codestyle check 4

beast/tools/cut_catalogs.py

@@ -107,7 +107,7 @@
  # do convex hull
  ra_col = [x for x in phot_cat.colnames if "RA" in x.upper()][0]
  dec_col = [x for x in phot_cat.colnames if "DEC" in x.upper()][0]
  phot_cat_boundary = convexhull_path(new_phot_cat[ra_col], new_phot_cat[dec_col],
  concave_alpha, input_ast_file)
  # check if points are inside
  ra_col = [x for x in ast_cat.colnames if "RA" in x.upper()][0]
@@ -258,18 +258,21 @@
  [x_coord, y_coord]
  ).T # there's a weird astropy datatype issue that requires numpy coercion
 
  print("using concave hull, alpha: " + str(concave_alpha) + " (default: 100)")
  concave_hull = alpha_shape(coords, concave_alpha)
  path_object = Path(np.array(concave_hull.boundary.xy).T)
 
  # create diagnostic plot
- ax = plt.subplots(1, 1, figsize=(5, 4))
+ fig = plt.figure(figsize=(5, 4))
+ ax = fig.subplots(1, 1)
  ax.scatter(x_coord, y_coord, s=1)
  ax.plot(path_object.vertices.T[0], path_object.vertices.T[1], c="r")
  ax.set_xlabel("x")
  ax.set_ylabel("y")
  ax.set_title(r"$\alpha$ = " + str(concave_alpha))
+ ax.spines['top'].set_visible(False)
+ ax.spines['right'].set_visible(False)
  plt.savefig(str(input_ast_file) + "_plot.png", bbox_inches="tight")
 
  return path_object
 
@@ -284,28 +287,28 @@
  don't fall inward as much as larger numbers.
  Too large, and you lose everything!
  """
  if len(coords) < 4:
  # When you have a triangle, there is no sense
  # in computing an alpha shape.
  return geometry.MultiPoint(list(coords)).convex_hull
 
  tri = Delaunay(coords)
  triangles = coords[tri.simplices]
  a = ((triangles[:, 0, 0] - triangles[:, 1, 0]) ** 2 + (triangles[:, 0, 1] - triangles[:, 1, 1]) ** 2) ** 0.5
  b = ((triangles[:, 1, 0] - triangles[:, 2, 0]) ** 2 + (triangles[:, 1, 1] - triangles[:, 2, 1]) ** 2) ** 0.5
  c = ((triangles[:, 2, 0] - triangles[:, 0, 0]) ** 2 + (triangles[:, 2, 1] - triangles[:, 0, 1]) ** 2) ** 0.5
  s = (a + b + c) / 2.0
  areas = (s * (s - a) * (s - b) * (s - c)) ** 0.5
  circums = a * b * c / (4.0 * areas)
  filtered = triangles[circums < (1.0 / alpha)]
  edge1 = filtered[:, (0, 1)]
  edge2 = filtered[:, (1, 2)]
  edge3 = filtered[:, (2, 0)]
  edge_points = np.unique(np.concatenate((edge1, edge2, edge3)), axis=0).tolist()
  m = geometry.MultiLineString(edge_points)
  triangles = list(polygonize(m))
 
  return unary_union(triangles)
 
 
 if __name__ == "__main__": # pragma: no cover