Implement 1D animations

xbout/boutdataarray.py

@@ -100,8 +100,7 @@ def animate1D(self, animate_over='t', x='x', y='y', animate=True,
             print("{} data passed has {} dimensions - will use "
                   "animatplot.blocks.Line()".format(variable, str(n_dims)))
             line_block = animate_line(data=data, animate_over=animate_over,
-                                      x=x, y=y, sep_pos=sep_pos,
-                                      animate=animate, fps=fps,
+                                      sep_pos=sep_pos, animate=animate, fps=fps,
                                       save_as=save_as, ax=ax, **kwargs)
             return line_block
 

xbout/plotting/animate.py

@@ -7,7 +7,7 @@
 
 
 def animate_imshow(data, animate_over='t', x='x', y='y', animate=True,
-                   vmin='min', vmax='max', fps=10, save_as=None,
+                   vmin=None, vmax=None, fps=10, save_as=None,
                    sep_pos=None, ax=None, **kwargs):
     """
     Plots a color plot which is animated with time over the specified
@@ -60,9 +60,9 @@ def animate_imshow(data, animate_over='t', x='x', y='y', animate=True,
     image_data = data.values
 
     # If not specified, determine max and min values across entire data series
-    if vmax is 'max':
+    if vmax is None:
         vmax = np.max(image_data)
-    if vmin is 'min':
+    if vmin is None:
         vmin = np.min(image_data)
 
     if not ax:
@@ -100,9 +100,86 @@ def animate_imshow(data, animate_over='t', x='x', y='y', animate=True,
     return imshow_block
 
 
-def animate_line(data, animate_over='t', x='x', y='y', animate=True,
-                 fps=10, save_as=None, sep_pos=None, ax=None, **kwargs):
+def animate_line(data, animate_over='t', animate=True,
+                 vmin=None, vmax=None, fps=10, save_as=None, sep_pos=None, ax=None,
+                 **kwargs):
+    """
+    Plots a line plot which is animated with time.
+
+    Currently only supports 1D+1 data, which it plots with xarray's
+    wrapping of matplotlib's plot.
+
+    Parameters
+    ----------
+    data : xarray.DataArray
+    animate_over : str, optional
+        Dimension over which to animate
+    vmin : float, optional
+        Minimum value to use for colorbar. Default is to use minimum value of
+        data across whole timeseries.
+    vmax : float, optional
+        Maximum value to use for colorbar. Default is to use maximum value of
+        data across whole timeseries.
+    sep_pos : int, optional
+        Radial position at which to plot the separatrix
+    save_as: str, optional
+        Filename to give to the resulting gif
+    fps : int, optional
+        Frames per second of resulting gif
+    kwargs : dict, optional
+        Additional keyword arguments are passed on to the plotting function
+        (e.g. imshow for 2D plots).
+    """
+
     variable = data.name
 
+    # Check plot is the right orientation
     t_read, x_read = data.dims
-    raise NotImplementedError
+    if (t_read is animate_over):
+        pass
+    else:
+        data = data.transpose(x_read, animate_over)
+
+    # Load values eagerly otherwise for some reason the plotting takes
+    # 100's of times longer - for some reason animatplot does not deal
+    # well with dask arrays!
+    image_data = data.values
+
+    # If not specified, determine max and min values across entire data series
+    if vmax is None:
+        vmax = np.max(image_data)
+    if vmin is None:
+        vmin = np.min(image_data)
+
+    if not ax:
+        fig, ax = plt.subplots()
+
+    # set range of plot
+    ax.set_ylim([vmin, vmax])
+
+    line_block = amp.blocks.Line(image_data, ax=ax, **kwargs)
+
+    timeline = amp.Timeline(np.arange(data.sizes[animate_over]), fps=fps)
+
+    if animate:
+        anim = amp.Animation([line_block], timeline)
+
+    # Add title and axis labels
+    ax.set_title("{} variation over {}".format(variable, animate_over))
+    ax.set_xlabel(x_read)
+    ax.set_ylabel(variable)
+
+    # Plot separatrix
+    if sep_pos:
+        ax.plot_vline(sep_pos, '--')
+
+    if animate:
+        anim.controls(timeline_slider_args={'text': animate_over})
+
+        if not save_as:
+            save_as = "{}_over_{}".format(variable, animate_over)
+        # TODO save using PillowWriter instead once matplotlib 3.1 comes out
+        # see https://github.com/t-makaro/animatplot/issues/24
+        anim.save(save_as + '.gif', writer='imagemagick')
+
+    return line_block