-active .navbar-link { + background-color: #e8e8e8; + color: rgba(0, 0, 0, 0.7); + } + .navbar.is-light .navbar-dropdown a.navbar-item.is-active { + background-color: whitesmoke; + color: rgba(0, 0, 0, 0.7); + } +} + +.navbar.is-dark { + background-color: #363636; + color: #fff; +} + +.navbar.is-dark .navbar-brand > .navbar-item, +.navbar.is-dark .navbar-brand .navbar-link { + color: #fff; +} + +.navbar.is-dark .navbar-brand > a.navbar-item:focus, .navbar.is-dark .navbar-brand > a.navbar-item:hover, .navbar.is-dark .navbar-brand > a.navbar-item.is-active, +.navbar.is-dark .navbar-brand .navbar-link:focus, +.navbar.is-dark .navbar-brand .navbar-link:hover, +.navbar.is-dark .navbar-brand .navbar-link.is-active { + background-color: #292929; + color: #fff; +} + +.navbar.is-dark .navbar-brand .navbar-link::after { + border-color: #fff; +} + +.navbar.is-dark .navbar-burger { + color: #fff; +} + +@media screen and (min-width: 1024px) { + .navbar.is-dark .navbar-start > .navbar-item, +.navbar.is-dark .navbar-start .navbar-link, +.navbar.is-dark .navbar-end > .navbar-item, +.navbar.is-dark .navbar-end .navbar-link { + color: #fff; + } + .navbar.is-dark .navbar-start > a.navbar-item:focus, .navbar.is-dark .navbar-start > a.navbar-item:hover, .navbar.is-dark .navbar-start > a.navbar-item.is-active, +.navbar.is-dark .navbar-start .navbar-link:focus, +.navbar.is-dark .navbar-start .navbar-link:hover, +.navbar.is-dark .navbar-start .navbar-link.is-active, +.navbar.is-dark .navbar-end > a.navbar-item:focus, +.navbar.is-dark .navbar-end > a.navbar-item:hover, +.navbar.is-dark .navbar-end > a.navbar-item.is-active, +.navbar.is-dark .navbar-end .navbar-link:focus, +.navbar.is-dark .navbar-end .navbar-link:hover, +.navbar.is-dark .navbar-end .navbar-link.is-active { + background-color: #292929; + color: #fff; + } + .navbar.is-dark .navbar-start .navbar-link::after, +.navbar.is-dark .navbar-end .navbar-link::after { + border-color: #fff; + } + .navbar.is-dark .navbar-item.has-dropdown:focus .navbar-link, +.navbar.is-dark .navbar-item.has-dropdown:hover .navbar-link, +.navbar.is-dark .navbar-item.has-dropdown.is-active .navbar-link { + background-color: #292929; + color: #fff; + } + .navbar.is-dark .navbar-dropdown a.navbar-item.is-active { + background-color: #363636; + color: #fff; + } +} + +.navbar.is-primary { + background-color: #FF9200; + color: #fff; +} + +.navbar.is-primary .navbar-brand > .navbar-item, +.navbar.is-primary .navbar-brand .navbar-link { + color: #fff; +} + +.navbar.is-primary .navbar-brand > a.navbar-item:focus, .navbar.is-primary .navbar-brand > a.navbar-item:hover, .navbar.is-primary .navbar-brand > a.navbar-item.is-active, +.navbar.is-primary .navbar-brand .navbar-link:focus, +.navbar.is-primary .navbar-brand .navbar-link:hover, +.navbar.is-primary .navbar-brand .navbar-link.is-active { + background-color: #e68300; + color: #fff; +} + +.navbar.is-primary .navbar-brand .navbar-link::after { + border-color: #fff; +} + +.navbar.is-primary .navbar-burger { + color: #fff; +} + +@media screen and (min-width: 1024px) { + .navbar.is-primary .navbar-start > .navbar-item, +.navbar.is-primary .navbar-start .navbar-link, +.navbar.is-primary .navbar-end > .navbar-item, +.navbar.is-primary .navbar-end .navbar-link { + color: #fff; + } + .navbar.is-primary .navbar-start > a.navbar-item:focus, .navbar.is-primary .navbar-start > a.navbar-item:hover, .navbar.is-primary .navbar-start > a.navbar-item.is-active, +.navbar.is-primary .navbar-start .navbar-link:focus, +.navbar.is-primary .navbar-start .navbar-link:hover, +.navbar.is-primary .navbar-start .navbar-link.is-active, +.navbar.is-primary .navbar-end > a.navbar-item:focus, +.navbar.is-primary .navbar-end > a.navbar-item:hover, +.navbar.is-primary .navbar-end > a.navbar-item.is-active, +.navbar.is-primary .navbar-end .navbar-link:focus, +.navbar.is-primary .navbar-end .navbar-link:hover, +.navbar.is-primary .navbar-end .navbar-link.is-active { + background-color: #e68300; + color: #fff; + } + .navbar.is-primary .navbar-start .navbar-link::after, +.navbar.is-primary .navbar-end .navbar-link::after { + border-color: #fff; + } + .navbar.is-primary .navbar-item.has-dropdown:focus .navbar-link, +.navbar.is-primary .navbar-item.has-dropdown:hover .navbar-link, +.navbar.is-primary .navbar-item.has-dropdown.is-active .navbar-link { + background-color: #e68300; + color: #fff; + } + .navbar.is-primary .navbar-dropdown a.navbar-item.is-active { + background-color: #FF9200; + color: #fff; + } +} + +.navbar.is-link { + background-color: #FF9200; + color: #fff; +} + +.navbar.is-link .navbar-brand > .navbar-item, +.navbar.is-link .navbar-brand .navbar-link { + color: #fff; +} + +.navbar.is-link .navbar-brand > a.navbar-item:focus, .navbar.is-link .navbar-brand > a.navbar-item:hover, .navbar.is-link .navbar-brand > a.navbar-item.is-active, +.navbar.is-link .navbar-brand .navbar-link:focus, +.navbar.is-link .navbar-brand .navbar-link:hover, +.navbar.is-link .navbar-brand .navbar-link.is-active { + background-color: #e68300; + color: #fff; +} + +.navbar.is-link .navbar-brand .navbar-link::after { + border-color: #fff; +} + +.navbar.is-link .navbar-burger { + color: #fff; +} + +@media screen and (min-width: 1024px) { + .navbar.is-link .navbar-start > .navbar-item, +.navbar.is-link .navbar-start .navbar-link, +.navbar.is-link .navbar-end > .navbar-item, +.navbar.is-link .navbar-end .navbar-link { + color: #fff; + } + .navbar.is-link .navbar-start > a.navbar-item:focus, .navbar.is-link .navbar-start > a.navbar-item:hover, .navbar.is-link .navbar-start > a.navbar-item.is-active, +.navbar.is-link .navbar-start .navbar-link:focus, +.navbar.is-link .navbar-start .navbar-link:hover, +.navbar.is-link .navbar-start .navbar-link.is-active, +.navbar.is-link .navbar-end > a.navbar-item:focus, +.navbar.is-link .navbar-end > a.navbar-item:hover, +.navbar.is-link .navbar-end > a.navbar-item.is-active, +.navbar.is-link .navbar-end .navbar-link:focus, +.navbar.is-link .navbar-end .navbar-link:hover, +.navbar.is-link .navbar-end .navbar-link.is-active { + background-color: #e68300; + color: #fff; + } + .navbar.is-link .navbar-start .navbar-link::after, +.navbar.is-link .navbar-end .navbar-link::after { + border-color: #fff; + } + .navbar.is-link .navbar-item.has-dropdown:focus .navbar-link, +.navbar.is-link .navbar-item.has-dropdown:hover .navbar-link, +.navbar.is-link .navbar-item.has-dropdown.is-active .navbar-link { + background-color: #e68300; + color: #fff; + } + .navbar.is-link .navbar-dropdown a.navbar-item.is-active { + background-color: #FF9200; + color: #fff; + } +} + +.navbar.is-info { + background-color: #3298dc; + color: #fff; +} + +.navbar.is-info .navbar-brand > .navbar-item, +.navbar.is-info .navbar-brand .navbar-link { + color: #fff; +} + +.navbar.is-info .navbar-brand > a.navbar-item:focus, .navbar.is-info .navbar-brand > a.navbar-item:hover, .navbar.is-info .navbar-brand > a.navbar-item.is-active, +.navbar.is-info .navbar-brand .navbar-link:focus, +.navbar.is-info .navbar-brand .navbar-link:hover, +.navbar.is-info .navbar-brand .navbar-link.is-active { + background-color: #238cd1; + color: #fff; +} + +.navbar.is-info .navbar-brand .navbar-link::after { + border-color: #fff; +} + +.navbar.is-info .navbar-burger { + color: #fff; +} + +@media screen and (min-width: 1024px) { + .navbar.is-info .navbar-start > .navbar-item, +.navbar.is-info .navbar-start .navbar-link, +.navbar.is-info .navbar-end > .navbar-item, +.navbar.is-info .navbar-end .navbar-link { + color: #fff; + } + .navbar.is-info .navbar-start > a.navbar-item:focus, .navbar.is-info .navbar-start > a.navbar-item:hover, .navbar.is-info .navbar-start > a.navbar-item.is-active, +.navbar.is-info .navbar-start .navbar-link:focus, +.navbar.is-info .navbar-start .navbar-link:hover, +.navbar.is-info .navbar-start .navbar-link.is-active, +.navbar.is-info .navbar-end > a.navbar-item:focus, +.navbar.is-info .navbar-end > a.navbar-item:hover, +.navbar.is-info .navbar-end > a.navbar-item.is-active, +.navbar.is-info .navbar-end .navbar-link:focus, +.navbar.is-info .navbar-end .navbar-link:hover, +.navbar.is-info .navbar-end .navbar-link.is-active { + background-color: #238cd1; + color: #fff; + } + .navbar.is-info .navbar-start .navbar-link::after, +.navbar.is-info .navbar-end .navbar-link::after { + border-color: #fff; + } + .navbar.is-info .navbar-item.has-dropdown:focus .navbar-link, +.navbar.is-info .navbar-item.has-dropdown:hover .navbar-link, +.navbar.is-info .navbar-item.has-dropdown.is-active .navbar-link { + background-color: #238cd1; + color: #fff; + } + .navbar.is-info .navbar-dropdown a.navbar-item.is-active { + background-color: #3298dc; + color: #fff; + } +} + +.navbar.is-success { + background-color: #01a901; + color: #fff; +} + +.navbar.is-success .navbar-brand > .navbar-item, +.navbar.is-success .navbar-brand .navbar-link { + color: #fff; +} + +.navbar.is-success .navbar-brand > a.navbar-item:focus, .navbar.is-success .navbar-brand > a.navbar-item:hover, .navbar.is-success .navbar-brand > a.navbar-item.is-active, +.navbar.is-success .navbar-brand .navbar-link:focus, +.navbar.is-success .navbar-brand .navbar-link:hover, +.navbar.is-success .navbar-brand .navbar-link.is-active { + background-color: #019001; + color: #fff; +} + +.navbar.is-success .navbar-brand .navbar-link::after { + border-color: #fff; +} + +.navbar.is-success .navbar-burger { + color: #fff; +} + +@media screen and (min-width: 1024px) { + .navbar.is-success .navbar-start > .navbar-item, +.navbar.is-success .navbar-start .navbar-link, +.navbar.is-success .navbar-end > .navbar-item, +.navbar.is-success .navbar-end .navbar-link { + color: #fff; + } + .navbar.is-success .navbar-start > a.navbar-item:focus, .navbar.is-success .navbar-start > a.navbar-item:hover, .navbar.is-success .navbar-start > a.navbar-item.is-active, +.navbar.is-success .navbar-start .navbar-link:focus, +.navbar.is-success .navbar-start .navbar-link:hover, +.navbar.is-success .navbar-start .navbar-link.is-active, +.navbar.is-success .navbar-end > a.navbar-item:focus, +.navbar.is-success .navbar-end > a.navbar-item:hover, +.navbar.is-success .navbar-end > a.navbar-item.is-active, +.navbar.is-success .navbar-end .navbar-link:focus, +.navbar.is-success .navbar-end .navbar-link:hover, +.navbar.is-success .navbar-end .navbar-link.is-active { + background-color: #019001; + color: #fff; + } + .navbar.is-success .navbar-start .navbar-link::after, +.navbar.is-success .navbar-end .navbar-link::after { + border-color: #fff; + } + .navbar.is-success .navbar-item.has-dropdown:focus .navbar-link, +.navbar.is-success .navbar-item.has-dropdown:hover .navbar-link, +.navbar.is-success .navbar-item.has-dropdown.is-active .navbar-link { + background-color: #019001; + color: #fff; + } + .navbar.is-success .navbar-dropdown a.navbar-item.is-active { + background-color: #01a901; + color: #fff; + } +} + +.navbar.is-warning { + background-color: #e7cb00; + color: rgba(0, 0, 0, 0.7); +} + +.navbar.is-warning .navbar-brand > .navbar-item, +.navbar.is-warning .navbar-brand .navbar-link { + color: rgba(0, 0, 0, 0.7); +} + +.navbar.is-warning .navbar-brand > a.navbar-item:focus, .navbar.is-warning .navbar-brand > a.navbar-item:hover, .navbar.is-warning .navbar-brand > a.navbar-item.is-active, +.navbar.is-warning .navbar-brand .navbar-link:focus, +.navbar.is-warning .navbar-brand .navbar-link:hover, +.navbar.is-warning .navbar-brand .navbar-link.is-active { + background-color: #ceb500; + color: rgba(0, 0, 0, 0.7); +} + +.navbar.is-warning .navbar-brand .navbar-link::after { + border-color: rgba(0, 0, 0, 0.7); +} + +.navbar.is-warning .navbar-burger { + color: rgba(0, 0, 0, 0.7); +} + +@media screen and (min-width: 1024px) { + .navbar.is-warning .navbar-start > .navbar-item, +.navbar.is-warning .navbar-start .navbar-link, +.navbar.is-warning .navbar-end > .navbar-item, +.navbar.is-warning .navbar-end .navbar-link { + color: rgba(0, 0, 0, 0.7); + } + .navbar.is-warning .navbar-start > a.navbar-item:focus, .navbar.is-warning .navbar-start > a.navbar-item:hover, .navbar.is-warning .navbar-start > a.navbar-item.is-active, +.navbar.is-warning .navbar-start .navbar-link:focus, +.navbar.is-warning .navbar-start .navbar-link:hover, +.navbar.is-warning .navbar-start .navbar-link.is-active, +.navbar.is-warning .navbar-end > a.navbar-item:focus, +.navbar.is-warning .navbar-end > a.navbar-item:hover, +.navbar.is-warning .navbar-end > a.navbar-item.is-active, +.navbar.is-warning .navbar-end .navbar-link:focus, +.navbar.is-warning .navbar-end .navbar-link:hover, +.navbar.is-warning .navbar-end .navbar-link.is-active { + background-color: #ceb500; + color: rgba(0, 0, 0, 0.7); + } + .navbar.is-warning .navbar-start .navbar-link::after, +.navbar.is-warning .navbar-end .navbar-link::after { + border-color: rgba(0, 0, 0, 0.7); + } + .navbar.is-warning .navbar-item.has-dropdown:focus .navbar-link, +.navbar.is-warning .navbar-item.has-dropdown:hover .navbar-link, +.navbar.is-warning .navbar-item.has-dropdown.is-active .navbar-link { + background-color: #ceb500; + color: rgba(0, 0, 0, 0.7); + } + .navbar.is-warning .navbar-dropdown a.navbar-item.is-active { + background-color: #e7cb00; + color: rgba(0, 0, 0, 0.7); + } +} + +.navbar.is-danger { + background-color: #F45F4B; + color: #fff; +} + +.navbar.is-danger .navbar-brand > .navbar-item, +.navbar.is-danger .navbar-brand .navbar-link { + color: #fff; +} + +.navbar.is-danger .navbar-brand > a.navbar-item:focus, .navbar.is-danger .navbar-brand > a.navbar-item:hover, .navbar.is-danger .navbar-brand > a.navbar-item.is-active, +.navbar.is-danger .navbar-brand .navbar-link:focus, +.navbar.is-danger .navbar-brand .navbar-link:hover, +.navbar.is-danger .navbar-brand .navbar-link.is-active { + background-color: #f34a33; + color: #fff; +} + +.navbar.is-danger .navbar-brand .navbar-link::after { + border-color: #fff; +} + +.navbar.is-danger .navbar-burger { + color: #fff; +} + +@media screen and (min-width: 1024px) { + .navbar.is-danger .navbar-start > .navbar-item, +.navbar.is-danger .navbar-start .navbar-link, +.navbar.is-danger .navbar-end > .navbar-item, +.navbar.is-danger .navbar-end .navbar-link { + color: #fff; + } + .navbar.is-danger .navbar-start > a.navbar-item:focus, .navbar.is-danger .navbar-start > a.navbar-item:hover, .navbar.is-danger .navbar-start > a.navbar-item.is-active, +.navbar.is-danger .navbar-start .navbar-link:focus, +.navbar.is-danger .navbar-start .navbar-link:hover, +.navbar.is-danger .navbar-start .navbar-link.is-active, +.navbar.is-danger .navbar-end > a.navbar-item:focus, +.navbar.is-danger .navbar-end > a.navbar-item:hover, +.navbar.is-danger .navbar-end > a.navbar-item.is-active, +.navbar.is-danger .navbar-end .navbar-link:focus, +.navbar.is-danger .navbar-end .navbar-link:hover, +.navbar.is-danger .navbar-end .navbar-link.is-active { + background-color: #f34a33; + color: #fff; + } + .navbar.is-danger .navbar-start .navbar-link::after, +.navbar.is-danger .navbar-end .navbar-link::after { + border-color: #fff; + } + .navbar.is-danger .navbar-item.has-dropdown:focus .navbar-link, +.navbar.is-danger .navbar-item.has-dropdown:hover .navbar-link, +.navbar.is-danger .navbar-item.has-dropdown.is-active .navbar-link { + background-color: #f34a33; + color: #fff; + } + .navbar.is-danger .navbar-dropdown a.navbar-item.is-active { + background-color: #F45F4B; + color: #fff; + } +} + +.navbar > .container { + align-items: stretch; + display: flex; + min-height: 4rem; + width: 100%; +} + +.navbar.has-shadow { + box-shadow: 0 2px 0 0 #FFFFFF; +} + +.navbar.is-fixed-bottom, .navbar.is-fixed-top { + left: 0; + position: fixed; + right: 0; + z-index: 30; +} + +.navbar.is-fixed-bottom { + bottom: 0; +} + +.navbar.is-fixed-bottom.has-shadow { + box-shadow: 0 -2px 0 0 #FFFFFF; +} + +.navbar.is-fixed-top { + top: 0; +} + +html.has-navbar-fixed-top, +body.has-navbar-fixed-top { + padding-top: 4rem; +} + +html.has-navbar-fixed-bottom, +body.has-navbar-fixed-bottom { + padding-bottom: 4rem; +} + +.navbar-brand, +.navbar-tabs { + align-items: stretch; + display: flex; + flex-shrink: 0; + min-height: 4rem; +} + +.navbar-brand a.navbar-item:focus, .navbar-brand a.navbar-item:hover { + background-color: transparent; +} + +.navbar-tabs { + -webkit-overflow-scrolling: touch; + max-width: 100vw; + overflow-x: auto; + overflow-y: hidden; +} + +.navbar-burger { + color: rgba(0, 0, 0, 0.87); + cursor: pointer; + display: block; + height: 4rem; + position: relative; + width: 4rem; + margin-left: auto; +} + +.navbar-burger span { + background-color: currentColor; + display: block; + height: 1px; + left: calc(50% - 8px); + position: absolute; + transform-origin: center; + transition-duration: 86ms; + transition-property: background-color, opacity, transform; + transition-timing-function: ease-out; + width: 16px; +} + +.navbar-burger span:nth-child(1) { + top: calc(50% - 6px); +} + +.navbar-burger span:nth-child(2) { + top: calc(50% - 1px); +} + +.navbar-burger span:nth-child(3) { + top: calc(50% + 4px); +} + +.navbar-burger:hover { + background-color: rgba(0, 0, 0, 0.05); +} + +.navbar-burger.is-active span:nth-child(1) { + transform: translateY(5px) rotate(45deg); +} + +.navbar-burger.is-active span:nth-child(2) { + opacity: 0; +} + +.navbar-burger.is-active span:nth-child(3) { + transform: translateY(-5px) rotate(-45deg); +} + +.navbar-menu { + display: none; +} + +.navbar-item, +.navbar-link { + color: rgba(0, 0, 0, 0.87); + display: block; + line-height: 1.5; + padding: 0.5rem 0.75rem; + position: relative; +} + +.navbar-item .icon:only-child, +.navbar-link .icon:only-child { + margin-left: -0.25rem; + margin-right: -0.25rem; +} + +a.navbar-item, +.navbar-link { + cursor: pointer; +} + +a.navbar-item:focus, a.navbar-item:focus-within, a.navbar-item:hover, a.navbar-item.is-active, +.navbar-link:focus, +.navbar-link:focus-within, +.navbar-link:hover, +.navbar-link.is-active { + background-color: #fafafa; + color: #FF9200; +} + +.navbar-item { + flex-grow: 0; + flex-shrink: 0; +} + +.navbar-item img { + max-height: 1.75rem; +} + +.navbar-item.has-dropdown { + padding: 0; +} + +.navbar-item.is-expanded { + flex-grow: 1; + flex-shrink: 1; +} + +.navbar-item.is-tab { + border-bottom: 1px solid transparent; + min-height: 4rem; + padding-bottom: calc(0.5rem - 1px); +} + +.navbar-item.is-tab:focus, .navbar-item.is-tab:hover { + background-color: transparent; + border-bottom-color: #FF9200; +} + +.navbar-item.is-tab.is-active { + background-color: transparent; + border-bottom-color: #FF9200; + border-bottom-style: solid; + border-bottom-width: 3px; + color: #FF9200; + padding-bottom: calc(0.5rem - 3px); +} + +.navbar-content { + flex-grow: 1; + flex-shrink: 1; +} + +.navbar-link:not(.is-arrowless) { + padding-right: 2.5em; +} + +.navbar-link:not(.is-arrowless)::after { + border-color: #FF9200; + margin-top: -0.375em; + right: 1.125em; +} + +.navbar-dropdown { + font-size: 0.875rem; + padding-bottom: 0.5rem; + padding-top: 0.5rem; +} + +.navbar-dropdown .navbar-item { + padding-left: 1.5rem; + padding-right: 1.5rem; +} + +.navbar-divider { + background-color: #FFFFFF; + border: none; + display: none; + height: 2px; + margin: 0.5rem 0; +} + +@media screen and (max-width: 1023px) { + .navbar > .container { + display: block; + } + .navbar-brand .navbar-item, +.navbar-tabs .navbar-item { + align-items: center; + display: flex; + } + .navbar-link::after { + display: none; + } + .navbar-menu { + background-color: white; + box-shadow: 0 8px 16px rgba(10, 10, 10, 0.1); + padding: 0.5rem 0; + } + .navbar-menu.is-active { + display: block; + } + .navbar.is-fixed-bottom-touch, .navbar.is-fixed-top-touch { + left: 0; + position: fixed; + right: 0; + z-index: 30; + } + .navbar.is-fixed-bottom-touch { + bottom: 0; + } + .navbar.is-fixed-bottom-touch.has-shadow { + box-shadow: 0 -2px 3px rgba(10, 10, 10, 0.1); + } + .navbar.is-fixed-top-touch { + top: 0; + } + .navbar.is-fixed-top .navbar-menu, .navbar.is-fixed-top-touch .navbar-menu { + -webkit-overflow-scrolling: touch; + max-height: calc(100vh - 4rem); + overflow: auto; + } + html.has-navbar-fixed-top-touch, +body.has-navbar-fixed-top-touch { + padding-top: 4rem; + } + html.has-navbar-fixed-bottom-touch, +body.has-navbar-fixed-bottom-touch { + padding-bottom: 4rem; + } +} + +@media screen and (min-width: 1024px) { + .navbar, +.navbar-menu, +.navbar-start, +.navbar-end { + align-items: stretch; + display: flex; + } + .navbar { + min-height: 4rem; + } + .navbar.is-spaced { + padding: 1rem 2rem; + } + .navbar.is-spaced .navbar-start, +.navbar.is-spaced .navbar-end { + align-items: center; + } + .navbar.is-spaced a.navbar-item, +.navbar.is-spaced .navbar-link { + border-radius: 4px; + } + .navbar.is-transparent a.navbar-item:focus, .navbar.is-transparent a.navbar-item:hover, .navbar.is-transparent a.navbar-item.is-active, +.navbar.is-transparent .navbar-link:focus, +.navbar.is-transparent .navbar-link:hover, +.navbar.is-transparent .navbar-link.is-active { + background-color: transparent !important; + } + .navbar.is-transparent .navbar-item.has-dropdown.is-active .navbar-link, .navbar.is-transparent .navbar-item.has-dropdown.is-hoverable:focus .navbar-link, .navbar.is-transparent .navbar-item.has-dropdown.is-hoverable:focus-within .navbar-link, .navbar.is-transparent .navbar-item.has-dropdown.is-hoverable:hover .navbar-link { + background-color: transparent !important; + } + .navbar.is-transparent .navbar-dropdown a.navbar-item:focus, .navbar.is-transparent .navbar-dropdown a.navbar-item:hover { + background-color: #FFFFFF; + color: #0a0a0a; + } + .navbar.is-transparent .navbar-dropdown a.navbar-item.is-active { + background-color: #FFFFFF; + color: #FF9200; + } + .navbar-burger { + display: none; + } + .navbar-item, +.navbar-link { + align-items: center; + display: flex; + } + .navbar-item.has-dropdown { + align-items: stretch; + } + .navbar-item.has-dropdown-up .navbar-link::after { + transform: rotate(135deg) translate(0.25em, -0.25em); + } + .navbar-item.has-dropdown-up .navbar-dropdown { + border-bottom: 2px solid #dbdbdb; + border-radius: 6px 6px 0 0; + border-top: none; + bottom: 100%; + box-shadow: 0 -8px 8px rgba(10, 10, 10, 0.1); + top: auto; + } + .navbar-item.is-active .navbar-dropdown, .navbar-item.is-hoverable:focus .navbar-dropdown, .navbar-item.is-hoverable:focus-within .navbar-dropdown, .navbar-item.is-hoverable:hover .navbar-dropdown { + display: block; + } + .navbar.is-spaced .navbar-item.is-active .navbar-dropdown, .navbar-item.is-active .navbar-dropdown.is-boxed, .navbar.is-spaced .navbar-item.is-hoverable:focus .navbar-dropdown, .navbar-item.is-hoverable:focus .navbar-dropdown.is-boxed, .navbar.is-spaced .navbar-item.is-hoverable:focus-within .navbar-dropdown, .navbar-item.is-hoverable:focus-within .navbar-dropdown.is-boxed, .navbar.is-spaced .navbar-item.is-hoverable:hover .navbar-dropdown, .navbar-item.is-hoverable:hover .navbar-dropdown.is-boxed { + opacity: 1; + pointer-events: auto; + transform: translateY(0); + } + .navbar-menu { + flex-grow: 1; + flex-shrink: 0; + } + .navbar-start { + justify-content: flex-start; + margin-right: auto; + } + .navbar-end { + justify-content: flex-end; + margin-left: auto; + } + .navbar-dropdown { + background-color: white; + border-bottom-left-radius: 6px; + border-bottom-right-radius: 6px; + border-top: 2px solid #dbdbdb; + box-shadow: 0 8px 8px rgba(10, 10, 10, 0.1); + display: none; + font-size: 0.875rem; + left: 0; + min-width: 100%; + position: absolute; + top: 100%; + z-index: 20; + } + .navbar-dropdown .navbar-item { + padding: 0.375rem 1rem; + white-space: nowrap; + } + .navbar-dropdown a.navbar-item { + padding-right: 3rem; + } + .navbar-dropdown a.navbar-item:focus, .navbar-dropdown a.navbar-item:hover { + background-color: #FFFFFF; + color: #0a0a0a; + } + .navbar-dropdown a.navbar-item.is-active { + background-color: #FFFFFF; + color: #FF9200; + } + .navbar.is-spaced .navbar-dropdown, .navbar-dropdown.is-boxed { + border-radius: 6px; + border-top: none; + box-shadow: 0 8px 8px rgba(10, 10, 10, 0.1), 0 0 0 1px rgba(10, 10, 10, 0.1); + display: block; + opacity: 0; + pointer-events: none; + top: calc(100% + (-4px)); + transform: translateY(-5px); + transition-duration: 86ms; + transition-property: opacity, transform; + } + .navbar-dropdown.is-right { + left: auto; + right: 0; + } + .navbar-divider { + display: block; + } + .navbar > .container .navbar-brand, +.container > .navbar .navbar-brand { + margin-left: -0.75rem; + } + .navbar > .container .navbar-menu, +.container > .navbar .navbar-menu { + margin-right: -0.75rem; + } + .navbar.is-fixed-bottom-desktop, .navbar.is-fixed-top-desktop { + left: 0; + position: fixed; + right: 0; + z-index: 30; + } + .navbar.is-fixed-bottom-desktop { + bottom: 0; + } + .navbar.is-fixed-bottom-desktop.has-shadow { + box-shadow: 0 -2px 3px rgba(10, 10, 10, 0.1); + } + .navbar.is-fixed-top-desktop { + top: 0; + } + html.has-navbar-fixed-top-desktop, +body.has-navbar-fixed-top-desktop { + padding-top: 4rem; + } + html.has-navbar-fixed-bottom-desktop, +body.has-navbar-fixed-bottom-desktop { + padding-bottom: 4rem; + } + html.has-spaced-navbar-fixed-top, +body.has-spaced-navbar-fixed-top { + padding-top: 6rem; + } + html.has-spaced-navbar-fixed-bottom, +body.has-spaced-navbar-fixed-bottom { + padding-bottom: 6rem; + } + a.navbar-item.is-active, +.navbar-link.is-active { + color: #0a0a0a; + } + a.navbar-item.is-active:not(:focus):not(:hover), +.navbar-link.is-active:not(:focus):not(:hover) { + background-color: transparent; + } + .navbar-item.has-dropdown:focus .navbar-link, .navbar-item.has-dropdown:hover .navbar-link, .navbar-item.has-dropdown.is-active .navbar-link { + background-color: #fafafa; + } +} + +.hero.is-fullheight-with-navbar { + min-height: calc(100vh - 4rem); +} + +.menu { + font-size: 1rem; +} + +.menu.is-small { + font-size: 0.75rem; +} + +.menu.is-medium { + font-size: 1.25rem; +} + +.menu.is-large { + font-size: 1.5rem; +} + +.menu-list { + line-height: 1.25; +} + +.menu-list a { + border-radius: 2px; + color: rgba(0, 0, 0, 0.87); + display: block; + padding: 0.5em 0.75em; +} + +.menu-list a:hover { + background-color: transparent; + color: #ca6500; +} + +.menu-list a.is-active { + background-color: #ca6500; + color: #fff; +} + +.menu-list li ul { + border-left: 1px solid #dbdbdb; + margin: 0.75em; + padding-left: 0.75em; +} + +.menu-label { + color: #7a7a7a; + font-size: 0.75em; + letter-spacing: 0.1em; + text-transform: uppercase; +} + +.menu-label:not(:first-child) { + margin-top: 1em; +} + +.menu-label:not(:last-child) { + margin-bottom: 1em; +} + +.tabs { + -webkit-overflow-scrolling: touch; + align-items: stretch; + display: flex; + font-size: 1rem; + justify-content: space-between; + overflow: hidden; + overflow-x: auto; + white-space: nowrap; +} + +.tabs a { + align-items: center; + border-bottom-color: #dbdbdb; + border-bottom-style: solid; + border-bottom-width: 1px; + color: rgba(0, 0, 0, 0.87); + display: flex; + justify-content: center; + margin-bottom: -1px; + padding: 0.5em 1em; + vertical-align: top; +} + +.tabs a:hover { + border-bottom-color: #363636; + color: #363636; +} + +.tabs li { + display: block; +} + +.tabs li.is-active a { + border-bottom-color: #FF9200; + color: #FF9200; +} + +.tabs ul { + align-items: center; + border-bottom-color: #dbdbdb; + border-bottom-style: solid; + border-bottom-width: 1px; + display: flex; + flex-grow: 1; + flex-shrink: 0; + justify-content: flex-start; +} + +.tabs ul.is-left { + padding-right: 0.75em; +} + +.tabs ul.is-center { + flex: none; + justify-content: center; + padding-left: 0.75em; + padding-right: 0.75em; +} + +.tabs ul.is-right { + justify-content: flex-end; + padding-left: 0.75em; +} + +.tabs .icon:first-child { + margin-right: 0.5em; +} + +.tabs .icon:last-child { + margin-left: 0.5em; +} + +.tabs.is-centered ul { + justify-content: center; +} + +.tabs.is-right ul { + justify-content: flex-end; +} + +.tabs.is-boxed a { + border: 1px solid transparent; + border-radius: 4px 4px 0 0; +} + +.tabs.is-boxed a:hover { + background-color: #FFFFFF; + border-bottom-color: #dbdbdb; +} + +.tabs.is-boxed li.is-active a { + background-color: white; + border-color: #dbdbdb; + border-bottom-color: transparent !important; +} + +.tabs.is-fullwidth li { + flex-grow: 1; + flex-shrink: 0; +} + +.tabs.is-toggle a { + border-color: #dbdbdb; + border-style: solid; + border-width: 1px; + margin-bottom: 0; + position: relative; +} + +.tabs.is-toggle a:hover { + background-color: #FFFFFF; + border-color: #b5b5b5; + z-index: 2; +} + +.tabs.is-toggle li + li { + margin-left: -1px; +} + +.tabs.is-toggle li:first-child a { + border-top-left-radius: 4px; + border-bottom-left-radius: 4px; +} + +.tabs.is-toggle li:last-child a { + border-top-right-radius: 4px; + border-bottom-right-radius: 4px; +} + +.tabs.is-toggle li.is-active a { + background-color: #FF9200; + border-color: #FF9200; + color: #fff; + z-index: 1; +} + +.tabs.is-toggle ul { + border-bottom: none; +} + +.tabs.is-toggle.is-toggle-rounded li:first-child a { + border-bottom-left-radius: 290486px; + border-top-left-radius: 290486px; + padding-left: 1.25em; +} + +.tabs.is-toggle.is-toggle-rounded li:last-child a { + border-bottom-right-radius: 290486px; + border-top-right-radius: 290486px; + padding-right: 1.25em; +} + +.tabs.is-small { + font-size: 0.75rem; +} + +.tabs.is-medium { + font-size: 1.25rem; +} + +.tabs.is-large { + font-size: 1.5rem; +} + +.icon { + align-items: center; + display: inline-flex; + justify-content: center; + height: 1.5rem; + width: 1.5rem; +} + +.icon.is-small { + height: 1rem; + width: 1rem; +} + +.icon.is-medium { + height: 2rem; + width: 2rem; +} + +.icon.is-large { + height: 3rem; + width: 3rem; +} + +.icon-text { + align-items: flex-start; + color: inherit; + display: inline-flex; + flex-wrap: wrap; + line-height: 1.5rem; + vertical-align: top; +} + +.icon-text .icon { + flex-grow: 0; + flex-shrink: 0; +} + +.icon-text .icon:not(:last-child) { + margin-right: 0.25em; +} + +.icon-text .icon:not(:first-child) { + margin-left: 0.25em; +} + +div.icon-text { + display: flex; +} + +.image { + display: block; + position: relative; +} + +.image img { + display: block; + height: auto; + width: 100%; +} + +.image img.is-rounded { + border-radius: 290486px; +} + +.image.is-fullwidth { + width: 100%; +} + +.image.is-square img, +.image.is-square .has-ratio, .image.is-1by1 img, +.image.is-1by1 .has-ratio, .image.is-5by4 img, +.image.is-5by4 .has-ratio, .image.is-4by3 img, +.image.is-4by3 .has-ratio, .image.is-3by2 img, +.image.is-3by2 .has-ratio, .image.is-5by3 img, +.image.is-5by3 .has-ratio, .image.is-16by9 img, +.image.is-16by9 .has-ratio, .image.is-2by1 img, +.image.is-2by1 .has-ratio, .image.is-3by1 img, +.image.is-3by1 .has-ratio, .image.is-4by5 img, +.image.is-4by5 .has-ratio, .image.is-3by4 img, +.image.is-3by4 .has-ratio, .image.is-2by3 img, +.image.is-2by3 .has-ratio, .image.is-3by5 img, +.image.is-3by5 .has-ratio, .image.is-9by16 img, +.image.is-9by16 .has-ratio, .image.is-1by2 img, +.image.is-1by2 .has-ratio, .image.is-1by3 img, +.image.is-1by3 .has-ratio { + height: 100%; + width: 100%; +} + +.image.is-square, .image.is-1by1 { + padding-top: 100%; +} + +.image.is-5by4 { + padding-top: 80%; +} + +.image.is-4by3 { + padding-top: 75%; +} + +.image.is-3by2 { + padding-top: 66.6666%; +} + +.image.is-5by3 { + padding-top: 60%; +} + +.image.is-16by9 { + padding-top: 56.25%; +} + +.image.is-2by1 { + padding-top: 50%; +} + +.image.is-3by1 { + padding-top: 33.3333%; +} + +.image.is-4by5 { + padding-top: 125%; +} + +.image.is-3by4 { + padding-top: 133.3333%; +} + +.image.is-2by3 { + padding-top: 150%; +} + +.image.is-3by5 { + padding-top: 166.6666%; +} + +.image.is-9by16 { + padding-top: 177.7777%; +} + +.image.is-1by2 { + padding-top: 200%; +} + +.image.is-1by3 { + padding-top: 300%; +} + +.image.is-16x16 { + height: 16px; + width: 16px; +} + +.image.is-24x24 { + height: 24px; + width: 24px; +} + +.image.is-32x32 { + height: 32px; + width: 32px; +} + +.image.is-48x48 { + height: 48px; + width: 48px; +} + +.image.is-64x64 { + height: 64px; + width: 64px; +} + +.image.is-96x96 { + height: 96px; + width: 96px; +} + +.image.is-128x128 { + height: 128px; + width: 128px; +} + +/* Bulma Form */ +.select select, .textarea, .input { + background-color: white; + border-color: #dbdbdb; + border-radius: 4px; + color: #363636; +} + +.select select::-moz-placeholder, .textarea::-moz-placeholder, .input::-moz-placeholder { + color: rgba(54, 54, 54, 0.3); +} + +.select select::-webkit-input-placeholder, .textarea::-webkit-input-placeholder, .input::-webkit-input-placeholder { + color: rgba(54, 54, 54, 0.3); +} + +.select select:-moz-placeholder, .textarea:-moz-placeholder, .input:-moz-placeholder { + color: rgba(54, 54, 54, 0.3); +} + +.select select:-ms-input-placeholder, .textarea:-ms-input-placeholder, .input:-ms-input-placeholder { + color: rgba(54, 54, 54, 0.3); +} + +.select select:hover, .textarea:hover, .input:hover, .select select.is-hovered, .is-hovered.textarea, .is-hovered.input { + border-color: #b5b5b5; +} + +.select select:focus, .textarea:focus, .input:focus, .select select.is-focused, .is-focused.textarea, .is-focused.input, .select select:active, .textarea:active, .input:active, .select select.is-active, .is-active.textarea, .is-active.input { + border-color: #FF9200; + box-shadow: 0 0 0 0.125em rgba(255, 146, 0, 0.25); +} + +.select select[disabled], [disabled].textarea, [disabled].input, fieldset[disabled] .select select, .select fieldset[disabled] select, fieldset[disabled] .textarea, fieldset[disabled] .input { + background-color: #FFFFFF; + border-color: #FFFFFF; + box-shadow: none; + color: #7a7a7a; +} + +.select select[disabled]::-moz-placeholder, [disabled].textarea::-moz-placeholder, [disabled].input::-moz-placeholder, fieldset[disabled] .select select::-moz-placeholder, .select fieldset[disabled] select::-moz-placeholder, fieldset[disabled] .textarea::-moz-placeholder, fieldset[disabled] .input::-moz-placeholder { + color: rgba(122, 122, 122, 0.3); +} + +.select select[disabled]::-webkit-input-placeholder, [disabled].textarea::-webkit-input-placeholder, [disabled].input::-webkit-input-placeholder, fieldset[disabled] .select select::-webkit-input-placeholder, .select fieldset[disabled] select::-webkit-input-placeholder, fieldset[disabled] .textarea::-webkit-input-placeholder, fieldset[disabled] .input::-webkit-input-placeholder { + color: rgba(122, 122, 122, 0.3); +} + +.select select[disabled]:-moz-placeholder, [disabled].textarea:-moz-placeholder, [disabled].input:-moz-placeholder, fieldset[disabled] .select select:-moz-placeholder, .select fieldset[disabled] select:-moz-placeholder, fieldset[disabled] .textarea:-moz-placeholder, fieldset[disabled] .input:-moz-placeholder { + color: rgba(122, 122, 122, 0.3); +} + +.select select[disabled]:-ms-input-placeholder, [disabled].textarea:-ms-input-placeholder, [disabled].input:-ms-input-placeholder, fieldset[disabled] .select select:-ms-input-placeholder, .select fieldset[disabled] select:-ms-input-placeholder, fieldset[disabled] .textarea:-ms-input-placeholder, fieldset[disabled] .input:-ms-input-placeholder { + color: rgba(122, 122, 122, 0.3); +} + +.textarea, .input { + box-shadow: inset 0 0.0625em 0.125em rgba(10, 10, 10, 0.05); + max-width: 100%; + width: 100%; +} + +[readonly].textarea, [readonly].input { + box-shadow: none; +} + +.is-white.textarea, .is-white.input { + border-color: white; +} + +.is-white.textarea:focus, .is-white.input:focus, .is-white.is-focused.textarea, .is-white.is-focused.input, .is-white.textarea:active, .is-white.input:active, .is-white.is-active.textarea, .is-white.is-active.input { + box-shadow: 0 0 0 0.125em rgba(255, 255, 255, 0.25); +} + +.is-black.textarea, .is-black.input { + border-color: #0a0a0a; +} + +.is-black.textarea:focus, .is-black.input:focus, .is-black.is-focused.textarea, .is-black.is-focused.input, .is-black.textarea:active, .is-black.input:active, .is-black.is-active.textarea, .is-black.is-active.input { + box-shadow: 0 0 0 0.125em rgba(10, 10, 10, 0.25); +} + +.is-light.textarea, .is-light.input { + border-color: whitesmoke; +} + +.is-light.textarea:focus, .is-light.input:focus, .is-light.is-focused.textarea, .is-light.is-focused.input, .is-light.textarea:active, .is-light.input:active, .is-light.is-active.textarea, .is-light.is-active.input { + box-shadow: 0 0 0 0.125em rgba(245, 245, 245, 0.25); +} + +.is-dark.textarea, .is-dark.input { + border-color: #363636; +} + +.is-dark.textarea:focus, .is-dark.input:focus, .is-dark.is-focused.textarea, .is-dark.is-focused.input, .is-dark.textarea:active, .is-dark.input:active, .is-dark.is-active.textarea, .is-dark.is-active.input { + box-shadow: 0 0 0 0.125em rgba(54, 54, 54, 0.25); +} + +.is-primary.textarea, .is-primary.input { + border-color: #FF9200; +} + +.is-primary.textarea:focus, .is-primary.input:focus, .is-primary.is-focused.textarea, .is-primary.is-focused.input, .is-primary.textarea:active, .is-primary.input:active, .is-primary.is-active.textarea, .is-primary.is-active.input { + box-shadow: 0 0 0 0.125em rgba(255, 146, 0, 0.25); +} + +.is-link.textarea, .is-link.input { + border-color: #FF9200; +} + +.is-link.textarea:focus, .is-link.input:focus, .is-link.is-focused.textarea, .is-link.is-focused.input, .is-link.textarea:active, .is-link.input:active, .is-link.is-active.textarea, .is-link.is-active.input { + box-shadow: 0 0 0 0.125em rgba(255, 146, 0, 0.25); +} + +.is-info.textarea, .is-info.input { + border-color: #3298dc; +} + +.is-info.textarea:focus, .is-info.input:focus, .is-info.is-focused.textarea, .is-info.is-focused.input, .is-info.textarea:active, .is-info.input:active, .is-info.is-active.textarea, .is-info.is-active.input { + box-shadow: 0 0 0 0.125em rgba(50, 152, 220, 0.25); +} + +.is-success.textarea, .is-success.input { + border-color: #01a901; +} + +.is-success.textarea:focus, .is-success.input:focus, .is-success.is-focused.textarea, .is-success.is-focused.input, .is-success.textarea:active, .is-success.input:active, .is-success.is-active.textarea, .is-success.is-active.input { + box-shadow: 0 0 0 0.125em rgba(1, 169, 1, 0.25); +} + +.is-warning.textarea, .is-warning.input { + border-color: #e7cb00; +} + +.is-warning.textarea:focus, .is-warning.input:focus, .is-warning.is-focused.textarea, .is-warning.is-focused.input, .is-warning.textarea:active, .is-warning.input:active, .is-warning.is-active.textarea, .is-warning.is-active.input { + box-shadow: 0 0 0 0.125em rgba(231, 203, 0, 0.25); +} + +.is-danger.textarea, .is-danger.input { + border-color: #F45F4B; +} + +.is-danger.textarea:focus, .is-danger.input:focus, .is-danger.is-focused.textarea, .is-danger.is-focused.input, .is-danger.textarea:active, .is-danger.input:active, .is-danger.is-active.textarea, .is-danger.is-active.input { + box-shadow: 0 0 0 0.125em rgba(244, 95, 75, 0.25); +} + +.is-small.textarea, .is-small.input { + border-radius: 2px; + font-size: 0.75rem; +} + +.is-medium.textarea, .is-medium.input { + font-size: 1.25rem; +} + +.is-large.textarea, .is-large.input { + font-size: 1.5rem; +} + +.is-fullwidth.textarea, .is-fullwidth.input { + display: block; + width: 100%; +} + +.is-inline.textarea, .is-inline.input { + display: inline; + width: auto; +} + +.input.is-rounded { + border-radius: 290486px; + padding-left: calc(calc(0.75em - 1px) + 0.375em); + padding-right: calc(calc(0.75em - 1px) + 0.375em); +} + +.input.is-static { + background-color: transparent; + border-color: transparent; + box-shadow: none; + padding-left: 0; + padding-right: 0; +} + +.textarea { + display: block; + max-width: 100%; + min-width: 100%; + padding: calc(0.75em - 1px); + resize: vertical; +} + +.textarea:not([rows]) { + max-height: 40em; + min-height: 8em; +} + +.textarea[rows] { + height: initial; +} + +.textarea.has-fixed-size { + resize: none; +} + +.radio, .checkbox { + cursor: pointer; + display: inline-block; + line-height: 1.25; + position: relative; +} + +.radio input, .checkbox input { + cursor: pointer; +} + +.radio:hover, .checkbox:hover { + color: #363636; +} + +[disabled].radio, [disabled].checkbox, fieldset[disabled] .radio, fieldset[disabled] .checkbox, +.radio input[disabled], +.checkbox input[disabled] { + color: #7a7a7a; + cursor: not-allowed; +} + +.radio + .radio { + margin-left: 0.5em; +} + +.select { + display: inline-block; + max-width: 100%; + position: relative; + vertical-align: top; +} + +.select:not(.is-multiple) { + height: 2.5em; +} + +.select:not(.is-multiple):not(.is-loading)::after { + border-color: #FF9200; + right: 1.125em; + z-index: 4; +} + +.select.is-rounded select { + border-radius: 290486px; + padding-left: 1em; +} + +.select select { + cursor: pointer; + display: block; + font-size: 1em; + max-width: 100%; + outline: none; +} + +.select select::-ms-expand { + display: none; +} + +.select select[disabled]:hover, fieldset[disabled] .select select:hover { + border-color: #FFFFFF; +} + +.select select:not([multiple]) { + padding-right: 2.5em; +} + +.select select[multiple] { + height: auto; + padding: 0; +} + +.select select[multiple] option { + padding: 0.5em 1em; +} + +.select:not(.is-multiple):not(.is-loading):hover::after { + border-color: #363636; +} + +.select.is-white:not(:hover)::after { + border-color: white; +} + +.select.is-white select { + border-color: white; +} + +.select.is-white select:hover, .select.is-white select.is-hovered { + border-color: #f2f2f2; +} + +.select.is-white select:focus, .select.is-white select.is-focused, .select.is-white select:active, .select.is-white select.is-active { + box-shadow: 0 0 0 0.125em rgba(255, 255, 255, 0.25); +} + +.select.is-black:not(:hover)::after { + border-color: #0a0a0a; +} + +.select.is-black select { + border-color: #0a0a0a; +} + +.select.is-black select:hover, .select.is-black select.is-hovered { + border-color: black; +} + +.select.is-black select:focus, .select.is-black select.is-focused, .select.is-black select:active, .select.is-black select.is-active { + box-shadow: 0 0 0 0.125em rgba(10, 10, 10, 0.25); +} + +.select.is-light:not(:hover)::after { + border-color: whitesmoke; +} + +.select.is-light select { + border-color: whitesmoke; +} + +.select.is-light select:hover, .select.is-light select.is-hovered { + border-color: #e8e8e8; +} + +.select.is-light select:focus, .select.is-light select.is-focused, .select.is-light select:active, .select.is-light select.is-active { + box-shadow: 0 0 0 0.125em rgba(245, 245, 245, 0.25); +} + +.select.is-dark:not(:hover)::after { + border-color: #363636; +} + +.select.is-dark select { + border-color: #363636; +} + +.select.is-dark select:hover, .select.is-dark select.is-hovered { + border-color: #292929; +} + +.select.is-dark select:focus, .select.is-dark select.is-focused, .select.is-dark select:active, .select.is-dark select.is-active { + box-shadow: 0 0 0 0.125em rgba(54, 54, 54, 0.25); +} + +.select.is-primary:not(:hover)::after { + border-color: #FF9200; +} + +.select.is-primary select { + border-color: #FF9200; +} + +.select.is-primary select:hover, .select.is-primary select.is-hovered { + border-color: #e68300; +} + +.select.is-primary select:focus, .select.is-primary select.is-focused, .select.is-primary select:active, .select.is-primary select.is-active { + box-shadow: 0 0 0 0.125em rgba(255, 146, 0, 0.25); +} + +.select.is-link:not(:hover)::after { + border-color: #FF9200; +} + +.select.is-link select { + border-color: #FF9200; +} + +.select.is-link select:hover, .select.is-link select.is-hovered { + border-color: #e68300; +} + +.select.is-link select:focus, .select.is-link select.is-focused, .select.is-link select:active, .select.is-link select.is-active { + box-shadow: 0 0 0 0.125em rgba(255, 146, 0, 0.25); +} + +.select.is-info:not(:hover)::after { + border-color: #3298dc; +} + +.select.is-info select { + border-color: #3298dc; +} + +.select.is-info select:hover, .select.is-info select.is-hovered { + border-color: #238cd1; +} + +.select.is-info select:focus, .select.is-info select.is-focused, .select.is-info select:active, .select.is-info select.is-active { + box-shadow: 0 0 0 0.125em rgba(50, 152, 220, 0.25); +} + +.select.is-success:not(:hover)::after { + border-color: #01a901; +} + +.select.is-success select { + border-color: #01a901; +} + +.select.is-success select:hover, .select.is-success select.is-hovered { + border-color: #019001; +} + +.select.is-success select:focus, .select.is-success select.is-focused, .select.is-success select:active, .select.is-success select.is-active { + box-shadow: 0 0 0 0.125em rgba(1, 169, 1, 0.25); +} + +.select.is-warning:not(:hover)::after { + border-color: #e7cb00; +} + +.select.is-warning select { + border-color: #e7cb00; +} + +.select.is-warning select:hover, .select.is-warning select.is-hovered { + border-color: #ceb500; +} + +.select.is-warning select:focus, .select.is-warning select.is-focused, .select.is-warning select:active, .select.is-warning select.is-active { + box-shadow: 0 0 0 0.125em rgba(231, 203, 0, 0.25); +} + +.select.is-danger:not(:hover)::after { + border-color: #F45F4B; +} + +.select.is-danger select { + border-color: #F45F4B; +} + +.select.is-danger select:hover, .select.is-danger select.is-hovered { + border-color: #f34a33; +} + +.select.is-danger select:focus, .select.is-danger select.is-focused, .select.is-danger select:active, .select.is-danger select.is-active { + box-shadow: 0 0 0 0.125em rgba(244, 95, 75, 0.25); +} + +.select.is-small { + border-radius: 2px; + font-size: 0.75rem; +} + +.select.is-medium { + font-size: 1.25rem; +} + +.select.is-large { + font-size: 1.5rem; +} + +.select.is-disabled::after { + border-color: #7a7a7a; +} + +.select.is-fullwidth { + width: 100%; +} + +.select.is-fullwidth select { + width: 100%; +} + +.select.is-loading::after { + margin-top: 0; + position: absolute; + right: 0.625em; + top: 0.625em; + transform: none; +} + +.select.is-loading.is-small:after { + font-size: 0.75rem; +} + +.select.is-loading.is-medium:after { + font-size: 1.25rem; +} + +.select.is-loading.is-large:after { + font-size: 1.5rem; +} + +.file { + align-items: stretch; + display: flex; + justify-content: flex-start; + position: relative; +} + +.file.is-white .file-cta { + background-color: white; + border-color: transparent; + color: #0a0a0a; +} + +.file.is-white:hover .file-cta, .file.is-white.is-hovered .file-cta { + background-color: #f9f9f9; + border-color: transparent; + color: #0a0a0a; +} + +.file.is-white:focus .file-cta, .file.is-white.is-focused .file-cta { + border-color: transparent; + box-shadow: 0 0 0.5em rgba(255, 255, 255, 0.25); + color: #0a0a0a; +} + +.file.is-white:active .file-cta, .file.is-white.is-active .file-cta { + background-color: #f2f2f2; + border-color: transparent; + color: #0a0a0a; +} + +.file.is-black .file-cta { + background-color: #0a0a0a; + border-color: transparent; + color: white; +} + +.file.is-black:hover .file-cta, .file.is-black.is-hovered .file-cta { + background-color: #040404; + border-color: transparent; + color: white; +} + +.file.is-black:focus .file-cta, .file.is-black.is-focused .file-cta { + border-color: transparent; + box-shadow: 0 0 0.5em rgba(10, 10, 10, 0.25); + color: white; +} + +.file.is-black:active .file-cta, .file.is-black.is-active .file-cta { + background-color: black; + border-color: transparent; + color: white; +} + +.file.is-light .file-cta { + background-color: whitesmoke; + border-color: transparent; + color: rgba(0, 0, 0, 0.7); +} + +.file.is-light:hover .file-cta, .file.is-light.is-hovered .file-cta { + background-color: #eeeeee; + border-color: transparent; + color: rgba(0, 0, 0, 0.7); +} + +.file.is-light:focus .file-cta, .file.is-light.is-focused .file-cta { + border-color: transparent; + box-shadow: 0 0 0.5em rgba(245, 245, 245, 0.25); + color: rgba(0, 0, 0, 0.7); +} + +.file.is-light:active .file-cta, .file.is-light.is-active .file-cta { + background-color: #e8e8e8; + border-color: transparent; + color: rgba(0, 0, 0, 0.7); +} + +.file.is-dark .file-cta { + background-color: #363636; + border-color: transparent; + color: #fff; +} + +.file.is-dark:hover .file-cta, .file.is-dark.is-hovered .file-cta { + background-color: #2f2f2f; + border-color: transparent; + color: #fff; +} + +.file.is-dark:focus .file-cta, .file.is-dark.is-focused .file-cta { + border-color: transparent; + box-shadow: 0 0 0.5em rgba(54, 54, 54, 0.25); + color: #fff; +} + +.file.is-dark:active .file-cta, .file.is-dark.is-active .file-cta { + background-color: #292929; + border-color: transparent; + color: #fff; +} + +.file.is-primary .file-cta { + background-color: #FF9200; + border-color: transparent; + color: #fff; +} + +.file.is-primary:hover .file-cta, .file.is-primary.is-hovered .file-cta { + background-color: #f28b00; + border-color: transparent; + color: #fff; +} + +.file.is-primary:focus .file-cta, .file.is-primary.is-focused .file-cta { + border-color: transparent; + box-shadow: 0 0 0.5em rgba(255, 146, 0, 0.25); + color: #fff; +} + +.file.is-primary:active .file-cta, .file.is-primary.is-active .file-cta { + background-color: #e68300; + border-color: transparent; + color: #fff; +} + +.file.is-link .file-cta { + background-color: #FF9200; + border-color: transparent; + color: #fff; +} + +.file.is-link:hover .file-cta, .file.is-link.is-hovered .file-cta { + background-color: #f28b00; + border-color: transparent; + color: #fff; +} + +.file.is-link:focus .file-cta, .file.is-link.is-focused .file-cta { + border-color: transparent; + box-shadow: 0 0 0.5em rgba(255, 146, 0, 0.25); + color: #fff; +} + +.file.is-link:active .file-cta, .file.is-link.is-active .file-cta { + background-color: #e68300; + border-color: transparent; + color: #fff; +} + +.file.is-info .file-cta { + background-color: #3298dc; + border-color: transparent; + color: #fff; +} + +.file.is-info:hover .file-cta, .file.is-info.is-hovered .file-cta { + background-color: #2793da; + border-color: transparent; + color: #fff; +} + +.file.is-info:focus .file-cta, .file.is-info.is-focused .file-cta { + border-color: transparent; + box-shadow: 0 0 0.5em rgba(50, 152, 220, 0.25); + color: #fff; +} + +.file.is-info:active .file-cta, .file.is-info.is-active .file-cta { + background-color: #238cd1; + border-color: transparent; + color: #fff; +} + +.file.is-success .file-cta { + background-color: #01a901; + border-color: transparent; + color: #fff; +} + +.file.is-success:hover .file-cta, .file.is-success.is-hovered .file-cta { + background-color: #019c01; + border-color: transparent; + color: #fff; +} + +.file.is-success:focus .file-cta, .file.is-success.is-focused .file-cta { + border-color: transparent; + box-shadow: 0 0 0.5em rgba(1, 169, 1, 0.25); + color: #fff; +} + +.file.is-success:active .file-cta, .file.is-success.is-active .file-cta { + background-color: #019001; + border-color: transparent; + color: #fff; +} + +.file.is-warning .file-cta { + background-color: #e7cb00; + border-color: transparent; + color: rgba(0, 0, 0, 0.7); +} + +.file.is-warning:hover .file-cta, .file.is-warning.is-hovered .file-cta { + background-color: #dac000; + border-color: transparent; + color: rgba(0, 0, 0, 0.7); +} + +.file.is-warning:focus .file-cta, .file.is-warning.is-focused .file-cta { + border-color: transparent; + box-shadow: 0 0 0.5em rgba(231, 203, 0, 0.25); + color: rgba(0, 0, 0, 0.7); +} + +.file.is-warning:active .file-cta, .file.is-warning.is-active .file-cta { + background-color: #ceb500; + border-color: transparent; + color: rgba(0, 0, 0, 0.7); +} + +.file.is-danger .file-cta { + background-color: #F45F4B; + border-color: transparent; + color: #fff; +} + +.file.is-danger:hover .file-cta, .file.is-danger.is-hovered .file-cta { + background-color: #f3543f; + border-color: transparent; + color: #fff; +} + +.file.is-danger:focus .file-cta, .file.is-danger.is-focused .file-cta { + border-color: transparent; + box-shadow: 0 0 0.5em rgba(244, 95, 75, 0.25); + color: #fff; +} + +.file.is-danger:active .file-cta, .file.is-danger.is-active .file-cta { + background-color: #f34a33; + border-color: transparent; + color: #fff; +} + +.file.is-small { + font-size: 0.75rem; +} + +.file.is-medium { + font-size: 1.25rem; +} + +.file.is-medium .file-icon .fa { + font-size: 21px; +} + +.file.is-large { + font-size: 1.5rem; +} + +.file.is-large .file-icon .fa { + font-size: 28px; +} + +.file.has-name .file-cta { + border-bottom-right-radius: 0; + border-top-right-radius: 0; +} + +.file.has-name .file-name { + border-bottom-left-radius: 0; + border-top-left-radius: 0; +} + +.file.has-name.is-empty .file-cta { + border-radius: 4px; +} + +.file.has-name.is-empty .file-name { + display: none; +} + +.file.is-boxed .file-label { + flex-direction: column; +} + +.file.is-boxed .file-cta { + flex-direction: column; + height: auto; + padding: 1em 3em; +} + +.file.is-boxed .file-name { + border-width: 0 1px 1px; +} + +.file.is-boxed .file-icon { + height: 1.5em; + width: 1.5em; +} + +.file.is-boxed .file-icon .fa { + font-size: 21px; +} + +.file.is-boxed.is-small .file-icon .fa { + font-size: 14px; +} + +.file.is-boxed.is-medium .file-icon .fa { + font-size: 28px; +} + +.file.is-boxed.is-large .file-icon .fa { + font-size: 35px; +} + +.file.is-boxed.has-name .file-cta { + border-radius: 4px 4px 0 0; +} + +.file.is-boxed.has-name .file-name { + border-radius: 0 0 4px 4px; + border-width: 0 1px 1px; +} + +.file.is-centered { + justify-content: center; +} + +.file.is-fullwidth .file-label { + width: 100%; +} + +.file.is-fullwidth .file-name { + flex-grow: 1; + max-width: none; +} + +.file.is-right { + justify-content: flex-end; +} + +.file.is-right .file-cta { + border-radius: 0 4px 4px 0; +} + +.file.is-right .file-name { + border-radius: 4px 0 0 4px; + border-width: 1px 0 1px 1px; + order: -1; +} + +.file-label { + align-items: stretch; + display: flex; + cursor: pointer; + justify-content: flex-start; + overflow: hidden; + position: relative; +} + +.file-label:hover .file-cta { + background-color: #eeeeee; + color: #363636; +} + +.file-label:hover .file-name { + border-color: #d5d5d5; +} + +.file-label:active .file-cta { + background-color: #e8e8e8; + color: #363636; +} + +.file-label:active .file-name { + border-color: #cfcfcf; +} + +.file-input { + height: 100%; + left: 0; + opacity: 0; + outline: none; + position: absolute; + top: 0; + width: 100%; +} + +.file-cta, +.file-name { + border-color: #dbdbdb; + border-radius: 4px; + font-size: 1em; + padding-left: 1em; + padding-right: 1em; + white-space: nowrap; +} + +.file-cta { + background-color: whitesmoke; + color: rgba(0, 0, 0, 0.87); +} + +.file-name { + border-color: #dbdbdb; + border-style: solid; + border-width: 1px 1px 1px 0; + display: block; + max-width: 16em; + overflow: hidden; + text-align: inherit; + text-overflow: ellipsis; +} + +.file-icon { + align-items: center; + display: flex; + height: 1em; + justify-content: center; + margin-right: 0.5em; + width: 1em; +} + +.file-icon .fa { + font-size: 14px; +} + +.label { + color: #363636; + display: block; + font-size: 1rem; + font-weight: 700; +} + +.label:not(:last-child) { + margin-bottom: 0.5em; +} + +.label.is-small { + font-size: 0.75rem; +} + +.label.is-medium { + font-size: 1.25rem; +} + +.label.is-large { + font-size: 1.5rem; +} + +.help { + display: block; + font-size: 0.75rem; + margin-top: 0.25rem; +} + +.help.is-white { + color: white; +} + +.help.is-black { + color: #0a0a0a; +} + +.help.is-light { + color: whitesmoke; +} + +.help.is-dark { + color: #363636; +} + +.help.is-primary { + color: #FF9200; +} + +.help.is-link { + color: #FF9200; +} + +.help.is-info { + color: #3298dc; +} + +.help.is-success { + color: #01a901; +} + +.help.is-warning { + color: #e7cb00; +} + +.help.is-danger { + color: #F45F4B; +} + +.field:not(:last-child) { + margin-bottom: 0.75rem; +} + +.field.has-addons { + display: flex; + justify-content: flex-start; +} + +.field.has-addons .control:not(:last-child) { + margin-right: -1px; +} + +.field.has-addons .control:not(:first-child):not(:last-child) .button, +.field.has-addons .control:not(:first-child):not(:last-child) .input, +.field.has-addons .control:not(:first-child):not(:last-child) .select select { + border-radius: 0; +} + +.field.has-addons .control:first-child:not(:only-child) .button, +.field.has-addons .control:first-child:not(:only-child) .input, +.field.has-addons .control:first-child:not(:only-child) .select select { + border-bottom-right-radius: 0; + border-top-right-radius: 0; +} + +.field.has-addons .control:last-child:not(:only-child) .button, +.field.has-addons .control:last-child:not(:only-child) .input, +.field.has-addons .control:last-child:not(:only-child) .select select { + border-bottom-left-radius: 0; + border-top-left-radius: 0; +} + +.field.has-addons .control .button:not([disabled]):hover, .field.has-addons .control .button:not([disabled]).is-hovered, +.field.has-addons .control .input:not([disabled]):hover, +.field.has-addons .control .input:not([disabled]).is-hovered, +.field.has-addons .control .select select:not([disabled]):hover, +.field.has-addons .control .select select:not([disabled]).is-hovered { + z-index: 2; +} + +.field.has-addons .control .button:not([disabled]):focus, .field.has-addons .control .button:not([disabled]).is-focused, .field.has-addons .control .button:not([disabled]):active, .field.has-addons .control .button:not([disabled]).is-active, +.field.has-addons .control .input:not([disabled]):focus, +.field.has-addons .control .input:not([disabled]).is-focused, +.field.has-addons .control .input:not([disabled]):active, +.field.has-addons .control .input:not([disabled]).is-active, +.field.has-addons .control .select select:not([disabled]):focus, +.field.has-addons .control .select select:not([disabled]).is-focused, +.field.has-addons .control .select select:not([disabled]):active, +.field.has-addons .control .select select:not([disabled]).is-active { + z-index: 3; +} + +.field.has-addons .control .button:not([disabled]):focus:hover, .field.has-addons .control .button:not([disabled]).is-focused:hover, .field.has-addons .control .button:not([disabled]):active:hover, .field.has-addons .control .button:not([disabled]).is-active:hover, +.field.has-addons .control .input:not([disabled]):focus:hover, +.field.has-addons .control .input:not([disabled]).is-focused:hover, +.field.has-addons .control .input:not([disabled]):active:hover, +.field.has-addons .control .input:not([disabled]).is-active:hover, +.field.has-addons .control .select select:not([disabled]):focus:hover, +.field.has-addons .control .select select:not([disabled]).is-focused:hover, +.field.has-addons .control .select select:not([disabled]):active:hover, +.field.has-addons .control .select select:not([disabled]).is-active:hover { + z-index: 4; +} + +.field.has-addons .control.is-expanded { + flex-grow: 1; + flex-shrink: 1; +} + +.field.has-addons.has-addons-centered { + justify-content: center; +} + +.field.has-addons.has-addons-right { + justify-content: flex-end; +} + +.field.has-addons.has-addons-fullwidth .control { + flex-grow: 1; + flex-shrink: 0; +} + +.field.is-grouped { + display: flex; + justify-content: flex-start; +} + +.field.is-grouped > .control { + flex-shrink: 0; +} + +.field.is-grouped > .control:not(:last-child) { + margin-bottom: 0; + margin-right: 0.75rem; +} + +.field.is-grouped > .control.is-expanded { + flex-grow: 1; + flex-shrink: 1; +} + +.field.is-grouped.is-grouped-centered { + justify-content: center; +} + +.field.is-grouped.is-grouped-right { + justify-content: flex-end; +} + +.field.is-grouped.is-grouped-multiline { + flex-wrap: wrap; +} + +.field.is-grouped.is-grouped-multiline > .control:last-child, .field.is-grouped.is-grouped-multiline > .control:not(:last-child) { + margin-bottom: 0.75rem; +} + +.field.is-grouped.is-grouped-multiline:last-child { + margin-bottom: -0.75rem; +} + +.field.is-grouped.is-grouped-multiline:not(:last-child) { + margin-bottom: 0; +} + +@media screen and (min-width: 769px), print { + .field.is-horizontal { + display: flex; + } +} + +.field-label .label { + font-size: inherit; +} + +@media screen and (max-width: 768px) { + .field-label { + margin-bottom: 0.5rem; + } +} + +@media screen and (min-width: 769px), print { + .field-label { + flex-basis: 0; + flex-grow: 1; + flex-shrink: 0; + margin-right: 1.5rem; + text-align: right; + } + .field-label.is-small { + font-size: 0.75rem; + padding-top: 0.375em; + } + .field-label.is-normal { + padding-top: 0.375em; + } + .field-label.is-medium { + font-size: 1.25rem; + padding-top: 0.375em; + } + .field-label.is-large { + font-size: 1.5rem; + padding-top: 0.375em; + } +} + +.field-body .field .field { + margin-bottom: 0; +} + +@media screen and (min-width: 769px), print { + .field-body { + display: flex; + flex-basis: 0; + flex-grow: 5; + flex-shrink: 1; + } + .field-body .field { + margin-bottom: 0; + } + .field-body > .field { + flex-shrink: 1; + } + .field-body > .field:not(.is-narrow) { + flex-grow: 1; + } + .field-body > .field:not(:last-child) { + margin-right: 0.75rem; + } +} + +.control { + box-sizing: border-box; + clear: both; + font-size: 1rem; + position: relative; + text-align: inherit; +} + +.control.has-icons-left .input:focus ~ .icon, +.control.has-icons-left .select:focus ~ .icon, .control.has-icons-right .input:focus ~ .icon, +.control.has-icons-right .select:focus ~ .icon { + color: rgba(0, 0, 0, 0.87); +} + +.control.has-icons-left .input.is-small ~ .icon, +.control.has-icons-left .select.is-small ~ .icon, .control.has-icons-right .input.is-small ~ .icon, +.control.has-icons-right .select.is-small ~ .icon { + font-size: 0.75rem; +} + +.control.has-icons-left .input.is-medium ~ .icon, +.control.has-icons-left .select.is-medium ~ .icon, .control.has-icons-right .input.is-medium ~ .icon, +.control.has-icons-right .select.is-medium ~ .icon { + font-size: 1.25rem; +} + +.control.has-icons-left .input.is-large ~ .icon, +.control.has-icons-left .select.is-large ~ .icon, .control.has-icons-right .input.is-large ~ .icon, +.control.has-icons-right .select.is-large ~ .icon { + font-size: 1.5rem; +} + +.control.has-icons-left .icon, .control.has-icons-right .icon { + color: #dbdbdb; + height: 2.5em; + pointer-events: none; + position: absolute; + top: 0; + width: 2.5em; + z-index: 4; +} + +.control.has-icons-left .input, +.control.has-icons-left .select select { + padding-left: 2.5em; +} + +.control.has-icons-left .icon.is-left { + left: 0; +} + +.control.has-icons-right .input, +.control.has-icons-right .select select { + padding-right: 2.5em; +} + +.control.has-icons-right .icon.is-right { + right: 0; +} + +.control.is-loading::after { + position: absolute !important; + right: 0.625em; + top: 0.625em; + z-index: 4; +} + +.control.is-loading.is-small:after { + font-size: 0.75rem; +} + +.control.is-loading.is-medium:after { + font-size: 1.25rem; +} + +.control.is-loading.is-large:after { + font-size: 1.5rem; +} + +/* Bulma Helpers */ +.has-text-white { + color: white !important; +} + +a.has-text-white:hover, a.has-text-white:focus { + color: #e6e6e6 !important; +} + +.has-background-white { + background-color: white !important; +} + +.has-text-black { + color: #0a0a0a !important; +} + +a.has-text-black:hover, a.has-text-black:focus { + color: black !important; +} + +.has-background-black { + background-color: #0a0a0a !important; +} + +.has-text-light { + color: whitesmoke !important; +} + +a.has-text-light:hover, a.has-text-light:focus { + color: #dbdbdb !important; +} + +.has-background-light { + background-color: whitesmoke !important; +} + +.has-text-dark { + color: #363636 !important; +} + +a.has-text-dark:hover, a.has-text-dark:focus { + color: #1c1c1c !important; +} + +.has-background-dark { + background-color: #363636 !important; +} + +.has-text-primary { + color: #FF9200 !important; +} + +a.has-text-primary:hover, a.has-text-primary:focus { + color: #cc7500 !important; +} + +.has-background-primary { + background-color: #FF9200 !important; +} + +.has-text-primary-light { + color: #fff6eb !important; +} + +a.has-text-primary-light:hover, a.has-text-primary-light:focus { + color: #ffe0b8 !important; +} + +.has-background-primary-light { + background-color: #fff6eb !important; +} + +.has-text-primary-dark { + color: #a35d00 !important; +} + +a.has-text-primary-dark:hover, a.has-text-primary-dark:focus { + color: #d67b00 !important; +} + +.has-background-primary-dark { + background-color: #a35d00 !important; +} + +.has-text-link { + color: #FF9200 !important; +} + +a.has-text-link:hover, a.has-text-link:focus { + color: #cc7500 !important; +} + +.has-background-link { + background-color: #FF9200 !important; +} + +.has-text-link-light { + color: #fff6eb !important; +} + +a.has-text-link-light:hover, a.has-text-link-light:focus { + color: #ffe0b8 !important; +} + +.has-background-link-light { + background-color: #fff6eb !important; +} + +.has-text-link-dark { + color: #a35d00 !important; +} + +a.has-text-link-dark:hover, a.has-text-link-dark:focus { + color: #d67b00 !important; +} + +.has-background-link-dark { + background-color: #a35d00 !important; +} + +.has-text-info { + color: #3298dc !important; +} + +a.has-text-info:hover, a.has-text-info:focus { + color: #207dbc !important; +} + +.has-background-info { + background-color: #3298dc !important; +} + +.has-text-info-light { + color: #eef6fc !important; +} + +a.has-text-info-light:hover, a.has-text-info-light:focus { + color: #c2e0f5 !important; +} + +.has-background-info-light { + background-color: #eef6fc !important; +} + +.has-text-info-dark { + color: #1d72aa !important; +} + +a.has-text-info-dark:hover, a.has-text-info-dark:focus { + color: #248fd6 !important; +} + +.has-background-info-dark { + background-color: #1d72aa !important; +} + +.has-text-success { + color: #01a901 !important; +} + +a.has-text-success:hover, a.has-text-success:focus { + color: #017601 !important; +} + +.has-background-success { + background-color: #01a901 !important; +} + +.has-text-success-light { + color: #ebffeb !important; +} + +a.has-text-success-light:hover, a.has-text-success-light:focus { + color: #b8ffb8 !important; +} + +.has-background-success-light { + background-color: #ebffeb !important; +} + +.has-text-success-dark { + color: #01cb01 !important; +} + +a.has-text-success-dark:hover, a.has-text-success-dark:focus { + color: #02fe02 !important; +} + +.has-background-success-dark { + background-color: #01cb01 !important; +} + +.has-text-warning { + color: #e7cb00 !important; +} + +a.has-text-warning:hover, a.has-text-warning:focus { + color: #b49e00 !important; +} + +.has-background-warning { + background-color: #e7cb00 !important; +} + +.has-text-warning-light { + color: #fffdeb !important; +} + +a.has-text-warning-light:hover, a.has-text-warning-light:focus { + color: #fff6b8 !important; +} + +.has-background-warning-light { + background-color: #fffdeb !important; +} + +.has-text-warning-dark { + color: #948200 !important; +} + +a.has-text-warning-dark:hover, a.has-text-warning-dark:focus { + color: #c7af00 !important; +} + +.has-background-warning-dark { + background-color: #948200 !important; +} + +.has-text-danger { + color: #F45F4B !important; +} + +a.has-text-danger:hover, a.has-text-danger:focus { + color: #f1341b !important; +} + +.has-background-danger { + background-color: #F45F4B !important; +} + +.has-text-danger-light { + color: #feeeec !important; +} + +a.has-text-danger-light:hover, a.has-text-danger-light:focus { + color: #fbc3bc !important; +} + +.has-background-danger-light { + background-color: #feeeec !important; +} + +.has-text-danger-dark { + color: #c0210c !important; +} + +a.has-text-danger-dark:hover, a.has-text-danger-dark:focus { + color: #f0290f !important; +} + +.has-background-danger-dark { + background-color: #c0210c !important; +} + +.has-text-black-bis { + color: #121212 !important; +} + +.has-background-black-bis { + background-color: #121212 !important; +} + +.has-text-black-ter { + color: #242424 !important; +} + +.has-background-black-ter { + background-color: #242424 !important; +} + +.has-text-grey-darker { + color: #363636 !important; +} + +.has-background-grey-darker { + background-color: #363636 !important; +} + +.has-text-grey-dark { + color: #4a4a4a !important; +} + +.has-background-grey-dark { + background-color: #4a4a4a !important; +} + +.has-text-grey { + color: #7a7a7a !important; +} + +.has-background-grey { + background-color: #7a7a7a !important; +} + +.has-text-grey-light { + color: #b5b5b5 !important; +} + +.has-background-grey-light { + background-color: #b5b5b5 !important; +} + +.has-text-grey-lighter { + color: #dbdbdb !important; +} + +.has-background-grey-lighter { + background-color: #dbdbdb !important; +} + +.has-text-white-ter { + color: whitesmoke !important; +} + +.has-background-white-ter { + background-color: whitesmoke !important; +} + +.has-text-white-bis { + color: #fafafa !important; +} + +.has-background-white-bis { + background-color: #fafafa !important; +} + +.is-flex-direction-row { + flex-direction: row !important; +} + +.is-flex-direction-row-reverse { + flex-direction: row-reverse !important; +} + +.is-flex-direction-column { + flex-direction: column !important; +} + +.is-flex-direction-column-reverse { + flex-direction: column-reverse !important; +} + +.is-flex-wrap-nowrap { + flex-wrap: nowrap !important; +} + +.is-flex-wrap-wrap { + flex-wrap: wrap !important; +} + +.is-flex-wrap-wrap-reverse { + flex-wrap: wrap-reverse !important; +} + +.is-justify-content-flex-start { + justify-content: flex-start !important; +} + +.is-justify-content-flex-end { + justify-content: flex-end !important; +} + +.is-justify-content-center { + justify-content: center !important; +} + +.is-justify-content-space-between { + justify-content: space-between !important; +} + +.is-justify-content-space-around { + justify-content: space-around !important; +} + +.is-justify-content-space-evenly { + justify-content: space-evenly !important; +} + +.is-justify-content-start { + justify-content: start !important; +} + +.is-justify-content-end { + justify-content: end !important; +} + +.is-justify-content-left { + justify-content: left !important; +} + +.is-justify-content-right { + justify-content: right !important; +} + +.is-align-content-flex-start { + align-content: flex-start !important; +} + +.is-align-content-flex-end { + align-content: flex-end !important; +} + +.is-align-content-center { + align-content: center !important; +} + +.is-align-content-space-between { + align-content: space-between !important; +} + +.is-align-content-space-around { + align-content: space-around !important; +} + +.is-align-content-space-evenly { + align-content: space-evenly !important; +} + +.is-align-content-stretch { + align-content: stretch !important; +} + +.is-align-content-start { + align-content: start !important; +} + +.is-align-content-end { + align-content: end !important; +} + +.is-align-content-baseline { + align-content: baseline !important; +} + +.is-align-items-stretch { + align-items: stretch !important; +} + +.is-align-items-flex-start { + align-items: flex-start !important; +} + +.is-align-items-flex-end { + align-items: flex-end !important; +} + +.is-align-items-center { + align-items: center !important; +} + +.is-align-items-baseline { + align-items: baseline !important; +} + +.is-align-items-start { + align-items: start !important; +} + +.is-align-items-end { + align-items: end !important; +} + +.is-align-items-self-start { + align-items: self-start !important; +} + +.is-align-items-self-end { + align-items: self-end !important; +} + +.is-align-self-auto { + align-self: auto !important; +} + +.is-align-self-flex-start { + align-self: flex-start !important; +} + +.is-align-self-flex-end { + align-self: flex-end !important; +} + +.is-align-self-center { + align-self: center !important; +} + +.is-align-self-baseline { + align-self: baseline !important; +} + +.is-align-self-stretch { + align-self: stretch !important; +} + +.is-flex-grow-0 { + flex-grow: 0 !important; +} + +.is-flex-grow-1 { + flex-grow: 1 !important; +} + +.is-flex-grow-2 { + flex-grow: 2 !important; +} + +.is-flex-grow-3 { + flex-grow: 3 !important; +} + +.is-flex-grow-4 { + flex-grow: 4 !important; +} + +.is-flex-grow-5 { + flex-grow: 5 !important; +} + +.is-flex-shrink-0 { + flex-shrink: 0 !important; +} + +.is-flex-shrink-1 { + flex-shrink: 1 !important; +} + +.is-flex-shrink-2 { + flex-shrink: 2 !important; +} + +.is-flex-shrink-3 { + flex-shrink: 3 !important; +} + +.is-flex-shrink-4 { + flex-shrink: 4 !important; +} + +.is-flex-shrink-5 { + flex-shrink: 5 !important; +} + +.is-clearfix::after { + clear: both; + content: " "; + display: table; +} + +.is-pulled-left { + float: left !important; +} + +.is-pulled-right { + float: right !important; +} + +.is-radiusless { + border-radius: 0 !important; +} + +.is-shadowless { + box-shadow: none !important; +} + +.is-clickable { + cursor: pointer !important; + pointer-events: all !important; +} + +.is-clipped { + overflow: hidden !important; +} + +.is-relative { + position: relative !important; +} + +.is-marginless { + margin: 0 !important; +} + +.is-paddingless { + padding: 0 !important; +} + +.m-0 { + margin: 0 !important; +} + +.mt-0 { + margin-top: 0 !important; +} + +.mr-0 { + margin-right: 0 !important; +} + +.mb-0 { + margin-bottom: 0 !important; +} + +.ml-0 { + margin-left: 0 !important; +} + +.mx-0 { + margin-left: 0 !important; + margin-right: 0 !important; +} + +.my-0 { + margin-top: 0 !important; + margin-bottom: 0 !important; +} + +.m-1 { + margin: 0.25rem !important; +} + +.mt-1 { + margin-top: 0.25rem !important; +} + +.mr-1 { + margin-right: 0.25rem !important; +} + +.mb-1 { + margin-bottom: 0.25rem !important; +} + +.ml-1 { + margin-left: 0.25rem !important; +} + +.mx-1 { + margin-left: 0.25rem !important; + margin-right: 0.25rem !important; +} + +.my-1 { + margin-top: 0.25rem !important; + margin-bottom: 0.25rem !important; +} + +.m-2 { + margin: 0.5rem !important; +} + +.mt-2 { + margin-top: 0.5rem !important; +} + +.mr-2 { + margin-right: 0.5rem !important; +} + +.mb-2 { + margin-bottom: 0.5rem !important; +} + +.ml-2 { + margin-left: 0.5rem !important; +} + +.mx-2 { + margin-left: 0.5rem !important; + margin-right: 0.5rem !important; +} + +.my-2 { + margin-top: 0.5rem !important; + margin-bottom: 0.5rem !important; +} + +.m-3 { + margin: 0.75rem !important; +} + +.mt-3 { + margin-top: 0.75rem !important; +} + +.mr-3 { + margin-right: 0.75rem !important; +} + +.mb-3 { + margin-bottom: 0.75rem !important; +} + +.ml-3 { + margin-left: 0.75rem !important; +} + +.mx-3 { + margin-left: 0.75rem !important; + margin-right: 0.75rem !important; +} + +.my-3 { + margin-top: 0.75rem !important; + margin-bottom: 0.75rem !important; +} + +.m-4 { + margin: 1rem !important; +} + +.mt-4 { + margin-top: 1rem !important; +} + +.mr-4 { + margin-right: 1rem !important; +} + +.mb-4 { + margin-bottom: 1rem !important; +} + +.ml-4 { + margin-left: 1rem !important; +} + +.mx-4 { + margin-left: 1rem !important; + margin-right: 1rem !important; +} + +.my-4 { + margin-top: 1rem !important; + margin-bottom: 1rem !important; +} + +.m-5 { + margin: 1.5rem !important; +} + +.mt-5 { + margin-top: 1.5rem !important; +} + +.mr-5 { + margin-right: 1.5rem !important; +} + +.mb-5 { + margin-bottom: 1.5rem !important; +} + +.ml-5 { + margin-left: 1.5rem !important; +} + +.mx-5 { + margin-left: 1.5rem !important; + margin-right: 1.5rem !important; +} + +.my-5 { + margin-top: 1.5rem !important; + margin-bottom: 1.5rem !important; +} + +.m-6 { + margin: 3rem !important; +} + +.mt-6 { + margin-top: 3rem !important; +} + +.mr-6 { + margin-right: 3rem !important; +} + +.mb-6 { + margin-bottom: 3rem !important; +} + +.ml-6 { + margin-left: 3rem !important; +} + +.mx-6 { + margin-left: 3rem !important; + margin-right: 3rem !important; +} + +.my-6 { + margin-top: 3rem !important; + margin-bottom: 3rem !important; +} + +.p-0 { + padding: 0 !important; +} + +.pt-0 { + padding-top: 0 !important; +} + +.pr-0 { + padding-right: 0 !important; +} + +.pb-0 { + padding-bottom: 0 !important; +} + +.pl-0 { + padding-left: 0 !important; +} + +.px-0 { + padding-left: 0 !important; + padding-right: 0 !important; +} + +.py-0 { + padding-top: 0 !important; + padding-bottom: 0 !important; +} + +.p-1 { + padding: 0.25rem !important; +} + +.pt-1 { + padding-top: 0.25rem !important; +} + +.pr-1 { + padding-right: 0.25rem !important; +} + +.pb-1 { + padding-bottom: 0.25rem !important; +} + +.pl-1 { + padding-left: 0.25rem !important; +} + +.px-1 { + padding-left: 0.25rem !important; + padding-right: 0.25rem !important; +} + +.py-1 { + padding-top: 0.25rem !important; + padding-bottom: 0.25rem !important; +} + +.p-2 { + padding: 0.5rem !important; +} + +.pt-2 { + padding-top: 0.5rem !important; +} + +.pr-2 { + padding-right: 0.5rem !important; +} + +.pb-2 { + padding-bottom: 0.5rem !important; +} + +.pl-2 { + padding-left: 0.5rem !important; +} + +.px-2 { + padding-left: 0.5rem !important; + padding-right: 0.5rem !important; +} + +.py-2 { + padding-top: 0.5rem !important; + padding-bottom: 0.5rem !important; +} + +.p-3 { + padding: 0.75rem !important; +} + +.pt-3 { + padding-top: 0.75rem !important; +} + +.pr-3 { + padding-right: 0.75rem !important; +} + +.pb-3 { + padding-bottom: 0.75rem !important; +} + +.pl-3 { + padding-left: 0.75rem !important; +} + +.px-3 { + padding-left: 0.75rem !important; + padding-right: 0.75rem !important; +} + +.py-3 { + padding-top: 0.75rem !important; + padding-bottom: 0.75rem !important; +} + +.p-4 { + padding: 1rem !important; +} + +.pt-4 { + padding-top: 1rem !important; +} + +.pr-4 { + padding-right: 1rem !important; +} + +.pb-4 { + padding-bottom: 1rem !important; +} + +.pl-4 { + padding-left: 1rem !important; +} + +.px-4 { + padding-left: 1rem !important; + padding-right: 1rem !important; +} + +.py-4 { + padding-top: 1rem !important; + padding-bottom: 1rem !important; +} + +.p-5 { + padding: 1.5rem !important; +} + +.pt-5 { + padding-top: 1.5rem !important; +} + +.pr-5 { + padding-right: 1.5rem !important; +} + +.pb-5 { + padding-bottom: 1.5rem !important; +} + +.pl-5 { + padding-left: 1.5rem !important; +} + +.px-5 { + padding-left: 1.5rem !important; + padding-right: 1.5rem !important; +} + +.py-5 { + padding-top: 1.5rem !important; + padding-bottom: 1.5rem !important; +} + +.p-6 { + padding: 3rem !important; +} + +.pt-6 { + padding-top: 3rem !important; +} + +.pr-6 { + padding-right: 3rem !important; +} + +.pb-6 { + padding-bottom: 3rem !important; +} + +.pl-6 { + padding-left: 3rem !important; +} + +.px-6 { + padding-left: 3rem !important; + padding-right: 3rem !important; +} + +.py-6 { + padding-top: 3rem !important; + padding-bottom: 3rem !important; +} + +.is-size-1 { + font-size: 3rem !important; +} + +.is-size-2 { + font-size: 2.5rem !important; +} + +.is-size-3 { + font-size: 2rem !important; +} + +.is-size-4 { + font-size: 1.5rem !important; +} + +.is-size-5 { + font-size: 1.25rem !important; +} + +.is-size-6 { + font-size: 1rem !important; +} + +.is-size-7 { + font-size: 0.75rem !important; +} + +@media screen and (max-width: 768px) { + .is-size-1-mobile { + font-size: 3rem !important; + } + .is-size-2-mobile { + font-size: 2.5rem !important; + } + .is-size-3-mobile { + font-size: 2rem !important; + } + .is-size-4-mobile { + font-size: 1.5rem !important; + } + .is-size-5-mobile { + font-size: 1.25rem !important; + } + .is-size-6-mobile { + font-size: 1rem !important; + } + .is-size-7-mobile { + font-size: 0.75rem !important; + } +} + +@media screen and (min-width: 769px), print { + .is-size-1-tablet { + font-size: 3rem !important; + } + .is-size-2-tablet { + font-size: 2.5rem !important; + } + .is-size-3-tablet { + font-size: 2rem !important; + } + .is-size-4-tablet { + font-size: 1.5rem !important; + } + .is-size-5-tablet { + font-size: 1.25rem !important; + } + .is-size-6-tablet { + font-size: 1rem !important; + } + .is-size-7-tablet { + font-size: 0.75rem !important; + } +} + +@media screen and (max-width: 1023px) { + .is-size-1-touch { + font-size: 3rem !important; + } + .is-size-2-touch { + font-size: 2.5rem !important; + } + .is-size-3-touch { + font-size: 2rem !important; + } + .is-size-4-touch { + font-size: 1.5rem !important; + } + .is-size-5-touch { + font-size: 1.25rem !important; + } + .is-size-6-touch { + font-size: 1rem !important; + } + .is-size-7-touch { + font-size: 0.75rem !important; + } +} + +@media screen and (min-width: 1024px) { + .is-size-1-desktop { + font-size: 3rem !important; + } + .is-size-2-desktop { + font-size: 2.5rem !important; + } + .is-size-3-desktop { + font-size: 2rem !important; + } + .is-size-4-desktop { + font-size: 1.5rem !important; + } + .is-size-5-desktop { + font-size: 1.25rem !important; + } + .is-size-6-desktop { + font-size: 1rem !important; + } + .is-size-7-desktop { + font-size: 0.75rem !important; + } +} + +@media screen and (min-width: 1216px) { + .is-size-1-widescreen { + font-size: 3rem !important; + } + .is-size-2-widescreen { + font-size: 2.5rem !important; + } + .is-size-3-widescreen { + font-size: 2rem !important; + } + .is-size-4-widescreen { + font-size: 1.5rem !important; + } + .is-size-5-widescreen { + font-size: 1.25rem !important; + } + .is-size-6-widescreen { + font-size: 1rem !important; + } + .is-size-7-widescreen { + font-size: 0.75rem !important; + } +} + +@media screen and (min-width: 1408px) { + .is-size-1-fullhd { + font-size: 3rem !important; + } + .is-size-2-fullhd { + font-size: 2.5rem !important; + } + .is-size-3-fullhd { + font-size: 2rem !important; + } + .is-size-4-fullhd { + font-size: 1.5rem !important; + } + .is-size-5-fullhd { + font-size: 1.25rem !important; + } + .is-size-6-fullhd { + font-size: 1rem !important; + } + .is-size-7-fullhd { + font-size: 0.75rem !important; + } +} + +.has-text-centered { + text-align: center !important; +} + +.has-text-justified { + text-align: justify !important; +} + +.has-text-left { + text-align: left !important; +} + +.has-text-right { + text-align: right !important; +} + +@media screen and (max-width: 768px) { + .has-text-centered-mobile { + text-align: center !important; + } +} + +@media screen and (min-width: 769px), print { + .has-text-centered-tablet { + text-align: center !important; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .has-text-centered-tablet-only { + text-align: center !important; + } +} + +@media screen and (max-width: 1023px) { + .has-text-centered-touch { + text-align: center !important; + } +} + +@media screen and (min-width: 1024px) { + .has-text-centered-desktop { + text-align: center !important; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .has-text-centered-desktop-only { + text-align: center !important; + } +} + +@media screen and (min-width: 1216px) { + .has-text-centered-widescreen { + text-align: center !important; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .has-text-centered-widescreen-only { + text-align: center !important; + } +} + +@media screen and (min-width: 1408px) { + .has-text-centered-fullhd { + text-align: center !important; + } +} + +@media screen and (max-width: 768px) { + .has-text-justified-mobile { + text-align: justify !important; + } +} + +@media screen and (min-width: 769px), print { + .has-text-justified-tablet { + text-align: justify !important; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .has-text-justified-tablet-only { + text-align: justify !important; + } +} + +@media screen and (max-width: 1023px) { + .has-text-justified-touch { + text-align: justify !important; + } +} + +@media screen and (min-width: 1024px) { + .has-text-justified-desktop { + text-align: justify !important; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .has-text-justified-desktop-only { + text-align: justify !important; + } +} + +@media screen and (min-width: 1216px) { + .has-text-justified-widescreen { + text-align: justify !important; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .has-text-justified-widescreen-only { + text-align: justify !important; + } +} + +@media screen and (min-width: 1408px) { + .has-text-justified-fullhd { + text-align: justify !important; + } +} + +@media screen and (max-width: 768px) { + .has-text-left-mobile { + text-align: left !important; + } +} + +@media screen and (min-width: 769px), print { + .has-text-left-tablet { + text-align: left !important; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .has-text-left-tablet-only { + text-align: left !important; + } +} + +@media screen and (max-width: 1023px) { + .has-text-left-touch { + text-align: left !important; + } +} + +@media screen and (min-width: 1024px) { + .has-text-left-desktop { + text-align: left !important; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .has-text-left-desktop-only { + text-align: left !important; + } +} + +@media screen and (min-width: 1216px) { + .has-text-left-widescreen { + text-align: left !important; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .has-text-left-widescreen-only { + text-align: left !important; + } +} + +@media screen and (min-width: 1408px) { + .has-text-left-fullhd { + text-align: left !important; + } +} + +@media screen and (max-width: 768px) { + .has-text-right-mobile { + text-align: right !important; + } +} + +@media screen and (min-width: 769px), print { + .has-text-right-tablet { + text-align: right !important; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .has-text-right-tablet-only { + text-align: right !important; + } +} + +@media screen and (max-width: 1023px) { + .has-text-right-touch { + text-align: right !important; + } +} + +@media screen and (min-width: 1024px) { + .has-text-right-desktop { + text-align: right !important; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .has-text-right-desktop-only { + text-align: right !important; + } +} + +@media screen and (min-width: 1216px) { + .has-text-right-widescreen { + text-align: right !important; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .has-text-right-widescreen-only { + text-align: right !important; + } +} + +@media screen and (min-width: 1408px) { + .has-text-right-fullhd { + text-align: right !important; + } +} + +.is-capitalized { + text-transform: capitalize !important; +} + +.is-lowercase { + text-transform: lowercase !important; +} + +.is-uppercase { + text-transform: uppercase !important; +} + +.is-italic { + font-style: italic !important; +} + +.has-text-weight-light { + font-weight: 300 !important; +} + +.has-text-weight-normal { + font-weight: 400 !important; +} + +.has-text-weight-medium { + font-weight: 500 !important; +} + +.has-text-weight-semibold { + font-weight: 600 !important; +} + +.has-text-weight-bold { + font-weight: 700 !important; +} + +.is-family-primary { + font-family: "PT Sans", Helvetica, Arial, "sans-serif" !important; +} + +.is-family-secondary { + font-family: "PT Sans", Helvetica, Arial, "sans-serif" !important; +} + +.is-family-sans-serif { + font-family: "PT Sans", Helvetica, Arial, "sans-serif" !important; +} + +.is-family-monospace { + font-family: Menlo, Monaco, "Courier New", monospace !important; +} + +.is-family-code { + font-family: Menlo, Monaco, "Courier New", monospace !important; +} + +.is-block { + display: block !important; +} + +@media screen and (max-width: 768px) { + .is-block-mobile { + display: block !important; + } +} + +@media screen and (min-width: 769px), print { + .is-block-tablet { + display: block !important; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .is-block-tablet-only { + display: block !important; + } +} + +@media screen and (max-width: 1023px) { + .is-block-touch { + display: block !important; + } +} + +@media screen and (min-width: 1024px) { + .is-block-desktop { + display: block !important; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .is-block-desktop-only { + display: block !important; + } +} + +@media screen and (min-width: 1216px) { + .is-block-widescreen { + display: block !important; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .is-block-widescreen-only { + display: block !important; + } +} + +@media screen and (min-width: 1408px) { + .is-block-fullhd { + display: block !important; + } +} + +.is-flex { + display: flex !important; +} + +@media screen and (max-width: 768px) { + .is-flex-mobile { + display: flex !important; + } +} + +@media screen and (min-width: 769px), print { + .is-flex-tablet { + display: flex !important; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .is-flex-tablet-only { + display: flex !important; + } +} + +@media screen and (max-width: 1023px) { + .is-flex-touch { + display: flex !important; + } +} + +@media screen and (min-width: 1024px) { + .is-flex-desktop { + display: flex !important; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .is-flex-desktop-only { + display: flex !important; + } +} + +@media screen and (min-width: 1216px) { + .is-flex-widescreen { + display: flex !important; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .is-flex-widescreen-only { + display: flex !important; + } +} + +@media screen and (min-width: 1408px) { + .is-flex-fullhd { + display: flex !important; + } +} + +.is-inline { + display: inline !important; +} + +@media screen and (max-width: 768px) { + .is-inline-mobile { + display: inline !important; + } +} + +@media screen and (min-width: 769px), print { + .is-inline-tablet { + display: inline !important; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .is-inline-tablet-only { + display: inline !important; + } +} + +@media screen and (max-width: 1023px) { + .is-inline-touch { + display: inline !important; + } +} + +@media screen and (min-width: 1024px) { + .is-inline-desktop { + display: inline !important; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .is-inline-desktop-only { + display: inline !important; + } +} + +@media screen and (min-width: 1216px) { + .is-inline-widescreen { + display: inline !important; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .is-inline-widescreen-only { + display: inline !important; + } +} + +@media screen and (min-width: 1408px) { + .is-inline-fullhd { + display: inline !important; + } +} + +.is-inline-block { + display: inline-block !important; +} + +@media screen and (max-width: 768px) { + .is-inline-block-mobile { + display: inline-block !important; + } +} + +@media screen and (min-width: 769px), print { + .is-inline-block-tablet { + display: inline-block !important; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .is-inline-block-tablet-only { + display: inline-block !important; + } +} + +@media screen and (max-width: 1023px) { + .is-inline-block-touch { + display: inline-block !important; + } +} + +@media screen and (min-width: 1024px) { + .is-inline-block-desktop { + display: inline-block !important; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .is-inline-block-desktop-only { + display: inline-block !important; + } +} + +@media screen and (min-width: 1216px) { + .is-inline-block-widescreen { + display: inline-block !important; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .is-inline-block-widescreen-only { + display: inline-block !important; + } +} + +@media screen and (min-width: 1408px) { + .is-inline-block-fullhd { + display: inline-block !important; + } +} + +.is-inline-flex { + display: inline-flex !important; +} + +@media screen and (max-width: 768px) { + .is-inline-flex-mobile { + display: inline-flex !important; + } +} + +@media screen and (min-width: 769px), print { + .is-inline-flex-tablet { + display: inline-flex !important; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .is-inline-flex-tablet-only { + display: inline-flex !important; + } +} + +@media screen and (max-width: 1023px) { + .is-inline-flex-touch { + display: inline-flex !important; + } +} + +@media screen and (min-width: 1024px) { + .is-inline-flex-desktop { + display: inline-flex !important; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .is-inline-flex-desktop-only { + display: inline-flex !important; + } +} + +@media screen and (min-width: 1216px) { + .is-inline-flex-widescreen { + display: inline-flex !important; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .is-inline-flex-widescreen-only { + display: inline-flex !important; + } +} + +@media screen and (min-width: 1408px) { + .is-inline-flex-fullhd { + display: inline-flex !important; + } +} + +.is-hidden { + display: none !important; +} + +.is-sr-only { + border: none !important; + clip: rect(0, 0, 0, 0) !important; + height: 0.01em !important; + overflow: hidden !important; + padding: 0 !important; + position: absolute !important; + white-space: nowrap !important; + width: 0.01em !important; +} + +@media screen and (max-width: 768px) { + .is-hidden-mobile { + display: none !important; + } +} + +@media screen and (min-width: 769px), print { + .is-hidden-tablet { + display: none !important; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .is-hidden-tablet-only { + display: none !important; + } +} + +@media screen and (max-width: 1023px) { + .is-hidden-touch { + display: none !important; + } +} + +@media screen and (min-width: 1024px) { + .is-hidden-desktop { + display: none !important; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .is-hidden-desktop-only { + display: none !important; + } +} + +@media screen and (min-width: 1216px) { + .is-hidden-widescreen { + display: none !important; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .is-hidden-widescreen-only { + display: none !important; + } +} + +@media screen and (min-width: 1408px) { + .is-hidden-fullhd { + display: none !important; + } +} + +.is-invisible { + visibility: hidden !important; +} + +@media screen and (max-width: 768px) { + .is-invisible-mobile { + visibility: hidden !important; + } +} + +@media screen and (min-width: 769px), print { + .is-invisible-tablet { + visibility: hidden !important; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .is-invisible-tablet-only { + visibility: hidden !important; + } +} + +@media screen and (max-width: 1023px) { + .is-invisible-touch { + visibility: hidden !important; + } +} + +@media screen and (min-width: 1024px) { + .is-invisible-desktop { + visibility: hidden !important; + } +} + +@media screen and (min-width: 1024px) and (max-width: 1215px) { + .is-invisible-desktop-only { + visibility: hidden !important; + } +} + +@media screen and (min-width: 1216px) { + .is-invisible-widescreen { + visibility: hidden !important; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .is-invisible-widescreen-only { + visibility: hidden !important; + } +} + +@media screen and (min-width: 1408px) { + .is-invisible-fullhd { + visibility: hidden !important; + } +} + +.hero { + align-items: stretch; + display: flex; + flex-direction: column; + justify-content: space-between; +} + +.hero .navbar { + background: none; +} + +.hero .tabs ul { + border-bottom: none; +} + +.hero.is-white { + background-color: white; + color: #0a0a0a; +} + +.hero.is-white a:not(.button):not(.dropdown-item):not(.tag):not(.pagination-link.is-current), +.hero.is-white strong { + color: inherit; +} + +.hero.is-white .title { + color: #0a0a0a; +} + +.hero.is-white .subtitle { + color: rgba(10, 10, 10, 0.9); +} + +.hero.is-white .subtitle a:not(.button), +.hero.is-white .subtitle strong { + color: #0a0a0a; +} + +@media screen and (max-width: 1023px) { + .hero.is-white .navbar-menu { + background-color: white; + } +} + +.hero.is-white .navbar-item, +.hero.is-white .navbar-link { + color: rgba(10, 10, 10, 0.7); +} + +.hero.is-white a.navbar-item:hover, .hero.is-white a.navbar-item.is-active, +.hero.is-white .navbar-link:hover, +.hero.is-white .navbar-link.is-active { + background-color: #f2f2f2; + color: #0a0a0a; +} + +.hero.is-white .tabs a { + color: #0a0a0a; + opacity: 0.9; +} + +.hero.is-white .tabs a:hover { + opacity: 1; +} + +.hero.is-white .tabs li.is-active a { + opacity: 1; +} + +.hero.is-white .tabs.is-boxed a, .hero.is-white .tabs.is-toggle a { + color: #0a0a0a; +} + +.hero.is-white .tabs.is-boxed a:hover, .hero.is-white .tabs.is-toggle a:hover { + background-color: rgba(10, 10, 10, 0.1); +} + +.hero.is-white .tabs.is-boxed li.is-active a, .hero.is-white .tabs.is-boxed li.is-active a:hover, .hero.is-white .tabs.is-toggle li.is-active a, .hero.is-white .tabs.is-toggle li.is-active a:hover { + background-color: #0a0a0a; + border-color: #0a0a0a; + color: white; +} + +.hero.is-white.is-bold { + background-image: linear-gradient(141deg, #e8e3e4 0%, white 71%, white 100%); +} + +@media screen and (max-width: 768px) { + .hero.is-white.is-bold .navbar-menu { + background-image: linear-gradient(141deg, #e8e3e4 0%, white 71%, white 100%); + } +} + +.hero.is-black { + background-color: #0a0a0a; + color: white; +} + +.hero.is-black a:not(.button):not(.dropdown-item):not(.tag):not(.pagination-link.is-current), +.hero.is-black strong { + color: inherit; +} + +.hero.is-black .title { + color: white; +} + +.hero.is-black .subtitle { + color: rgba(255, 255, 255, 0.9); +} + +.hero.is-black .subtitle a:not(.button), +.hero.is-black .subtitle strong { + color: white; +} + +@media screen and (max-width: 1023px) { + .hero.is-black .navbar-menu { + background-color: #0a0a0a; + } +} + +.hero.is-black .navbar-item, +.hero.is-black .navbar-link { + color: rgba(255, 255, 255, 0.7); +} + +.hero.is-black a.navbar-item:hover, .hero.is-black a.navbar-item.is-active, +.hero.is-black .navbar-link:hover, +.hero.is-black .navbar-link.is-active { + background-color: black; + color: white; +} + +.hero.is-black .tabs a { + color: white; + opacity: 0.9; +} + +.hero.is-black .tabs a:hover { + opacity: 1; +} + +.hero.is-black .tabs li.is-active a { + opacity: 1; +} + +.hero.is-black .tabs.is-boxed a, .hero.is-black .tabs.is-toggle a { + color: white; +} + +.hero.is-black .tabs.is-boxed a:hover, .hero.is-black .tabs.is-toggle a:hover { + background-color: rgba(10, 10, 10, 0.1); +} + +.hero.is-black .tabs.is-boxed li.is-active a, .hero.is-black .tabs.is-boxed li.is-active a:hover, .hero.is-black .tabs.is-toggle li.is-active a, .hero.is-black .tabs.is-toggle li.is-active a:hover { + background-color: white; + border-color: white; + color: #0a0a0a; +} + +.hero.is-black.is-bold { + background-image: linear-gradient(141deg, black 0%, #0a0a0a 71%, #181616 100%); +} + +@media screen and (max-width: 768px) { + .hero.is-black.is-bold .navbar-menu { + background-image: linear-gradient(141deg, black 0%, #0a0a0a 71%, #181616 100%); + } +} + +.hero.is-light { + background-color: whitesmoke; + color: rgba(0, 0, 0, 0.7); +} + +.hero.is-light a:not(.button):not(.dropdown-item):not(.tag):not(.pagination-link.is-current), +.hero.is-light strong { + color: inherit; +} + +.hero.is-light .title { + color: rgba(0, 0, 0, 0.7); +} + +.hero.is-light .subtitle { + color: rgba(0, 0, 0, 0.9); +} + +.hero.is-light .subtitle a:not(.button), +.hero.is-light .subtitle strong { + color: rgba(0, 0, 0, 0.7); +} + +@media screen and (max-width: 1023px) { + .hero.is-light .navbar-menu { + background-color: whitesmoke; + } +} + +.hero.is-light .navbar-item, +.hero.is-light .navbar-link { + color: rgba(0, 0, 0, 0.7); +} + +.hero.is-light a.navbar-item:hover, .hero.is-light a.navbar-item.is-active, +.hero.is-light .navbar-link:hover, +.hero.is-light .navbar-link.is-active { + background-color: #e8e8e8; + color: rgba(0, 0, 0, 0.7); +} + +.hero.is-light .tabs a { + color: rgba(0, 0, 0, 0.7); + opacity: 0.9; +} + +.hero.is-light .tabs a:hover { + opacity: 1; +} + +.hero.is-light .tabs li.is-active a { + opacity: 1; +} + +.hero.is-light .tabs.is-boxed a, .hero.is-light .tabs.is-toggle a { + color: rgba(0, 0, 0, 0.7); +} + +.hero.is-light .tabs.is-boxed a:hover, .hero.is-light .tabs.is-toggle a:hover { + background-color: rgba(10, 10, 10, 0.1); +} + +.hero.is-light .tabs.is-boxed li.is-active a, .hero.is-light .tabs.is-boxed li.is-active a:hover, .hero.is-light .tabs.is-toggle li.is-active a, .hero.is-light .tabs.is-toggle li.is-active a:hover { + background-color: rgba(0, 0, 0, 0.7); + border-color: rgba(0, 0, 0, 0.7); + color: whitesmoke; +} + +.hero.is-light.is-bold { + background-image: linear-gradient(141deg, #dfd8d9 0%, whitesmoke 71%, white 100%); +} + +@media screen and (max-width: 768px) { + .hero.is-light.is-bold .navbar-menu { + background-image: linear-gradient(141deg, #dfd8d9 0%, whitesmoke 71%, white 100%); + } +} + +.hero.is-dark { + background-color: #363636; + color: #fff; +} + +.hero.is-dark a:not(.button):not(.dropdown-item):not(.tag):not(.pagination-link.is-current), +.hero.is-dark strong { + color: inherit; +} + +.hero.is-dark .title { + color: #fff; +} + +.hero.is-dark .subtitle { + color: rgba(255, 255, 255, 0.9); +} + +.hero.is-dark .subtitle a:not(.button), +.hero.is-dark .subtitle strong { + color: #fff; +} + +@media screen and (max-width: 1023px) { + .hero.is-dark .navbar-menu { + background-color: #363636; + } +} + +.hero.is-dark .navbar-item, +.hero.is-dark .navbar-link { + color: rgba(255, 255, 255, 0.7); +} + +.hero.is-dark a.navbar-item:hover, .hero.is-dark a.navbar-item.is-active, +.hero.is-dark .navbar-link:hover, +.hero.is-dark .navbar-link.is-active { + background-color: #292929; + color: #fff; +} + +.hero.is-dark .tabs a { + color: #fff; + opacity: 0.9; +} + +.hero.is-dark .tabs a:hover { + opacity: 1; +} + +.hero.is-dark .tabs li.is-active a { + opacity: 1; +} + +.hero.is-dark .tabs.is-boxed a, .hero.is-dark .tabs.is-toggle a { + color: #fff; +} + +.hero.is-dark .tabs.is-boxed a:hover, .hero.is-dark .tabs.is-toggle a:hover { + background-color: rgba(10, 10, 10, 0.1); +} + +.hero.is-dark .tabs.is-boxed li.is-active a, .hero.is-dark .tabs.is-boxed li.is-active a:hover, .hero.is-dark .tabs.is-toggle li.is-active a, .hero.is-dark .tabs.is-toggle li.is-active a:hover { + background-color: #fff; + border-color: #fff; + color: #363636; +} + +.hero.is-dark.is-bold { + background-image: linear-gradient(141deg, #1f191a 0%, #363636 71%, #46403f 100%); +} + +@media screen and (max-width: 768px) { + .hero.is-dark.is-bold .navbar-menu { + background-image: linear-gradient(141deg, #1f191a 0%, #363636 71%, #46403f 100%); + } +} + +.hero.is-primary { + background-color: #FF9200; + color: #fff; +} + +.hero.is-primary a:not(.button):not(.dropdown-item):not(.tag):not(.pagination-link.is-current), +.hero.is-primary strong { + color: inherit; +} + +.hero.is-primary .title { + color: #fff; +} + +.hero.is-primary .subtitle { + color: rgba(255, 255, 255, 0.9); +} + +.hero.is-primary .subtitle a:not(.button), +.hero.is-primary .subtitle strong { + color: #fff; +} + +@media screen and (max-width: 1023px) { + .hero.is-primary .navbar-menu { + background-color: #FF9200; + } +} + +.hero.is-primary .navbar-item, +.hero.is-primary .navbar-link { + color: rgba(255, 255, 255, 0.7); +} + +.hero.is-primary a.navbar-item:hover, .hero.is-primary a.navbar-item.is-active, +.hero.is-primary .navbar-link:hover, +.hero.is-primary .navbar-link.is-active { + background-color: #e68300; + color: #fff; +} + +.hero.is-primary .tabs a { + color: #fff; + opacity: 0.9; +} + +.hero.is-primary .tabs a:hover { + opacity: 1; +} + +.hero.is-primary .tabs li.is-active a { + opacity: 1; +} + +.hero.is-primary .tabs.is-boxed a, .hero.is-primary .tabs.is-toggle a { + color: #fff; +} + +.hero.is-primary .tabs.is-boxed a:hover, .hero.is-primary .tabs.is-toggle a:hover { + background-color: rgba(10, 10, 10, 0.1); +} + +.hero.is-primary .tabs.is-boxed li.is-active a, .hero.is-primary .tabs.is-boxed li.is-active a:hover, .hero.is-primary .tabs.is-toggle li.is-active a, .hero.is-primary .tabs.is-toggle li.is-active a:hover { + background-color: #fff; + border-color: #fff; + color: #FF9200; +} + +.hero.is-primary.is-bold { + background-image: linear-gradient(141deg, #cc5300 0%, #FF9200 71%, #ffc31a 100%); +} + +@media screen and (max-width: 768px) { + .hero.is-primary.is-bold .navbar-menu { + background-image: linear-gradient(141deg, #cc5300 0%, #FF9200 71%, #ffc31a 100%); + } +} + +.hero.is-link { + background-color: #FF9200; + color: #fff; +} + +.hero.is-link a:not(.button):not(.dropdown-item):not(.tag):not(.pagination-link.is-current), +.hero.is-link strong { + color: inherit; +} + +.hero.is-link .title { + color: #fff; +} + +.hero.is-link .subtitle { + color: rgba(255, 255, 255, 0.9); +} + +.hero.is-link .subtitle a:not(.button), +.hero.is-link .subtitle strong { + color: #fff; +} + +@media screen and (max-width: 1023px) { + .hero.is-link .navbar-menu { + background-color: #FF9200; + } +} + +.hero.is-link .navbar-item, +.hero.is-link .navbar-link { + color: rgba(255, 255, 255, 0.7); +} + +.hero.is-link a.navbar-item:hover, .hero.is-link a.navbar-item.is-active, +.hero.is-link .navbar-link:hover, +.hero.is-link .navbar-link.is-active { + background-color: #e68300; + color: #fff; +} + +.hero.is-link .tabs a { + color: #fff; + opacity: 0.9; +} + +.hero.is-link .tabs a:hover { + opacity: 1; +} + +.hero.is-link .tabs li.is-active a { + opacity: 1; +} + +.hero.is-link .tabs.is-boxed a, .hero.is-link .tabs.is-toggle a { + color: #fff; +} + +.hero.is-link .tabs.is-boxed a:hover, .hero.is-link .tabs.is-toggle a:hover { + background-color: rgba(10, 10, 10, 0.1); +} + +.hero.is-link .tabs.is-boxed li.is-active a, .hero.is-link .tabs.is-boxed li.is-active a:hover, .hero.is-link .tabs.is-toggle li.is-active a, .hero.is-link .tabs.is-toggle li.is-active a:hover { + background-color: #fff; + border-color: #fff; + color: #FF9200; +} + +.hero.is-link.is-bold { + background-image: linear-gradient(141deg, #cc5300 0%, #FF9200 71%, #ffc31a 100%); +} + +@media screen and (max-width: 768px) { + .hero.is-link.is-bold .navbar-menu { + background-image: linear-gradient(141deg, #cc5300 0%, #FF9200 71%, #ffc31a 100%); + } +} + +.hero.is-info { + background-color: #3298dc; + color: #fff; +} + +.hero.is-info a:not(.button):not(.dropdown-item):not(.tag):not(.pagination-link.is-current), +.hero.is-info strong { + color: inherit; +} + +.hero.is-info .title { + color: #fff; +} + +.hero.is-info .subtitle { + color: rgba(255, 255, 255, 0.9); +} + +.hero.is-info .subtitle a:not(.button), +.hero.is-info .subtitle strong { + color: #fff; +} + +@media screen and (max-width: 1023px) { + .hero.is-info .navbar-menu { + background-color: #3298dc; + } +} + +.hero.is-info .navbar-item, +.hero.is-info .navbar-link { + color: rgba(255, 255, 255, 0.7); +} + +.hero.is-info a.navbar-item:hover, .hero.is-info a.navbar-item.is-active, +.hero.is-info .navbar-link:hover, +.hero.is-info .navbar-link.is-active { + background-color: #238cd1; + color: #fff; +} + +.hero.is-info .tabs a { + color: #fff; + opacity: 0.9; +} + +.hero.is-info .tabs a:hover { + opacity: 1; +} + +.hero.is-info .tabs li.is-active a { + opacity: 1; +} + +.hero.is-info .tabs.is-boxed a, .hero.is-info .tabs.is-toggle a { + color: #fff; +} + +.hero.is-info .tabs.is-boxed a:hover, .hero.is-info .tabs.is-toggle a:hover { + background-color: rgba(10, 10, 10, 0.1); +} + +.hero.is-info .tabs.is-boxed li.is-active a, .hero.is-info .tabs.is-boxed li.is-active a:hover, .hero.is-info .tabs.is-toggle li.is-active a, .hero.is-info .tabs.is-toggle li.is-active a:hover { + background-color: #fff; + border-color: #fff; + color: #3298dc; +} + +.hero.is-info.is-bold { + background-image: linear-gradient(141deg, #159dc6 0%, #3298dc 71%, #4389e5 100%); +} + +@media screen and (max-width: 768px) { + .hero.is-info.is-bold .navbar-menu { + background-image: linear-gradient(141deg, #159dc6 0%, #3298dc 71%, #4389e5 100%); + } +} + +.hero.is-success { + background-color: #01a901; + color: #fff; +} + +.hero.is-success a:not(.button):not(.dropdown-item):not(.tag):not(.pagination-link.is-current), +.hero.is-success strong { + color: inherit; +} + +.hero.is-success .title { + color: #fff; +} + +.hero.is-success .subtitle { + color: rgba(255, 255, 255, 0.9); +} + +.hero.is-success .subtitle a:not(.button), +.hero.is-success .subtitle strong { + color: #fff; +} + +@media screen and (max-width: 1023px) { + .hero.is-success .navbar-menu { + background-color: #01a901; + } +} + +.hero.is-success .navbar-item, +.hero.is-success .navbar-link { + color: rgba(255, 255, 255, 0.7); +} + +.hero.is-success a.navbar-item:hover, .hero.is-success a.navbar-item.is-active, +.hero.is-success .navbar-link:hover, +.hero.is-success .navbar-link.is-active { + background-color: #019001; + color: #fff; +} + +.hero.is-success .tabs a { + color: #fff; + opacity: 0.9; +} + +.hero.is-success .tabs a:hover { + opacity: 1; +} + +.hero.is-success .tabs li.is-active a { + opacity: 1; +} + +.hero.is-success .tabs.is-boxed a, .hero.is-success .tabs.is-toggle a { + color: #fff; +} + +.hero.is-success .tabs.is-boxed a:hover, .hero.is-success .tabs.is-toggle a:hover { + background-color: rgba(10, 10, 10, 0.1); +} + +.hero.is-success .tabs.is-boxed li.is-active a, .hero.is-success .tabs.is-boxed li.is-active a:hover, .hero.is-success .tabs.is-toggle li.is-active a, .hero.is-success .tabs.is-toggle li.is-active a:hover { + background-color: #fff; + border-color: #fff; + color: #01a901; +} + +.hero.is-success.is-bold { + background-image: linear-gradient(141deg, #147700 0%, #01a901 71%, #00c421 100%); +} + +@media screen and (max-width: 768px) { + .hero.is-success.is-bold .navbar-menu { + background-image: linear-gradient(141deg, #147700 0%, #01a901 71%, #00c421 100%); + } +} + +.hero.is-warning { + background-color: #e7cb00; + color: rgba(0, 0, 0, 0.7); +} + +.hero.is-warning a:not(.button):not(.dropdown-item):not(.tag):not(.pagination-link.is-current), +.hero.is-warning strong { + color: inherit; +} + +.hero.is-warning .title { + color: rgba(0, 0, 0, 0.7); +} + +.hero.is-warning .subtitle { + color: rgba(0, 0, 0, 0.9); +} + +.hero.is-warning .subtitle a:not(.button), +.hero.is-warning .subtitle strong { + color: rgba(0, 0, 0, 0.7); +} + +@media screen and (max-width: 1023px) { + .hero.is-warning .navbar-menu { + background-color: #e7cb00; + } +} + +.hero.is-warning .navbar-item, +.hero.is-warning .navbar-link { + color: rgba(0, 0, 0, 0.7); +} + +.hero.is-warning a.navbar-item:hover, .hero.is-warning a.navbar-item.is-active, +.hero.is-warning .navbar-link:hover, +.hero.is-warning .navbar-link.is-active { + background-color: #ceb500; + color: rgba(0, 0, 0, 0.7); +} + +.hero.is-warning .tabs a { + color: rgba(0, 0, 0, 0.7); + opacity: 0.9; +} + +.hero.is-warning .tabs a:hover { + opacity: 1; +} + +.hero.is-warning .tabs li.is-active a { + opacity: 1; +} + +.hero.is-warning .tabs.is-boxed a, .hero.is-warning .tabs.is-toggle a { + color: rgba(0, 0, 0, 0.7); +} + +.hero.is-warning .tabs.is-boxed a:hover, .hero.is-warning .tabs.is-toggle a:hover { + background-color: rgba(10, 10, 10, 0.1); +} + +.hero.is-warning .tabs.is-boxed li.is-active a, .hero.is-warning .tabs.is-boxed li.is-active a:hover, .hero.is-warning .tabs.is-toggle li.is-active a, .hero.is-warning .tabs.is-toggle li.is-active a:hover { + background-color: rgba(0, 0, 0, 0.7); + border-color: rgba(0, 0, 0, 0.7); + color: #e7cb00; +} + +.hero.is-warning.is-bold { + background-image: linear-gradient(141deg, #b48000 0%, #e7cb00 71%, #f3ff02 100%); +} + +@media screen and (max-width: 768px) { + .hero.is-warning.is-bold .navbar-menu { + background-image: linear-gradient(141deg, #b48000 0%, #e7cb00 71%, #f3ff02 100%); + } +} + +.hero.is-danger { + background-color: #F45F4B; + color: #fff; +} + +.hero.is-danger a:not(.button):not(.dropdown-item):not(.tag):not(.pagination-link.is-current), +.hero.is-danger strong { + color: inherit; +} + +.hero.is-danger .title { + color: #fff; +} + +.hero.is-danger .subtitle { + color: rgba(255, 255, 255, 0.9); +} + +.hero.is-danger .subtitle a:not(.button), +.hero.is-danger .subtitle strong { + color: #fff; +} + +@media screen and (max-width: 1023px) { + .hero.is-danger .navbar-menu { + background-color: #F45F4B; + } +} + +.hero.is-danger .navbar-item, +.hero.is-danger .navbar-link { + color: rgba(255, 255, 255, 0.7); +} + +.hero.is-danger a.navbar-item:hover, .hero.is-danger a.navbar-item.is-active, +.hero.is-danger .navbar-link:hover, +.hero.is-danger .navbar-link.is-active { + background-color: #f34a33; + color: #fff; +} + +.hero.is-danger .tabs a { + color: #fff; + opacity: 0.9; +} + +.hero.is-danger .tabs a:hover { + opacity: 1; +} + +.hero.is-danger .tabs li.is-active a { + opacity: 1; +} + +.hero.is-danger .tabs.is-boxed a, .hero.is-danger .tabs.is-toggle a { + color: #fff; +} + +.hero.is-danger .tabs.is-boxed a:hover, .hero.is-danger .tabs.is-toggle a:hover { + background-color: rgba(10, 10, 10, 0.1); +} + +.hero.is-danger .tabs.is-boxed li.is-active a, .hero.is-danger .tabs.is-boxed li.is-active a:hover, .hero.is-danger .tabs.is-toggle li.is-active a, .hero.is-danger .tabs.is-toggle li.is-active a:hover { + background-color: #fff; + border-color: #fff; + color: #F45F4B; +} + +.hero.is-danger.is-bold { + background-image: linear-gradient(141deg, #fd0f1a 0%, #F45F4B 71%, #fa8b5f 100%); +} + +@media screen and (max-width: 768px) { + .hero.is-danger.is-bold .navbar-menu { + background-image: linear-gradient(141deg, #fd0f1a 0%, #F45F4B 71%, #fa8b5f 100%); + } +} + +.hero.is-small .hero-body { + padding: 1.5rem; +} + +@media screen and (min-width: 769px), print { + .hero.is-medium .hero-body { + padding: 9rem 1.5rem; + } +} + +@media screen and (min-width: 769px), print { + .hero.is-large .hero-body { + padding: 18rem 1.5rem; + } +} + +.hero.is-halfheight .hero-body, .hero.is-fullheight .hero-body, .hero.is-fullheight-with-navbar .hero-body { + align-items: center; + display: flex; +} + +.hero.is-halfheight .hero-body > .container, .hero.is-fullheight .hero-body > .container, .hero.is-fullheight-with-navbar .hero-body > .container { + flex-grow: 1; + flex-shrink: 1; +} + +.hero.is-halfheight { + min-height: 50vh; +} + +.hero.is-fullheight { + min-height: 100vh; +} + +.hero-video { + overflow: hidden; +} + +.hero-video video { + left: 50%; + min-height: 100%; + min-width: 100%; + position: absolute; + top: 50%; + transform: translate3d(-50%, -50%, 0); +} + +.hero-video.is-transparent { + opacity: 0.3; +} + +@media screen and (max-width: 768px) { + .hero-video { + display: none; + } +} + +.hero-buttons { + margin-top: 1.5rem; +} + +@media screen and (max-width: 768px) { + .hero-buttons .button { + display: flex; + } + .hero-buttons .button:not(:last-child) { + margin-bottom: 0.75rem; + } +} + +@media screen and (min-width: 769px), print { + .hero-buttons { + display: flex; + justify-content: center; + } + .hero-buttons .button:not(:last-child) { + margin-right: 1.5rem; + } +} + +.hero-head, +.hero-foot { + flex-grow: 0; + flex-shrink: 0; +} + +.hero-body { + flex-grow: 1; + flex-shrink: 0; + padding: 3rem 1.5rem; +} + +html { + scroll-padding-top: 4.5rem; +} + +h1, h2, .rst-content #index h3, .rst-content .toctree-wrapper .caption, h3, h4, h5, h6 { + overflow-wrap: break-word; +} + +.viewcode-back { + float: right; + color: #FF9200; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple), html.writer-html4 .rst-content dl:not(.docutils) { + padding-bottom: 0.5em; + box-shadow: 0 2px 2px 0 rgba(0, 0, 0, 0.14), 0 1px 5px 0 rgba(0, 0, 0, 0.12), 0 3px 1px -2px rgba(0, 0, 0, 0.2); +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) .property, html.writer-html4 .rst-content dl:not(.docutils) .property { + display: inherit; + padding-right: 0px; + max-width: 100%; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dt, html.writer-html4 .rst-content dl:not(.docutils) > dt { + border-top: 3px solid #ca6500; + color: #343131; + display: inherit; + line-height: 1.4; + font-family: Menlo, Monaco, "Courier New", monospace; + font-size: 0.9rem; + background-color: #FFEBD0; + border-radius: 4px; + overflow-wrap: break-word; + position: relative; + padding-left: 0.45rem; + padding-right: 5.625rem; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dt:target::before, html.writer-html4 .rst-content dl:not(.docutils) > dt:target::before { + background-color: #FFFFFF; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dt > .property, html.writer-html4 .rst-content dl:not(.docutils) > dt > .property { + display: unset; + padding-right: 0px; + max-width: 100%; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dt .viewcode-link, html.writer-html4 .rst-content dl:not(.docutils) > dt .viewcode-link { + position: absolute; + top: 0.45rem; + right: 1.8rem; + color: #808080; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dt .viewcode-link .pre:hover, html.writer-html4 .rst-content dl:not(.docutils) > dt .viewcode-link .pre:hover { + color: #FF9200; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dt .headerlink, html.writer-html4 .rst-content dl:not(.docutils) > dt .headerlink { + position: absolute; + top: 0.45rem; + right: 0.45rem; + color: #FF9200; + opacity: 1; + margin-top: -0.1rem; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd, html.writer-html4 .rst-content dl:not(.docutils) > dd { + margin: 1em; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd:empty, html.writer-html4 .rst-content dl:not(.docutils) > dd:empty { + padding-bottom: 0 !important; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd > .field-list > dt, html.writer-html4 .rst-content dl:not(.docutils) > dd > .field-list > dt { + font-weight: bold; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd > .field-list > dd > ul.simple, html.writer-html4 .rst-content dl:not(.docutils) > dd > .field-list > dd > ul.simple { + margin-left: 0; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd > .field-list > dd > dl > dt > strong, html.writer-html4 .rst-content dl:not(.docutils) > dd > .field-list > dd > dl > dt > strong, html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd > .field-list > dd > ul.simple:first-child > li > p:first-child > strong, html.writer-html4 .rst-content dl:not(.docutils) > dd > .field-list > dd > ul.simple:first-child > li > p:first-child > strong, html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd > .field-list > dd > p:first-child > strong, html.writer-html4 .rst-content dl:not(.docutils) > dd > .field-list > dd > p:first-child > strong { + font-family: Menlo, Monaco, "Courier New", monospace; + color: #343131; + font-weight: normal; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd > .field-list > dd > dl > dt > .classifier, html.writer-html4 .rst-content dl:not(.docutils) > dd > .field-list > dd > dl > dt > .classifier, html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd > .field-list > dd > ul.simple:first-child > li > p:first-child > .classifier, html.writer-html4 .rst-content dl:not(.docutils) > dd > .field-list > dd > ul.simple:first-child > li > p:first-child > .classifier, html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd > .field-list > dd > p:first-child > .classifier, html.writer-html4 .rst-content dl:not(.docutils) > dd > .field-list > dd > p:first-child > .classifier { + font-family: Menlo, Monaco, "Courier New", monospace; + color: #4a4a4a; + overflow-wrap: break-word; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd > .field-list > dd > dl > dt > a.reference > em, html.writer-html4 .rst-content dl:not(.docutils) > dd > .field-list > dd > dl > dt > a.reference > em, html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd > .field-list > dd > p:first-child > a.reference > em, html.writer-html4 .rst-content dl:not(.docutils) > dd > .field-list > dd > p:first-child > a.reference > em { + font-family: Menlo, Monaco, "Courier New", monospace; + font-style: normal; +} + +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) > dd > .field-list > dd > dl > dt > strong::after, html.writer-html4 .rst-content dl:not(.docutils) > dd > .field-list > dd > dl > dt > strong::after { + content: ": "; +} + +.rst-content { + font-size: 1rem; + line-height: 1.6; + color-adjust: exact; +} + +@media print { + .rst-content { + font-size: 0.85rem; + } +} + +.rst-content ul, +.rst-content ol, +.rst-content dl, +.rst-content figure, +.rst-content p, +.rst-content pre { + margin: 1em 0; +} + +.rst-content h1 { + margin: 0 0 1.25em; + color: #121212; + font-weight: 700; + line-height: 1.3; + letter-spacing: -0.01em; + font-size: 175%; +} + +.rst-content h2, .rst-content #index h3, .rst-content .toctree-wrapper .caption { + margin: 1.6em 0 0.64em; + font-weight: 600; + font-size: 1.5625em; + line-height: 1.4; + letter-spacing: -0.01em; +} + +.rst-content h3 { + margin: 1.6em 0 0.8em; + font-weight: 500; + font-size: 1.25em; + line-height: 1.5; + letter-spacing: -0.01em; +} + +.rst-content h2 + h3, .rst-content #index h3 + h3, .rst-content .toctree-wrapper .caption + h3 { + margin-top: 0.8em; +} + +.rst-content h4 { + margin: 1em 0; + font-weight: 700; + letter-spacing: -0.01em; +} + +.rst-content h5, +.rst-content h6 { + margin: 1.25em 0; + color: #121212; + font-weight: 700; + font-size: 0.8em; + letter-spacing: -0.01em; +} + +.rst-content h5 { + text-transform: uppercase; +} + +.rst-content hr { + display: flow-root; + margin: 1.5em 0; + border-bottom: 0.0625rem solid #0a0a0a; +} + +.rst-content a { + color: #FF9200; + overflow-wrap: break-word; +} + +.rst-content a, .rst-content a::before { + transition: color 125ms; +} + +.rst-content a:focus { + color: #ca6500; +} + +.rst-content a:hover { + color: #ca6500; +} + +.rst-content a.focus-visible { + outline-color: #ca6500; + outline-offset: 0.25rem; +} + +.rst-content code, +.rst-content pre, +.rst-content kbd { + color: #0a0a0a; + direction: ltr; +} + +@media print { + .rst-content code, +.rst-content pre, +.rst-content kbd { + white-space: pre-wrap; + } +} + +.rst-content code { + padding: 0 0.29412em; + font-size: 0.85em; + overflow-wrap: break-word; + background-color: #f8f8f8; + border-radius: 0.125rem; + box-decoration-break: clone; +} + +.rst-content code:not(.focus-visible) { + outline: none; + -webkit-tap-highlight-color: transparent; +} + +.rst-content h1 code, +.rst-content h2 code, +.rst-content #index h3 code, +.rst-content .toctree-wrapper .caption code, +.rst-content h3 code, +.rst-content h4 code, +.rst-content h5 code, +.rst-content h6 code { + background-color: transparent; + box-shadow: none; +} + +.rst-content a code { + color: currentColor; +} + +.rst-content pre { + position: relative; + display: flow-root; + line-height: 1.4; +} + +.rst-content pre > code { + display: block; + margin: 0; + padding: 0.77206em 1.17647em; + overflow: auto; + word-break: normal; + box-shadow: none; + box-decoration-break: slice; + touch-action: auto; + scrollbar-width: thin; + scrollbar-color: #242424 transparent; +} + +.rst-content pre > code:hover { + scrollbar-color: #ca6500 transparent; +} + +.rst-content pre > code::-webkit-scrollbar { + width: 0.25rem; + height: 0.25rem; +} + +.rst-content pre > code::-webkit-scrollbar-thumb { + background-color: #242424; +} + +.rst-content pre > code::-webkit-scrollbar-thumb:hover { + background-color: #ca6500; +} + +@media screen and (max-width: 768px) { + .rst-content > pre code { + border-radius: 0; + } +} + +.rst-content kbd { + display: inline-block; + padding: 0 0.66667em; + color: #0a0a0a; + font-size: 0.75em; + vertical-align: text-top; + overflow-wrap: break-word; + background-color: whitesmoke; + border-radius: 0.125rem; + box-shadow: 0 0.125rem 0 0.0625rem #dbdbdb, 0 0.125rem 0 #dbdbdb, 0 -0.125rem 0.25rem #ededed inset; +} + +.rst-content mark { + color: inherit; + overflow-wrap: break-word; + background-color: #e7cb00; + box-decoration-break: clone; +} + +.rst-content abbr { + text-decoration: none; + border-bottom: 0.0625rem dotted #121212; + cursor: help; +} + +@media (hover: none) { + .rst-content abbr { + position: relative; + } + .rst-content abbr[title]:focus::after, .rst-content abbr[title]:hover::after { + box-shadow: 0 2px 2px 0 rgba(0, 0, 0, 0.14), 0 1px 5px 0 rgba(0, 0, 0, 0.12), 0 3px 1px -2px rgba(0, 0, 0, 0.2); + position: absolute; + left: 0; + display: inline-block; + width: auto; + min-width: max-content; + max-width: 80%; + margin-top: 2em; + padding: 0.25rem 0.375rem; + color: #FFFFFF; + font-size: 0.875rem; + background-color: #0a0a0a; + border-radius: 0.125rem; + content: attr(title); + } +} + +.rst-content small { + opacity: 0.75; +} + +.rst-content sup, +.rst-content sub { + margin-left: 0.07812em; +} + +[dir="rtl"] .rst-content sup, [dir="rtl"] .rst-content sub { + margin-right: 0.07812em; + margin-left: initial; +} + +.rst-content blockquote { + display: flow-root; + padding-left: 0.75rem; + color: #4a4a4a; +} + +[dir="rtl"] .rst-content blockquote { + padding-right: 0.75rem; + padding-left: initial; + border-right: 0.25rem solid #7a7a7a; + border-left: initial; +} + +.rst-content li > blockquote { + border-left: none; +} + +[dir="rtl"] .rst-content li > blockquote { + border-right: none; +} + +.rst-content blockquote +ul { + list-style-type: disc; +} + +.rst-content ul, +.rst-content ol { + display: flow-root; + margin-left: 0.625em; + padding: 0; +} + +[dir="rtl"] .rst-content ul, [dir="rtl"] .rst-content ol { + margin-right: 0.625em; + margin-left: initial; +} + +.rst-content ul ol, +.rst-content ol ol { + list-style-type: lower-alpha; +} + +.rst-content ul ol ol, +.rst-content ol ol ol { + list-style-type: lower-roman; +} + +.rst-content ul li, +.rst-content ol li { + margin-bottom: 0.5em; + margin-left: 1.25em; +} + +[dir="rtl"] .rst-content ul li, [dir="rtl"] .rst-content ol li { + margin-right: 1.25em; + margin-left: initial; +} + +.rst-content ul li p, +.rst-content ul li blockquote, +.rst-content ol li p, +.rst-content ol li blockquote { + margin: 0.5em 0; +} + +.rst-content ul li:last-child, +.rst-content ol li:last-child { + margin-bottom: 0; +} + +.rst-content ul li ul, +.rst-content ul li ol, +.rst-content ol li ul, +.rst-content ol li ol { + margin: 0.5em 0 0.5em 0.625em; +} + +[dir="rtl"] .rst-content ul li ul, [dir="rtl"] .rst-content ul li ol, [dir="rtl"] .rst-content ol li ul, [dir="rtl"] .rst-content ol li ol { + margin-right: 0.625em; + margin-left: initial; +} + +.rst-content dd { + margin: 1em 0 1.5em 1.875em; +} + +@media screen and (max-width: 769px) { + .rst-content dd { + margin-left: 0.625em; + } +} + +[dir="rtl"] .rst-content dd { + margin-right: 1.875em; + margin-left: initial; +} + +@media screen and (max-width: 769px) { + [dir="rtl"] .rst-content dd { + margin-right: 0.625em; + } +} + +.rst-content dl:not([class]) dt, .rst-content dl.simple dt { + font-weight: 200; +} + +.rst-content img, +.rst-content svg { + max-width: 100%; + height: auto; +} + +.rst-content img[align="left"], +.rst-content svg[align="left"] { + margin: 1em; + margin-left: 0; +} + +.rst-content img[align="right"], +.rst-content svg[align="right"] { + margin: 1em; + margin-right: 0; +} + +.rst-content img[align]:only-child, +.rst-content svg[align]:only-child { + margin-top: 0; +} + +.rst-content figure { + display: flow-root; + width: fit-content; + max-width: 100%; + margin: 0 auto; + text-align: center; +} + +.rst-content figure img { + display: block; + margin: 0 auto; +} + +.rst-content figcaption { + margin: 1em auto 2em; + text-align: justify; + font-size: 90%; + hyphens: auto; + width: 80%; +} + +.rst-content iframe { + max-width: 100%; +} + +.rst-content .align-left { + text-align: left; +} + +.rst-content .align-right { + text-align: right; +} + +.rst-content .align-center { + clear: both; + text-align: center; +} + +.rst-content .align-top { + vertical-align: top; +} + +.rst-content .align-middle { + vertical-align: middle; +} + +.rst-content .align-bottom { + vertical-align: bottom; +} + +.rst-content .figure.align-left, +.rst-content figure.align-left, +.rst-content img.align-left, +.rst-content object.align-left, +.rst-content table.align-left { + margin-right: auto; +} + +.rst-content .figure.align-center, +.rst-content figure.align-center, +.rst-content img.align-center, +.rst-content object.align-center, +.rst-content table.align-center, +.rst-content table.align-default { + margin-right: auto; + margin-left: auto; +} + +.rst-content .figure.align-right, +.rst-content figure.align-right, +.rst-content img.align-right, +.rst-content object.align-right, +.rst-content table.align-right { + margin-left: auto; +} + +.rst-content .figure.align-center, +.rst-content .figure.align-right, +.rst-content figure.align-center, +.rst-content figure.align-right, +.rst-content img.align-center, +.rst-content img.align-right, +.rst-content object.align-center, +.rst-content object.align-right { + display: block; +} + +.rst-content .figure.align-left, +.rst-content .figure.align-right, +.rst-content figure.align-left, +.rst-content figure.align-right, +.rst-content table.align-left, +.rst-content table.align-center, +.rst-content table.align-right { + text-align: inherit; +} + +.rst-content .rubric { + font-weight: bold; +} + +.rst-content table.highlighttable td.linenos { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + padding-left: 0; + padding-right: 0; +} + +.rst-content table.highlighttable td.linenos .linenodiv pre { + padding-right: 0; +} + +@media screen and (max-width: 768px) { + .rst-content table.highlighttable td.linenos .linenodiv pre { + display: none; + } +} + +.rst-content table.highlighttable td.linenos + td.code { + margin-left: 0; + padding-left: 0; + padding-right: 0; +} + +.rst-content table.highlighttable td.linenos + td.code .highlight pre { + overflow-x: auto; +} + +@media screen and (max-width: 768px) { + .rst-content table.highlighttable td.linenos + td.code .highlight pre { + width: 96vw; + } +} + +.rst-content .highlight { + background-color: #f8f8f8; + border-radius: 4px; + box-shadow: 0 2px 2px 0 rgba(0, 0, 0, 0.14), 0 1px 5px 0 rgba(0, 0, 0, 0.12), 0 3px 1px -2px rgba(0, 0, 0, 0.2); + overflow-x: auto; + margin: 1em 0; +} + +.rst-content .highlight .gp, .rst-content .highlight .linenos { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + +.rst-content .highlight pre { + overflow-x: unset; + margin: unset; +} + +.rst-content .highlight span.linenos { + margin-right: 0.5rem; + margin-left: -0.5rem; + color: #666666; +} + +@media screen and (max-width: 768px) { + .rst-content .highlight span.linenos { + display: none; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .rst-content section > .notranslate > .highlight, .rst-content .section > .notranslate > .highlight { + margin-left: calc(-0.5 * (42.5rem - 42.5rem)); + width: 42.5rem; + } +} + +@media screen and (min-width: 1408px) { + .rst-content section > .notranslate > .highlight, .rst-content .section > .notranslate > .highlight { + margin-left: 0rem; + width: 42.5rem; + } +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .rst-content section > .notranslate > .highlight::before, .rst-content .section > .notranslate > .highlight::before { + right: calc($code-lang-ident-padding - 0.5 * (42.5rem - 42.5rem)); + } +} + +@media screen and (min-width: 1408px) { + .rst-content section > .notranslate > .highlight::before, .rst-content .section > .notranslate > .highlight::before { + right: calc($code-lang-ident-padding - 0.5 * (42.5rem - 42.5rem)); + } +} + +.rst-content .wy-table-responsive.autosummary { + overflow-x: hidden; +} + +.rst-content .wy-table-responsive.autosummary table { + table-layout: fixed; + width: 100%; +} + +.rst-content .wy-table-responsive.autosummary table colgroup col:first-child { + width: 30% !important; +} + +.rst-content .wy-table-responsive.autosummary table colgroup col:last-child { + width: 70% !important; +} + +.rst-content .wy-table-responsive.autosummary table td:first-child { + overflow-wrap: break-word; +} + +.rst-content .wy-table-responsive.autosummary table td:first-child a, .rst-content .wy-table-responsive.autosummary table td:first-child code { + overflow-wrap: break-word; +} + +.rst-content .wy-table-responsive.autosummary table td:first-child a::after, .rst-content .wy-table-responsive.autosummary table td:first-child code::after { + content: "​"; +} + +.rst-content .wy-table-responsive:not(.autosummary).expanded { + box-shadow: 0 2px 2px 0 rgba(0, 0, 0, 0.14), 0 1px 5px 0 rgba(0, 0, 0, 0.12), 0 3px 1px -2px rgba(0, 0, 0, 0.2); +} + +@media screen and (min-width: 1216px) and (max-width: 1407px) { + .rst-content .wy-table-responsive:not(.autosummary).expanded { + margin-left: calc(-0.5 * (66vw - 42.5rem)); + width: 66vw; + max-width: 66vw; + } + .rst-content .wy-table-responsive:not(.autosummary).expanded table { + min-width: 66vw; + } +} + +@media screen and (min-width: 1408px) { + .rst-content .wy-table-responsive:not(.autosummary).expanded { + margin-left: -7.75rem; + width: 58rem; + max-width: 58rem; + } + .rst-content .wy-table-responsive:not(.autosummary).expanded table { + min-width: 58rem; + } +} + +.rst-content .wy-table-responsive:not(.autosummary) table { + font-size: 85%; +} + +.rst-content .wy-table-responsive:not(.autosummary) table tbody tr { + transition: background-color 125ms; +} + +.rst-content .wy-table-responsive:not(.autosummary) table tbody tr:hover { + background-color: rgba(0, 0, 0, 0.035); +} + +.rst-content .headerlink { + font-size: 1em; + margin-left: 0.5em; + color: #b5b5b5; +} + +@media screen and (min-width: 769px) { + .rst-content .headerlink { + display: inline-block; + transform: translateY(0.25rem); + transition: transform .25s 0.2s,color .25s,opacity .125s 0.2s; + opacity: 0; + } +} + +.rst-content *:hover > .headerlink { + transition: transform .25s,color .25s,opacity .125s; + -webkit-transform: translate(0); + transform: translate(0); + opacity: 1; +} + +.rst-content dl.citation > dd { + margin-top: 0; +} + +.rst-content dl.citation > dd :first-child { + margin-top: 0; +} + +.rst-content .file { + align-items: unset; + display: unset; + justify-content: unset; + position: unset; +} + +.rst-content a.brackets::before { + content: "["; +} + +.rst-content a.brackets::after { + content: "]"; +} + +.rst-content .highlight-pycon span.go { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + +.rst-content .highlight-python, .rst-content .highlight-py, .rst-content .highlight-python3, .rst-content .highlight-py3, .rst-content .highlight-pycon { + position: relative; +} + +.rst-content .highlight-python .highlight::before, .rst-content .highlight-py .highlight::before, .rst-content .highlight-python3 .highlight::before, .rst-content .highlight-py3 .highlight::before, .rst-content .highlight-pycon .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "Python"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-sh, .rst-content .highlight-shell-session, .rst-content .highlight-shell { + position: relative; +} + +.rst-content .highlight-sh .highlight::before, .rst-content .highlight-shell-session .highlight::before, .rst-content .highlight-shell .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "Shell"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-bash { + position: relative; +} + +.rst-content .highlight-bash .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "BASH"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-yaml, .rst-content .highlight-yml { + position: relative; +} + +.rst-content .highlight-yaml .highlight::before, .rst-content .highlight-yml .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "YAML"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-toml { + position: relative; +} + +.rst-content .highlight-toml .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "TOML"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-json { + position: relative; +} + +.rst-content .highlight-json .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "JSON"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-html { + position: relative; +} + +.rst-content .highlight-html .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "HTML"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-xml { + position: relative; +} + +.rst-content .highlight-xml .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "XML"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-javascript, .rst-content .highlight-js { + position: relative; +} + +.rst-content .highlight-javascript .highlight::before, .rst-content .highlight-js .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "JavaScript"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-jinja { + position: relative; +} + +.rst-content .highlight-jinja .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "Jinja"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-c { + position: relative; +} + +.rst-content .highlight-c .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "C"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-cxx, .rst-content .highlight-cpp, .rst-content .highlight-c\+\+ { + position: relative; +} + +.rst-content .highlight-cxx .highlight::before, .rst-content .highlight-cpp .highlight::before, .rst-content .highlight-c\+\+ .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "C++"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-rs, .rst-content .highlight-rust { + position: relative; +} + +.rst-content .highlight-rs .highlight::before, .rst-content .highlight-rust .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "Rust"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-julia { + position: relative; +} + +.rst-content .highlight-julia .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "Julia"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-r { + position: relative; +} + +.rst-content .highlight-r .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "R"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-restructuredtext, .rst-content .highlight-rst, .rst-content .highlight-rest { + position: relative; +} + +.rst-content .highlight-restructuredtext .highlight::before, .rst-content .highlight-rst .highlight::before, .rst-content .highlight-rest .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "reStructuredText"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-md, .rst-content .highlight-markdown { + position: relative; +} + +.rst-content .highlight-md .highlight::before, .rst-content .highlight-markdown .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "Markdown"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-tex { + position: relative; +} + +.rst-content .highlight-tex .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "TeX"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .highlight-latex { + position: relative; +} + +.rst-content .highlight-latex .highlight::before { + -webkit-touch-callout: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; + content: "LaTeX"; + color: #696969; + font-size: 80%; + font-family: Menlo, Monaco, "Courier New", monospace; + font-variant: small-caps; + position: absolute; + z-index: 10; + right: 0.18rem; + top: 0.18rem; + line-height: 0.8; +} + +.rst-content .nbinput > .prompt, .rst-content .nboutput > .prompt { + display: None; +} + +.rst-content .nbinput > .output_area, .rst-content .nbinput > .input_area, .rst-content .nboutput > .output_area, .rst-content .nboutput > .input_area { + border: None !important; + box-shadow: 0 2px 2px 0 rgba(0, 0, 0, 0.14), 0 2px 2px 0 rgba(0, 0, 0, 0.12), 0 3px 1px -2px rgba(0, 0, 0, 0.2); +} + +.rst-content .nbinput .highlight, .rst-content .nboutput .highlight { + width: 100%; +} + +.rst-content .nbinput:not(.nblast) > .input_area { + border-radius: 4px 0 0 0 !important; +} + +.rst-content .nbinput.nblast > .input_area { + border-radius: 4px 0 0 4px !important; +} + +.rst-content .nbinput > .input_area { + border-left: medium #808080 solid !important; +} + +.rst-content .nbinput > .input_area pre { + padding: 1.25rem 1.5rem !important; +} + +.rst-content .nboutput.nblast > .output_area { + border-radius: 0 0 0 4px !important; +} + +.rst-content .nboutput > .stderr.output_area { + border-left: medium #b5b5b5 solid !important; + background: #fee !important; +} + +.rst-content .nboutput > :not(.stderr).output_area { + border-left: medium #b5b5b5 solid !important; + background: #FFFFFF !important; +} + +.rst-content .cell.container { + box-shadow: 0 2px 2px 0 rgba(0, 0, 0, 0.14), 0 1px 5px 0 rgba(0, 0, 0, 0.12), 0 3px 1px -2px rgba(0, 0, 0, 0.2); + border-radius: 4px 2px 2px 4px; +} + +.rst-content .cell.container > .cell_input { + border: none; + border-left: 4px green solid; +} + +.rst-content .cell.container > .cell_input:last-child { + border-radius: 4px 0 0 4px; +} + +.rst-content .cell.container > .cell_input:not(:last-child) { + border-radius: 4px 0 0 0; +} + +.rst-content .cell.container .highlight { + border: None; + border-radius: 0; + box-shadow: None; +} + +.rst-content .cell.container > .cell_output { + box-shadow: 0 2px 2px 0 rgba(0, 0, 0, 0.14), 0 1px 5px 0 rgba(0, 0, 0, 0.12), 0 3px 1px -2px rgba(0, 0, 0, 0.2); + border-left: 4px gray solid; + margin-top: -1em; + padding-left: 0; +} + +.rst-content .cell.container > .cell_output:last-child { + border-radius: 0 0 0 4px; +} + +.rst-content .cell.container > .cell_output > .output, .rst-content .cell.container > .cell_output > img { + margin-top: 0; +} + +.rst-content .cell.container > .cell_output > .output.stderr, .rst-content .cell.container > .cell_output > img.stderr { + background: #fee; +} + +.rst-content .cell.container > .cell_output > .output.stderr .highlight, .rst-content .cell.container > .cell_output > .output.stderr pre, .rst-content .cell.container > .cell_output > img.stderr .highlight, .rst-content .cell.container > .cell_output > img.stderr pre { + background: None; 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+} + +.rst-content .admonition-title::before, .rst-content .versionmodified.deprecated::before { + position: absolute; + left: 0.75rem; + width: 1.25rem; + height: 1.25rem; + font-family: "FontAwesome"; + content: "\f12a"; +} + +[dir="rtl"] .rst-content .admonition-title::before, [dir="rtl"] .rst-content .versionmodified.deprecated::before { + right: 0.75rem; + left: initial; +} + +.rst-content .admonition-title + .tabbed-set:last-child, .rst-content .versionmodified.deprecated + .tabbed-set:last-child { + margin-top: 0; +} + +@media screen and (max-width: 768px) { + .rst-content { + width: 96vw; + margin-left: 2vw; + margin-right: 2vw; + } +} + +@media screen and (min-width: 769px) and (max-width: 1023px) { + .rst-content { + margin-left: 2vw; + } +} + +@media screen and (min-width: 1024px) { + .rst-content { + max-width: 42.5rem; + margin: auto; + } +} + +header, .navbar.is-primary.has-shadow { + box-shadow: 0 2px 3px 0 #FF9200; +} + +.navbar.is-fixed-bottom, .navbar.is-fixed-top { + height: 4rem; +} + +.navbar.is-fixed-bottom .navbar-item img, .navbar.is-fixed-top .navbar-item img { + max-height: 3rem; +} + +.burger.is-light { + color: whitesmoke; +} + +@media screen and (max-width: 768px) { + .burger { + position: fixed; + top: 0; + left: 90vw; + z-index: 10; + width: 10vw; + } + .burger span:nth-child(4) { + opacity: 0%; + transition: opacity 0.5s; + background-color: black; + position: fixed; + left: 0; + top: 0; + width: 100vw; + height: 100vh; + z-index: 11; + pointer-events: none; + } + #drawer-toggle:checked { + /* show navbar-menu on phones and tablets */ + /* make navbar-burger become cross on screen less than 1024px */ + } + #drawer-toggle:checked ~ #drawer { + transform: translate(20rem, 0); + } + #drawer-toggle:checked + .burger span:nth-child(1) { + transform: translateY(5px) rotate(45deg); + } + #drawer-toggle:checked + .burger span:nth-child(2) { + opacity: 0; + } + #drawer-toggle:checked + .burger span:nth-child(3) { + transform: translateY(-5px) rotate(-45deg); + } + #drawer-toggle:checked + .burger span:nth-child(4) { + opacity: 50%; + pointer-events: auto; + } + #drawer { + left: -20rem; + transition: transform 0.5s; + width: 20rem; + max-width: 90vw; + top: 0; + height: 100vh; + background-color: #FFFFFF; + position: fixed; + display: block; + z-index: 12; + } + #drawer .ff-globaltoc { + position: unset; + } + header { + overflow-wrap: break-word; + } +} + +.has-text-light .breadcrumb a { + color: #fff; +} + +.has-text-light .breadcrumb a code { + color: #fff; + background-color: transparent; +} + +.has-text-light .breadcrumb a:hover { + color: #ffb264; +} + +.has-text-light .breadcrumb li.is-active a { + color: #ffb264; +} + +.has-text-light .breadcrumb li + li::before { + color: #fff; +} + +.clip-siblings { + background: #FFFFFF; + position: relative; +} + +.ff-localtoc, .ff-globaltoc { + position: sticky; + padding: 0.5rem; + overflow-y: auto; + top: 0; + padding-top: 4.5rem; + margin-top: -4rem; + max-height: 100vh; + -ms-overflow-style: none; + scrollbar-width: none; +} + +@media screen and (max-width: 769px) { + .ff-localtoc, .ff-globaltoc { + position: fixed; + top: 4rem; + } +} + +.ff-localtoc::-webkit-scrollbar, .ff-globaltoc::-webkit-scrollbar { + display: none; +} + +.menu { + overflow-wrap: break-word; +} + +.menu code { + background-color: transparent; + color: unset; +} + +body { + min-height: 100vh; + display: flex; + flex-direction: column; + font-family: 'PT Sans', Helvetica, Arial, 'sans-serif'; +} + +header { + z-index: 1; + background-color: #FF9200; +} + +header .nav-title { + padding-left: 0.5rem; + align-items: center; + display: inline-flex; +} + +header .navbar.is-primary .navbar-brand > a.navbar-item:hover { + background-color: #e68300; +} + +header .nav-tabs a { + color: white; + padding-top: 0.5rem; + padding-bottom: 0.5rem; +} + +header .nav-tabs a:hover { + color: #ca6500; +} + +header .is-hidden-tablet.nav-title { + max-width: 90vw; +} + +header .navbar > .navbar-end { + flex: none; + margin-left: auto; + margin-top: auto; + margin-bottom: auto; +} + +header .nav-search input { + transition: width 0.2s, background-color 0.2s; +} + +@media screen and (max-width: 1215px) { + header .nav-search .control { + position: relative; + height: 2.5em; + } + header .nav-search .control input { + background-color: unset; + width: 2.5em; + position: absolute; + right: 0; + } + header .nav-search .control input:hover, header .nav-search .control input:focus, header .nav-search .control input:active { + width: 15rem; + max-width: 15rem; + } + header .nav-search .control input:hover { + background-color: #cc7500; + color: white; + } + header .nav-search .control input:hover::placeholder { + color: #dbdbdb; + } + header .nav-search .control input:focus, header .nav-search .control input:active { + background-color: white; + color: #cc7500; + } + header .nav-search .control input:focus::placeholder, header .nav-search .control input:active::placeholder { + color: rgba(54, 54, 54, 0.3); + } + header .nav-search .control.has-icons-right { + padding-right: 0; + } + header .nav-search .control.has-icons-left { + padding-left: 0; + } +} + +@media screen and (min-width: 1216px) { + header .nav-search input { + background-color: #cc7500; + color: white; + } + header .nav-search input::placeholder { + color: #dbdbdb; + } + header .nav-search input:hover, header .nav-search input:focus, header .nav-search input:active { + background-color: white; + color: #cc7500; + } + header .nav-search input:hover::placeholder, header .nav-search input:focus::placeholder, header .nav-search input:active::placeholder { + color: rgba(54, 54, 54, 0.3); + } +} + +main { + padding-top: 1rem; +} + +footer { + margin-top: auto; + overflow-wrap: break-word; +} + +footer nav { + margin-bottom: 3rem !important; +} + +footer .fineprint { + font-size: 0.8em; + font-weight: 100; +} + +footer .fineprint a { + color: rgba(0, 0, 0, 0.7); + font-weight: 500; +} + +footer .fineprint a:hover { + color: #ca6500; +} + +footer .fineprint .copyright { + font-weight: 400; + margin-bottom: 1rem; +} + +footer .footer-content { + max-width: 1408px; + margin-left: auto; + margin-right: auto; +} + +@media screen and (min-width: 769px) { + footer .socials { + margin-top: auto; + text-align: right; + } +} + +footer .socials .icon { + border: solid 1px; + border-radius: 50%; +} + +.ff-localtoc a { + color: rgba(0, 0, 0, 0.87); + display: block; +} + +.ff-localtoc a:hover { + color: #ca6500; +} + +.ff-localtoc > ul { + padding-left: 0.5rem; +} + +.ff-localtoc > ul ul { + padding-top: 0.2rem; + padding-left: 1rem; + font-size: 0.9em; +} + +.ff-localtoc > ul li { + padding-bottom: 0.2rem; +} + +.ff-localtoc > ul li:last-child { + padding-bottom: 0; +} + +@media screen and (min-width: 1407px) { + main { + max-width: 1508px; + width: 100%; + margin-left: auto; + margin-right: auto; + } +} + +@media screen and (max-width: 1408px) { + .menu-list li ul { + padding-left: 0; + } +} + +a:hover:not(.is-active) code, a:hover:not(.is-active) pre { + color: #ca6500; +} + +.navbar-burger-spacer { + width: 4rem; + display: inline-block; +} + +main > .columns { + max-width: 100vw; +} + +.wy-nav-content-wrap { + background: #fcfcfc; +} + +.wy-nav-top { + background: #343131; +} + +.wy-side-nav-search { + background-color: white; +} + +.wy-side-nav-search > a { + color: #343131; +} + +.wy-side-nav-search > div.version { + color: #808080; +} + +.wy-side-nav-search input[type="text"] { + border-color: #808080; +} + +.wy-menu { + overflow-wrap: break-word; + white-space: inherit; +} + +.wy-menu .caption-text { + color: #FF9200; +} + +.wy-menu a:hover, .wy-menu a:hover:not(.is-active) code { + color: #FF9200; +} + +code { + white-space: inherit; +} + +.rst-content .guilabel { + background: #FFEBD0; + border: 1px solid #808080; +} + +.rst-content code.literal { + color: #ca6500; + background-color: #FFFFFF; +} + +.rst-content dt code.literal { + font-weight: 700; +} + +.wy-table-responsive table td { + white-space: inherit; +} + +.dataTables_wrapper.no-footer .wy-table-responsive { + overflow: unset; +} + +div[role=navigation] > .wy-breadcrumbs { + margin: 0; +} + +div[role=navigation] > .wy-breadcrumbs .breadcrumb-item { + margin-top: 0; + margin-bottom: 0; + padding-top: 0; + padding-bottom: 0; +} + diff --git a/_static/sphinx_highlight.js b/_static/sphinx_highlight.js new file mode 100644 index 0000000..aae669d --- /dev/null +++ b/_static/sphinx_highlight.js @@ -0,0 +1,144 @@ +/* Highlighting utilities for Sphinx HTML documentation. */ +"use strict"; + +const SPHINX_HIGHLIGHT_ENABLED = true + +/** + * highlight a given string on a node by wrapping it in + * span elements with the given class name. + */ +const _highlight = (node, addItems, text, className) => { + if (node.nodeType === Node.TEXT_NODE) { + const val = node.nodeValue; + const parent = node.parentNode; + const pos = val.toLowerCase().indexOf(text); + if ( + pos >= 0 && + !parent.classList.contains(className) && + !parent.classList.contains("nohighlight") + ) { + let span; + + const closestNode = parent.closest("body, svg, foreignObject"); + const isInSVG = closestNode && closestNode.matches("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.classList.add(className); + } + + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + parent.insertBefore( + span, + parent.insertBefore( + document.createTextNode(val.substr(pos + text.length)), + node.nextSibling + ) + ); + node.nodeValue = val.substr(0, pos); + + if (isInSVG) { + const rect = document.createElementNS( + "http://www.w3.org/2000/svg", + "rect" + ); + const bbox = parent.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute("class", className); + addItems.push({ parent: parent, target: rect }); + } + } + } else if (node.matches && !node.matches("button, select, textarea")) { + node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); + } +}; +const _highlightText = (thisNode, text, className) => { + let addItems = []; + _highlight(thisNode, addItems, text, className); + addItems.forEach((obj) => + obj.parent.insertAdjacentElement("beforebegin", obj.target) + ); +}; + +/** + * Small JavaScript module for the documentation. + */ +const SphinxHighlight = { + + /** + * highlight the search words provided in localstorage in the text + */ + highlightSearchWords: () => { + if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight + + // get and clear terms from localstorage + const url = new URL(window.location); + const highlight = + localStorage.getItem("sphinx_highlight_terms") + || url.searchParams.get("highlight") + || ""; + localStorage.removeItem("sphinx_highlight_terms") + url.searchParams.delete("highlight"); + window.history.replaceState({}, "", url); + + // get individual terms from highlight string + const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); + if (terms.length === 0) return; // nothing to do + + // There should never be more than one element matching "div.body" + const divBody = document.querySelectorAll("div.body"); + const body = divBody.length ? divBody[0] : document.querySelector("body"); + window.setTimeout(() => { + terms.forEach((term) => _highlightText(body, term, "highlighted")); + }, 10); + + const searchBox = document.getElementById("searchbox"); + if (searchBox === null) return; + searchBox.appendChild( + document + .createRange() + .createContextualFragment( + '

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+ + +
+ +
+
+
+ +
+
+
+
+ +
+

API Documentation

+
+

Calculating path similarity — pathsimanalysis.psa

+
+

New in version 0.10.0.

+
+

The module contains code to calculate the geometric similarity of trajectories +using path metrics such as the Hausdorff or Fréchet distances +[1]. The path metrics are functions of two paths and return a +nonnegative number, i.e., a distance. Two paths are identical if their distance +is zero, and large distances indicate dissimilarity. Each path metric is a +function of the individual points (e.g., coordinate snapshots) that comprise +each path and, loosely speaking, identify the two points, one per path of a +pair of paths, where the paths deviate the most. The distance between these +points of maximal deviation is measured by the root mean square deviation +(RMSD), i.e., to compute structural similarity.

+

One typically computes the pairwise similarity for an ensemble of paths to +produce a symmetric distance matrix, which can be clustered to, at a glance, +identify patterns in the trajectory data. To properly analyze a path ensemble, +one must select a suitable reference structure to which all paths (each +conformer in each path) will be universally aligned using the rotations +determined by the best-fit rmsds. Distances between paths and their structures +are then computed directly with no further alignment. This pre-processing step +is necessary to preserve the metric properties of the Hausdorff and Fréchet +metrics; using the best-fit rmsd on a pairwise basis does not generally +preserve the triangle inequality.

+
+

Note

+

The PSAnalysisTutorial outlines a typical application of PSA to +a set of trajectories, including doing proper alignment, +performing distance comparisons, and generating heat +map-dendrogram plots from hierarchical clustering.

+
+
+

Helper functions and variables

+

The following convenience functions are used by other functions in this module.

+
+
+pathsimanalysis.psa.sqnorm(v, axis=None)[source]
+

Compute the sum of squares of elements along specified axes.

+
+
Parameters:
+
    +

  • v (numpy.ndarray) – coordinates

    • +

  • axes (None / int / tuple (optional)) – Axes or axes along which a sum is performed. The default +(axes = None) performs a sum over all the dimensions of +the input array. The value of axes may be negative, in +which case it counts from the last axis to the zeroth axis.

    • +
+
+
Returns:
+

the sum of the squares of the elements of v along axes

+
+
Return type:
+

float

+
+
+
+ +
+
+pathsimanalysis.psa.get_msd_matrix(P, Q, axis=None)[source]
+

Generate the matrix of pairwise mean-squared deviations between paths.

+

The MSDs between all pairs of points in P and Q are +calculated, each pair having a point from P and a point from +Q.

+

P (Q) is a numpy.ndarray of \(N_p\) (\(N_q\)) time +steps, \(N\) atoms, and \(3N\) coordinates (e.g., +MDAnalysis.core.groups.AtomGroup.positions). The pairwise MSD +matrix has dimensions \(N_p\) by \(N_q\).

+
+
Parameters:
+
    +

  • P (numpy.ndarray) – the points in the first path

    • +

  • Q (numpy.ndarray) – the points in the second path

    • +
+
+
Returns:
+

msd_matrix – matrix of pairwise MSDs between points in P and points +in Q

+
+
Return type:
+

numpy.ndarray

+
+
+

Notes

+

We calculate the MSD matrix

+
+\[M_{ij} = ||p_i - q_j||^2\]
+

where \(p_i \in P\) and \(q_j \in Q\).

+
+ +
+
+pathsimanalysis.psa.get_coord_axes(path)[source]
+

Return the number of atoms and the axes corresponding to atoms +and coordinates for a given path.

+

The path is assumed to be a numpy.ndarray where the 0th axis +corresponds to a frame (a snapshot of coordinates). The \(3N\) +(Cartesian) coordinates are assumed to be either:

+
    +

  1. all in the 1st axis, starting with the x,y,z coordinates of the +first atom, followed by the x,*y*,*z* coordinates of the 2nd, etc.

    2. +

  2. in the 1st and 2nd axis, where the 1st axis indexes the atom +number and the 2nd axis contains the x,*y*,*z* coordinates of +each atom.

    3. +
+
+
Parameters:
+

path (numpy.ndarray) – representing a path

+
+
Returns:
+

the number of atoms and the axes containing coordinates

+
+
Return type:
+

(int, (int, …))

+
+
+
+ +
+
+

Classes, methods, and functions

+
+
+pathsimanalysis.psa.get_path_metric_func(name)[source]
+

Selects a path metric function by name.

+
+
Parameters:
+

name (str) – name of path metric

+
+
Returns:
+

path_metric – The path metric function specified by name (if found).

+
+
Return type:
+

function

+
+
+
+ +
+
+pathsimanalysis.psa.hausdorff(P, Q)[source]
+

Calculate the symmetric Hausdorff distance between two paths.

+

The metric used is RMSD, as opposed to the more conventional L2 +(Euclidean) norm, because this is convenient for i.e., comparing +protein configurations.

+

P (Q) is a numpy.ndarray of \(N_p\) (\(N_q\)) time +steps, \(N\) atoms, and \(3N\) coordinates (e.g., +MDAnalysis.core.groups.AtomGroup.positions). P (Q) has +either shape \(N_p \times N \times 3\) (\(N_q \times N \times 3\)), or \(N_p \times (3N)\) (\(N_q \times (3N)\)) in flattened form.

+

Note that reversing the path does not change the Hausdorff distance.

+
+
Parameters:
+
    +

  • P (numpy.ndarray) – the points in the first path

    • +

  • Q (numpy.ndarray) – the points in the second path

    • +
+
+
Returns:
+

the Hausdorff distance between paths P and Q

+
+
Return type:
+

float

+
+
+

Example

+

Calculate the Hausdorff distance between two halves of a trajectory:

+
>>> import MDAnalysis as mda
+>>> import numpy
+>>> from MDAnalysis.tests.datafiles import PSF, DCD
+>>> import pathsimanalysis as psa
+>>> u = mda.Universe(PSF,DCD)
+>>> mid = int(len(u.trajectory)/2)
+>>> ca = u.select_atoms('name CA')
+>>> P = numpy.array([
+...                ca.positions for _ in u.trajectory[:mid:]
+...              ]) # first half of trajectory
+>>> Q = numpy.array([
+...                ca.positions for _ in u.trajectory[mid::]
+...              ]) # second half of trajectory
+>>> psa.hausdorff(P,Q)
+4.778663899862152
+>>> psa.hausdorff(P,Q[::-1]) # hausdorff distance w/ reversed 2nd trajectory
+4.778663899862152
+
+
+

Notes

+

scipy.spatial.distance.directed_hausdorff() is an optimized +implementation of the early break algorithm of [2]; the +latter code is used here to calculate the symmetric Hausdorff +distance with an RMSD metric

+
+ +
+
+pathsimanalysis.psa.hausdorff_wavg(P, Q)[source]
+

Calculate the weighted average Hausdorff distance between two paths.

+

P (Q) is a numpy.ndarray of \(N_p\) (\(N_q\)) time +steps, \(N\) atoms, and \(3N\) coordinates (e.g., +MDAnalysis.core.groups.AtomGroup.positions). P (Q) has +either shape \(N_p \times N \times 3\) (\(N_q \times N \times 3\)), or \(N_p \times (3N)\) (\(N_q \times (3N)\)) in flattened form. The nearest +neighbor distances for P (to Q) and those of Q (to P) are averaged +individually to get the average nearest neighbor distance for P and +likewise for Q. These averages are then summed and divided by 2 to get a +measure that gives equal weight to P and Q.

+
+
Parameters:
+
    +

  • P (numpy.ndarray) – the points in the first path

    • +

  • Q (numpy.ndarray) – the points in the second path

    • +
+
+
Returns:
+

the weighted average Hausdorff distance between paths P and Q

+
+
Return type:
+

float

+
+
+

Example

+
>>> import MDAnalysis as mda
+>>> from MDAnalysis import Universe
+>>> from MDAnalysis.tests.datafiles import PSF, DCD
+>>> import pathsimanalysis as psa
+>>> u = mda.Universe(PSF,DCD)
+>>> mid = int(len(u.trajectory)/2)
+>>> ca = u.select_atoms('name CA')
+>>> P = numpy.array([
+...                ca.positions for _ in u.trajectory[:mid:]
+...              ]) # first half of trajectory
+>>> Q = numpy.array([
+...                ca.positions for _ in u.trajectory[mid::]
+...              ]) # second half of trajectory
+>>> psa.hausdorff_wavg(P,Q)
+2.5669644353703447
+>>> psa.hausdorff_wavg(P,Q[::-1]) # weighted avg hausdorff dist w/ Q reversed
+2.5669644353703447
+
+
+

Notes

+

The weighted average Hausdorff distance is not a true metric (it does not +obey the triangle inequality); see [1] for further +details.

+
+ +
+
+pathsimanalysis.psa.hausdorff_avg(P, Q)[source]
+

Calculate the average Hausdorff distance between two paths.

+

P (Q) is a numpy.ndarray of \(N_p\) (\(N_q\)) time +steps, \(N\) atoms, and \(3N\) coordinates (e.g., +MDAnalysis.core.groups.AtomGroup.positions). P (Q) has +either shape \(N_p \times N \times 3\) (\(N_q \times N \times 3\)), or \(N_p \times (3N)\) (\(N_q \times (3N)\)) in flattened form. The nearest +neighbor distances for P (to Q) and those of Q (to P) are all +averaged together to get a mean nearest neighbor distance. This measure +biases the average toward the path that has more snapshots, whereas weighted +average Hausdorff gives equal weight to both paths.

+
+
Parameters:
+
    +

  • P (numpy.ndarray) – the points in the first path

    • +

  • Q (numpy.ndarray) – the points in the second path

    • +
+
+
Returns:
+

the average Hausdorff distance between paths P and Q

+
+
Return type:
+

float

+
+
+

Example

+
>>> import MDAnalysis as mda
+>>> from MDAnalysis.tests.datafiles import PSF, DCD
+>>> import pathsimanalysis as psa
+>>> u = mda.Universe(PSF,DCD)
+>>> mid = int(len(u.trajectory)/2)
+>>> ca = u.select_atoms('name CA')
+>>> P = numpy.array([
+...                ca.positions for _ in u.trajectory[:mid:]
+...              ]) # first half of trajectory
+>>> Q = numpy.array([
+...                ca.positions for _ in u.trajectory[mid::]
+...              ]) # second half of trajectory
+>>> psa.hausdorff_avg(P,Q)
+2.5669646575869005
+>>> psa.hausdorff_avg(P,Q[::-1]) # hausdorff distance w/ reversed 2nd trajectory
+2.5669646575869005
+
+
+

Notes

+

The average Hausdorff distance is not a true metric (it does not obey the +triangle inequality); see [1] for further details.

+
+ +
+
+pathsimanalysis.psa.hausdorff_neighbors(P, Q)[source]
+

Find the Hausdorff neighbors of two paths.

+

P (Q) is a numpy.ndarray of \(N_p\) (\(N_q\)) time +steps, \(N\) atoms, and \(3N\) coordinates (e.g., +MDAnalysis.core.groups.AtomGroup.positions). P (Q) has +either shape \(N_p \times N \times 3\) (\(N_q \times N \times 3\)), or \(N_p \times (3N)\) (\(N_q \times (3N)\)) in flattened form.

+
+
Parameters:
+
    +

  • P (numpy.ndarray) – the points in the first path

    • +

  • Q (numpy.ndarray) – the points in the second path

    • +
+
+
Returns:
+

dictionary of two pairs of numpy arrays, the first pair (key +“frames”) containing the indices of (Hausdorff) nearest +neighbors for P and Q, respectively, the second (key +“distances”) containing (corresponding) nearest neighbor +distances for P and Q, respectively

+
+
Return type:
+

dict

+
+
+

Notes

+
    +

  • Hausdorff neighbors are those points on the two paths that are separated by +the Hausdorff distance. They are the farthest nearest neighbors and are +maximally different in the sense of the Hausdorff distance +[1].

    • +

  • scipy.spatial.distance.directed_hausdorff() can also provide the +hausdorff neighbors.

    • +
+
+ +
+
+pathsimanalysis.psa.discrete_frechet(P, Q)[source]
+

Calculate the discrete Fréchet distance between two paths.

+

P (Q) is a numpy.ndarray of \(N_p\) (\(N_q\)) time +steps, \(N\) atoms, and \(3N\) coordinates (e.g., +MDAnalysis.core.groups.AtomGroup.positions). P (Q) has +either shape \(N_p \times N \times 3\) (\(N_q \times N \times 3\)), or :\(N_p \times (3N)\) (\(N_q \times (3N)\)) in flattened form.

+
+
Parameters:
+
    +

  • P (numpy.ndarray) – the points in the first path

    • +

  • Q (numpy.ndarray) – the points in the second path

    • +
+
+
Returns:
+

the discrete Fréchet distance between paths P and Q

+
+
Return type:
+

float

+
+
+

Example

+

Calculate the discrete Fréchet distance between two halves of a +trajectory.

+
>>> import MDAnalysis as mda
+>>> import numpy as np
+>>> from MDAnalysis.tests.datafiles import PSF, DCD
+>>> import pathsimanalysis as psa
+>>> u = mda.Universe(PSF,DCD)
+>>> mid = int(len(u.trajectory)/2)
+>>> ca = u.select_atoms('name CA')
+>>> P = np.array([
+...                ca.positions for _ in u.trajectory[:mid:]
+...              ]) # first half of trajectory
+>>> Q = np.array([
+...                ca.positions for _ in u.trajectory[mid::]
+...              ]) # second half of trajectory
+>>> psa.discrete_frechet(P,Q)
+4.778663984013591
+>>> psa.discrete_frechet(P,Q[::-1]) # frechet distance w/ 2nd trj reversed 2nd
+6.842901117711383
+
+
+

Note that reversing the direction increased the Fréchet distance: +it is sensitive to the direction of the path.

+

Notes

+

The discrete Fréchet metric is an approximation to the continuous Fréchet +metric [3][4]. The calculation of the continuous +Fréchet distance is implemented with the dynamic programming algorithm of +[5][6].

+
+ +
+
+pathsimanalysis.psa.dist_mat_to_vec(N, i, j)[source]
+

Convert distance matrix indices (in the upper triangle) to the index of +the corresponding distance vector.

+

This is a convenience function to locate distance matrix elements (and the +pair generating it) in the corresponding distance vector. The row index j +should be greater than i+1, corresponding to the upper triangle of the +distance matrix.

+
+
Parameters:
+
    +

  • N (int) – size of the distance matrix (of shape N-by-N)

    • +

  • i (int) – row index (starting at 0) of the distance matrix

    • +

  • j (int) – column index (starting at 0) of the distance matrix

    • +
+
+
Returns:
+

index (of the matrix element) in the corresponding distance vector

+
+
Return type:
+

int

+
+
+
+ +
+
+class pathsimanalysis.psa.Path(universe, reference, select='name CA', path_select='all', ref_frame=0)[source]
+

Represent a path based on a Universe.

+

Pre-process a Universe object: (1) fit the trajectory to a +reference structure, (2) convert fitted time series to a +numpy.ndarray representation of Path.path.

+

The analysis is performed with PSAnalysis.run() and stores the result +in the numpy.ndarray distance matrix PSAnalysis.D. +PSAnalysis.run() also generates a fitted trajectory and path from +alignment of the original trajectories to a reference structure.

+
+

New in version 0.9.1.

+
+
+
+u_original
+

Universe object with a trajectory

+
+ +
+
+u_reference
+

Universe object containing a reference structure

+
+ +
+
+select
+

string, selection for +select_atoms() to select frame +from Path.u_reference

+
+ +
+
+path_select
+

string, selection for +select_atoms() to select atoms +to compose Path.path

+
+ +
+
+ref_frame
+

int, frame index to select frame from Path.u_reference

+
+ +
+
+u_fitted
+

Universe object with the fitted trajectory

+
+ +
+
+path
+

numpy.ndarray object representation of the fitted trajectory

+
+ +
+
+fit_to_reference(filename=None, prefix='', postfix='_fit', rmsdfile=None, targetdir='.', weights=None, tol_mass=0.1)[source]
+

Align each trajectory frame to the reference structure

+
+
Parameters:
+
    +

  • filename (str (optional)) – file name for the RMS-fitted trajectory or pdb; defaults to the +original trajectory filename (from Path.u_original) with +prefix prepended

    • +

  • prefix (str (optional)) – prefix for auto-generating the new output filename

    • +

  • rmsdfile (str (optional)) – file name for writing the RMSD time series [None]

    • +

  • weights ({“mass”, None} or array_like (optional)) – choose weights. With "mass" uses masses as weights; with +None weigh each atom equally. If a float array of the same +length as the selected AtomGroup is provided, use each element of +the array_like as a weight for the corresponding atom in the +AtomGroup.

    • +

  • tol_mass (float (optional)) – Reject match if the atomic masses for matched atoms differ by more +than tol_mass [0.1]

    • +
+
+
Returns:
+

MDAnalysis.Universe object containing a fitted trajectory

+
+
Return type:
+

Universe

+
+
+

Notes

+

Uses MDAnalysis.analysis.align.AlignTraj for the fitting.

+
+

Deprecated since version 0.16.1: Instead of mass_weighted=True use new weights='mass'; +refactored to fit with AnalysisBase API

+
+
+

Changed in version 0.17.0: Deprecated keyword mass_weighted was removed.

+
+
+ +
+
+get_num_atoms()[source]
+

Return the number of atoms used to construct the Path.

+

Must run Path.to_path() prior to calling this method.

+
+
Returns:
+

the number of atoms in the Path

+
+
Return type:
+

int

+
+
+
+ +
+
+run(align=False, filename=None, postfix='_fit', rmsdfile=None, targetdir='.', weights=None, tol_mass=0.1, flat=False)[source]
+

Generate a path from a trajectory and reference structure.

+

As part of the path generation, the trajectory can be superimposed +(“aligned”) to a reference structure if specified.

+

This is a convenience method to generate a fitted trajectory from an +inputted universe (Path.u_original) and reference structure +(Path.u_reference). Path.fit_to_reference() and +Path.to_path() are used consecutively to generate a new universe +(Path.u_fitted) containing the fitted trajectory along with the +corresponding Path.path represented as an +numpy.ndarray. The method returns a tuple of the topology name +and new trajectory name, which can be fed directly into an +MDAnalysis.Universe object after unpacking the tuple using the +* operator, as in +MDAnalysis.Universe(*(top_name, newtraj_name)).

+
+
Parameters:
+
    +

  • align (bool (optional)) – Align trajectory to atom selection Path.select of +Path.u_reference. If True, a universe containing an +aligned trajectory is produced with Path.fit_to_reference() +[False]

    • +

  • filename (str (optional)) – filename for the RMS-fitted trajectory or pdb; defaults to the +original trajectory filename (from Path.u_original) with +prefix prepended

    • +

  • postfix (str (optional)) – prefix for auto-generating the new output filename

    • +

  • rmsdfile (str (optional)) – file name for writing the RMSD time series [None]

    • +

  • weights ({“mass”, None} or array_like (optional)) – choose weights. With "mass" uses masses as weights; with +None weigh each atom equally. If a float array of the same +length as the selected AtomGroup is provided, use each element of +the array_like as a weight for the corresponding atom in the +AtomGroup.

    • +

  • tol_mass (float (optional)) – Reject match if the atomic masses for matched atoms differ by more +than tol_mass [0.1]

    • +

  • flat (bool (optional)) – represent Path.path with 2D (\(N_p\times 3N\)) numpy.ndarray; +if False then Path.path is a 3D (\(N_p\times N\times 3\)) +numpy.ndarray [False]

    • +
+
+
Returns:
+

topology_trajectory – A tuple of the topology name and new trajectory name.

+
+
Return type:
+

tuple

+
+
+
+

Deprecated since version 0.16.1: Instead of mass_weighted=True use new weights='mass'; +refactored to fit with AnalysisBase API

+
+
+

Changed in version 0.17.0: Deprecated keyword mass_weighted was removed.

+
+
+ +
+
+to_path(fitted=False, select=None, flat=False)[source]
+

Generates a coordinate time series from the fitted universe +trajectory.

+

Given a selection of N atoms from select, the atomic positions for +each frame in the fitted universe (Path.u_fitted) trajectory +(with \(N_p\) total frames) are appended sequentially to form a 3D or 2D +(if flat is True) numpy.ndarray representation of the +fitted trajectory (with dimensions \(N_p\times N\times 3\) or \(N_p\times 3N\), respectively).

+
+
Parameters:
+
    +

  • fitted (bool (optional)) – construct a Path.path from the Path.u_fitted +trajectory; if False then Path.path is generated with +the trajectory from Path.u_original [False]

    • +

  • select (str (optional)) – the selection for constructing the coordinates of each frame in +Path.path; if None then Path.path_select +is used, else it is overridden by select [None]

    • +

  • flat (bool (optional)) – represent Path.path as a 2D (\(N_p\times 3N\)) numpy.ndarray; +if False then Path.path is a 3D (\(N_p\times N\times 3\)) +numpy.ndarray [False]

    • +
+
+
Returns:
+

representing a time series of atomic positions of an +MDAnalysis.core.groups.AtomGroup selection from +Path.u_fitted.trajectory

+
+
Return type:
+

numpy.ndarray

+
+
+
+ +
+ +
+
+class pathsimanalysis.psa.PSAPair(npaths, i, j)[source]
+

Generate nearest neighbor and Hausdorff pair information between a pair +of paths from an all-pairs comparison generated by PSA.

+

The nearest neighbors for each path of a pair of paths is generated by +PSAPair.compute_nearest_neighbors() and stores the result +in a dictionary (nearest_neighbors): each path has a +numpy.ndarray of the frames of its nearest neighbors, and a +numpy.ndarray of its nearest neighbor distances +PSAnalysis.D. For example, nearest_neighbors[‘frames’] is a pair +of numpy.ndarray, the first being the frames of the nearest +neighbors of the first path, i, the second being those of the second path, +j.

+

The Hausdorff pair for the pair of paths is found by calling +find_hausdorff_pair() (locates the nearest neighbor pair having the +largest overall distance separating them), which stores the result in a +dictionary (hausdorff_pair) containing the frames (indices) of the +pair along with the corresponding (Hausdorff) distance. +hausdorff_pair[‘frame’] contains a pair of frames in the first path, i, +and the second path, j, respectively, that correspond to the Hausdorff +distance between them.

+
+

New in version 0.11.

+
+
+
+npaths
+

int, total number of paths in the comparison in which this +PSAPair was generated

+
+ +
+
+matrix_id
+

(int, int), (row, column) indices of the location of this +PSAPair in the corresponding pairwise distance matrix

+
+ +
+
+pair_id
+

int, ID of this PSAPair (the pair_id:math:^text{th} +comparison) in the distance vector corresponding to the pairwise distance +matrix

+
+ +
+
+nearest_neighbors
+

dict, contains the nearest neighbors by frame index and the +nearest neighbor distances for each path in this PSAPair

+
+ +
+
+hausdorff_pair
+

dict, contains the frame indices of the Hausdorff pair for each path in +this PSAPair and the corresponding (Hausdorff) distance

+
+ +
+ +
+
+class pathsimanalysis.psa.PSAnalysis(universes, reference=None, select='name CA', ref_frame=0, path_select=None, labels=None, targetdir='.')[source]
+

Perform Path Similarity Analysis (PSA) on a set of trajectories.

+

The analysis is performed with PSAnalysis.run() and stores the result +in the numpy.ndarray distance matrix PSAnalysis.D. +PSAnalysis.run() also generates a fitted trajectory and path from +alignment of the original trajectories to a reference structure.

+
+

New in version 0.8.

+
+
+

Changed in version 1.0.0: save_result() method has been removed. You can use np.save() on +PSAnalysis.D instead.

+
+
+
+universes
+

list of MDAnalysis.Universe objects containing trajectories

+
+ +
+
+u_reference
+

MDAnalysis.Universe object containing a reference structure

+
+ +
+
+select
+

string, selection for +select_atoms() to select frame +from PSAnalysis.u_reference

+
+ +
+
+path_select
+

string, selection for +select_atoms() to select atoms +to compose Path.path

+
+ +
+
+ref_frame
+

int, frame index to select frame from Path.u_reference

+
+ +
+
+paths
+

list of numpy.ndarray objects representing the set/ensemble of +fitted trajectories

+
+ +
+
+D
+

numpy.ndarray which stores the calculated distance matrix

+
+ +
+
+cluster(dist_mat=None, method='ward', count_sort=False, distance_sort=False, no_plot=False, no_labels=True, color_threshold=4)[source]
+

Cluster trajectories and optionally plot the dendrogram.

+

This method is used by PSAnalysis.plot() to generate a heatmap- +dendrogram combination plot. By default, the distance matrix, +PSAnalysis.D, is assumed to exist, converted to +distance-vector form, and inputted to cluster.hierarchy.linkage() +to generate a clustering. For convenience in plotting arbitrary +distance matrices, one can also be specify dist_mat, which will be +checked for proper distance matrix form by +spatial.distance.squareform()

+
+
Parameters:
+
    +

  • dist_mat (numpy.ndarray) – user-specified distance matrix to be clustered [None]

    • +

  • method (str) – name of linkage criterion for clustering ['ward']

    • +

  • no_plot (bool) – if True, do not render the dendrogram [False]

    • +

  • no_labels (bool) – if True then do not label dendrogram [True]

    • +

  • color_threshold (float) – For brevity, let t be the color_threshold. Colors all the +descendent links below a cluster node k the same color if k is +the first node below the cut threshold t. All links connecting +nodes with distances greater than or equal to the threshold are +colored blue. If t is less than or equal to zero, all nodes are +colored blue. If color_threshold is None or ‘default’, +corresponding with MATLAB(TM) behavior, the threshold is set to +0.7*max(Z[:,2]). [4]]

    • +
+
+
Returns:
+

    +

  • Z – output from scipy.cluster.hierarchy.linkage(); +list of indices representing the row-wise order of the objects +after clustering

    • +

  • dgram – output from scipy.cluster.hierarchy.dendrogram()

    • +
+

+
+
+
+ +
+
+generate_paths(align=False, filename=None, infix='', weights=None, tol_mass=False, ref_frame=None, flat=False, save=True, store=False)[source]
+

Generate paths, aligning each to reference structure if necessary.

+
+
Parameters:
+
    +

  • align (bool) – Align trajectories to atom selection PSAnalysis.select +of PSAnalysis.u_reference [False]

    • +

  • filename (str) – strings representing base filename for fitted trajectories and +paths [None]

    • +

  • infix (str) – additional tag string that is inserted into the output filename of +the fitted trajectory files [‘’]

    • +

  • weights ({“mass”, None} or array_like (optional)) – choose weights. With "mass" uses masses as weights; with +None weigh each atom equally. If a float array of the same +length as the selected AtomGroup is provided, use each element of +the array_like as a weight for the corresponding atom in the +AtomGroup [None]

    • +

  • tol_mass (float) – Reject match if the atomic masses for matched atoms differ by more +than tol_mass [False]

    • +

  • ref_frame (int) – frame index to select frame from reference [None]

    • +

  • flat (bool) – represent Path.path as a 2D (\(N_p\times 3N\)) numpy.ndarray; +if False then Path.path is a 3D (\(N_p\times N\times 3\)) +numpy.ndarray [False]

    • +

  • save (bool) – if True, pickle list of names for fitted trajectories +[True]

    • +

  • store (bool) – if True then writes each path (numpy.ndarray) +in PSAnalysis.paths to compressed npz (numpy) files +[False]

    • +
+
+
+

The fitted trajectories are written to new files in the +“/trj_fit” subdirectory in PSAnalysis.targetdir named +“filename(trajectory)XXX*infix*_psa”, where “XXX” is a number between +000 and 999; the extension of each file is the same as its original. +Optionally, the trajectories can also be saved in numpy compressed npz +format in the “/paths” subdirectory in PSAnalysis.targetdir for +persistence and can be accessed as the attribute +PSAnalysis.paths.

+
+

Deprecated since version 0.16.1: Instead of mass_weighted=True use new weights='mass'; +refactored to fit with AnalysisBase API

+
+
+

Changed in version 0.17.0: Deprecated keyword mass_weighted was removed.

+
+
+

Changed in version 1.0.0: Defaults for the store and filename keywords have been changed +from True and fitted to False and None respectively. These +now match the docstring documented defaults.

+
+
+ +
+
+get_num_atoms()[source]
+

Return the number of atoms used to construct the Path instances in +PSA.

+
+
Returns:
+

the number of atoms in any path

+
+
Return type:
+

int

+
+
+
+

Note

+

Must run PSAnalysis.generate_paths() prior to calling this +method.

+
+
+ +
+
+get_num_paths()[source]
+

Return the number of paths in PSA.

+
+

Note

+

Must run PSAnalysis.generate_paths() prior to calling this method.

+
+
+
Returns:
+

the number of paths in PSA

+
+
Return type:
+

int

+
+
+
+ +
+
+get_pairwise_distances(vectorform=False, checks=False)[source]
+

Return the distance matrix (or vector) of pairwise path distances.

+
+

Note

+

Must run PSAnalysis.run() prior to calling this method.

+
+
+
Parameters:
+
    +

  • vectorform (bool) – if True, return the distance vector instead [False]

    • +

  • checks (bool) – if True, check that PSAnalysis.D is a proper distance +matrix [False]

    • +
+
+
Returns:
+

representation of the distance matrix (or vector)

+
+
Return type:
+

numpy.ndarray

+
+
+
+ +
+
+get_paths()[source]
+

Return the paths in PSA.

+
+

Note

+

Must run PSAnalysis.generate_paths() prior to calling this +method.

+
+
+
Returns:
+

list of numpy.ndarray representations of paths in +PSA

+
+
Return type:
+

list

+
+
+
+ +
+
+property hausdorff_pairs
+

The Hausdorff pair for each (unique) pairs of paths.

+

This attribute contains a list of Hausdorff pair information (in +distance vector order), where each element is a dictionary containing +the pair of frames and the (Hausdorff) distance between a pair of +paths. See PSAnalysis.psa_pairs() and +PSAPair.hausdorff_pair for more information about accessing +Hausdorff pair data.

+
+

Note

+

Must run PSAnalysis.run_pairs_analysis() with +hausdorff_pairs=True prior to calling this method.

+
+
+ +
+
+load()[source]
+

Load fitted paths specified by ‘psa_path-names.pkl’ in +PSAnalysis.targetdir.

+

All filenames are determined by PSAnalysis.

+
+

See also

+

save_paths

+
+
+ +
+
+property nearest_neighbors
+

The nearest neighbors for each (unique) pair of paths.

+

This attribute contains a list of nearest neighbor information (in +distance vector order), where each element is a dictionary containing +the nearest neighbor frames and distances between a pair of paths. See +PSAnalysis.psa_pairs() and PSAPair.nearest_neighbors for +more information about accessing nearest neighbor data.

+
+

Note

+

Must run PSAnalysis.run_pairs_analysis() with +neighbors=True prior to calling this method.

+
+
+ +
+
+plot(filename=None, linkage='ward', count_sort=False, distance_sort=False, figsize=4.5, labelsize=12)[source]
+

Plot a clustered distance matrix.

+

Usese method linkage and plots the corresponding dendrogram. Rows +(and columns) are identified using the list of strings specified by +PSAnalysis.labels.

+

If filename is supplied then the figure is also written to file (the +suffix determines the file type, e.g. pdf, png, eps, …). All other +keyword arguments are passed on to matplotlib.pyplot.matshow().

+
+
Parameters:
+
    +

  • filename (str) – save figure to filename [None]

    • +

  • linkage (str) – name of linkage criterion for clustering ['ward']

    • +

  • count_sort (bool) – see scipy.cluster.hierarchy.dendrogram() [False]

    • +

  • distance_sort (bool) – see scipy.cluster.hierarchy.dendrogram() [False]

    • +

  • figsize (float) – set the vertical size of plot in inches [4.5]

    • +

  • labelsize (float) – set the font size for colorbar labels; font size for path labels on +dendrogram default to 3 points smaller [12]

    • +
+
+
Returns:
+

    +

  • Z – Z from cluster()

    • +

  • dgram – dgram from cluster()

    • +

  • dist_matrix_clus – clustered distance matrix (reordered)

    • +

  • .. versionchanged:: 1.0.0 – tick1On, tick2On, label1On and label2On +changed to tick1line, tick2line, label1 and +label2 due to upstream deprecation (see #2493)

    • +
+

+
+
+
+ +
+
+plot_annotated_heatmap(filename=None, linkage='ward', count_sort=False, distance_sort=False, figsize=8, annot_size=6.5)[source]
+

Plot a clustered distance matrix.

+

Uses method linkage and plots annotated distances in the matrix. Rows +(and columns) are identified using the list of strings specified by +PSAnalysis.labels.

+

If filename is supplied then the figure is also written to file (the +suffix determines the file type, e.g. pdf, png, eps, …). All other +keyword arguments are passed on to matplotlib.pyplot.imshow().

+
+
Parameters:
+
    +

  • filename (str) – save figure to filename [None]

    • +

  • linkage (str) – name of linkage criterion for clustering ['ward']

    • +

  • count_sort (bool) – see scipy.cluster.hierarchy.dendrogram() [False]

    • +

  • distance_sort (bool) – see scipy.cluster.hierarchy.dendrogram() [False]

    • +

  • figsize (float) – set the vertical size of plot in inches [4.5]

    • +

  • annot_size (float) – font size of annotation labels on heat map [6.5]

    • +
+
+
Returns:
+

    +

  • Z – Z from cluster()

    • +

  • dgram – dgram from cluster()

    • +

  • dist_matrix_clus – clustered distance matrix (reordered)

    • +
+

+
+
+
+

Note

+

This function requires the seaborn package, which can be installed +with pip install seaborn or conda install seaborn.

+
+

Changed in version 1.0.0: tick1On, tick2On, label1On and label2On +changed to tick1line, tick2line, label1 and +label2 due to upstream deprecation (see #2493)

+
+
+
+ +
+
+plot_nearest_neighbors(filename=None, idx=0, labels=('Path 1', 'Path 2'), figsize=4.5, multiplot=False, aspect_ratio=1.75, labelsize=12)[source]
+

Plot nearest neighbor distances as a function of normalized frame +number.

+

The frame number is mapped to the interval [0, 1].

+

If filename is supplied then the figure is also written to file (the +suffix determines the file type, e.g. pdf, png, eps, …). All other +keyword arguments are passed on to matplotlib.pyplot.imshow().

+
+
Parameters:
+
    +

  • filename (str) – save figure to filename [None]

    • +

  • idx (int) – index of path (pair) comparison to plot [0]

    • +

  • labels ((str, str)) – pair of names to label nearest neighbor distance +curves [('Path 1', 'Path 2')]

    • +

  • figsize (float) – set the vertical size of plot in inches [4.5]

    • +

  • multiplot (bool) – set to True to enable plotting multiple nearest +neighbor distances on the same figure [False]

    • +

  • aspect_ratio (float) – set the ratio of width to height of the plot [1.75]

    • +

  • labelsize (float) – set the font size for colorbar labels; font size for path labels on +dendrogram default to 3 points smaller [12]

    • +
+
+
Returns:
+

ax

+
+
Return type:
+

axes

+
+
+
+

Note

+

This function requires the seaborn package, which can be installed +with pip install seaborn or conda install seaborn.

+
+
+ +
+
+property psa_pairs
+

The list of PSAPair instances for each pair of paths.

+

psa_pairs is a list of all PSAPair objects (in +distance vector order). The elements of a PSAPair are pairs of +paths that have been compared using +PSAnalysis.run_pairs_analysis(). Each PSAPair contains +nearest neighbor and Hausdorff pair information specific to a pair of +paths. The nearest neighbor frames and distances for a PSAPair +can be accessed in the nearest neighbor dictionary using the keys +‘frames’ and ‘distances’, respectively. E.g., +PSAPair.nearest_neighbors['distances'] returns a pair of +numpy.ndarray corresponding to the nearest neighbor distances +for each path. Similarly, Hausdorff pair information can be accessed +using PSAPair.hausdorff_pair with the keys ‘frames’ and +‘distance’.

+
+

Note

+

Must run PSAnalysis.run_pairs_analysis() prior to calling this +method.

+
+
+ +
+
+run(**kwargs)[source]
+

Perform path similarity analysis on the trajectories to compute +the distance matrix.

+

A number of parameters can be changed from the defaults. The +result is stored as the array PSAnalysis.D.

+
+
Parameters:
+
    +

  • metric (str or callable) – selection string specifying the path metric to measure pairwise +distances among PSAnalysis.paths or a callable with the +same call signature as hausdorff() +['hausdorff']

    • +

  • start (int) – start and stop frame index with step size: analyze +trajectory[start:stop:step] [None]

    • +

  • stop (int)

    • +

  • step (int)

    • +

  • .. versionchanged:: 1.0.0 – store and filename have been removed.

    • +
+
+
+
+ +
+
+run_pairs_analysis(**kwargs)[source]
+

Perform PSA Hausdorff (nearest neighbor) pairs analysis on all unique +pairs of paths in PSAnalysis.paths.

+

Partial results can be stored in separate lists, where each list is +indexed according to distance vector convention (i.e., element (i,j) +in distance matrix representation corresponds to element +\(s=N*i+j-(i+1)*(i+2)\) in distance vector representation, which is +the \(s\)th comparison). For each unique pair of paths, the +nearest neighbors for that pair can be stored in NN and the +Hausdorff pair in HP. PP stores the full information +of Hausdorff pairs analysis that is available for each pair of path, +including nearest neighbors lists and the Hausdorff pairs.

+

The pairwise distances are stored as the array PSAnalysis.D.

+
+
Parameters:
+
    +

  • start (int) – start and stop frame index with step size: analyze +trajectory[start:stop:step] [None]

    • +

  • stop (int)

    • +

  • step (int)

    • +

  • neighbors (bool) – if True, then stores dictionary of nearest neighbor +frames/distances in PSAnalysis.NN [False]

    • +

  • hausdorff_pairs (bool) – if True, then stores dictionary of Hausdorff pair +frames/distances in PSAnalysis.HP [False]

    • +
+
+
+
+ +
+
+save_paths(filename=None)[source]
+

Save fitted PSAnalysis.paths to numpy compressed npz files.

+

The data are saved with numpy.savez_compressed() in the directory +specified by PSAnalysis.targetdir.

+
+
Parameters:
+

filename (str) – specifies filename [None]

+
+
Returns:
+

filename

+
+
Return type:
+

str

+
+
+
+

See also

+

load

+
+
+ +
+ +

References

+
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Getting Started

+

This page details how to get started with PathSimAnalysis.

+
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Installation

+

PathSimAnalysis is currently only installable from source.

+
git clone --depth=1 https://github.com/MDAnalysis/PathSimAnalysis
+cd PathSimAnalysis
+pip install .
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Welcome to PathSimAnalysis’s documentation!

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PathSimAnalysis is an MDAnalysis based analysis package for calculating the similarity between molecular dynamics trajectories.

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+
+ + + + + + + + \ No newline at end of file diff --git a/searchindex.js b/searchindex.js new file mode 100644 index 0000000..64db3fe --- /dev/null +++ b/searchindex.js @@ -0,0 +1 @@ +Search.setIndex({"docnames": ["api", "getting_started", "index"], "filenames": ["api.rst", "getting_started.rst", "index.rst"], "titles": ["API Documentation", "Getting Started", "Welcome to PathSimAnalysis\u2019s documentation!"], "terms": {"new": 0, "version": 0, "0": 0, "10": 0, "The": 0, "modul": [0, 2], "contain": 0, "code": 0, "geometr": 0, "trajectori": [0, 2], "us": 0, "metric": 0, "hausdorff": 0, "fr\u00e9chet": 0, "distanc": 0, "1": [0, 1], "ar": 0, "two": 0, "return": 0, "nonneg": 0, "number": 0, "i": [0, 1, 2], "e": 0, "ident": 0, "zero": 0, "larg": 0, "indic": 0, "dissimilar": 0, "each": 0, "individu": 0, "point": 0, "g": 0, "coordin": 0, "snapshot": 0, "compris": 0, "loos": 0, "speak": 0, "identifi": 0, "one": 0, "per": 0, "pair": 0, "where": 0, "deviat": 0, "most": 0, "between": [0, 2], 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