def update(self, data):
"""
Map new values to integer identifiers.
Parameters
----------
data : iterable of str or bytes
Raises
------
TypeError
If elements in *data* are neither str nor bytes.
"""
data = np.atleast_1d(np.array(data, dtype=object))
# check if convertible to number:
convertible = True
for val in OrderedDict.fromkeys(data):
# OrderedDict just iterates over unique values in data.
_api.check_isinstance((str, bytes), value=val)
if convertible:
# this will only be called so long as convertible is True.
convertible = self._str_is_convertible(val)
if val not in self._mapping:
self._mapping[val] = next(self._counter)
if convertible:
_log.info('Using categorical units to plot a list of strings '
'that are all parsable as floats or dates. If these '
'strings should be plotted as numbers, cast to the '
'appropriate data type before plotting.')
def register_cmap(name=None, cmap=None, *, override_builtin=False):
"""
Add a colormap to the set recognized by :func:`get_cmap`.
Register a new colormap to be accessed by name ::
LinearSegmentedColormap('swirly', data, lut)
register_cmap(cmap=swirly_cmap)
Parameters
----------
name : str, optional
The name that can be used in :func:`get_cmap` or :rc:`image.cmap`
If absent, the name will be the :attr:`~matplotlib.colors.Colormap.name`
attribute of the *cmap*.
cmap : matplotlib.colors.Colormap
Despite being the second argument and having a default value, this
is a required argument.
override_builtin : bool
Allow built-in colormaps to be overridden by a user-supplied
colormap.
Please do not use this unless you are sure you need it.
Notes
-----
Registering a colormap stores a reference to the colormap object
which can currently be modified and inadvertently change the global
colormap state. This behavior is deprecated and in Matplotlib 3.5
the registered colormap will be immutable.
"""
_api.check_isinstance((str, None), name=name)
if name is None:
try:
name = cmap.name
except AttributeError as err:
raise ValueError("Arguments must include a name or a "
"Colormap") from err
if name in _cmap_registry:
if not override_builtin and name in __builtin_cmaps:
msg = f"Trying to re-register the builtin cmap {name!r}."
raise ValueError(msg)
else:
msg = f"Trying to register the cmap {name!r} which already exists."
_api.warn_external(msg)
if not isinstance(cmap, colors.Colormap):
raise ValueError("You must pass a Colormap instance. "
f"You passed {cmap} a {type(cmap)} object.")
cmap._global = True
_cmap_registry[name] = cmap
return
def __init__(self, scale, tfm, texname, vf):
_api.check_isinstance(bytes, texname=texname)
self._scale = scale
self._tfm = tfm
self.texname = texname
self._vf = vf
self.size = scale * (72.0 / (72.27 * 2**16))
try:
nchars = max(tfm.width) + 1
except ValueError:
nchars = 0
self.widths = [(1000 * tfm.width.get(char, 0)) >> 20
for char in range(nchars)]
def validate_hatch(s):
r"""
Validate a hatch pattern.
A hatch pattern string can have any sequence of the following
characters: ``\ / | - + * . x o O``.
"""
if not isinstance(s, str):
raise ValueError("Hatch pattern must be a string")
_api.check_isinstance(str, hatch_pattern=s)
unknown = set(s) - {'\\', '/', '|', '-', '+', '*', '.', 'x', 'o', 'O'}
if unknown:
raise ValueError("Unknown hatch symbol(s): %s" % list(unknown))
return s
def __init__(self, axes, spine_type, path, **kwargs):
"""
Parameters
----------
axes : `~matplotlib.axes.Axes`
The `~.axes.Axes` instance containing the spine.
spine_type : str
The spine type.
path : `~matplotlib.path.Path`
The `.Path` instance used to draw the spine.
Other Parameters
----------------
**kwargs
Valid keyword arguments are:
%(Patch:kwdoc)s
"""
super().__init__(**kwargs)
self.axes = axes
self.set_figure(self.axes.figure)
self.spine_type = spine_type
self.set_facecolor('none')
self.set_edgecolor(rcParams['axes.edgecolor'])
self.set_linewidth(rcParams['axes.linewidth'])
self.set_capstyle('projecting')
self.axis = None
self.set_zorder(2.5)
self.set_transform(self.axes.transData) # default transform
self._bounds = None # default bounds
# Defer initial position determination. (Not much support for
# non-rectangular axes is currently implemented, and this lets
# them pass through the spines machinery without errors.)
self._position = None
_api.check_isinstance(matplotlib.path.Path, path=path)
self._path = path
# To support drawing both linear and circular spines, this
# class implements Patch behavior three ways. If
# self._patch_type == 'line', behave like a mpatches.PathPatch
# instance. If self._patch_type == 'circle', behave like a
# mpatches.Ellipse instance. If self._patch_type == 'arc', behave like
# a mpatches.Arc instance.
self._patch_type = 'line'
# Behavior copied from mpatches.Ellipse:
# Note: This cannot be calculated until this is added to an Axes
self._patch_transform = mtransforms.IdentityTransform()
def norm(self, norm):
_api.check_isinstance((colors.Normalize, None), norm=norm)
if norm is None:
norm = colors.Normalize()
if norm is self.norm:
# We aren't updating anything
return
in_init = self.norm is None
# Remove the current callback and connect to the new one
if not in_init:
self.norm.callbacks.disconnect(self._id_norm)
self._norm = norm
self._id_norm = self.norm.callbacks.connect('changed', self.changed)
if not in_init:
self.changed()
def register(self, cmap, *, name=None, force=False):
"""
Register a new colormap.
The colormap name can then be used as a string argument to any ``cmap``
parameter in Matplotlib. It is also available in ``pyplot.get_cmap``.
The colormap registry stores a copy of the given colormap, so that
future changes to the original colormap instance do not affect the
registered colormap. Think of this as the registry taking a snapshot
of the colormap at registration.
Parameters
----------
cmap : matplotlib.colors.Colormap
The colormap to register.
name : str, optional
The name for the colormap. If not given, ``cmap.name`` is used.
force : bool, default: False
If False, a ValueError is raised if trying to overwrite an already
registered name. True supports overwriting registered colormaps
other than the builtin colormaps.
"""
_api.check_isinstance(colors.Colormap, cmap=cmap)
name = name or cmap.name
if name in self:
if not force:
# don't allow registering an already existing cmap
# unless explicitly asked to
raise ValueError(
f'A colormap named "{name}" is already registered.')
elif (name in self._builtin_cmaps
and not self._allow_override_builtin):
# We don't allow overriding a builtin unless privately
# coming from register_cmap()
raise ValueError("Re-registering the builtin cmap "
f"{name!r} is not allowed.")
# Warn that we are updating an already existing colormap
_api.warn_external(f"Overwriting the cmap {name!r} "
"that was already in the registry.")
self._cmaps[name] = cmap.copy()
def __call__(self, n=1, timeout=30):
"""Blocking call to retrieve *n* events."""
_api.check_isinstance(Integral, n=n)
self.n = n
self.events = []
if hasattr(self.fig.canvas, "manager"):
# Ensure that the figure is shown, if we are managing it.
self.fig.show()
# Connect the events to the on_event function call.
self.callbacks = [self.fig.canvas.mpl_connect(name, self.on_event)
for name in self.eventslist]
try:
# Start event loop.
self.fig.canvas.start_event_loop(timeout=timeout)
finally: # Run even on exception like ctrl-c.
# Disconnect the callbacks.
self.cleanup()
# Return the events in this case.
return self.events
def register_cmap(name=None, cmap=None, *, override_builtin=False):
"""
Add a colormap to the set recognized by :func:`get_cmap`.
Register a new colormap to be accessed by name ::
LinearSegmentedColormap('swirly', data, lut)
register_cmap(cmap=swirly_cmap)
Parameters
----------
name : str, optional
The name that can be used in :func:`get_cmap` or :rc:`image.cmap`
If absent, the name will be the :attr:`~matplotlib.colors.Colormap.name`
attribute of the *cmap*.
cmap : matplotlib.colors.Colormap
Despite being the second argument and having a default value, this
is a required argument.
override_builtin : bool
Allow built-in colormaps to be overridden by a user-supplied
colormap.
Please do not use this unless you are sure you need it.
"""
_api.check_isinstance((str, None), name=name)
if name is None:
try:
name = cmap.name
except AttributeError as err:
raise ValueError("Arguments must include a name or a "
"Colormap") from err
# override_builtin is allowed here for backward compatibility
# this is just a shim to enable that to work privately in
# the global ColormapRegistry
_colormaps._allow_override_builtin = override_builtin
_colormaps.register(cmap, name=name, force=override_builtin)
_colormaps._allow_override_builtin = False
def set_norm(self, norm):
"""
Set the normalization instance.
Parameters
----------
norm : `.Normalize` or None
Notes
-----
If there are any colorbars using the mappable for this norm, setting
the norm of the mappable will reset the norm, locator, and formatters
on the colorbar to default.
"""
_api.check_isinstance((colors.Normalize, None), norm=norm)
in_init = self.norm is None
if norm is None:
norm = colors.Normalize()
self.norm = norm
if not in_init:
self.changed() # Things are not set up properly yet.
def refine_field(self, z, triinterpolator=None, subdiv=3):
"""
Refine a field defined on the encapsulated triangulation.
Parameters
----------
z : array-like of length ``n_points``
Values of the field to refine, defined at the nodes of the
encapsulated triangulation. (``n_points`` is the number of points
in the initial triangulation)
triinterpolator : `~matplotlib.tri.TriInterpolator`, optional
Interpolator used for field interpolation. If not specified,
a `~matplotlib.tri.CubicTriInterpolator` will be used.
subdiv : int, default: 3
Recursion level for the subdivision.
Each triangle is divided into ``4**subdiv`` child triangles.
Returns
-------
refi_tri : `~matplotlib.tri.Triangulation`
The returned refined triangulation.
refi_z : 1D array of length: *refi_tri* node count.
The returned interpolated field (at *refi_tri* nodes).
"""
if triinterpolator is None:
interp = matplotlib.tri.CubicTriInterpolator(
self._triangulation, z)
else:
_api.check_isinstance(matplotlib.tri.TriInterpolator,
triinterpolator=triinterpolator)
interp = triinterpolator
refi_tri, found_index = self.refine_triangulation(
subdiv=subdiv, return_tri_index=True)
refi_z = interp._interpolate_multikeys(refi_tri.x,
refi_tri.y,
tri_index=found_index)[0]
return refi_tri, refi_z
def __init__(self, triangulation):
_api.check_isinstance(Triangulation, triangulation=triangulation)
self._triangulation = triangulation
def _validate_cmap(s):
_api.check_isinstance((str, Colormap), cmap=s)
return s
def tripcolor(ax,
*args,
alpha=1.0,
norm=None,
cmap=None,
vmin=None,
vmax=None,
shading='flat',
facecolors=None,
**kwargs):
"""
Create a pseudocolor plot of an unstructured triangular grid.
Call signatures::
tripcolor(triangulation, C, *, ...)
tripcolor(x, y, C, *, [triangles=triangles], [mask=mask], ...)
The triangular grid can be specified either by passing a `.Triangulation`
object as the first parameter, or by passing the points *x*, *y* and
optionally the *triangles* and a *mask*. See `.Triangulation` for an
explanation of these parameters.
If neither of *triangulation* or *triangles* are given, the triangulation
is calculated on the fly. In this case, it does not make sense to provide
colors at the triangle faces via *C* or *facecolors* because there are
multiple possible triangulations for a group of points and you don't know
which triangles will be constructed.
Parameters
----------
triangulation : `.Triangulation`
An already created triangular grid.
x, y, triangles, mask
Parameters defining the triangular grid. See `.Triangulation`.
This is mutually exclusive with specifying *triangulation*.
C : array-like
The color values, either for the points or for the triangles. Which one
is automatically inferred from the length of *C*, i.e. does it match
the number of points or the number of triangles. If there are the same
number of points and triangles in the triangulation it is assumed that
color values are defined at points; to force the use of color values at
triangles use the keyword argument ``facecolors=C`` instead of just
``C``.
This parameter is position-only.
facecolors : array-like, optional
Can be used alternatively to *C* to specify colors at the triangle
faces. This parameter takes precedence over *C*.
shading : {'flat', 'gouraud'}, default: 'flat'
If 'flat' and the color values *C* are defined at points, the color
values used for each triangle are from the mean C of the triangle's
three points. If *shading* is 'gouraud' then color values must be
defined at points.
other_parameters
All other parameters are the same as for `~.Axes.pcolor`.
Notes
-----
It is possible to pass the triangles positionally, i.e.
``tripcolor(x, y, triangles, C, ...)``. However, this is discouraged.
For more clarity, pass *triangles* via keyword argument.
"""
_api.check_in_list(['flat', 'gouraud'], shading=shading)
tri, args, kwargs = Triangulation.get_from_args_and_kwargs(*args, **kwargs)
# Parse the color to be in one of (the other variable will be None):
# - facecolors: if specified at the triangle faces
# - point_colors: if specified at the points
if facecolors is not None:
if args:
_api.warn_external(
"Positional parameter C has no effect when the keyword "
"facecolors is given")
point_colors = None
if len(facecolors) != len(tri.triangles):
raise ValueError("The length of facecolors must match the number "
"of triangles")
else:
# Color from positional parameter C
if not args:
raise ValueError(
"Missing color parameter. Please pass C positionally or "
"facecolors via keyword")
elif len(args) > 1:
_api.warn_external(
"Additional positional parameters {args[1:]!r} are ignored")
C = np.asarray(args[0])
if len(C) == len(tri.x):
# having this before the len(tri.triangles) comparison gives
# precedence to nodes if there are as many nodes as triangles
point_colors = C
facecolors = None
elif len(C) == len(tri.triangles):
point_colors = None
facecolors = C
else:
raise ValueError('The length of C must match either the number '
'of points or the number of triangles')
# Handling of linewidths, shading, edgecolors and antialiased as
# in Axes.pcolor
linewidths = (0.25, )
if 'linewidth' in kwargs:
kwargs['linewidths'] = kwargs.pop('linewidth')
kwargs.setdefault('linewidths', linewidths)
edgecolors = 'none'
if 'edgecolor' in kwargs:
kwargs['edgecolors'] = kwargs.pop('edgecolor')
ec = kwargs.setdefault('edgecolors', edgecolors)
if 'antialiased' in kwargs:
kwargs['antialiaseds'] = kwargs.pop('antialiased')
if 'antialiaseds' not in kwargs and ec.lower() == "none":
kwargs['antialiaseds'] = False
_api.check_isinstance((Normalize, None), norm=norm)
if shading == 'gouraud':
if facecolors is not None:
raise ValueError(
"shading='gouraud' can only be used when the colors "
"are specified at the points, not at the faces.")
collection = TriMesh(tri,
alpha=alpha,
array=point_colors,
cmap=cmap,
norm=norm,
**kwargs)
else:
# Vertices of triangles.
maskedTris = tri.get_masked_triangles()
verts = np.stack((tri.x[maskedTris], tri.y[maskedTris]), axis=-1)
# Color values.
if facecolors is None:
# One color per triangle, the mean of the 3 vertex color values.
colors = point_colors[maskedTris].mean(axis=1)
elif tri.mask is not None:
# Remove color values of masked triangles.
colors = facecolors[~tri.mask]
else:
colors = facecolors
collection = PolyCollection(verts,
alpha=alpha,
array=colors,
cmap=cmap,
norm=norm,
**kwargs)
collection._scale_norm(norm, vmin, vmax)
ax.grid(False)
minx = tri.x.min()
maxx = tri.x.max()
miny = tri.y.min()
maxy = tri.y.max()
corners = (minx, miny), (maxx, maxy)
ax.update_datalim(corners)
ax.autoscale_view()
ax.add_collection(collection)
return collection
def __init__(self, fraction, ref_size):
_api.check_isinstance(Number, fraction=fraction)
self._fraction_ref = ref_size
self._fraction = fraction
def __init__(self, *args, grid_helper, **kwargs):
_api.check_isinstance(GridHelperCurveLinear, grid_helper=grid_helper)
super().__init__(*args, grid_helper=grid_helper, **kwargs)
self.set_aspect(1.)
self.adjust_axes_lim()
def tripcolor(ax,
*args,
alpha=1.0,
norm=None,
cmap=None,
vmin=None,
vmax=None,
shading='flat',
facecolors=None,
**kwargs):
"""
Create a pseudocolor plot of an unstructured triangular grid.
The triangulation can be specified in one of two ways; either::
tripcolor(triangulation, ...)
where triangulation is a `.Triangulation` object, or
::
tripcolor(x, y, ...)
tripcolor(x, y, triangles, ...)
tripcolor(x, y, triangles=triangles, ...)
tripcolor(x, y, mask=mask, ...)
tripcolor(x, y, triangles, mask=mask, ...)
in which case a Triangulation object will be created. See `.Triangulation`
for a explanation of these possibilities.
The next argument must be *C*, the array of color values, either
one per point in the triangulation if color values are defined at
points, or one per triangle in the triangulation if color values
are defined at triangles. If there are the same number of points
and triangles in the triangulation it is assumed that color
values are defined at points; to force the use of color values at
triangles use the kwarg ``facecolors=C`` instead of just ``C``.
*shading* may be 'flat' (the default) or 'gouraud'. If *shading*
is 'flat' and C values are defined at points, the color values
used for each triangle are from the mean C of the triangle's
three points. If *shading* is 'gouraud' then color values must be
defined at points.
The remaining kwargs are the same as for `~.Axes.pcolor`.
"""
_api.check_in_list(['flat', 'gouraud'], shading=shading)
tri, args, kwargs = Triangulation.get_from_args_and_kwargs(*args, **kwargs)
# C is the colors array defined at either points or faces (i.e. triangles).
# If facecolors is None, C are defined at points.
# If facecolors is not None, C are defined at faces.
if facecolors is not None:
C = facecolors
else:
C = np.asarray(args[0])
# If there are a different number of points and triangles in the
# triangulation, can omit facecolors kwarg as it is obvious from
# length of C whether it refers to points or faces.
# Do not do this for gouraud shading.
if (facecolors is None and len(C) == len(tri.triangles)
and len(C) != len(tri.x) and shading != 'gouraud'):
facecolors = C
# Check length of C is OK.
if ((facecolors is None and len(C) != len(tri.x))
or (facecolors is not None and len(C) != len(tri.triangles))):
raise ValueError('Length of color values array must be the same '
'as either the number of triangulation points '
'or triangles')
# Handling of linewidths, shading, edgecolors and antialiased as
# in Axes.pcolor
linewidths = (0.25, )
if 'linewidth' in kwargs:
kwargs['linewidths'] = kwargs.pop('linewidth')
kwargs.setdefault('linewidths', linewidths)
edgecolors = 'none'
if 'edgecolor' in kwargs:
kwargs['edgecolors'] = kwargs.pop('edgecolor')
ec = kwargs.setdefault('edgecolors', edgecolors)
if 'antialiased' in kwargs:
kwargs['antialiaseds'] = kwargs.pop('antialiased')
if 'antialiaseds' not in kwargs and ec.lower() == "none":
kwargs['antialiaseds'] = False
if shading == 'gouraud':
if facecolors is not None:
raise ValueError('Gouraud shading does not support the use '
'of facecolors kwarg')
if len(C) != len(tri.x):
raise ValueError('For gouraud shading, the length of color '
'values array must be the same as the '
'number of triangulation points')
collection = TriMesh(tri, **kwargs)
else:
# Vertices of triangles.
maskedTris = tri.get_masked_triangles()
verts = np.stack((tri.x[maskedTris], tri.y[maskedTris]), axis=-1)
# Color values.
if facecolors is None:
# One color per triangle, the mean of the 3 vertex color values.
C = C[maskedTris].mean(axis=1)
elif tri.mask is not None:
# Remove color values of masked triangles.
C = C[~tri.mask]
collection = PolyCollection(verts, **kwargs)
collection.set_alpha(alpha)
collection.set_array(C)
_api.check_isinstance((Normalize, None), norm=norm)
collection.set_cmap(cmap)
collection.set_norm(norm)
collection._scale_norm(norm, vmin, vmax)
ax.grid(False)
minx = tri.x.min()
maxx = tri.x.max()
miny = tri.y.min()
maxy = tri.y.max()
corners = (minx, miny), (maxx, maxy)
ax.update_datalim(corners)
ax.autoscale_view()
ax.add_collection(collection)
return collection
def __init__(self, fixed_size):
_api.check_isinstance(Number, fixed_size=fixed_size)
self.fixed_size = fixed_size
