def colormap(x, col0=None, col1=None):
"""Colorize a 2D grayscale array.
Arguments:
* x:an NxM array with values in [0,1].
* col0=None: a tuple (H, S, V) corresponding to color 0. By default, a
rainbow color gradient is used.
* col1=None: a tuple (H, S, V) corresponding to color 1.
Returns:
* y: an NxMx3 array with a rainbow color palette.
"""
# record values to be removed
removed = x == -1
x[np.isnan(x)] = 0.
# x -= x.min()
# x *= (1. / x.max())
# Set the maximum values above which the max color should be used.
max = .1
x = np.clip(x / max, 0., 1.)
# Gamma correction. Doesn't look very good.
# x = x ** .2
shape = x.shape
if col0 is None:
col0 = (.67, .91, .65)
if col1 is None:
col1 = (0., 1., 1.)
col0 = np.array(col0).reshape((1, 1, -1))
col1 = np.array(col1).reshape((1, 1, -1))
col0 = np.tile(col0, x.shape + (1, ))
col1 = np.tile(col1, x.shape + (1, ))
x = np.tile(x.reshape(shape + (1, )), (1, 1, 3))
y = hsv_to_rgb(col0 + (col1 - col0) * x)
# value of -1 = black
y[removed, :] = 0
# Remove diagonal.
n = y.shape[0]
y[xrange(n), xrange(n), :] = 0
return y
def colormap(x, col0=None, col1=None):
"""Colorize a 2D grayscale array.
Arguments:
* x:an NxM array with values in [0,1].
* col0=None: a tuple (H, S, V) corresponding to color 0. By default, a
rainbow color gradient is used.
* col1=None: a tuple (H, S, V) corresponding to color 1.
Returns:
* y: an NxMx3 array with a rainbow color palette.
"""
# record values to be removed
removed = x == -1
x[np.isnan(x)] = 0.
# x -= x.min()
# x *= (1. / x.max())
# Set the maximum values above which the max color should be used.
max = .1
x = np.clip(x / max, 0., 1.)
# Gamma correction. Doesn't look very good.
# x = x ** .2
shape = x.shape
if col0 is None:
col0 = (.67, .91, .65)
if col1 is None:
col1 = (0., 1., 1.)
col0 = np.array(col0).reshape((1, 1, -1))
col1 = np.array(col1).reshape((1, 1, -1))
col0 = np.tile(col0, x.shape + (1,))
col1 = np.tile(col1, x.shape + (1,))
x = np.tile(x.reshape(shape + (1,)), (1, 1, 3))
y = hsv_to_rgb(col0 + (col1 - col0) * x)
# value of -1 = black
y[removed,:] = 0
# Remove diagonal.
n = y.shape[0]
y[xrange(n), xrange(n), :] = 0
return y
def colormap(x):
"""Colorize a 2D grayscale array.
Arguments:
* x:an NxM array with values in [0,1]
Returns:
* y: an NxMx3 array with a rainbow color palette.
"""
x = np.clip(x, 0., 1.)
# initial and final gradient colors, here rainbow gradient
col0 = np.array([.67, .91, .65]).reshape((1, 1, -1))
col1 = np.array([0., 1., 1.]).reshape((1, 1, -1))
col0 = np.tile(col0, x.shape + (1,))
col1 = np.tile(col1, x.shape + (1,))
x = np.tile(x.reshape(x.shape + (1,)), (1, 1, 3))
return hsv_to_rgb(col0 + (col1 - col0) * x)
def colormap(x):
"""Colorize a 2D grayscale array.
Arguments:
* x:an NxM array with values in [0,1]
Returns:
* y: an NxMx3 array with a rainbow color palette.
"""
x = np.clip(x, 0., 1.)
# initial and final gradient colors, here rainbow gradient
col0 = np.array([.67, .91, .65]).reshape((1, 1, -1))
col1 = np.array([0., 1., 1.]).reshape((1, 1, -1))
col0 = np.tile(col0, x.shape + (1, ))
col1 = np.tile(col1, x.shape + (1, ))
x = np.tile(x.reshape(x.shape + (1, )), (1, 1, 3))
return hsv_to_rgb(col0 + (col1 - col0) * x)
