diff --git a/doc/source/code/figure/discretize.py.diff b/doc/source/code/figure/discretize.py.diff
index 9ca0df555e3b8553f7772d6f2253e485e6d4df73..aebaf3e03c10d291d2b25789c1145b90d6210a15 100644
--- a/doc/source/code/figure/discretize.py.diff
+++ b/doc/source/code/figure/discretize.py.diff
@@ -1,4 +1,4 @@
-@@ -1,222 +1,236 @@
+@@ -1,225 +1,239 @@
# Tutorial 2.9. Processing continuum Hamiltonians with discretize
# ===============================================================
#
@@ -13,6 +13,9 @@
+import _defs
import kwant
+ #HIDDEN_BEGIN_import
+ import kwant.continuum
+ #HIDDEN_END_import
import scipy.sparse.linalg
import scipy.linalg
import numpy as np
diff --git a/doc/source/code/figure/plot_qahe.py.diff b/doc/source/code/figure/plot_qahe.py.diff
index d726f98e908feac22a767b4387c8e6b561523bb4..1788f677df857d1b75b8706aa0907fad4b9a467d 100644
--- a/doc/source/code/figure/plot_qahe.py.diff
+++ b/doc/source/code/figure/plot_qahe.py.diff
@@ -1,4 +1,4 @@
-@@ -1,71 +1,75 @@
+@@ -1,72 +1,76 @@
# Comprehensive example: quantum anomalous Hall effect
# ====================================================
#
@@ -16,6 +16,7 @@
import math
import matplotlib.pyplot
import kwant
+ import kwant.continuum
# 2 band model exhibiting quantum anomalous Hall effect
diff --git a/doc/source/conf.py b/doc/source/conf.py
index f0272556a1cee688b73c60fdea6574d8792ba5ee..9790aaa58434a0eb868d66bf2b2243677611ee4c 100644
--- a/doc/source/conf.py
+++ b/doc/source/conf.py
@@ -16,7 +16,9 @@ import sys, os
from distutils.util import get_platform
sys.path.insert(0, "../../build/lib.{0}-{1}.{2}".format(
get_platform(), *sys.version_info[:2]))
+
import kwant
+import kwant.continuum # sphinx gets confused with lazy loading
# -- General configuration -----------------------------------------------------
diff --git a/doc/source/tutorial/discretize.rst b/doc/source/tutorial/discretize.rst
index d3c58219ea2baf593bc96fc6e9ded1073aabc634..1ed5015cd2203e100d1d4e4cf9f21ae283716f04 100644
--- a/doc/source/tutorial/discretize.rst
+++ b/doc/source/tutorial/discretize.rst
@@ -53,6 +53,11 @@ with :math:`A(x) = \frac{\hbar^2}{2 m(x)}`.
Using `~kwant.continuum.discretize` to obtain a template
........................................................
+First we must explicitly import the `kwant.continuum` package:
+
+.. literalinclude:: /code/include/discretize.py
+ :start-after: #HIDDEN_BEGIN_import
+ :end-before: #HIDDEN_END_import
The function `kwant.continuum.discretize` takes a symbolic Hamiltonian and
turns it into a `~kwant.builder.Builder` instance with appropriate spatial
diff --git a/kwant/__init__.py b/kwant/__init__.py
index 1fddab25426261753a81e358a30ddab009ac3171..054657c308607608b1c9c8a893680231b21c59f6 100644
--- a/kwant/__init__.py
+++ b/kwant/__init__.py
@@ -33,7 +33,7 @@ from ._common import KwantDeprecationWarning, UserCodeError
__all__.extend(['KwantDeprecationWarning', 'UserCodeError'])
for module in ['system', 'builder', 'lattice', 'solvers', 'digest', 'rmt',
- 'operator', 'kpm', 'wraparound', 'continuum']:
+ 'operator', 'kpm', 'wraparound']:
exec('from . import {0}'.format(module))
__all__.append(module)
@@ -56,6 +56,13 @@ except:
else:
__all__.extend(['plotter', 'plot'])
+# Lazy import continuum package for backwards compatibility
+from ._common import lazy_import
+
+continuum = lazy_import('continuum', deprecation_warning=True)
+__all__.append('continuum')
+del lazy_import
+
def test(verbose=True):
from pytest import main
diff --git a/kwant/_common.py b/kwant/_common.py
index 76e952cf6c0d2ffc437d42ca5c093a5825aac0e9..4cd0de1a3e6d4b084f3434bbfffef08871d51ded 100644
--- a/kwant/_common.py
+++ b/kwant/_common.py
@@ -6,10 +6,12 @@
# the file AUTHORS.rst at the top-level directory of this distribution and at
# http://kwant-project.org/authors.
+import sys
import numpy as np
import numbers
import inspect
import warnings
+import importlib
from contextlib import contextmanager
__all__ = ['KwantDeprecationWarning', 'UserCodeError']
@@ -39,30 +41,6 @@ class UserCodeError(Exception):
pass
-class ExtensionUnavailable:
- """Class that replaces unavailable extension modules in the Kwant namespace.
-
- Some extensions for Kwant (e.g. 'kwant.continuum') require additional
- dependencies that are not required for core functionality. When the
- additional dependencies are not installed an instance of this class will
- be inserted into Kwant's root namespace to simulate the presence of the
- extension and inform users that they need to install additional
- dependencies.
-
- See https://mail.python.org/pipermail/python-ideas/2012-May/014969.html
- for more details.
- """
-
- def __init__(self, name, dependencies):
- self.name = name
- self.dependencies = ', '.join(dependencies)
-
- def __getattr__(self, _):
- msg = ("'{}' is not available because one or more of the following "
- "dependencies are not installed: {}")
- raise RuntimeError(msg.format(self.name, self.dependencies))
-
-
def ensure_isinstance(obj, typ, msg=None):
if isinstance(obj, typ):
return
@@ -123,3 +101,25 @@ def get_parameters(func):
takes_kwargs = any(i.kind is inspect.Parameter.VAR_KEYWORD
for i in pars.values())
return required_params, default_params, takes_kwargs
+
+
+class lazy_import:
+ def __init__(self, module, package='kwant', deprecation_warning=False):
+ if module.startswith('.') and not package:
+ raise ValueError('Cannot import a relative module without a package.')
+ self.__module = module
+ self.__package = package
+ self.__deprecation_warning = deprecation_warning
+
+ def __getattr__(self, name):
+ if self.__deprecation_warning:
+ msg = ("Accessing {0} without an explicit import is deprecated. "
+ "Instead, explicitly 'import {0}'."
+ ).format('.'.join((self.__package, self.__module)))
+ warnings.warn(msg, KwantDeprecationWarning, stacklevel=2)
+ relative_module = '.' + self.__module
+ mod = importlib.import_module(relative_module, self.__package)
+ # Replace this _LazyModuleProxy with an actual module
+ package = sys.modules[self.__package]
+ setattr(package, self.__module, mod)
+ return getattr(mod, name)
diff --git a/kwant/_plotter.py b/kwant/_plotter.py
new file mode 100644
index 0000000000000000000000000000000000000000..771e9ba281999efc07f2aece0a7fc0169d19be63
--- /dev/null
+++ b/kwant/_plotter.py
@@ -0,0 +1,320 @@
+# -*- coding: utf-8 -*-
+# Copyright 2011-2018 Kwant authors.
+#
+# This file is part of Kwant. It is subject to the license terms in the file
+# LICENSE.rst found in the top-level directory of this distribution and at
+# http://kwant-project.org/license. A list of Kwant authors can be found in
+# the file AUTHORS.rst at the top-level directory of this distribution and at
+# http://kwant-project.org/authors.
+
+# This module is imported by plotter.py. It contains all the expensive imports
+# that we want to remove from plotter.py
+
+# All matplotlib imports must be isolated in a try, because even without
+# matplotlib iterators remain useful. Further, mpl_toolkits used for 3D
+# plotting are also imported separately, to ensure that 2D plotting works even
+# if 3D does not.
+
+import warnings
+from math import sqrt, pi
+import numpy as np
+
+try:
+ import matplotlib
+ import matplotlib.colors
+ import matplotlib.cm
+ from matplotlib.figure import Figure
+ from matplotlib import collections
+ from . import _colormaps
+ mpl_available = True
+ try:
+ from mpl_toolkits import mplot3d
+ has3d = True
+ except ImportError:
+ warnings.warn("3D plotting not available.", RuntimeWarning)
+ has3d = False
+except ImportError:
+ warnings.warn("matplotlib is not available, only iterator-providing "
+ "functions will work.", RuntimeWarning)
+ mpl_available = False
+
+
+# Collections that allow for symbols and linewiths to be given in data space
+# (not for general use, only implement what's needed for plotter)
+def isarray(var):
+ if hasattr(var, '__getitem__') and not isinstance(var, str):
+ return True
+ else:
+ return False
+
+
+def nparray_if_array(var):
+ return np.asarray(var) if isarray(var) else var
+
+
+if mpl_available:
+ class LineCollection(collections.LineCollection):
+ def __init__(self, segments, reflen=None, **kwargs):
+ super().__init__(segments, **kwargs)
+ self.reflen = reflen
+
+ def set_linewidths(self, linewidths):
+ self.linewidths_orig = nparray_if_array(linewidths)
+
+ def draw(self, renderer):
+ if self.reflen is not None:
+ # Note: only works for aspect ratio 1!
+ # 72.0 - there is 72 points in an inch
+ factor = (self.axes.transData.frozen().to_values()[0] * 72.0 *
+ self.reflen / self.figure.dpi)
+ else:
+ factor = 1
+
+ super().set_linewidths(self.linewidths_orig *
+ factor)
+ return super().draw(renderer)
+
+
+ class PathCollection(collections.PathCollection):
+ def __init__(self, paths, sizes=None, reflen=None, **kwargs):
+ super().__init__(paths, sizes=sizes, **kwargs)
+
+ self.reflen = reflen
+ self.linewidths_orig = nparray_if_array(self.get_linewidths())
+
+ self.transforms = np.array(
+ [matplotlib.transforms.Affine2D().scale(x).get_matrix()
+ for x in sizes])
+
+ def get_transforms(self):
+ return self.transforms
+
+ def get_transform(self):
+ Affine2D = matplotlib.transforms.Affine2D
+ if self.reflen is not None:
+ # For the paths, use the data transformation but strip the
+ # offset (will be added later with offsets)
+ args = self.axes.transData.frozen().to_values()[:4] + (0, 0)
+ return Affine2D().from_values(*args).scale(self.reflen)
+ else:
+ return Affine2D().scale(self.figure.dpi / 72.0)
+
+ def draw(self, renderer):
+ if self.reflen:
+ # Note: only works for aspect ratio 1!
+ factor = (self.axes.transData.frozen().to_values()[0] /
+ self.figure.dpi * 72.0 * self.reflen)
+ self.set_linewidths(self.linewidths_orig * factor)
+
+ return collections.Collection.draw(self, renderer)
+
+
+ if has3d:
+ # Sorting is optional.
+ sort3d = True
+
+ # Compute the projection of a 3D length into 2D data coordinates
+ # for this we use 2 3D half-circles that are projected into 2D.
+ # (This gives the same length as projecting the full unit sphere.)
+
+ phi = np.linspace(0, pi, 21)
+ xyz = np.c_[np.cos(phi), np.sin(phi), 0 * phi].T.reshape(-1, 1, 21)
+ unit_sphere = np.bmat([[xyz[0], xyz[2]], [xyz[1], xyz[0]],
+ [xyz[2], xyz[1]]])
+ unit_sphere = np.asarray(unit_sphere)
+
+ def projected_length(ax, length):
+ rc = np.array([ax.get_xlim3d(), ax.get_ylim3d(), ax.get_zlim3d()])
+ rc = np.apply_along_axis(np.sum, 1, rc) / 2.
+
+ rs = unit_sphere * length + rc.reshape(-1, 1)
+
+ transform = mplot3d.proj3d.proj_transform
+ rp = np.asarray(transform(*(list(rs) + [ax.get_proj()]))[:2])
+ rc[:2] = transform(*(list(rc) + [ax.get_proj()]))[:2]
+
+ coords = rp - np.repeat(rc[:2].reshape(-1, 1), len(rs[0]), axis=1)
+ return sqrt(np.sum(coords**2, axis=0).max())
+
+
+ # Auxiliary array for calculating corners of a cube.
+ corners = np.zeros((3, 8, 6), np.float_)
+ corners[0, [0, 1, 2, 3], 0] = corners[0, [4, 5, 6, 7], 1] = \
+ corners[0, [0, 1, 4, 5], 2] = corners[0, [2, 3, 6, 7], 3] = \
+ corners[0, [0, 2, 4, 6], 4] = corners[0, [1, 3, 5, 7], 5] = 1.0
+
+
+ class Line3DCollection(mplot3d.art3d.Line3DCollection):
+ def __init__(self, segments, reflen=None, zorder=0, **kwargs):
+ super().__init__(segments, **kwargs)
+ self.reflen = reflen
+ self.zorder3d = zorder
+
+ def set_linewidths(self, linewidths):
+ self.linewidths_orig = nparray_if_array(linewidths)
+
+ def do_3d_projection(self, renderer):
+ super().do_3d_projection(renderer)
+ # The whole 3D ordering is flawed in mplot3d when several
+ # collections are added. We just use normal zorder. Note the
+ # "-" due to the different logic in the 3d plotting, we still
+ # want larger zorder values to be plotted on top of smaller
+ # ones.
+ return -self.zorder3d
+
+ def draw(self, renderer):
+ if self.reflen:
+ proj_len = projected_length(self.axes, self.reflen)
+ args = self.axes.transData.frozen().to_values()
+ # Note: unlike in the 2D case, where we can enforce equal
+ # aspect ratio, this (currently) does not work with
+ # 3D plots in matplotlib. As an approximation, we
+ # thus scale with the average of the x- and y-axis
+ # transformation.
+ factor = proj_len * (args[0] +
+ args[3]) * 0.5 * 72.0 / self.figure.dpi
+ else:
+ factor = 1
+
+ super().set_linewidths(
+ self.linewidths_orig * factor)
+ super().draw(renderer)
+
+
+ class Path3DCollection(mplot3d.art3d.Patch3DCollection):
+ def __init__(self, paths, sizes, reflen=None, zorder=0,
+ offsets=None, **kwargs):
+ paths = [matplotlib.patches.PathPatch(path) for path in paths]
+
+ if offsets is not None:
+ kwargs['offsets'] = offsets[:, :2]
+
+ super().__init__(paths, **kwargs)
+
+ if offsets is not None:
+ self.set_3d_properties(zs=offsets[:, 2], zdir="z")
+
+ self.reflen = reflen
+ self.zorder3d = zorder
+
+ self.paths_orig = np.array(paths, dtype='object')
+ self.linewidths_orig = nparray_if_array(self.get_linewidths())
+ self.linewidths_orig2 = self.linewidths_orig
+ self.array_orig = nparray_if_array(self.get_array())
+ self.facecolors_orig = nparray_if_array(self.get_facecolors())
+ self.edgecolors_orig = nparray_if_array(self.get_edgecolors())
+
+ Affine2D = matplotlib.transforms.Affine2D
+ self.orig_transforms = np.array(
+ [Affine2D().scale(x).get_matrix() for x in sizes])
+ self.transforms = self.orig_transforms
+
+ def set_array(self, array):
+ self.array_orig = nparray_if_array(array)
+ super().set_array(array)
+
+ def set_color(self, colors):
+ self.facecolors_orig = nparray_if_array(colors)
+ self.edgecolors_orig = self.facecolors_orig
+ super().set_color(colors)
+
+ def set_edgecolors(self, colors):
+ colors = matplotlib.colors.colorConverter.to_rgba_array(colors)
+ self.edgecolors_orig = nparray_if_array(colors)
+ super().set_edgecolors(colors)
+
+ def get_transforms(self):
+ # this is exact only for an isometric projection, for the
+ # perspective projection used in mplot3d it's an approximation
+ return self.transforms
+
+ def get_transform(self):
+ Affine2D = matplotlib.transforms.Affine2D
+ if self.reflen:
+ proj_len = projected_length(self.axes, self.reflen)
+
+ # For the paths, use the data transformation but strip the
+ # offset (will be added later with the offsets).
+ args = self.axes.transData.frozen().to_values()[:4] + (0, 0)
+ return Affine2D().from_values(*args).scale(proj_len)
+ else:
+ return Affine2D().scale(self.figure.dpi / 72.0)
+
+ def do_3d_projection(self, renderer):
+ xs, ys, zs = self._offsets3d
+
+ # numpy complains about zero-length index arrays
+ if len(xs) == 0:
+ return -self.zorder3d
+
+ proj = mplot3d.proj3d.proj_transform_clip
+ vs = np.array(proj(xs, ys, zs, renderer.M)[:3])
+
+ if sort3d:
+ indx = vs[2].argsort()[::-1]
+
+ self.set_offsets(vs[:2, indx].T)
+
+ if len(self.paths_orig) > 1:
+ paths = np.resize(self.paths_orig, (vs.shape[1],))
+ self.set_paths(paths[indx])
+
+ if len(self.orig_transforms) > 1:
+ self.transforms = self.transforms[indx]
+
+ lw_orig = self.linewidths_orig
+ if (isinstance(lw_orig, np.ndarray) and len(lw_orig) > 1):
+ self.linewidths_orig2 = np.resize(lw_orig,
+ (vs.shape[1],))[indx]
+
+ # Note: here array, facecolors and edgecolors are
+ # guaranteed to be 2d numpy arrays or None. (And
+ # array is the same length as the coordinates)
+
+ if self.array_orig is not None:
+ super(Path3DCollection,
+ self).set_array(self.array_orig[indx])
+
+ if (self.facecolors_orig is not None and
+ self.facecolors_orig.shape[0] > 1):
+ shape = list(self.facecolors_orig.shape)
+ shape[0] = vs.shape[1]
+ super().set_facecolors(
+ np.resize(self.facecolors_orig, shape)[indx])
+
+ if (self.edgecolors_orig is not None and
+ self.edgecolors_orig.shape[0] > 1):
+ shape = list(self.edgecolors_orig.shape)
+ shape[0] = vs.shape[1]
+ super().set_edgecolors(
+ np.resize(self.edgecolors_orig,
+ shape)[indx])
+ else:
+ self.set_offsets(vs[:2].T)
+
+ # the whole 3D ordering is flawed in mplot3d when several
+ # collections are added. We just use normal zorder, but correct
+ # by the projected z-coord of the "center of gravity",
+ # normalized by the projected z-coord of the world coordinates.
+ # In doing so, several Path3DCollections are plotted probably
+ # in the right order (it's not exact) if they have the same
+ # zorder. Still, smaller and larger integer zorders are plotted
+ # below or on top.
+
+ bbox = np.asarray(self.axes.get_w_lims())
+
+ proj = mplot3d.proj3d.proj_transform_clip
+ cz = proj(*(list(np.dot(corners, bbox)) + [renderer.M]))[2]
+
+ return -self.zorder3d + vs[2].mean() / cz.ptp()
+
+ def draw(self, renderer):
+ if self.reflen:
+ proj_len = projected_length(self.axes, self.reflen)
+ args = self.axes.transData.frozen().to_values()
+ factor = proj_len * (args[0] +
+ args[3]) * 0.5 * 72.0 / self.figure.dpi
+
+ self.set_linewidths(self.linewidths_orig2 * factor)
+
+ super().draw(renderer)
diff --git a/kwant/continuum/__init__.py b/kwant/continuum/__init__.py
index 718f50151795830b73df1f9327aa591997d0cbdc..bc2420e9c7998af5cb7f3b33fe72555e778156d4 100644
--- a/kwant/continuum/__init__.py
+++ b/kwant/continuum/__init__.py
@@ -6,18 +6,15 @@
# the file AUTHORS.rst at the top-level directory of this distribution and at
# http://kwant-project.org/authors.
-import sys
-
-from .._common import ExtensionUnavailable
-
try:
from .discretizer import discretize, discretize_symbolic, build_discretized
from ._common import sympify, lambdify
from ._common import momentum_operators, position_operators
-except ImportError:
- sys.modules[__name__] = ExtensionUnavailable(__name__, ('sympy',))
+except ImportError as error:
+ msg = ("'kwant.continuum' is not available because one or more of its "
+ "dependencies is not installed.")
+ raise ImportError(msg) from error
-del sys, ExtensionUnavailable
__all__ = ['discretize', 'discretize_symbolic', 'build_discretized',
'sympify', 'lambdify']
diff --git a/kwant/plotter.py b/kwant/plotter.py
index 2112e5b98334cd15e22ef1dcebc09aaa59ed61c9..2fc6b6acf2e21e7d65f8b0b3336394c836389858 100644
--- a/kwant/plotter.py
+++ b/kwant/plotter.py
@@ -26,29 +26,6 @@ import tinyarray as ta
from scipy import spatial, interpolate
from math import cos, sin, pi, sqrt
-# All matplotlib imports must be isolated in a try, because even without
-# matplotlib iterators remain useful. Further, mpl_toolkits used for 3D
-# plotting are also imported separately, to ensure that 2D plotting works even
-# if 3D does not.
-try:
- import matplotlib
- import matplotlib.colors
- import matplotlib.cm
- from matplotlib.figure import Figure
- from matplotlib import collections
- from . import _colormaps
- mpl_available = True
- try:
- from mpl_toolkits import mplot3d
- has3d = True
- except ImportError:
- warnings.warn("3D plotting not available.", RuntimeWarning)
- has3d = False
-except ImportError:
- warnings.warn("matplotlib is not available, only iterator-providing "
- "functions will work.", RuntimeWarning)
- mpl_available = False
-
from . import system, builder, _common
@@ -57,18 +34,9 @@ __all__ = ['plot', 'map', 'bands', 'spectrum', 'current',
'sys_leads_sites', 'sys_leads_hoppings', 'sys_leads_pos',
'sys_leads_hopping_pos', 'mask_interpolate']
-
-# Collections that allow for symbols and linewiths to be given in data space
-# (not for general use, only implement what's needed for plotter)
-def isarray(var):
- if hasattr(var, '__getitem__') and not isinstance(var, str):
- return True
- else:
- return False
-
-
-def nparray_if_array(var):
- return np.asarray(var) if isarray(var) else var
+# All the expensive imports are done in _plotter.py. We lazy load the module
+# to avoid slowing down the initial import of Kwant.
+_p = _common.lazy_import('_plotter')
def _sample_array(array, n_samples, rng=None):
@@ -77,278 +45,10 @@ def _sample_array(array, n_samples, rng=None):
return array[rng.choice(range(la), min(n_samples, la))]
-if mpl_available:
- class LineCollection(collections.LineCollection):
- def __init__(self, segments, reflen=None, **kwargs):
- super().__init__(segments, **kwargs)
- self.reflen = reflen
-
- def set_linewidths(self, linewidths):
- self.linewidths_orig = nparray_if_array(linewidths)
-
- def draw(self, renderer):
- if self.reflen is not None:
- # Note: only works for aspect ratio 1!
- # 72.0 - there is 72 points in an inch
- factor = (self.axes.transData.frozen().to_values()[0] * 72.0 *
- self.reflen / self.figure.dpi)
- else:
- factor = 1
-
- super().set_linewidths(self.linewidths_orig *
- factor)
- return super().draw(renderer)
-
-
- class PathCollection(collections.PathCollection):
- def __init__(self, paths, sizes=None, reflen=None, **kwargs):
- super().__init__(paths, sizes=sizes, **kwargs)
-
- self.reflen = reflen
- self.linewidths_orig = nparray_if_array(self.get_linewidths())
-
- self.transforms = np.array(
- [matplotlib.transforms.Affine2D().scale(x).get_matrix()
- for x in sizes])
-
- def get_transforms(self):
- return self.transforms
-
- def get_transform(self):
- Affine2D = matplotlib.transforms.Affine2D
- if self.reflen is not None:
- # For the paths, use the data transformation but strip the
- # offset (will be added later with offsets)
- args = self.axes.transData.frozen().to_values()[:4] + (0, 0)
- return Affine2D().from_values(*args).scale(self.reflen)
- else:
- return Affine2D().scale(self.figure.dpi / 72.0)
-
- def draw(self, renderer):
- if self.reflen:
- # Note: only works for aspect ratio 1!
- factor = (self.axes.transData.frozen().to_values()[0] /
- self.figure.dpi * 72.0 * self.reflen)
- self.set_linewidths(self.linewidths_orig * factor)
-
- return collections.Collection.draw(self, renderer)
-
-
- if has3d:
- # Sorting is optional.
- sort3d = True
-
- # Compute the projection of a 3D length into 2D data coordinates
- # for this we use 2 3D half-circles that are projected into 2D.
- # (This gives the same length as projecting the full unit sphere.)
-
- phi = np.linspace(0, pi, 21)
- xyz = np.c_[np.cos(phi), np.sin(phi), 0 * phi].T.reshape(-1, 1, 21)
- unit_sphere = np.bmat([[xyz[0], xyz[2]], [xyz[1], xyz[0]],
- [xyz[2], xyz[1]]])
- unit_sphere = np.asarray(unit_sphere)
-
- def projected_length(ax, length):
- rc = np.array([ax.get_xlim3d(), ax.get_ylim3d(), ax.get_zlim3d()])
- rc = np.apply_along_axis(np.sum, 1, rc) / 2.
-
- rs = unit_sphere * length + rc.reshape(-1, 1)
-
- transform = mplot3d.proj3d.proj_transform
- rp = np.asarray(transform(*(list(rs) + [ax.get_proj()]))[:2])
- rc[:2] = transform(*(list(rc) + [ax.get_proj()]))[:2]
-
- coords = rp - np.repeat(rc[:2].reshape(-1, 1), len(rs[0]), axis=1)
- return sqrt(np.sum(coords**2, axis=0).max())
-
-
- # Auxiliary array for calculating corners of a cube.
- corners = np.zeros((3, 8, 6), np.float_)
- corners[0, [0, 1, 2, 3], 0] = corners[0, [4, 5, 6, 7], 1] = \
- corners[0, [0, 1, 4, 5], 2] = corners[0, [2, 3, 6, 7], 3] = \
- corners[0, [0, 2, 4, 6], 4] = corners[0, [1, 3, 5, 7], 5] = 1.0
-
-
- class Line3DCollection(mplot3d.art3d.Line3DCollection):
- def __init__(self, segments, reflen=None, zorder=0, **kwargs):
- super().__init__(segments, **kwargs)
- self.reflen = reflen
- self.zorder3d = zorder
-
- def set_linewidths(self, linewidths):
- self.linewidths_orig = nparray_if_array(linewidths)
-
- def do_3d_projection(self, renderer):
- super().do_3d_projection(renderer)
- # The whole 3D ordering is flawed in mplot3d when several
- # collections are added. We just use normal zorder. Note the
- # "-" due to the different logic in the 3d plotting, we still
- # want larger zorder values to be plotted on top of smaller
- # ones.
- return -self.zorder3d
-
- def draw(self, renderer):
- if self.reflen:
- proj_len = projected_length(self.axes, self.reflen)
- args = self.axes.transData.frozen().to_values()
- # Note: unlike in the 2D case, where we can enforce equal
- # aspect ratio, this (currently) does not work with
- # 3D plots in matplotlib. As an approximation, we
- # thus scale with the average of the x- and y-axis
- # transformation.
- factor = proj_len * (args[0] +
- args[3]) * 0.5 * 72.0 / self.figure.dpi
- else:
- factor = 1
-
- super().set_linewidths(
- self.linewidths_orig * factor)
- super().draw(renderer)
-
-
- class Path3DCollection(mplot3d.art3d.Patch3DCollection):
- def __init__(self, paths, sizes, reflen=None, zorder=0,
- offsets=None, **kwargs):
- paths = [matplotlib.patches.PathPatch(path) for path in paths]
-
- if offsets is not None:
- kwargs['offsets'] = offsets[:, :2]
-
- super().__init__(paths, **kwargs)
-
- if offsets is not None:
- self.set_3d_properties(zs=offsets[:, 2], zdir="z")
-
- self.reflen = reflen
- self.zorder3d = zorder
-
- self.paths_orig = np.array(paths, dtype='object')
- self.linewidths_orig = nparray_if_array(self.get_linewidths())
- self.linewidths_orig2 = self.linewidths_orig
- self.array_orig = nparray_if_array(self.get_array())
- self.facecolors_orig = nparray_if_array(self.get_facecolors())
- self.edgecolors_orig = nparray_if_array(self.get_edgecolors())
-
- Affine2D = matplotlib.transforms.Affine2D
- self.orig_transforms = np.array(
- [Affine2D().scale(x).get_matrix() for x in sizes])
- self.transforms = self.orig_transforms
-
- def set_array(self, array):
- self.array_orig = nparray_if_array(array)
- super().set_array(array)
-
- def set_color(self, colors):
- self.facecolors_orig = nparray_if_array(colors)
- self.edgecolors_orig = self.facecolors_orig
- super().set_color(colors)
-
- def set_edgecolors(self, colors):
- colors = matplotlib.colors.colorConverter.to_rgba_array(colors)
- self.edgecolors_orig = nparray_if_array(colors)
- super().set_edgecolors(colors)
-
- def get_transforms(self):
- # this is exact only for an isometric projection, for the
- # perspective projection used in mplot3d it's an approximation
- return self.transforms
-
- def get_transform(self):
- Affine2D = matplotlib.transforms.Affine2D
- if self.reflen:
- proj_len = projected_length(self.axes, self.reflen)
-
- # For the paths, use the data transformation but strip the
- # offset (will be added later with the offsets).
- args = self.axes.transData.frozen().to_values()[:4] + (0, 0)
- return Affine2D().from_values(*args).scale(proj_len)
- else:
- return Affine2D().scale(self.figure.dpi / 72.0)
-
- def do_3d_projection(self, renderer):
- xs, ys, zs = self._offsets3d
-
- # numpy complains about zero-length index arrays
- if len(xs) == 0:
- return -self.zorder3d
-
- proj = mplot3d.proj3d.proj_transform_clip
- vs = np.array(proj(xs, ys, zs, renderer.M)[:3])
-
- if sort3d:
- indx = vs[2].argsort()[::-1]
-
- self.set_offsets(vs[:2, indx].T)
-
- if len(self.paths_orig) > 1:
- paths = np.resize(self.paths_orig, (vs.shape[1],))
- self.set_paths(paths[indx])
-
- if len(self.orig_transforms) > 1:
- self.transforms = self.transforms[indx]
-
- lw_orig = self.linewidths_orig
- if (isinstance(lw_orig, np.ndarray) and len(lw_orig) > 1):
- self.linewidths_orig2 = np.resize(lw_orig,
- (vs.shape[1],))[indx]
-
- # Note: here array, facecolors and edgecolors are
- # guaranteed to be 2d numpy arrays or None. (And
- # array is the same length as the coordinates)
-
- if self.array_orig is not None:
- super(Path3DCollection,
- self).set_array(self.array_orig[indx])
-
- if (self.facecolors_orig is not None and
- self.facecolors_orig.shape[0] > 1):
- shape = list(self.facecolors_orig.shape)
- shape[0] = vs.shape[1]
- super().set_facecolors(
- np.resize(self.facecolors_orig, shape)[indx])
-
- if (self.edgecolors_orig is not None and
- self.edgecolors_orig.shape[0] > 1):
- shape = list(self.edgecolors_orig.shape)
- shape[0] = vs.shape[1]
- super().set_edgecolors(
- np.resize(self.edgecolors_orig,
- shape)[indx])
- else:
- self.set_offsets(vs[:2].T)
-
- # the whole 3D ordering is flawed in mplot3d when several
- # collections are added. We just use normal zorder, but correct
- # by the projected z-coord of the "center of gravity",
- # normalized by the projected z-coord of the world coordinates.
- # In doing so, several Path3DCollections are plotted probably
- # in the right order (it's not exact) if they have the same
- # zorder. Still, smaller and larger integer zorders are plotted
- # below or on top.
-
- bbox = np.asarray(self.axes.get_w_lims())
-
- proj = mplot3d.proj3d.proj_transform_clip
- cz = proj(*(list(np.dot(corners, bbox)) + [renderer.M]))[2]
-
- return -self.zorder3d + vs[2].mean() / cz.ptp()
-
- def draw(self, renderer):
- if self.reflen:
- proj_len = projected_length(self.axes, self.reflen)
- args = self.axes.transData.frozen().to_values()
- factor = proj_len * (args[0] +
- args[3]) * 0.5 * 72.0 / self.figure.dpi
-
- self.set_linewidths(self.linewidths_orig2 * factor)
-
- super().draw(renderer)
-
-
# matplotlib helper functions.
def _make_figure(dpi, fig_size):
- fig = Figure()
+ fig = _p.Figure()
if dpi is not None:
fig.set_dpi(dpi)
if fig_size is not None:
@@ -377,10 +77,10 @@ def set_colors(color, collection, cmap, norm=None):
if (isinstance(color, np.ndarray) and color.dtype == np.dtype('object')):
color = tuple(color)
- if isinstance(collection, mplot3d.art3d.Line3DCollection):
+ if isinstance(collection, _p.mplot3d.art3d.Line3DCollection):
length = len(collection._segments3d) # Once again, matplotlib fault!
- if isarray(color) and len(color) == length:
+ if _p.isarray(color) and len(color) == length:
try:
# check if it is an array of floats for color mapping
color = np.asarray(color, dtype=float)
@@ -393,7 +93,7 @@ def set_colors(color, collection, cmap, norm=None):
except (TypeError, ValueError):
pass
- colors = matplotlib.colors.colorConverter.to_rgba_array(color)
+ colors = _p.matplotlib.colors.colorConverter.to_rgba_array(color)
collection.set_color(colors)
@@ -414,7 +114,7 @@ def get_symbol(symbols):
paths = []
for symbol in symbols:
- if isinstance(symbol, matplotlib.path.Path):
+ if isinstance(symbol, _p.matplotlib.path.Path):
return symbol
elif hasattr(symbol, '__getitem__') and len(symbol) == 3:
kind, n, angle = symbol
@@ -428,13 +128,13 @@ def get_symbol(symbols):
radius = sqrt(2 * pi / (n * sin(2 * pi / n)))
angle = pi * angle / 180
- patch = matplotlib.patches.RegularPolygon((0, 0), n,
- radius=radius,
- orientation=angle)
+ patch = _p.matplotlib.patches.RegularPolygon((0, 0), n,
+ radius=radius,
+ orientation=angle)
else:
raise ValueError("Unknown symbol definition " + str(symbol))
elif symbol == 'o':
- patch = matplotlib.patches.Circle((0, 0), 1)
+ patch = _p.matplotlib.patches.Circle((0, 0), 1)
paths.append(patch.get_path().transformed(patch.get_transform()))
@@ -495,9 +195,9 @@ def symbols(axes, pos, symbol='o', size=1, reflen=None, facecolor='k',
size = (size, )
if dim == 2:
- Collection = PathCollection
+ Collection = _p.PathCollection
else:
- Collection = Path3DCollection
+ Collection = _p.Path3DCollection
if len(pos) == 0 or np.all(symbol == 'no symbol') or np.all(size == 0):
paths = []
@@ -569,9 +269,9 @@ def lines(axes, pos0, pos1, reflen=None, colors='k', linestyles='solid',
dim = pos0.shape[1]
assert dim == 2 or dim == 3
if dim == 2:
- Collection = LineCollection
+ Collection = _p.LineCollection
else:
- Collection = Line3DCollection
+ Collection = _p.Line3DCollection
if (len(pos0) == 0 or
('linewidths' in kwargs and kwargs['linewidths'] == 0)):
@@ -631,7 +331,7 @@ def output_fig(fig, output_mode='auto', file=None, savefile_opts=None,
matplotlib in that the `dpi` attribute of the figure is used by defaul
instead of the matplotlib config setting.
"""
- if not mpl_available:
+ if not _p.mpl_available:
raise RuntimeError('matplotlib is not installed.')
# We import backends and pyplot only at the last possible moment (=now)
@@ -1111,7 +811,7 @@ def plot(sys, num_lead_cells=2, unit='nn',
its aspect ratio.
"""
- if not mpl_available:
+ if not _p.mpl_available:
raise RuntimeError("matplotlib was not found, but is required "
"for plot()")
@@ -1161,7 +861,7 @@ def plot(sys, num_lead_cells=2, unit='nn',
start_pos = np.apply_along_axis(pos_transform, 1, start_pos)
dim = 3 if (sites_pos.shape[1] == 3) else 2
- if dim == 3 and not has3d:
+ if dim == 3 and not _p.has3d:
raise RuntimeError("Installed matplotlib does not support 3d plotting")
sites_pos = resize_to_dim(sites_pos)
end_pos = resize_to_dim(end_pos)
@@ -1202,7 +902,7 @@ def plot(sys, num_lead_cells=2, unit='nn',
def make_proper_site_spec(spec, fancy_indexing=False):
if callable(spec):
spec = [spec(i[0]) for i in sites if i[1] is None]
- if (fancy_indexing and isarray(spec)
+ if (fancy_indexing and _p.isarray(spec)
and not isinstance(spec, np.ndarray)):
try:
spec = np.asarray(spec)
@@ -1213,7 +913,7 @@ def plot(sys, num_lead_cells=2, unit='nn',
def make_proper_hop_spec(spec, fancy_indexing=False):
if callable(spec):
spec = [spec(*i[0]) for i in hops if i[1] is None]
- if (fancy_indexing and isarray(spec)
+ if (fancy_indexing and _p.isarray(spec)
and not isinstance(spec, np.ndarray)):
try:
spec = np.asarray(spec)
@@ -1225,7 +925,7 @@ def plot(sys, num_lead_cells=2, unit='nn',
if site_symbol is None: site_symbol = defaults['site_symbol'][dim]
# separate different symbols (not done in 3D, the separation
# would mess up sorting)
- if (isarray(site_symbol) and dim != 3 and
+ if (_p.isarray(site_symbol) and dim != 3 and
(len(site_symbol) != 3 or site_symbol[0] not in ('p', 'P'))):
symbol_dict = defaultdict(list)
for i, symbol in enumerate(site_symbol):
@@ -1239,7 +939,7 @@ def plot(sys, num_lead_cells=2, unit='nn',
fancy_indexing = False
if site_color is None:
- cycle = (x['color'] for x in matplotlib.rcParams['axes.prop_cycle'])
+ cycle = (x['color'] for x in _p.matplotlib.rcParams['axes.prop_cycle'])
if isinstance(syst, (builder.FiniteSystem, builder.InfiniteSystem)):
# Skipping the leads for brevity.
families = sorted({site.family for site in syst.sites})
@@ -1279,30 +979,30 @@ def plot(sys, num_lead_cells=2, unit='nn',
try:
if site_color.ndim == 1 and len(site_color) == n_syst_sites:
site_color = np.asarray(site_color, dtype=float)
- norm = matplotlib.colors.Normalize(site_color.min(),
- site_color.max())
+ norm = _p.matplotlib.colors.Normalize(site_color.min(),
+ site_color.max())
except:
pass
# take spec also for lead, if it's not a list/array, default, otherwise
if lead_site_symbol is None:
- lead_site_symbol = (site_symbol if not isarray(site_symbol)
+ lead_site_symbol = (site_symbol if not _p.isarray(site_symbol)
else defaults['site_symbol'][dim])
if lead_site_size is None:
- lead_site_size = (site_size if not isarray(site_size)
+ lead_site_size = (site_size if not _p.isarray(site_size)
else defaults['site_size'][dim])
if lead_color is None:
lead_color = defaults['lead_color'][dim]
- lead_color = matplotlib.colors.colorConverter.to_rgba(lead_color)
+ lead_color = _p.matplotlib.colors.colorConverter.to_rgba(lead_color)
if lead_site_edgecolor is None:
- lead_site_edgecolor = (site_edgecolor if not isarray(site_edgecolor)
+ lead_site_edgecolor = (site_edgecolor if not _p.isarray(site_edgecolor)
else defaults['site_edgecolor'][dim])
if lead_site_lw is None:
- lead_site_lw = (site_lw if not isarray(site_lw)
+ lead_site_lw = (site_lw if not _p.isarray(site_lw)
else defaults['site_lw'][dim])
if lead_hop_lw is None:
- lead_hop_lw = (hop_lw if not isarray(hop_lw)
+ lead_hop_lw = (hop_lw if not _p.isarray(hop_lw)
else defaults['hop_lw'][dim])
hop_cmap = None
@@ -1328,11 +1028,11 @@ def plot(sys, num_lead_cells=2, unit='nn',
# plot system sites and hoppings
for symbol, slc in symbol_slcs:
- size = site_size[slc] if isarray(site_size) else site_size
- col = site_color[slc] if isarray(site_color) else site_color
- edgecol = (site_edgecolor[slc] if isarray(site_edgecolor) else
+ size = site_size[slc] if _p.isarray(site_size) else site_size
+ col = site_color[slc] if _p.isarray(site_color) else site_color
+ edgecol = (site_edgecolor[slc] if _p.isarray(site_edgecolor) else
site_edgecolor)
- lw = site_lw[slc] if isarray(site_lw) else site_lw
+ lw = site_lw[slc] if _p.isarray(site_lw) else site_lw
symbol_coll = symbols(ax, sites_pos[slc], size=size,
reflen=reflen, symbol=symbol,
@@ -1344,8 +1044,8 @@ def plot(sys, num_lead_cells=2, unit='nn',
zorder=1, cmap=hop_cmap)
# plot lead sites and hoppings
- norm = matplotlib.colors.Normalize(-0.5, num_lead_cells - 0.5)
- cmap_from_list = matplotlib.colors.LinearSegmentedColormap.from_list
+ norm = _p.matplotlib.colors.Normalize(-0.5, num_lead_cells - 0.5)
+ cmap_from_list = _p.matplotlib.colors.LinearSegmentedColormap.from_list
lead_cmap = cmap_from_list(None, [lead_color, (1, 1, 1, lead_color[3])])
for sites_slc, hops_slc in zip(lead_sites_slcs, lead_hops_slcs):
@@ -1543,7 +1243,7 @@ def map(sys, value, colorbar=True, cmap=None, vmin=None, vmax=None, a=None,
correspond to exactly one pixel.
"""
- if not mpl_available:
+ if not _p.mpl_available:
raise RuntimeError("matplotlib was not found, but is required "
"for map()")
@@ -1576,7 +1276,7 @@ def map(sys, value, colorbar=True, cmap=None, vmin=None, vmax=None, a=None,
fig = None
if cmap is None:
- cmap = _colormaps.kwant_red
+ cmap = _p._colormaps.kwant_red
# Note that we tell imshow to show the array created by mask_interpolate
# faithfully and not to interpolate by itself another time.
@@ -1640,7 +1340,7 @@ def bands(sys, args=(), momenta=65, file=None, show=True, dpi=None,
See `~kwant.physics.Bands` for the calculation of dispersion without plotting.
"""
- if not mpl_available:
+ if not _p.mpl_available:
raise RuntimeError("matplotlib was not found, but is required "
"for bands()")
@@ -1715,10 +1415,10 @@ def spectrum(syst, x, y=None, params=None, mask=None, file=None,
A figure with the output if `ax` is not set, else None.
"""
- if not mpl_available:
+ if not _p.mpl_available:
raise RuntimeError("matplotlib was not found, but is required "
"for plot_spectrum()")
- if y is not None and not has3d:
+ if y is not None and not _p.has3d:
raise RuntimeError("Installed matplotlib does not support 3d plotting")
if isinstance(syst, system.FiniteSystem):
@@ -1754,7 +1454,7 @@ def spectrum(syst, x, y=None, params=None, mask=None, file=None,
# set up axes
if ax is None:
- fig = Figure()
+ fig = _p.Figure()
if dpi is not None:
fig.set_dpi(dpi)
if fig_size is not None:
@@ -1996,8 +1696,8 @@ _gamma_expand = np.vectorize(_gamma_expand, otypes=[float])
def _linear_cmap(a, b):
"""Make a colormap that linearly interpolates between the colors a and b."""
- a = matplotlib.colors.colorConverter.to_rgb(a)
- b = matplotlib.colors.colorConverter.to_rgb(b)
+ a = _p.matplotlib.colors.colorConverter.to_rgb(a)
+ b = _p.matplotlib.colors.colorConverter.to_rgb(b)
a_linear = _gamma_expand(a)
b_linear = _gamma_expand(b)
color_diff = a_linear - b_linear
@@ -2005,7 +1705,7 @@ def _linear_cmap(a, b):
* color_diff.reshape((1, -1)))
palette += b_linear
palette = _gamma_compress(palette)
- return matplotlib.colors.ListedColormap(palette)
+ return _p.matplotlib.colors.ListedColormap(palette)
def streamplot(field, box, cmap=None, bgcolor=None, linecolor='k',
@@ -2074,7 +1774,7 @@ def streamplot(field, box, cmap=None, bgcolor=None, linecolor='k',
fig : matplotlib figure
A figure with the output if `ax` is not set, else None.
"""
- if not mpl_available:
+ if not _p.mpl_available:
raise RuntimeError("matplotlib was not found, but is required "
"for current()")
@@ -2090,8 +1790,8 @@ def streamplot(field, box, cmap=None, bgcolor=None, linecolor='k',
if bgcolor is None:
if cmap is None:
- cmap = _colormaps.kwant_red
- cmap = matplotlib.cm.get_cmap(cmap)
+ cmap = _p._colormaps.kwant_red
+ cmap = _p.matplotlib.cm.get_cmap(cmap)
bgcolor = cmap(0)[:3]
elif cmap is not None:
raise ValueError("The parameters 'cmap' and 'bgcolor' are "
@@ -2129,7 +1829,7 @@ def streamplot(field, box, cmap=None, bgcolor=None, linecolor='k',
ax.streamplot(X, Y, field[:,:,0], field[:,:,1],
density=density, linewidth=linewidth,
color=color, cmap=line_cmap, arrowstyle='->',
- norm=matplotlib.colors.Normalize(0, 1))
+ norm=_p.matplotlib.colors.Normalize(0, 1))
ax.set_xlim(*box[0])
ax.set_ylim(*box[1])
diff --git a/kwant/tests/test_plotter.py b/kwant/tests/test_plotter.py
index ff2e55caa18b693b23eca9f219d4d22afcff54e8..a5d06a36bf13e1a8a549620fda9d98ff762d699d 100644
--- a/kwant/tests/test_plotter.py
+++ b/kwant/tests/test_plotter.py
@@ -36,6 +36,7 @@ except ImportError:
matplotlib_backend_chosen = False
from kwant import plotter
+from kwant import _plotter # for mpl_available
def test_matplotlib_backend_unset():
@@ -44,7 +45,7 @@ def test_matplotlib_backend_unset():
def test_importable_without_matplotlib():
- prefix, sep, suffix = plotter.__file__.rpartition('.')
+ prefix, sep, suffix = _plotter.__file__.rpartition('.')
if suffix in ['pyc', 'pyo']:
suffix = 'py'
assert suffix == 'py'
@@ -111,7 +112,7 @@ def syst_3d(W=3, r1=2, r2=4, a=1, t=1.0):
return syst
-@pytest.mark.skipif(not plotter.mpl_available, reason="Matplotlib unavailable.")
+@pytest.mark.skipif(not _plotter.mpl_available, reason="Matplotlib unavailable.")
def test_plot():
plot = plotter.plot
syst2d = syst_2d()
@@ -161,7 +162,7 @@ def bad_transform(pos):
x, y = pos
return x, y, 0
-@pytest.mark.skipif(not plotter.mpl_available, reason="Matplotlib unavailable.")
+@pytest.mark.skipif(not _plotter.mpl_available, reason="Matplotlib unavailable.")
def test_map():
syst = syst_2d()
with tempfile.TemporaryFile('w+b') as out:
@@ -197,7 +198,7 @@ def test_mask_interpolate():
coords, np.ones(2 * len(coords)))
-@pytest.mark.skipif(not plotter.mpl_available, reason="Matplotlib unavailable.")
+@pytest.mark.skipif(not _plotter.mpl_available, reason="Matplotlib unavailable.")
def test_bands():
syst = syst_2d().finalized().leads[0]
@@ -212,7 +213,7 @@ def test_bands():
plotter.bands(syst, ax=ax, file=out)
-@pytest.mark.skipif(not plotter.mpl_available, reason="Matplotlib unavailable.")
+@pytest.mark.skipif(not _plotter.mpl_available, reason="Matplotlib unavailable.")
def test_spectrum():
def ham_1d(a, b, c):
@@ -423,7 +424,7 @@ def test_current_interpolation():
assert scipy.stats.linregress(np.log(data))[2] < -0.8
-@pytest.mark.skipif(not plotter.mpl_available, reason="Matplotlib unavailable.")
+@pytest.mark.skipif(not _plotter.mpl_available, reason="Matplotlib unavailable.")
def test_current():
syst = syst_2d().finalized()
J = kwant.operator.Current(syst)
diff --git a/kwant/tests/test_wraparound.py b/kwant/tests/test_wraparound.py
index eb981d2798fa1b8fd42e36d26a0cd88039274b11..f59ec8cb15953446b7ce44b745adf6b0c3b98ed7 100644
--- a/kwant/tests/test_wraparound.py
+++ b/kwant/tests/test_wraparound.py
@@ -13,11 +13,11 @@ import tinyarray as ta
import pytest
import kwant
-from kwant import plotter
+from kwant import _plotter
from kwant.wraparound import wraparound, plot_2d_bands
from kwant._common import get_parameters
-if plotter.mpl_available:
+if _plotter.mpl_available:
from mpl_toolkits import mplot3d # pragma: no flakes
from matplotlib import pyplot # pragma: no flakes
@@ -201,7 +201,7 @@ def test_symmetry():
assert np.all(orig == new)
-@pytest.mark.skipif(not plotter.mpl_available, reason="Matplotlib unavailable.")
+@pytest.mark.skipif(not _plotter.mpl_available, reason="Matplotlib unavailable.")
def test_plot_2d_bands():
chain = kwant.lattice.chain()
square = kwant.lattice.square()
diff --git a/pytest.ini b/pytest.ini
index 6c8258daf2ed83d5fb6da872d379c2ad36d42c25..c7f56a4768a2f6f410c50545cc5740b85baef3d7 100644
--- a/pytest.ini
+++ b/pytest.ini
@@ -2,5 +2,6 @@
testpaths = kwant
flakes-ignore =
__init__.py UnusedImport
+ kwant/_plotter.py UnusedImport
graph/tests/test_scotch.py UndefinedName
graph/tests/test_dissection.py UndefinedName