How to add a color bar to this example?

Question

In this example, color correlates with the radius of each bar. How to add a color bar to this plot?

My code mimics the projection of the "pink diagram", which is essentially a histogram on the polar projection.

here is part of it:

angle = radians(10.) patches = radians(360.)/angle theta = np.arange(0,radians(360.),angle) count = [0]*patches for i, item in enumerate(some_array_of_azimuth_directions): temp = int((item - item%angle)/angle) count[temp] += 1 width = angle * np.ones(patches) # force square figure and square axes looks better for polar, IMO fig = plt.figure(figsize=(8,8)) ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True) rmax = max(count) + 1 ax.set_rlim(0,rmax) ax.set_theta_offset(np.pi/2) ax.set_thetagrids(np.arange(0,360,10)) ax.set_theta_direction(-1) # project strike distribution as histogram bars bars = ax.bar(theta, count, width=width) r_values = [] colors = [] for r,bar in zip(count, bars): r_values.append(r/float(max(count))) colors.append(cm.jet(r_values[-1], alpha=0.5)) bar.set_facecolor(colors[-1]) bar.set_edgecolor('grey') bar.set_alpha(0.5) # Add colorbar, make sure to specify tick locations to match desired ticklabels colorlist = [] r_values.sort() values = [] for val in r_values: if val not in values: values.append(val*float(max(count))) color = cm.jet(val, alpha=0.5) if color not in colorlist: colorlist.append(color) cpt = mpl.colors.ListedColormap(colorlist) bounds = range(max(count)+1) norm = mpl.colors.BoundaryNorm(values, cpt.N-1) cax = fig.add_axes([0.97, 0.3, 0.03, 0.4]) cb = mpl.colorbar.ColorbarBase(cax, cmap=cpt, norm=norm, boundaries=bounds, # Make the length of each extension # the same as the length of the # interior colors: extendfrac='auto', ticks=[bounds[i] for i in range(0, len(bounds), 2)], #ticks=bounds, spacing='uniform') 

and here is the result:

as you can see, the color bar is not quite right. I've played so much with code, and I just can't figure out how to properly normalize the color bar.

Answer 1

The easiest way is to use PatchCollection and pass in your "z" (ie the values ​​you want to mark) as array kwarg.

As a simple example:

 import itertools import matplotlib.pyplot as plt from matplotlib.patches import Rectangle from matplotlib.collections import PatchCollection import numpy as np def main(): fig = plt.figure() ax = fig.add_subplot(111, projection='polar') x = np.radians(np.arange(0, 360, 10)) y = np.random.random(x.size) z = np.random.random(y.size) cmap = plt.get_cmap('cool') coll = colored_bar(x, y, z, ax=ax, width=np.radians(10), cmap=cmap) fig.colorbar(coll) ax.set_yticks([0.5, 1.0]) plt.show() def colored_bar(left, height, z=None, width=0.8, bottom=0, ax=None, **kwargs): if ax is None: ax = plt.gca() width = itertools.cycle(np.atleast_1d(width)) bottom = itertools.cycle(np.atleast_1d(bottom)) rects = [] for x, y, h, w in zip(left, bottom, height, width): rects.append(Rectangle((x,y), w, h)) coll = PatchCollection(rects, array=z, **kwargs) ax.add_collection(coll) ax.autoscale() return coll if __name__ == '__main__': main() 

If you need a discrete color map, the easiest way is to specify the number of intervals you want when you call plt.get_cmap . For example, in the above code, if you replace the line cmap = plt.get_cmap('cool') with:

 cmap = plt.get_cmap('cool', 5) 

Then you get a discrete color palette with 5 intervals. (Alternatively, you can pass the ListedColormap that you created in your example.)

If you want a “fully functional” draw chart function, you can do something like this:

 import itertools import matplotlib.pyplot as plt from matplotlib.patches import Rectangle from matplotlib.collections import PatchCollection import numpy as np def main(): azi = np.random.normal(20, 30, 100) z = np.cos(np.radians(azi + 45)) plt.figure(figsize=(5,6)) plt.subplot(111, projection='polar') coll = rose(azi, z=z, bidirectional=True) plt.xticks(np.radians(range(0, 360, 45)), ['N', 'NE', 'E', 'SE', 'S', 'SW', 'W', 'NW']) plt.colorbar(coll, orientation='horizontal') plt.xlabel('A rose diagram colored by a second variable') plt.rgrids(range(5, 20, 5), angle=290) plt.show() def rose(azimuths, z=None, ax=None, bins=30, bidirectional=False, color_by=np.mean, **kwargs): """Create a "rose" diagram (aka circular histogram). Parameters: ----------- azimuths: sequence of numbers The observed azimuths in degrees. z: sequence of numbers (optional) A second, co-located variable to color the plotted rectangles by. ax: a matplotlib Axes (optional) The axes to plot on. Defaults to the current axes. bins: int or sequence of numbers (optional) The number of bins or a sequence of bin edges to use. bidirectional: boolean (optional) Whether or not to treat the observed azimuths as bi-directional measurements (ie if True, 0 and 180 are identical). color_by: function or string (optional) A function to reduce the binned z values with. Alternately, if the string "count" is passed in, the displayed bars will be colored by their y-value (the number of azimuths measurements in that bin). Additional keyword arguments are passed on to PatchCollection. Returns: -------- A matplotlib PatchCollection """ azimuths = np.asanyarray(azimuths) if color_by == 'count': z = np.ones_like(azimuths) color_by = np.sum if ax is None: ax = plt.gca() ax.set_theta_direction(-1) ax.set_theta_offset(np.radians(90)) if bidirectional: other = azimuths + 180 azimuths = np.concatenate([azimuths, other]) if z is not None: z = np.concatenate([z, z]) # Convert to 0-360, in case negative or >360 azimuths are passed in. azimuths[azimuths > 360] -= 360 azimuths[azimuths < 0] += 360 counts, edges = np.histogram(azimuths, range=[0, 360], bins=bins) if z is not None: idx = np.digitize(azimuths, edges) z = np.array([color_by(z[idx == i]) for i in range(1, idx.max() + 1)]) z = np.ma.masked_invalid(z) edges = np.radians(edges) coll = colored_bar(edges[:-1], counts, z=z, width=np.diff(edges), ax=ax, **kwargs) return coll def colored_bar(left, height, z=None, width=0.8, bottom=0, ax=None, **kwargs): """A bar plot colored by a scalar sequence.""" if ax is None: ax = plt.gca() width = itertools.cycle(np.atleast_1d(width)) bottom = itertools.cycle(np.atleast_1d(bottom)) rects = [] for x, y, h, w in zip(left, bottom, height, width): rects.append(Rectangle((x,y), w, h)) coll = PatchCollection(rects, array=z, **kwargs) ax.add_collection(coll) ax.autoscale() return coll if __name__ == '__main__': main()