I am looking for a way to rotate a plot generated in matplotlib-pyplot (Python libraries) by 45 degrees (so that instead of a square shape you would have a diamond shape, for example), anyone know if this can be done?
One way I can think of is to use a rotation filter on all the data so that it appears rotated, but then the plot itself will still be in the original orientation.
I want to be able to use the matplotlib interactive features, so saving as an image and then rotating won't work.
Also, I want to use pyplot functions to draw the plot, so using a different library for the plotting is not an ideal solution.
Ok so currently the only partial solution I found is to apply a rotation to the plot. This allows to use the interactive interface that matplotlib/pyplot offers.
For dot plots like plot() and scatter() this is trivial, but I was specifically interested in rotating imshow(). This link discusses the transform keyword that could have potentially been used for this task, but it is apparently not working.
Fortunately, I found a workaround using pcolormesh(). pcolormesh() plots a quadrilateral mesh and allows you to specify the corner coordinates. So, the answer is to just apply the relevant transformations to the corner coordinates. Note however, that pcolormesh() works a bit different than imshow - it plots your matrix flipped.
I haven't seen this solution anywhere on the web, so here is some code for pcolormesh()/imshow() rotated by 45 degrees:
import matplotlib.pyplot as plt import numpy as np def pcolormesh_45deg(C): n = C.shape # create rotation/scaling matrix t = np.array([[1,0.5],[-1,0.5]]) # create coordinate matrix and transform it A = np.dot(np.array([(i,i) for i in itertools.product(range(n,-1,-1),range(0,n+1,1))]),t) # plot plt.pcolormesh(A[:,1].reshape(n+1,n+1),A[:,0].reshape(n+1,n+1),np.flipud(C))
Based on Bitwise anwer, you can use the following function:
def pcolormesh_45deg(C, ax=None, xticks=None, xticklabels=None, yticks=None, yticklabels=None, aspect='equal', rotation=45, *args, **kwargs): import itertools if ax is None: ax = plt.gca() n = C.shape # create rotation/scaling matrix t = np.array([[1, .5], [-1, .5]]) # create coordinate matrix and transform it product = itertools.product(range(n, -1, -1), range(0, n + 1, 1)) A = np.dot(np.array([(ii, ii) for ii in product]), t) # plot ax.pcolormesh((2 * A[:, 1].reshape(n + 1, n + 1) - n), A[:, 0].reshape(n + 1, n + 1), np.flipud(C), *args, **kwargs) xticks = np.linspace(0, n - 1, n, dtype=int) if xticks is None else xticks yticks = np.linspace(0, n - 1, n, dtype=int) if yticks is None else yticks if xticks is not None: xticklabels = xticks if xticklabels is None else xticklabels for tick, label, in zip(xticks, xticklabels): ax.scatter(-n + tick + .5, tick + .5, marker='x', color='k') ax.text(-n + tick + .5, tick + .5, label, horizontalalignment='right', rotation=-rotation) if yticks is not None: yticklabels = yticks if yticklabels is None else yticklabels for tick, label, in zip(yticks, yticklabels): ax.scatter(tick + .5, n - tick - .5, marker='x', color='k') ax.text(tick + .5, n - tick - .5, label, horizontalalignment='left', rotation=rotation) if aspect: ax.set_aspect(aspect) ax.set_xlim(-n, n) ax.set_ylim(-n, n) ax.plot([-n, 0, n, 0., -n], [0, n, 0, -n, 0], color='k') ax.axis('off') return ax