Removed animation function, not compatible with GaussianPuff simulati…

…on, use static graphics options

chama/graphics.py

@@ -7,21 +7,16 @@
 
     signal_convexhull
     signal_xsection
-    animate_puffs
     sensor_locations
 """
 from __future__ import print_function, division
 try:
     import matplotlib.pyplot as plt
     from matplotlib import ticker
-    from mpl_toolkits.mplot3d import Axes3D
-    from matplotlib.patches import Circle, Ellipse, Rectangle
-    from matplotlib.collections import PatchCollection
-    from matplotlib.animation import FuncAnimation
 except:
     plt = None
-    
-from scipy.spatial import ConvexHull  
+
+from scipy.spatial import ConvexHull
 import numpy as np
 from chama.sensors import Mobile
 
@@ -247,114 +242,6 @@ def contour_data(temp, threshold, log_flag):
     fig.show()
 
 
-def animate_puffs(puff, x_range=(None, None), y_range=(None, None)):
-    """
-    Plots the horizontal movement of puffs from a GaussianPuff simulation
-    over time. Each puff is represented as a circle centered at the puff
-    center location with radius equal to the standard deviation in the
-    horizontal direction (sigmaY).
-
-    Parameters
-    ------------------
-    puff: pandas DataFrame
-        The puff DataFrame created by a GaussianPuff object
-    x_range: tuple (xmin, xmax) (optional)
-        The x-axis limits for the plot
-    y_range: tuple (ymin, ymax) (optional)
-        The y-axis limits for the plot
-    """
-
-    def circles(x, y, s, c='b', vmin=None, vmax=None, **kwargs):
-        """
-        Make a scatter plot of circles. 
-        Similar to plt.scatter, but the size of circles are in data scale.
-
-        Parameters
-        ----------
-        x, y : scalar or array_like, shape (n, )
-            Input data
-        s : scalar or array_like, shape (n, ) 
-            Radius of circles.
-        c : color or sequence of color, optional, default : 'b'
-            `c` can be a single color format string, or a sequence of color
-            specifications of length `N`, or a sequence of `N` numbers to be
-            mapped to colors using the `cmap` and `norm` specified via kwargs.
-            Note that `c` should not be a single numeric RGB or RGBA sequence 
-            because that is indistinguishable from an array of values
-            to be colormapped. (If you insist, use `color` instead.)  
-            `c` can be a 2-D array in which the rows are RGB or RGBA, however. 
-        vmin, vmax : scalar, optional, default: None
-            `vmin` and `vmax` are used in conjunction with `norm` to normalize
-            luminance data.  If either are `None`, the min and max of the
-            color array is used.
-        kwargs : `~matplotlib.collections.Collection` properties
-            Eg. alpha, edgecolor(ec), facecolor(fc), linewidth(lw),
-            linestyle(ls), norm, cmap, transform, etc.
-
-        Returns
-        -------
-        paths : `~matplotlib.collections.PathCollection`
-        """
-
-        if np.isscalar(c):
-            kwargs.setdefault('color', c)
-            c = None
-
-        if 'fc' in kwargs:
-            kwargs.setdefault('facecolor', kwargs.pop('fc'))
-        if 'ec' in kwargs:
-            kwargs.setdefault('edgecolor', kwargs.pop('ec'))
-        if 'ls' in kwargs:
-            kwargs.setdefault('linestyle', kwargs.pop('ls'))
-        if 'lw' in kwargs:
-            kwargs.setdefault('linewidth', kwargs.pop('lw'))
-        # You can set `facecolor` with an array for each patch,
-        # while you can only set `facecolors` with a value for all.
-
-        zipped = np.broadcast(x, y, s)
-        patches = [Circle((x_, y_), s_)
-                   for x_, y_, s_ in zipped]
-        collection = PatchCollection(patches, **kwargs)
-        if c is not None:
-            c = np.broadcast_to(c, zipped.shape).ravel()
-            collection.set_array(c)
-            collection.set_clim(vmin, vmax)
-
-        ax = plt.gca()
-        ax.add_collection(collection)
-        ax.autoscale_view()
-        plt.draw_if_interactive()
-        if c is not None:
-            plt.sci(collection)
-        return collection
-
-    if plt is None:
-        raise ImportError('matplotlib is required for graphics')
-
-    fig, ax = plt.subplots()
-    # ln, = plt.plot([],[],animated=True)
-
-    def update(time):
-        plt.cla()
-        ax.set_xlim(x_range[0], x_range[1])
-        ax.set_ylim(y_range[0], y_range[1])
-        ax.set_title('T = %6.2f' % time)
-        ax.set_xlabel('X')
-        ax.set_ylabel('Y')
-
-        temp = puff.loc[puff['T'] == time]
-        out = circles(temp['X'], temp['Y'], temp['sigmaY'], alpha=0.5,
-                      edgecolor='none')
-        return out
-
-    ani = FuncAnimation(fig, update, frames=puff['T'].unique())
-
-    # Need a coder like ffmpeg installed in order to save
-    # ani.save('puff.mp4')
-
-    plt.show()
-
-
 def sensor_locations(sensors, x_range=(None, None), y_range=(None, None), 
                      z_range=(None, None), legend=False,
                      colors=None, markers=None):
@@ -415,3 +302,116 @@ def sensor_locations(sensors, x_range=(None, None), y_range=(None, None),
     if legend:
         ax.legend()
     fig.show()
+
+# Animation function is no longer working
+# Use convex hull or xsection on individual timesteps
+# def animate_puffs(puff, x_range=(None, None), y_range=(None, None)):
+#     """
+#     Plots the horizontal movement of puffs from a GaussianPuff simulation
+#     over time. Each puff is represented as a circle centered at the puff
+#     center location with radius equal to the standard deviation in the
+#     horizontal direction (sigmaY).
+
+#     Parameters
+#     ------------------
+#     puff: pandas DataFrame
+#         The puff DataFrame created by a GaussianPuff object
+#     x_range: tuple (xmin, xmax) (optional)
+#         The x-axis limits for the plot
+#     y_range: tuple (ymin, ymax) (optional)
+#         The y-axis limits for the plot
+#     """
+
+#     def circles(x, y, s, c='b', vmin=None, vmax=None, **kwargs):
+#         """
+#         Make a scatter plot of circles. 
+#         Similar to plt.scatter, but the size of circles are in data scale.
+
+#         Parameters
+#         ----------
+#         x, y : scalar or array_like, shape (n, )
+#             Input data
+#         s : scalar or array_like, shape (n, ) 
+#             Radius of circles.
+#         c : color or sequence of color, optional, default : 'b'
+#             `c` can be a single color format string, or a sequence of color
+#             specifications of length `N`, or a sequence of `N` numbers to be
+#             mapped to colors using the `cmap` and `norm` specified via kwargs.
+#             Note that `c` should not be a single numeric RGB or RGBA sequence 
+#             because that is indistinguishable from an array of values
+#             to be colormapped. (If you insist, use `color` instead.)  
+#             `c` can be a 2-D array in which the rows are RGB or RGBA, however. 
+#         vmin, vmax : scalar, optional, default: None
+#             `vmin` and `vmax` are used in conjunction with `norm` to normalize
+#             luminance data.  If either are `None`, the min and max of the
+#             color array is used.
+#         kwargs : `~matplotlib.collections.Collection` properties
+#             Eg. alpha, edgecolor(ec), facecolor(fc), linewidth(lw),
+#             linestyle(ls), norm, cmap, transform, etc.
+
+#         Returns
+#         -------
+#         paths : `~matplotlib.collections.PathCollection`
+#         """
+
+#         if np.isscalar(c):
+#             kwargs.setdefault('color', c)
+#             c = None
+
+#         if 'fc' in kwargs:
+#             kwargs.setdefault('facecolor', kwargs.pop('fc'))
+#         if 'ec' in kwargs:
+#             kwargs.setdefault('edgecolor', kwargs.pop('ec'))
+#         if 'ls' in kwargs:
+#             kwargs.setdefault('linestyle', kwargs.pop('ls'))
+#         if 'lw' in kwargs:
+#             kwargs.setdefault('linewidth', kwargs.pop('lw'))
+#         # You can set `facecolor` with an array for each patch,
+#         # while you can only set `facecolors` with a value for all.
+
+#         zipped = np.broadcast(x, y, s)
+#         patches = [Circle((x_, y_), s_)
+#                    for x_, y_, s_ in zipped]
+#         collection = PatchCollection(patches, **kwargs)
+#         if c is not None:
+#             c = np.broadcast_to(c, zipped.shape).ravel()
+#             collection.set_array(c)
+#             collection.set_clim(vmin, vmax)
+
+#         ax = plt.gca()
+#         ax.add_collection(collection)
+#         ax.autoscale_view()
+#         plt.draw_if_interactive()
+#         if c is not None:
+#             plt.sci(collection)
+#         return collection
+
+#     if plt is None:
+#         raise ImportError('matplotlib is required for graphics')
+
+#     from matplotlib.patches import Circle, Ellipse, Rectangle
+#     from matplotlib.collections import PatchCollection
+#     from matplotlib.animation import FuncAnimation
+
+#     fig, ax = plt.subplots()
+#     # ln, = plt.plot([],[],animated=True)
+
+#     def update(time):
+#         plt.cla()
+#         ax.set_xlim(x_range[0], x_range[1])
+#         ax.set_ylim(y_range[0], y_range[1])
+#         ax.set_title('T = %6.2f' % time)
+#         ax.set_xlabel('X')
+#         ax.set_ylabel('Y')
+
+#         temp = puff.loc[puff['T'] == time]
+#         out = circles(temp['X'], temp['Y'], temp['sigmaY'], alpha=0.5,
+#                       edgecolor='none')
+#         return out
+
+#     ani = FuncAnimation(fig, update, frames=puff['T'].unique())
+
+#     # Need a coder like ffmpeg installed in order to save
+#     # ani.save('puff.mp4')
+
+#     plt.show()

chama/tests/test_graphics.py

@@ -58,9 +58,6 @@ def test_signal_xsection(self):
 
         self.assertTrue(isfile(filename))
 
-    def test_signal_animate(self):
-        pass
-
 
 class TestSensorGraphics(unittest.TestCase):