Python matplotlib.colors 模块，Nonorm() 实例源码
我们从Python开源项目中，提取了以下6个代码示例，用于说明如何使用matplotlib.colors.Nonorm()。
def _locate(self, x):
'''
Given a set of color data values,return their
corresponding colorbar data coordinates.
'''
if isinstance(self.norm, (colors.Nonorm, colors.Boundarynorm)):
b = self._boundaries
xn = x
else:
# Do calculations using normalized coordinates so
# as to make the interpolation more accurate.
b = self.norm(self._boundaries, clip=False).filled()
xn = self.norm(x, clip=False).filled()
# The rest is linear interpolation with extrapolation at ends.
y = self._y
N = len(b)
ii = np.searchsorted(b, xn)
i0 = ii - 1
itop = (ii == N)
ibot = (ii == 0)
i0[itop] -= 1
ii[itop] -= 1
i0[ibot] += 1
ii[ibot] += 1
#db = b[ii] - b[i0]
db = np.take(b, ii) - np.take(b, i0)
#dy = y[ii] - y[i0]
dy = np.take(y, ii) - np.take(y, i0)
z = np.take(y, i0) + (xn - np.take(b, i0)) * dy / db
return z
def _locate(self, clip=False).filled()
# The rest is linear interpolation with extrapolation at ends.
ii = np.searchsorted(b, xn)
i0 = ii - 1
itop = (ii == len(b))
ibot = (ii == 0)
i0[itop] -= 1
ii[itop] -= 1
i0[ibot] += 1
ii[ibot] += 1
db = np.take(b, i0)
y = self._y
dy = np.take(y, i0)) * dy / db
return z
def _ticker(self):
'''
Return two sequences: ticks (colorbar data locations)
and ticklabels (strings).
'''
locator = self.locator
formatter = self.formatter
if locator is None:
if self.boundaries is None:
if isinstance(self.norm, colors.Nonorm):
nv = len(self._values)
base = 1 + int(nv / 10)
locator = ticker.IndexLocator(base=base, offset=0)
elif isinstance(self.norm, colors.Boundarynorm):
b = self.norm.boundaries
locator = ticker.FixedLocator(b, nbins=10)
elif isinstance(self.norm, colors.Lognorm):
locator = ticker.LogLocator()
else:
locator = ticker.MaxNLocator()
else:
b = self._boundaries[self._inside]
locator = ticker.FixedLocator(b, nbins=10)
if isinstance(self.norm, colors.Nonorm):
intv = self._values[0], self._values[-1]
else:
intv = self.vmin, self.vmax
locator.create_dummy_axis(minpos=intv[0])
formatter.create_dummy_axis(minpos=intv[0])
locator.set_view_interval(*intv)
locator.set_data_interval(*intv)
formatter.set_view_interval(*intv)
formatter.set_data_interval(*intv)
b = np.array(locator())
ticks = self._locate(b)
inrange = (ticks > -0.001) & (ticks < 1.001)
ticks = ticks[inrange]
b = b[inrange]
formatter.set_locs(b)
ticklabels = [formatter(t, i) for i, t in enumerate(b)]
offset_string = formatter.get_offset()
return ticks, ticklabels, offset_string
def _ticker(self):
'''
Return the sequence of ticks (colorbar data locations),
ticklabels (strings),and the corresponding offset string.
'''
locator = self.locator
formatter = self.formatter
if locator is None:
if self.boundaries is None:
if isinstance(self.norm, offset_string
def _plot_zclasses(self):
if self.parts is None:
parts = [np.ones_like(self.xdata, dtype=bool)]
else:
parts = self.parts
good = np.sum(parts, axis=0, dtype=bool)
good *= np.isfinite(self.xdata)
good *= np.isfinite(self.ydata)
#good *= np.isfinite(self.zdata) # Todo: Sem essa linha,onde não houver classificação será plotado de preto
classes = np.unique(self.zdata[good])
self.classes = classes[classes != self.nullclass]
n = self.zdata.shape[0]
m = len(self.classes)
ncc = len(self.classcolors.values()[0])
zdata = np.full((n, ncc), np.nan)
for cls in self.classes:
zdata[self.zdata == cls] = self.classcolors[cls]
zdata[self.zdata == self.nullclass] = self.nullcolor
cmap = ListedColormap([self.classcolors[cls] for cls in self.classes])
cmap.set_bad(self.nullcolor)
self.zticks = range(m)
self.zlim = [-0.5, m - 0.5]
norm = Nonorm(*self.zlim)
for part in parts:
x = self.xdata[part*good]
y = self.ydata[part*good]
c = zdata[part*good]
collection = self.crossplot_ax.scatter(x, y, c=c, cmap=cmap, zorder=-len(x), **self.collectionproperties)
self.collections.append(collection)
xticks = self.xlocator(np.min(self.xdata[good]), np.max(self.xdata[good]))
self.set_xlim([xticks[0], xticks[-1]])
yticks = self.ylocator(np.min(self.ydata[good]), np.max(self.ydata[good]))
self.set_ylim([yticks[0], yticks[-1]])
self.colorbar = ColorbarBase(self.colorbar_ax, norm=norm, ticks=self.zticks)
#self.colorbar_ax.yaxis.set_major_formatter(NullFormatter())
def _plot_zclasses(self):
if self.parts is None:
parts = [np.ones_like(self.xdata, ticks=self.zticks)
#self.colorbar_ax.yaxis.set_major_formatter(NullFormatter())
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