Merge branch 'release/1.15.2'

CHANGELOG.md

@@ -4,6 +4,32 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](http://keepachangelog.com/).
 
 ## Unreleased
+## 1.15.2 - 2024-11-12
+### Added
+- 'ng_generate_data'
+    - Another file, 'start_points.csv' is generated. It contains positions of the centerline along with the distances to the walls.
+
+### Changed
+- Criterions
+    - _Profile_
+        - `saveState()` now also saves backward nad maximum speeds that are computed within the speed profiler.
+    - _Profile2_
+        - Remove majority of flake8 warnings.
+- 'ng_generate_data'
+    - Generated `start_points.npy` contains additional two columns with distances to the walls.
+- 'plot'
+    - Support older matplotlib versions in `rectanglePlot()`.
+
+### Fixed
+- Criterions
+    - _Profile_
+        - Properly construct conditional-based dictionary is `saveState()`.
+    - _Profile2_
+        - Properly obtain logfile name.
+        - Load first four columns of the reference instead of just three.
+        - Add missing import of `pointToMap()`.
+        - Properly construct conditional-based dictionary is `saveState()`.
+
 ## 1.15.1 - 2024-09-10
 ### Added
 - Optimizers

CITATION.cff

@@ -5,8 +5,8 @@ authors:
   given-names: "Jaroslav"
   orcid: "https://orcid.org/0000-0001-8816-2773"
 title: "ng_trajectory"
-version: 1.15.1
-date-released: 2024-09-10
+version: 1.15.2
+date-released: 2024-11-12
 url: "https://github.com/jara001/ng_trajectory"
 license: GPL-3.0
 preferred-citation:

bin/ng_generate_data

@@ -825,27 +825,49 @@ def processImage(im: Image) -> None:
     saveim(nndi, "generated_data.png")
 
 
+    # # Compute distances to the walls # #
+    dists = []
+
+    walls = getWalls(im)
+    for wall in walls:
+        dists.append([
+            numpy.hypot(
+                wall[:, 0] - sorted_points[i][0],
+                wall[:, 1] - sorted_points[i][1]
+            ).min() for i in range(len(sorted_points))
+        ])
+
+
     # # Save into npy # #
 
     start_points = numpy.asarray(sorted_points).astype(float)
 
     # Flip y-axis
     start_points -= [im.size[1], 0]
     start_points[:, 0] = numpy.abs(start_points[:, 0])
+    start_points = numpy.hstack((start_points, numpy.asarray(dists).T))
 
     # Convert to real units (if required)
     if args.resolution != 1.0 or args.scale != 1.0:  # or args.resize != 1.0:
         start_points *= (args.resolution * args.scale) / args.resize
 
     # Move the origin (if required)
     if args.originx != 0.0 or args.originy != 0.0:
-        start_points += [args.originy, args.originx]
+        start_points += [args.originy, args.originx, 0, 0]
 
     # Swap yx
-    start_points = numpy.vstack((start_points[:, 1], start_points[:, 0])).T
-
+    start_points = numpy.hstack((
+        numpy.vstack((start_points[:, 1], start_points[:, 0])).T,
+        start_points[:, 2:]
+    ))
     save(start_points, "start_points.npy")
 
+    with open(generate_filename("start_points.csv"), "w") as f:
+        f.write("x_m,y_m,d1_m,d2_m\n")
+        for _sp in start_points:
+            m = [_sp[0], _sp[1], _sp[3], _sp[2]]
+            f.write(",".join(["%f" % v for v in m]) + "\n")
+
     valid_points = numpy.asarray(im, dtype = int)
     valid_points = numpy.argwhere(
         (valid_points == FREE) & (~invalid)

ng_trajectory/criterions/profile/profiler.py

@@ -16,7 +16,7 @@
 
 from ng_trajectory.segmentators.utils import pointToMap
 
-from typing import List, Tuple, TextIO
+from typing import List, Tuple, TextIO, Optional
 
 
 _mu = 0.2           # Friction coeficient
@@ -339,7 +339,10 @@ def saveState(
         points: numpy.ndarray,
         t: numpy.ndarray,
         v: numpy.ndarray,
-        a: numpy.ndarray) -> bool:
+        a: numpy.ndarray,
+        *,
+        bwd: Optional[numpy.ndarray] = None,
+        mx: Optional[numpy.ndarray] = None) -> bool:
     """Save the computed profile into a CSV file.
 
     Arguments:
@@ -349,6 +352,11 @@ def saveState(
     a -- acceleration profile of the trajectory, [m.s^-2], nx1 numpy.ndarray
     t -- time of reaching the points of the trajectory,
          [s], nx1 or (n+1)x1 numpy.ndarray
+    *
+    bwd -- speed profile after the backward pass, [m.s^-1],
+           optional, nx1 numpy.ndarray
+    mx -- maximum permissible speed, [m.s^-1],
+          optional, nx1 numpy.ndarray
 
     Returns:
     success -- True if saved, otherwise False
@@ -407,6 +415,12 @@ def saveState(
     x, y, k = points[:, :3].T
     t, v, a = t.flatten(), v.flatten(), a.flatten()
 
+    if bwd is not None:
+        bwd = bwd.flatten()
+
+    if mx is not None:
+        mx = mx.flatten()
+
     # Line distance (d) !! NOT TRACK PROGRESS !!
     d = pointsDistance(points)
     _d = d[0]
@@ -436,12 +450,18 @@ def saveState(
     with open(filename, "w", newline = "") as f:
         writer = csv.DictWriter(
             f,
-            fieldnames = [
-                "t_s", "d_m", "x_m", "y_m",
-                "psi_rad", "k_radpm",
-                "vx_mps", "vy_mps", "a_mps2",
-                "omega_radps", "delta_rad"
-            ] + ([] if CENTERLINE is None else ["s_m"])
+            fieldnames = (
+                [
+                    "t_s", "d_m", "x_m", "y_m",
+                    "psi_rad", "k_radpm",
+                    "vx_mps", "vy_mps", "a_mps2",
+                    "omega_radps", "delta_rad"
+                ]
+                + ([] if CENTERLINE is None else ["s_m"])
+                + ["vfwd_mps"]
+                + ([] if bwd is None else ["vbwd_mps"])
+                + ([] if mx is None else ["vmax_mps"])
+            )
         )
 
         writer.writeheader()
@@ -462,14 +482,23 @@ def saveState(
                     "a_mps2": a[_i],
                     "omega_radps": v[_i] * math.cos(_beta) * k[_i],
                     "delta_rad": math.atan((_lf + _lr) * k[_i])
-                }, **{
-                    [] if CENTERLINE is None
-                    else "s_m": cd[
+                }, **(
+                    {} if CENTERLINE is None
+                    else {"s_m": cd[
                         trajectoryClosestIndex(
                             CENTERLINE,
                             numpy.asarray([x[_i], y[_i]])
                         )
                     ]}
+                ), **{
+                    "vfwd_mps": v[_i]
+                }, **(
+                    {} if bwd is None
+                    else {"vbwd_mps": bwd[_i]}
+                ), **(
+                    {} if mx is None
+                    else {"vmax_mps": mx[_i]}
+                )
             })
 
 
@@ -591,6 +620,6 @@ def profileCompute(
         _t[0] = 0
 
     if save is not None:
-        saveState(save, points, _t, _v, _a)
+        saveState(save, points, _t, _v, _a, bwd = bwd, mx = mx)
 
     return _v, _a, _t