How to plot a 2d structured mesh in matplotlib
I'd use two linecollections for this:
import numpy as npimport matplotlib.pyplot as pltfrom matplotlib.collections import LineCollectionx, y = np.meshgrid(np.linspace(0,1, 11), np.linspace(0, 0.6, 7))plt.scatter(x, y)segs1 = np.stack((x,y), axis=2)segs2 = segs1.transpose(1,0,2)plt.gca().add_collection(LineCollection(segs1))plt.gca().add_collection(LineCollection(segs2))plt.show()
Also see How to plot using matplotlib (python) colah's deformed grid?
Because if the grid is not deformed, it would be more efficient to draw a single linecollection, like
import numpy as npimport matplotlib.pyplot as pltfrom matplotlib.collections import LineCollectionx, y = np.meshgrid(np.linspace(0,1, 11), np.linspace(0, 0.6, 7))segs1 = np.stack((x[:,[0,-1]],y[:,[0,-1]]), axis=2)segs2 = np.stack((x[[0,-1],:].T,y[[0,-1],:].T), axis=2)plt.gca().add_collection(LineCollection(np.concatenate((segs1, segs2))))plt.autoscale()plt.show()
You can np.transpose
the points you already have, while using a line plot()
rather than scatter()
.
import numpy as npimport matplotlib.pyplot as pltx, y = np.meshgrid(np.linspace(0,1, 11), np.linspace(0, 0.6, 7))plt.plot(x, y) # use plot, not scatterplt.plot(np.transpose(x), np.transpose(y)) # add this hereplt.show()
IIUC, vlines
and hlines
would do:
plt.vlines(np.linspace(0,1,11), 0, 0.6)plt.hlines(np.linspace(0,0.6,7), 0, 1)
If you already have mesh x,y
:
plt.vlines(x[0], *y[[0,-1],0])plt.hlines(y[:,0], *x[0, [0,-1]])
Out: