Moved plotting from lbmpy to pystencils

- lbmpy plotting uses the pystencils plotting now

plot2d.py

+from matplotlib.pyplot import *
+
+
+def vectorField(field, step=2, **kwargs):
+    """
+    Plot given vector field as quiver (arrow) plot.
+
+    :param field: numpy array with 3 dimensions, first two are spatial x,y coordinate, the last
+                  coordinate should have shape 2 and stores the 2 velocity components
+    :param step: plots only every steps's cell
+    :param kwargs: keyword arguments passed to :func:`matplotlib.pyplot.quiver`
+    """
+    veln = field.swapaxes(0, 1)
+    res = quiver(veln[::step, ::step, 0], veln[::step, ::step, 1], **kwargs)
+    axis('equal')
+    return res
+
+
+def vectorFieldMagnitude(field, **kwargs):
+    """
+    Plots the magnitude of a vector field as colormap
+    :param field: numpy array with 3 dimensions, first two are spatial x,y coordinate, the last
+                  coordinate should have shape 2 and stores the 2 velocity components
+    :param kwargs: keyword arguments passed to :func:`matplotlib.pyplot.imshow`
+    """
+    from numpy.linalg import norm
+    norm = norm(field, axis=2, ord=2)
+    if hasattr(field, 'mask'):
+        norm = np.ma.masked_array(norm, mask=field.mask[:, :, 0])
+    return scalarField(norm, **kwargs)
+
+
+def scalarField(field, **kwargs):
+    """
+    Plots field values as colormap
+
+    :param field: two dimensional numpy array
+    :param kwargs: keyword arguments passed to :func:`matplotlib.pyplot.imshow`
+    """
+    import numpy as np
+    field = np.swapaxes(field, 0, 1)
+    res = imshow(field, origin='lower', **kwargs)
+    axis('equal')
+    return res
+
+
+def multipleScalarFields(field, **kwargs):
+    subPlots = field.shape[-1]
+    for i in range(subPlots):
+        subplot(1, subPlots, i + 1)
+        title(str(i))
+        scalarField(field[..., i])
+        colorbar()
+
+
+def plotBoundaryHandling(boundaryHandling, boundaryNameToColor=None):
+    """
+    Shows boundary cells
+
+    :param boundaryHandling: instance of :class:`lbmpy.boundaries.BoundaryHandling`
+    :param boundaryNameToColor: optional dictionary mapping boundary names to colors
+    """
+    import matplotlib
+    import matplotlib.pyplot as plt
+
+    if len(boundaryHandling.flagField.shape) != 2:
+        raise NotImplementedError("Only implemented for 2D boundary handlings")
+
+    if boundaryNameToColor:
+        fixedColors = boundaryNameToColor
+    else:
+        fixedColors = {
+            'fluid': '#1f77ff11',
+            'noSlip': '#000000'
+        }
+
+    boundaryNames = []
+    flagValues = []
+    for name, flag in sorted(boundaryHandling.getBoundaryNameToFlagDict().items(), key=lambda l: l[1]):
+        boundaryNames.append(name)
+        flagValues.append(flag)
+    defaultCycler = matplotlib.rcParams['axes.prop_cycle']
+    colorValues = [fixedColors[name] if name in fixedColors else cycle['color']
+                   for cycle, name in zip(defaultCycler, boundaryNames)]
+
+    cmap = matplotlib.colors.ListedColormap(colorValues)
+    bounds = np.array(flagValues, dtype=float) - 0.5
+    bounds = list(bounds) + [bounds[-1] + 1]
+    norm = matplotlib.colors.BoundaryNorm(bounds, cmap.N)
+
+    flagField = boundaryHandling.flagField.swapaxes(0, 1)
+    plt.imshow(flagField, interpolation='none', origin='lower',
+               cmap=cmap, norm=norm)
+
+    patches = [matplotlib.patches.Patch(color=color, label=name) for color, name in zip(colorValues, boundaryNames)]
+    plt.axis('equal')
+    plt.legend(handles=patches, bbox_to_anchor=(1.02, 0.5), loc=2, borderaxespad=0.)
+
+# ------------------------------------------- Animations ---------------------------------------------------------------
+
+
+def vectorFieldAnimation(runFunction, step=2, rescale=True, plotSetupFunction=lambda: None,
+                         plotUpdateFunction=lambda: None, interval=30, frames=180, **kwargs):
+    import matplotlib.animation as animation
+    from numpy.linalg import norm
+
+    fig = gcf()
+    im = None
+    field = runFunction()
+    if rescale:
+        maxNorm = np.max(norm(field, axis=2, ord=2))
+        field /= maxNorm
+        if 'scale' not in kwargs:
+            kwargs['scale'] = 1.0
+
+    quiverPlot = vectorField(field, step=step, **kwargs)
+    plotSetupFunction()
+
+    def updatefig(*args):
+        f = runFunction()
+        f = np.swapaxes(f, 0, 1)
+        if rescale:
+            maxNorm = np.max(norm(f, axis=2, ord=2))
+            f /= maxNorm
+        u, v = f[::step, ::step, 0], f[::step, ::step, 1]
+        quiverPlot.set_UVC(u, v)
+        plotUpdateFunction()
+        return im,
+
+    return animation.FuncAnimation(fig, updatefig, interval=interval, frames=frames)
+
+
+def vectorFieldMagnitudeAnimation(runFunction, plotSetupFunction=lambda: None,
+                                  plotUpdateFunction=lambda: None, interval=30, frames=180, **kwargs):
+    import matplotlib.animation as animation
+    from numpy.linalg import norm
+
+    fig = gcf()
+    im = None
+    field = runFunction()
+    im = vectorFieldMagnitude(field, **kwargs)
+    plotSetupFunction()
+
+    def updatefig(*args):
+        f = runFunction()
+        normed = norm(f, axis=2, ord=2)
+        if hasattr(f, 'mask'):
+            normed = np.ma.masked_array(normed, mask=f.mask[:, :, 0])
+        normed = np.swapaxes(normed, 0, 1)
+        im.set_array(normed)
+        plotUpdateFunction()
+        return im,
+
+    return animation.FuncAnimation(fig, updatefig, interval=interval, frames=frames)
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