dunno

tfields/bounding_box.py

@@ -331,33 +331,41 @@ class Node(object):
 
 
 class Searcher(Node):
-    def __init__(self, mesh, n_sections=None, delta=0.):
+    def __init__(self, mesh, n_sections=None, delta=0.,
+                 cut_length=None):
         """
+        Special cutting tree root node.
+        Provides a fast point in mesh search algorithm (Searcher.in_faces)
+
         Args:
             n_sections (None or list of len 3):
                 None: auto search n_sections
                 list: number of sections in the index dimension
+            delta (float): safety margin around the mesh to search in
+            cut_length (None / float): characteristic cell size. Be carefull,
+                to choose it high enough. If it is smaller than the largest
+                triangle, a box could lie in the triangle without containing it.
         """
         minima = mesh.min(axis=0) - 0.0001
         maxima = mesh.max(axis=0) + 0.0001
 
         if n_sections is None or any([ns is None for ns in n_sections]):
-            # project all triangels to have one point at 0, 0, 0
-            triangles = mesh.triangles().copy()
-            triangles.fields = []
-
-            ab, ac = triangles.edges()
-            bc = ac - ab
-            side_lengths = np.concatenate([np.linalg.norm(side, axis=1)
-                                           for side in [ab, ac, bc]])
-            # import mplTools as mpl
-            # axis= tfields.plotting.gca(2)
-            # mpl.plotHistogram(side_lengths, axis=axis)
-            # mpl.plt.show()
-            # quit()
-            characteristic_side_length = np.max(side_lengths)
-
-            cut_length = characteristic_side_length * 1.1
+            if cut_length is None:
+                # project all triangels to have one point at 0, 0, 0
+                triangles = mesh.triangles().copy()
+                triangles.fields = []
+
+                ab, ac = triangles.edges()
+                bc = ac - ab
+                side_lengths = np.concatenate([np.linalg.norm(side, axis=1)
+                                               for side in [ab, ac, bc]])
+                # import mplTools as mpl
+                # axis= tfields.plotting.gca(2)
+                # mpl.plotHistogram(side_lengths, axis=axis)
+                # mpl.plt.show()
+                # quit()
+                characteristic_side_length = np.max(side_lengths)
+                cut_length = characteristic_side_length * 1.1
 
             elongation = maxima - minima
             n_sections_auto = np.round(elongation / cut_length).astype(int)
@@ -367,6 +375,8 @@ class Searcher(Node):
                     if ns is not None:
                         n_sections_auto[i] = int(ns)
             n_sections = n_sections_auto
+        elif cut_length is not None:
+            raise ValueError("cut_length not used.")
 
         cut = {}
         for i, key in enumerate(['x', 'y', 'z']):

tfields/lib/sets.py

@@ -100,9 +100,14 @@ class UnionFind(object):
         Build unions for whole iterators of any size
         """
         self.insert_objects(tfields.lib.util.flatten(iterator))
+        log = logging.getLogger("UnionFind.__call__")
+        i = 0
+        n = len(iterator)
         for item in iterator:
+            log.info("Step {i} / n")
             for i1, i2 in tfields.lib.util.pairwise(item):
                 self.union(i1, i2)
+            i += 1
 
     def groups(self, iterator):
         """

tfields/mesh3D.py

@@ -245,7 +245,6 @@ class Mesh3D(tfields.TensorMaps):
         directory, name = os.path.split(path)
 
         if not (self.faceScalars.size == 0 or map_index is None):
-            import matplotlib.colors as colors
             scalars = self.maps[0].fields[map_index]
             min_scalar = scalars[~np.isnan(scalars)].min()
             max_scalar = scalars[~np.isnan(scalars)].max()
@@ -256,12 +255,17 @@ class Mesh3D(tfields.TensorMaps):
                     vmax = 1.
                 else:
                     vmin = 0.
+            import matplotlib.colors as colors
+            import matplotlib.pyplot as plt
             norm = colors.Normalize(vmin, vmax)
             color_map = plt.get_cmap(cmap)
         else:
             # switch for not coloring the triangles and thus not producing the materials
             norm = None
 
+        if len(kwargs) != 0:
+            raise ValueError("Unused arguments.")
+
         if norm is not None:
             mat_name = name + '_frame_{0}.mat'.format(map_index)
             scalars[np.isnan(scalars)] = min_scalar - 1
@@ -428,10 +432,10 @@ class Mesh3D(tfields.TensorMaps):
             >>> sphere[:, 1] += 2
 
             Oktaeder
-            >>> oktder = tfields.Mesh3D.grid((1, 1, 1),
-            ...                              (-np.pi, np.pi, 5),
-            ...                              (-np.pi / 2, np.pi / 2, 3),
-            ...                              coord_sys='spherical')
+            >>> oktaeder = tfields.Mesh3D.grid((1, 1, 1),
+            ...                                (-np.pi, np.pi, 5),
+            ...                                (-np.pi / 2, np.pi / 2, 3),
+            ...                                coord_sys='spherical')
 
             Cube with edge length of 2 units
             >>> cube = tfields.Mesh3D.grid((-1, 1, 2),
@@ -707,7 +711,7 @@ class Mesh3D(tfields.TensorMaps):
                         nTrue = vertices_rejected.count(True)
                         lonely_bool = True if nTrue == 1 else False
 
-                        triangle_points = [inst[f] for f in face]
+                        triangle_points = [vertices[f] for f in face]
                         """
                         Add the intersection points and faces
                         """

tfields/plotting/mpl.py

@@ -447,10 +447,11 @@ def to_colors(scalars, cmap=None, vmin=None, vmax=None):
     """
     if not hasattr(scalars, '__iter__'):
         scalars = [scalars]
+    scalars = np.array(scalars)
     if vmin is None:
-        vmin = min(scalars)
+        vmin = min(scalars.flat)
     if vmax is None:
-        vmax = max(scalars)
+        vmax = max(scalars.flat)
     color_map = plt.get_cmap(cmap)
     norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
     return color_map([norm(s) for s in scalars])
@@ -600,7 +601,10 @@ def set_legend(axis, artists, **kwargs):
     return axis.legend(handles=handles, **kwargs)
 
 
-def set_colorbar(axis, artist, label=None, divide=True, **kwargs):
+def set_colorbar(axis, artist, label=None, divide=True,
+                 position='right', size="2%", pad=0.05,
+                 labelpad = None,
+                 **kwargs):
     """
     Note:
         Bug found in matplotlib:
@@ -616,11 +620,28 @@ def set_colorbar(axis, artist, label=None, divide=True, **kwargs):
         >> axis.clear()
 
     """
+    ticks_position = 'default'
+    label_position = 'bottom'
+    labelpad = 30 if labelpad is None else labelpad
+    if position == 'right':
+        rotation = 270
+    elif position == 'left':
+        rotation = 90
+    elif position == 'top':
+        rotation = 0
+        ticks_position = 'top'
+        label_position = 'top'
+        labelpad = 5
+    elif position == 'bottom':
+        rotation = 0
     # colorbar
     if divide:
         divider = make_axes_locatable(axis)
-        axis = divider.append_axes("right", size="2%", pad=0.05)
+        axis = divider.append_axes(position, size=size, pad=pad)
     cbar = plt.colorbar(artist, cax=axis, **kwargs)
+    cbar.ax.xaxis.set_ticks_position(ticks_position)
+    cbar.ax.xaxis.set_label_position(label_position)
+    cbar.ax.tick_params(axis='x', which='major', pad=0)
 
     # label
     if label is None:
@@ -628,8 +649,7 @@ def set_colorbar(axis, artist, label=None, divide=True, **kwargs):
         if art_label:
             label = art_label
     if label is not None:
-        labelpad = 30
-        cbar.set_label(label, rotation=270, labelpad=labelpad)
+        cbar.set_label(label, rotation=rotation, labelpad=labelpad)
     return cbar