我正在尝试绘制光线跟踪路径,其中像素值在matplotlib中变为非“-1”值。换句话说,我有跟随2D阵列,代表4条光线路径。由光线穿过的每个像素具有随机值。除了这些相交的像素,其余的都是“-1”。我希望在白色或不可见(不存在)中显示值“-1”。怎么可能?
import numpy as np
import scipy as sp
import pylab as pl
M = np.array([[ 0. , -1., -1., -1., -1., -1.],
[ 0.25, -1.,-1.,-1.,-1.,-1.],
[ 0.25, -1., -1., -1.,-1.,-1.],
[ 0.22, -1., -1., -1., -1.,-1.],
[ 0.16, -1., -1., -1., -1.,-1.],
[ 0.16, -1., -1., -1., -1.,-1.],
[ 0.13, -1., -1., -1., -1.,-1.],
[ 0.10, -1., -1., -1., -1.,-1.],
[-1., 0.06, 0.14, 0.087, 0.079,0.],
[ 0., 0.16, 0.10, 0.15, 0.16, 0.],
[-1., -1., 0., 0.004,-1., -1.]])
pl.subplot(111)
pl.imshow(M, origin='lower', interpolation='nearest')
pl.show()
答案 0 :(得分:4)
另一种方法是使用色彩映射的set_under
,set_over
和set_bad
属性(doc)
from copy import copy
# normalize data between vmin and vmax
my_norm = matplotlib.colors.Normalize(vmin=.25, vmax=.75, clip=False)
# clip=False is important, if clip=True, then the normalize function
# clips out of range values to 0 or 1 which defeats what we want to do here.
my_cmap = copy(cm.get_cmap('gray')) # make a copy so we don't mess up system copy
my_cmap.set_under('r', alpha=.5) # make locations over vmax translucent red
my_cmap.set_over('w', alpha=0) # make location under vmin transparent white
my_cmap.set_bad('g') # make location with invalid data green
test_data = np.random.rand(10, 10) # some random data between [0, 1]
test_data[5, 5] = np.nan # add one NaN
# plot!
imshow(test_data, norm=my_norm, cmap=my_cmap, interpolation='nearest')
我认为这是一种比手工制作蒙版数组更好的方法,因为让matplotlib
为你完成工作,它可以让你独立地明确设置三种不同条件的颜色。
答案 1 :(得分:2)
您可以使用蒙面数组。 http://docs.scipy.org/doc/numpy/reference/generated/numpy.ma.masked_where.html
>>> masked = np.ma.masked_where(M==-1,M)
>>> pl.subplot(111)
>>> pl.imshow(masked, origin='lower', interpolation='nearest')
>>> pl.show()