Merge branch 'develop'

asteca/cluster.py

@@ -1,15 +1,16 @@
 import warnings
-from dataclasses import dataclass
 import numpy as np
 import pandas as pd
 from .modules import cluster_priv as cp
 from .modules import nmembers as nm
 
 
-@dataclass
 class Cluster:
     """Define a :py:class:`Cluster` object.
 
+    This object contains the basic data required to load a group of observed stars
+    that could represent a cluster or an entire field.
+
     :param obs_df: `pandas DataFrame <https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html>`__
         with the observed loaded data.
     :type obs_df: pd.DataFrame
@@ -42,7 +43,7 @@ class Cluster:
     :type plx: str | None
     :param e_plx: Name of the DataFrame column that contains the parallax uncertainty,
         defaults to ``None``
-    :type plx: str | None
+    :type e_plx: str | None
     :param pmra: Name of the DataFrame column that contains the RA proper motion,
         defaults to ``None``
     :type pmra: str | None
@@ -59,43 +60,71 @@ class Cluster:
     :type N_clust_min: int
     :param N_clust_max: Maximum number of cluster members, defaults to ``5000``
     :type N_clust_max: int
+
+    :raises ValueError: If there are missing required attributes to generate the
+        :py:class:`Cluster <asteca.cluster.Cluster>` object
     """
 
-    obs_df: pd.DataFrame
-    ra: str | None = None
-    dec: str | None = None
-    magnitude: str | None = None
-    e_mag: str | None = None
-    color: str | None = None
-    e_color: str | None = None
-    color2: str | None = None
-    e_color2: str | None = None
-    plx: str | None = None
-    pmra: str | None = None
-    pmde: str | None = None
-    e_plx: str | None = None
-    e_pmra: str | None = None
-    e_pmde: str | None = None
-    N_clust_min: int = 25
-    N_clust_max: int = 5000
-
-    def __post_init__(self):
-        """The photometry is stored with a '_p' to differentiate from the
-        self.magnitude, self.color, etc that are defined with the class is called.
-        """
+    def __init__(
+        self,
+        obs_df: pd.DataFrame,
+        ra: str | None = None,
+        dec: str | None = None,
+        magnitude: str | None = None,
+        e_mag: str | None = None,
+        color: str | None = None,
+        e_color: str | None = None,
+        color2: str | None = None,
+        e_color2: str | None = None,
+        plx: str | None = None,
+        e_plx: str | None = None,
+        pmra: str | None = None,
+        e_pmra: str | None = None,
+        pmde: str | None = None,
+        e_pmde: str | None = None,
+        N_clust_min: int = 25,
+        N_clust_max: int = 5000,
+    ) -> None:
+        self.obs_df = obs_df
+        self.ra = ra
+        self.dec = dec
+        self.magnitude = magnitude
+        self.e_mag = e_mag
+        self.color = color
+        self.e_color = e_color
+        self.color2 = color2
+        self.e_color2 = e_color2
+        self.plx = plx
+        self.pmra = pmra
+        self.pmde = pmde
+        self.e_plx = e_plx
+        self.e_pmra = e_pmra
+        self.e_pmde = e_pmde
+        self.N_clust_min = N_clust_min
+        self.N_clust_max = N_clust_max
+
         self.N_stars = len(self.obs_df)
         print("\nInstantiating cluster...")
         print(f"N_stars        : {self.N_stars}")
         print(f"N_clust_min    : {self.N_clust_min}")
         print(f"N_clust_max    : {self.N_clust_max}")
 
+        dim_count = self._load()
+        if dim_count > 0:
+            print("Cluster object generated")
+        else:
+            raise ValueError("No column names defined for cluster")
+
+    def _load(self):
         dim_count = 0
+
         if self.ra is not None:
             self.ra_v = self.obs_df[self.ra].values
             self.dec_v = self.obs_df[self.dec].values
             print(f"(RA, DEC)      : ({self.ra}, {self.dec})")
             dim_count += 1
 
+        # TODO: change _p to _v
         if self.magnitude is not None:
             self.mag_p = self.obs_df[self.magnitude].values
             if self.e_mag is not None:
@@ -148,10 +177,7 @@ def __post_init__(self):
             print(f"pmDE           : {self.pmra} [{self.e_pmde}]")
             dim_count += 1
 
-        if dim_count > 0:
-            print("Cluster object generated")
-        else:
-            raise ValueError("No column names defined for cluster")
+        return dim_count
 
     def get_center(
         self,

asteca/isochrones.py

@@ -1,10 +1,8 @@
 import os
 import numpy as np
-from dataclasses import dataclass
 from .modules import isochrones_priv
 
 
-@dataclass
 class Isochrones:
     """Define an :py:class:`Isochrones` object.
 
@@ -16,7 +14,7 @@ class Isochrones:
         `PARSEC <http://stev.oapd.inaf.it/cgi-bin/cmd_3.7>`__,
         `MIST <https://waps.cfa.harvard.edu/MIST/>`__, or
         `BASTI <http://basti-iac.oa-abruzzo.inaf.it/isocs.html>`__.
-    :type model: str: ``PARSEC, MIST, BASTI``
+    :type model: str
     :param isochs_path: Path to the folder that contains the files for the theoretical
         isochrones
     :type isochs_path: str
@@ -52,13 +50,6 @@ class Isochrones:
         :py:meth:`Synthetic.generate() <asteca.synthetic.Synthetic.generate>` method,
         defaults to ``None``
     :type z_to_FeH: float | None
-    :param column_names: Column names for the initial mass, metallicity, and age for
-        the photometric system's isochrones files. Example:
-        ``{"mass_col": "Mini", "met_col": "Zini", "age_col": "logAge"}``.
-        This dictionary is defined internally in **ASteCA** and should only be given
-        by the user if the isochrone service changes its format and the `isochrones`
-        class fails to load the files, defaults to ``None``
-    :type column_names: dict, optional
     :param N_interp: Number of interpolation points used to ensure that all isochrones
         are the same shape, defaults to ``2500``
     :type N_interp: int
@@ -67,22 +58,46 @@ class fails to load the files, defaults to ``None``
         "`in preparation <http://stev.oapd.inaf.it/cmd_3.7/faq.html>`__", defaults
         to ``True``
     :type parsec_rm_stage_9: bool
+    :param column_names: Column names for the initial mass, metallicity, and age for
+        the photometric system's isochrones files. Example:
+        ``{"mass_col": "Mini", "met_col": "Zini", "age_col": "logAge"}``.
+        This dictionary is defined internally in **ASteCA** and should only be given
+        by the user if the isochrone service changes its format and the `isochrones`
+        class fails to load the files, defaults to ``None``
+    :type column_names: dict | None
+
+    :raises ValueError: If any of the attributes is not recognized as a valid option,
+        or there are missing required attributes
     """
 
-    model: str
-    isochs_path: str
-    magnitude: str
-    color: tuple
-    color2: tuple | None = None
-    magnitude_effl: float | None = None
-    color_effl: tuple | None = None
-    color2_effl: tuple | None = None
-    z_to_FeH: float | None = None
-    column_names: dict | None = None
-    N_interp: int = 2500
-    parsec_rm_stage_9: bool = True
+    def __init__(
+        self,
+        model: str,
+        isochs_path: str,
+        magnitude: str,
+        color: tuple,
+        color2: tuple | None = None,
+        magnitude_effl: float | None = None,
+        color_effl: tuple | None = None,
+        color2_effl: tuple | None = None,
+        z_to_FeH: float | None = None,
+        N_interp: int = 2500,
+        parsec_rm_stage_9: bool = True,
+        column_names: dict | None = None,
+    ) -> None:
+        self.model = model
+        self.isochs_path = isochs_path
+        self.magnitude = magnitude
+        self.color = color
+        self.color2 = color2
+        self.magnitude_effl = magnitude_effl
+        self.color_effl = color_effl
+        self.color2_effl = color2_effl
+        self.z_to_FeH = z_to_FeH
+        self.column_names = column_names
+        self.N_interp = N_interp
+        self.parsec_rm_stage_9 = parsec_rm_stage_9
 
-    def __post_init__(self):
         # Check that the number of colors match
         if self.color2 is not None and self.color2_effl is None:
             raise ValueError(

asteca/likelihood.py

@@ -1,10 +1,8 @@
-from dataclasses import dataclass
 import numpy as np
 from .cluster import Cluster
 from .modules import likelihood_priv as lpriv
 
 
-@dataclass
 class Likelihood:
     """Define a :py:class:`Likelihood` object.
 
@@ -15,24 +13,30 @@ class Likelihood:
 
     :param my_cluster: :py:class:`Cluster <asteca.cluster.Cluster>` object with the
         loaded data for the observed cluster
-    :type my_cluster: :py:class:`Cluster <asteca.cluster.Cluster>`
+    :type my_cluster: Cluster
     :param lkl_name: Currently only the Poisson likelihood ratio defined in
-        `Tremmel et al. (2013) <https://ui.adsabs.harvard.edu/abs/2013ApJ...766...19T/abstract)>`__
+        `Tremmel et al. (2013)
+        <https://ui.adsabs.harvard.edu/abs/2013ApJ...766...19T/abstract)>`__
         is accepted, defaults to ``plr``
     :type lkl_name: str
     :param bin_method: Bin method used to split the color-magnitude diagram into cells
-        (`Hess diagram <https://en.wikipedia.org/wiki/Hess_diagram>`__). If ``manual``
+        (`Hess diagram <https://en.wikipedia.org/wiki/Hess_diagram>`__); one of:
+        ``knuth, fixed, bayes_blocks, manual``. If ``manual``
         is selected, a list containing an array of edge values for the magnitude,
         followed by one or two arrays (depending on the number of colors defined) for
         the color(s), also with edge values,  defaults to ``knuth``
-    :type bin_method: str: ``knuth, fixed, bayes_blocks, manual``
+    :type bin_method: str
+
+    :raises ValueError: If any of the attributes is not recognized as a valid option
     """
 
-    my_cluster: Cluster
-    lkl_name: str = "plr"
-    bin_method: str = "knuth"
+    def __init__(
+        self, my_cluster: Cluster, lkl_name: str = "plr", bin_method: str = "knuth"
+    ) -> None:
+        self.my_cluster = my_cluster
+        self.lkl_name = lkl_name
+        self.bin_method = bin_method
 
-    def __post_init__(self):
         likelihoods = ("plr", "bins_distance")
         if self.lkl_name not in likelihoods:
             raise ValueError(
@@ -54,7 +58,7 @@ def __post_init__(self):
             np.array([self.my_cluster.mag_p, *self.my_cluster.colors_p])
         )
 
-        print("Likelihood object generated")
+        print("\nLikelihood object generated")
 
     def get(self, synth_clust: np.array) -> float:
         """Evaluate the selected likelihood function.
@@ -70,9 +74,9 @@ def get(self, synth_clust: np.array) -> float:
         """
         if self.lkl_name == "plr":
             return lpriv.tremmel(self, synth_clust)
-        if self.lkl_name == "visual":
-            return lpriv.visual(self, synth_clust)
-        if self.lkl_name == "mean_dist":
-            return lpriv.mean_dist(self, synth_clust)
+        # if self.lkl_name == "visual":
+        #     return lpriv.visual(self, synth_clust)
+        # if self.lkl_name == "mean_dist":
+        #     return lpriv.mean_dist(self, synth_clust)
         if self.lkl_name == "bins_distance":
             return lpriv.bins_distance(self, synth_clust)

asteca/membership.py

@@ -1,12 +1,10 @@
-from dataclasses import dataclass
 import numpy as np
 from .cluster import Cluster
 from .modules import cluster_priv as cp
 from .modules.fastmp import fastMP
 from .modules.bayesian_da import bayesian_mp
 
 
-@dataclass
 class Membership:
     """Define a :py:class:`Membership` object.
 
@@ -27,14 +25,17 @@ class Membership:
     :py:class:`Cluster <asteca.cluster.Cluster>` object. Photometry data is not
     employed.
 
-    :param cluster: :py:class:`Cluster <asteca.cluster.Cluster>` object with the
+    :param my_field: :py:class:`Cluster <asteca.cluster.Cluster>` object with the
         loaded data for the observed field
-    :type cluster: :py:class:`Cluster <asteca.cluster.Cluster>`
+    :type my_field: Cluster
+
+    :raises ValueError: If there are missing required attributes in the
+        :py:class:`Cluster <asteca.cluster.Cluster>` object
     """
 
-    my_field: Cluster
+    def __init__(self, my_field: Cluster) -> None:
+        self.my_field = my_field
 
-    def __post_init__(self):
         noradeg_flag = False
         try:
             self.my_field.ra