python - Draw a plot of glyphs in Matplotlib -
i using matplotlib plot scientific visualizations heat map plots (as 1 below) sufficient. code written in python too.
however, need present more "elaborated" plot, consists of glyphs. following image (the second one) shows example:
in image, each point of plot glyph represents probability of vector field orientation. glyph draw circle main direction , standard deviation direction.
i similar. idea draw polar histogram @ each position , have plot comprised polar charts. however, don't think possible matplotlib; @ least don't have idea how can done. whole code written in python, wondering if somehow can stand matplotlib, or if should study how opengl or api/libraty.
thank you.
perhaps whole lot of this:
import matplotlib.pyplot plt import numpy np matplotlib.collections import patchcollection matplotlib.patches import wedge, circle math import degrees, pi fig, ax = plt.subplots() wedges = [] circles = [] x in np.arange(0, 3.3, .3): y in np.arange(0, 3.3, .3): theta, phi = np.random.random(2) # functions of (x,y) in reality v in (0, pi): wedges.append(wedge((x, y), .15, degrees(v - phi - theta/2), degrees(v - phi + theta/2), edgecolor='none'), ) circles.append(circle((x, y), .15, edgecolor='none')) colors = np.linspace(0, 1, len(circles)) # function of (x,y) in reality collection = patchcollection(circles, cmap=plt.cm.jet, alpha=0.2) collection.set_array(np.array(colors)) collection.set_edgecolor('none') ax.add_collection(collection) #wedgecolors = list(chain.from_iterable(repeat(i,2) in colors)) wedgecolors = np.array([colors, colors]).flatten('f') # no itertools collection = patchcollection(wedges, cmap=plt.cm.jet, alpha=1) collection.set_array(np.array(wedgecolors)) collection.set_edgecolor('none') ax.add_collection(collection) ax.set_xlim(0,3) ax.set_ylim(0,3) ax.set_aspect('equal') plt.show() (setting edgecolor has done (redone?) after collection.set_array call, apparently.)
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