I want to superimpose Circles on top of a 2D plot in Matplotlib as position markers. Currently they look very much like what they are, colored Circles:
import matplotlib.pyplot as plt
plt.axes()
circle = plt.Circle((0, 0), radius=0.3,fc='b')
circle1 = plt.Circle((1, 1), radius=0.3, fc='y')
circle2 = plt.Circle((1, 0), radius=0.3, fc='r')
plt.gca().add_patch(circle)
plt.gca().add_patch(circle1)
plt.gca().add_patch(circle2)
plt.axis('scaled')
plt.show()
Is there a way to give theses circles the appearance of a 3D object without using mayavi?
These are examples of my goal:
EDIT
With the information in the link supplied by user3419537 and the idea presented here Custom color maps i created the following idea, that lets me somehow plot circles filled with a gradient:
import numpy as np
import matplotlib.colors as mcolors
def make_colormap(seq):
"""Return a LinearSegmentedColormap
seq: a sequence of floats and RGB-tuples. The floats should be increasing
and in the interval (0,1).
"""
seq = [(None,) * 3, 0.0] + list(seq) + [1.0, (None,) * 3]
cdict = {'red': [], 'green': [], 'blue': []}
for i, item in enumerate(seq):
if isinstance(item, float):
r1, g1, b1 = seq[i - 1]
r2, g2, b2 = seq[i + 1]
cdict['red'].append([item, r1, r2])
cdict['green'].append([item, g1, g2])
cdict['blue'].append([item, b1, b2])
return mcolors.LinearSegmentedColormap('CustomMap', cdict)
def gauplot(centers, radiuses, xr=None, yr=None, P_color='black'):
c = mcolors.ColorConverter().to_rgb
# Maybe it is possible to change the values to get a better gradient?
current_cmap = make_colormap([c(P_color),0.05,c(P_color),0.1,c(P_color), c('white')])
nx, ny = 1000.,1000.
xgrid, ygrid = np.mgrid[xr[0]:xr[1]:(xr[1]-xr[0])/nx,yr[0]:yr[1]:(yr[1]-yr[0])/ny]
im = xgrid*0 + np.nan
xs = np.array([np.nan])
ys = np.array([np.nan])
fis = np.concatenate((np.linspace(-np.pi,np.pi,100), [np.nan]) )
#cmap = plt.cm.gray
cmap = current_cmap
cmap.set_bad('white')
thresh = 2.8
for curcen,currad in zip(centers,radiuses):
curim=(((xgrid-curcen[0])**2+(ygrid-curcen[1])**2)**.5)/currad*thresh
im[curim<thresh]=np.exp(-.5*curim**2)[curim<thresh]
xs = np.append(xs, curcen[0] + currad * np.cos(fis))
ys = np.append(ys, curcen[1] + currad * np.sin(fis))
plt.imshow(im.T, cmap=cmap, extent=xr+yr)
plt.plot(xs, ys, 'r-')
gauplot([(0,0), (2,3), (5,1), (6, 7), (6.1, 6.1)], [.3,.4, .5, 1, .4], [-1,10], [-1,10],P_color="#75507b")
plt.show()
Unfortunately only the red circles appear at the right position:
I would appreciate a tip what might be the cause of this.
At the moment i am plotting my circles in the script in question like this:
circle = Circle(x,y,*kwargs)
plt.gca().add_patch(circle)
would it be possible to adapt the above solution in a way that it can plot circles with different colors at the position (x,y) and superimpose them to an existing plot as well?
