def __init__(self, colors, N, stops=None):
# store stops
self.stops = stops
# set colors
self.set_color(colors)
# initialize
Colormap.__init__(self, "test", N)
def __init__(self, colors: Sequence, N: int, stops=None):
""" initialize with the given colors and stops """
# store stops
self.stops = stops
# set colors
self.set_color(colors)
# initialize
Colormap.__init__(self, "test", N)
def __init__(self, accels, max_accel=None, min_accel=None):
self.accels = accels
self.points = len(self.accels)
if min_accel is not None:
self.min_accel = min_accel
else:
self.min_accel = np.min(accels)
if max_accel is not None:
self.max_accel = max_accel
else:
self.max_accel = np.max(accels)
Colormap.__init__(self, None, 255)
def __init__(self, source, name='Variable'):
self.name = None # new VariableColormap object
self.bad_set = False
self.set_source(source)
self.monochrome = False
Colormap.__init__(self, name, self.worklut.shape[0]-3)
self.canvases = {}
self.frames = set()
self.slope = 1.0
self.shift = 0.0
self.invrt = 1.0
self.scale = 'LINEAR'
self.auto = True
def __init__(self, cmap):
"""
Make a colormap dynamic with respect to a hinge point.
Dynamic colormaps are stretched to the ``[vmin, vmax]`` range,
by separately scaling the lower part of the colormap
(v < ``hinge``) and the upper part (v > ``hinge``).
For instance, a colormap with v range `[-1, 1]` and hinge at
`0` with `min_color` at `-1`, `hinge_color` and the ``hinge``,
and `max_color` at `1`, can be dynamically scaled to
``[-10, 5]`` with `min_color` at `-10`, `hinge_color` and the
``hinge``, and `max_color` at `5`::
<|min_color-----------hinge_color-----------max_color|>
-1 0 1
\
\
\
\
<|min_color-----------------hinge_color-----max_color|>
-10 0 5
See Also
--------
DynamicColormap.set_range
Scale the colormap to a new range, keeping, or overriding
the hinge point.
"""
self.monochrome = False
Colormap.__init__(self, cmap.name, cmap.N)
try:
self.values = cmap.values
except AttributeError:
self.values = np.linspace(-1, 1, self.N)
self._vmin = self.values[0]
try:
self._hinge = cmap.hinge
except AttributeError:
self._hinge = 0
self._vmax = self.values[-1]
try:
self.colors = cmap.colors
except AttributeError:
self.colors = cmap(self.values)
self.set_range(self.vmin, self.vmax, self.hinge)
self._lut = cmap._lut
self._isinit = True
self._set_extremes()
def __init__(self, source, name='Variable'):
self.name = None # new VariableColormap object
self.bad_set = False
self.set_source(source)
self.monochrome = False
Colormap.__init__(self, name, self.worklut.shape[0]-3)
self.canvases = {}
self.frames = set()
self.slope = 1.0
self.shift = 0.0
self.invrt = 1.0
self.scale = 'LINEAR'
self.auto = True
self.callback = None
def __init__(self, name, color, min_alpha=0.0, max_alpha=1.0, N=256):
Colormap.__init__(self, name, N)
self._color = color
self._min_alpha = min_alpha
self._max_alpha = max_alpha
def __init__(self, cmap, vmin=0, vmax=1):
if not has_mpl:
raise ImportError("Could not import all matplotlib dependencies!")
if isinstance(cmap, str):
Colormap.__init__(self, cmap, vmin, vmax)
cmap = mpl_get_cmap(cmap)
else:
try:
name = str(cmap.name)
except:
raise ValueError("The argument 'cmap' is of wrong type!")
Colormap.__init__(self, name, vmin, vmax)
# Obtain table to convert to .cpt:
if 'colors' in cmap.__dict__.keys():
if isinstance(cmap.colors, list):
N = len(cmap.colors)
elif isinstance(cmap.colors, np.ndarray):
N = cmap.colors.shape[0]
else:
raise ValueError("Data type not understood: " +
str(type(cmap.colors)))
self.cpt_table = np.zeros((N, 4))
self.cpt_table[:, 1:4] = cmap.colors
self.cpt_table[:, 0] = np.linspace(0, 1, N)
elif '_segmentdata' in cmap.__dict__.keys():
# Obtain the segments for all three colors:
segs = [
np.array(cmap._segmentdata['red']),
np.array(cmap._segmentdata['green']),
np.array(cmap._segmentdata['blue'])
]
changes = set([seg[0] for seg in segs[0]]) \
| set([seg[0] for seg in segs[1]]) \
| set([seg[0] for seg in segs[2]])
changes = np.sort(np.array(list(changes)))[1:]
colors = []
colors += [[0, segs[0][0, 1], segs[1][0, 1], segs[2][0, 1]]]
for x in changes:
c0 = [0, 0, 0]
c1 = [0, 0, 0]
for k in range(3):
id_ = np.argwhere(segs[k][:, 0] < x)[-1]
if id_ < len(segs[k]):
if segs[k][id_ + 1, 0] == x:
# Red value changes at x:
c0[k] = segs[k][id_ + 1, 1][0]
c1[k] = segs[k][id_ + 1, 2][0]
else:
# Red value does not change at x. Interpolate linearly:
x0 = segs[k][id_, 0][0]
v0 = segs[k][id_, 2][0]
x1 = segs[k][id_ + 1, 0][0]
v1 = segs[k][id_ + 1, 1][0]
c0[k] = (x - x0) / (x1 - x0) * v0 + (x1 - x) / (
x1 - x0) * v1
c1[k] = c0[k]
colors += [[x, c0[0], c0[1], c0[2]]]
if c0[0] != c1[0] or c0[0] != c1[0] or c0[0] != c1[0]:
colors += [[x, c1[0], c1[1], c1[2]]]
self.cpt_table = np.array(colors)
def __init__(self, name, color, min_alpha = 0.0, max_alpha = 1.0, N=256):
Colormap.__init__(self, name, N)
self._color = color
self._min_alpha = min_alpha
self._max_alpha = max_alpha
def __init__(self, name, color, N=256):
Colormap.__init__(self, name, N)
self.color = colorConverter.to_rgb(color)
