import math import types import numpy as np import matplotlib as mpl from matplotlib import _api, cbook from matplotlib.axes import Axes import matplotlib.axis as maxis import matplotlib.markers as mmarkers import matplotlib.patches as mpatches from matplotlib.path import Path import matplotlib.ticker as mticker import matplotlib.transforms as mtransforms from matplotlib.spines import Spine def _apply_theta_transforms_warn(): _api.warn_deprecated( "3.9", message=( "Passing `apply_theta_transforms=True` (the default) " "is deprecated since Matplotlib %(since)s. " "Support for this will be removed in Matplotlib %(removal)s. " "To prevent this warning, set `apply_theta_transforms=False`, " "and make sure to shift theta values before being passed to " "this transform." ) ) class PolarTransform(mtransforms.Transform): r""" The base polar transform. This transform maps polar coordinates :math:`\theta, r` into Cartesian coordinates :math:`x, y = r \cos(\theta), r \sin(\theta)` (but does not fully transform into Axes coordinates or handle positioning in screen space). This transformation is designed to be applied to data after any scaling along the radial axis (e.g. log-scaling) has been applied to the input data. Path segments at a fixed radius are automatically transformed to circular arcs as long as ``path._interpolation_steps > 1``. """ input_dims = output_dims = 2 def __init__(self, axis=None, use_rmin=True, *, apply_theta_transforms=True, scale_transform=None): """ Parameters ---------- axis : `~matplotlib.axis.Axis`, optional Axis associated with this transform. This is used to get the minimum radial limit. use_rmin : `bool`, optional If ``True``, subtract the minimum radial axis limit before transforming to Cartesian coordinates. *axis* must also be specified for this to take effect. """ super().__init__() self._axis = axis self._use_rmin = use_rmin self._apply_theta_transforms = apply_theta_transforms self._scale_transform = scale_transform if apply_theta_transforms: _apply_theta_transforms_warn() __str__ = mtransforms._make_str_method( "_axis", use_rmin="_use_rmin", apply_theta_transforms="_apply_theta_transforms") def _get_rorigin(self): # Get lower r limit after being scaled by the radial scale transform return self._scale_transform.transform( (0, self._axis.get_rorigin()))[1] @_api.rename_parameter("3.8", "tr", "values") def transform_non_affine(self, values): # docstring inherited theta, r = np.transpose(values) # PolarAxes does not use the theta transforms here, but apply them for # backwards-compatibility if not being used by it. if self._apply_theta_transforms and self._axis is not None: theta *= self._axis.get_theta_direction() theta += self._axis.get_theta_offset() if self._use_rmin and self._axis is not None: r = (r - self._get_rorigin()) * self._axis.get_rsign() r = np.where(r >= 0, r, np.nan) return np.column_stack([r * np.cos(theta), r * np.sin(theta)]) def transform_path_non_affine(self, path): # docstring inherited if not len(path) or path._interpolation_steps == 1: return Path(self.transform_non_affine(path.vertices), path.codes) xys = [] codes = [] last_t = last_r = None for trs, c in path.iter_segments(): trs = trs.reshape((-1, 2)) if c == Path.LINETO: (t, r), = trs if t == last_t: # Same angle: draw a straight line. xys.extend(self.transform_non_affine(trs)) codes.append(Path.LINETO) elif r == last_r: # Same radius: draw an arc. # The following is complicated by Path.arc() being # "helpful" and unwrapping the angles, but we don't want # that behavior here. last_td, td = np.rad2deg([last_t, t]) if self._use_rmin and self._axis is not None: r = ((r - self._get_rorigin()) * self._axis.get_rsign()) if last_td <= td: while td - last_td > 360: arc = Path.arc(last_td, last_td + 360) xys.extend(arc.vertices[1:] * r) codes.extend(arc.codes[1:]) last_td += 360 arc = Path.arc(last_td, td) xys.extend(arc.vertices[1:] * r) codes.extend(arc.codes[1:]) else: # The reverse version also relies on the fact that all # codes but the first one are the same. while last_td - td > 360: arc = Path.arc(last_td - 360, last_td) xys.extend(arc.vertices[::-1][1:] * r) codes.extend(arc.codes[1:]) last_td -= 360 arc = Path.arc(td, last_td) xys.extend(arc.vertices[::-1][1:] * r) codes.extend(arc.codes[1:]) else: # Interpolate. trs = cbook.simple_linear_interpolation( np.vstack([(last_t, last_r), trs]), path._interpolation_steps)[1:] xys.extend(self.transform_non_affine(trs)) codes.extend([Path.LINETO] * len(trs)) else: # Not a straight line. xys.extend(self.transform_non_affine(trs)) codes.extend([c] * len(trs)) last_t, last_r = trs[-1] return Path(xys, codes) def inverted(self): # docstring inherited return PolarAxes.InvertedPolarTransform( self._axis, self._use_rmin, apply_theta_transforms=self._apply_theta_transforms ) class PolarAffine(mtransforms.Affine2DBase): r""" The affine part of the polar projection. Scales the output so that maximum radius rests on the edge of the Axes circle and the origin is mapped to (0.5, 0.5). The transform applied is the same to x and y components and given by: .. math:: x_{1} = 0.5 \left [ \frac{x_{0}}{(r_{\max} - r_{\min})} + 1 \right ] :math:`r_{\min}, r_{\max}` are the minimum and maximum radial limits after any scaling (e.g. log scaling) has been removed. """ def __init__(self, scale_transform, limits): """ Parameters ---------- scale_transform : `~matplotlib.transforms.Transform` Scaling transform for the data. This is used to remove any scaling from the radial view limits. limits : `~matplotlib.transforms.BboxBase` View limits of the data. The only part of its bounds that is used is the y limits (for the radius limits). """ super().__init__() self._scale_transform = scale_transform self._limits = limits self.set_children(scale_transform, limits) self._mtx = None __str__ = mtransforms._make_str_method("_scale_transform", "_limits") def get_matrix(self): # docstring inherited if self._invalid: limits_scaled = self._limits.transformed(self._scale_transform) yscale = limits_scaled.ymax - limits_scaled.ymin affine = mtransforms.Affine2D() \ .scale(0.5 / yscale) \ .translate(0.5, 0.5) self._mtx = affine.get_matrix() self._inverted = None self._invalid = 0 return self._mtx class InvertedPolarTransform(mtransforms.Transform): """ The inverse of the polar transform, mapping Cartesian coordinate space *x* and *y* back to *theta* and *r*. """ input_dims = output_dims = 2 def __init__(self, axis=None, use_rmin=True, *, apply_theta_transforms=True): """ Parameters ---------- axis : `~matplotlib.axis.Axis`, optional Axis associated with this transform. This is used to get the minimum radial limit. use_rmin : `bool`, optional If ``True``, add the minimum radial axis limit after transforming from Cartesian coordinates. *axis* must also be specified for this to take effect. """ super().__init__() self._axis = axis self._use_rmin = use_rmin self._apply_theta_transforms = apply_theta_transforms if apply_theta_transforms: _apply_theta_transforms_warn() __str__ = mtransforms._make_str_method( "_axis", use_rmin="_use_rmin", apply_theta_transforms="_apply_theta_transforms") @_api.rename_parameter("3.8", "xy", "values") def transform_non_affine(self, values): # docstring inherited x, y = values.T r = np.hypot(x, y) theta = (np.arctan2(y, x) + 2 * np.pi) % (2 * np.pi) # PolarAxes does not use the theta transforms here, but apply them for # backwards-compatibility if not being used by it. if self._apply_theta_transforms and self._axis is not None: theta -= self._axis.get_theta_offset() theta *= self._axis.get_theta_direction() theta %= 2 * np.pi if self._use_rmin and self._axis is not None: r += self._axis.get_rorigin() r *= self._axis.get_rsign() return np.column_stack([theta, r]) def inverted(self): # docstring inherited return PolarAxes.PolarTransform( self._axis, self._use_rmin, apply_theta_transforms=self._apply_theta_transforms ) class ThetaFormatter(mticker.Formatter): """ Used to format the *theta* tick labels. Converts the native unit of radians into degrees and adds a degree symbol. """ def __call__(self, x, pos=None): vmin, vmax = self.axis.get_view_interval() d = np.rad2deg(abs(vmax - vmin)) digits = max(-int(np.log10(d) - 1.5), 0) return f"{np.rad2deg(x):0.{digits}f}\N{DEGREE SIGN}" class _AxisWrapper: def __init__(self, axis): self._axis = axis def get_view_interval(self): return np.rad2deg(self._axis.get_view_interval()) def set_view_interval(self, vmin, vmax): self._axis.set_view_interval(*np.deg2rad((vmin, vmax))) def get_minpos(self): return np.rad2deg(self._axis.get_minpos()) def get_data_interval(self): return np.rad2deg(self._axis.get_data_interval()) def set_data_interval(self, vmin, vmax): self._axis.set_data_interval(*np.deg2rad((vmin, vmax))) def get_tick_space(self): return self._axis.get_tick_space() class ThetaLocator(mticker.Locator): """ Used to locate theta ticks. This will work the same as the base locator except in the case that the view spans the entire circle. In such cases, the previously used default locations of every 45 degrees are returned. """ def __init__(self, base): self.base = base self.axis = self.base.axis = _AxisWrapper(self.base.axis) def set_axis(self, axis): self.axis = _AxisWrapper(axis) self.base.set_axis(self.axis) def __call__(self): lim = self.axis.get_view_interval() if _is_full_circle_deg(lim[0], lim[1]): return np.deg2rad(min(lim)) + np.arange(8) * 2 * np.pi / 8 else: return np.deg2rad(self.base()) def view_limits(self, vmin, vmax): vmin, vmax = np.rad2deg((vmin, vmax)) return np.deg2rad(self.base.view_limits(vmin, vmax)) class ThetaTick(maxis.XTick): """ A theta-axis tick. This subclass of `.XTick` provides angular ticks with some small modification to their re-positioning such that ticks are rotated based on tick location. This results in ticks that are correctly perpendicular to the arc spine. When 'auto' rotation is enabled, labels are also rotated to be parallel to the spine. The label padding is also applied here since it's not possible to use a generic axes transform to produce tick-specific padding. """ def __init__(self, axes, *args, **kwargs): self._text1_translate = mtransforms.ScaledTranslation( 0, 0, axes.figure.dpi_scale_trans) self._text2_translate = mtransforms.ScaledTranslation( 0, 0, axes.figure.dpi_scale_trans) super().__init__(axes, *args, **kwargs) self.label1.set( rotation_mode='anchor', transform=self.label1.get_transform() + self._text1_translate) self.label2.set( rotation_mode='anchor', transform=self.label2.get_transform() + self._text2_translate) def _apply_params(self, **kwargs): super()._apply_params(**kwargs) # Ensure transform is correct; sometimes this gets reset. trans = self.label1.get_transform() if not trans.contains_branch(self._text1_translate): self.label1.set_transform(trans + self._text1_translate) trans = self.label2.get_transform() if not trans.contains_branch(self._text2_translate): self.label2.set_transform(trans + self._text2_translate) def _update_padding(self, pad, angle): padx = pad * np.cos(angle) / 72 pady = pad * np.sin(angle) / 72 self._text1_translate._t = (padx, pady) self._text1_translate.invalidate() self._text2_translate._t = (-padx, -pady) self._text2_translate.invalidate() def update_position(self, loc): super().update_position(loc) axes = self.axes angle = loc * axes.get_theta_direction() + axes.get_theta_offset() text_angle = np.rad2deg(angle) % 360 - 90 angle -= np.pi / 2 marker = self.tick1line.get_marker() if marker in (mmarkers.TICKUP, '|'): trans = mtransforms.Affine2D().scale(1, 1).rotate(angle) elif marker == mmarkers.TICKDOWN: trans = mtransforms.Affine2D().scale(1, -1).rotate(angle) else: # Don't modify custom tick line markers. trans = self.tick1line._marker._transform self.tick1line._marker._transform = trans marker = self.tick2line.get_marker() if marker in (mmarkers.TICKUP, '|'): trans = mtransforms.Affine2D().scale(1, 1).rotate(angle) elif marker == mmarkers.TICKDOWN: trans = mtransforms.Affine2D().scale(1, -1).rotate(angle) else: # Don't modify custom tick line markers. trans = self.tick2line._marker._transform self.tick2line._marker._transform = trans mode, user_angle = self._labelrotation if mode == 'default': text_angle = user_angle else: if text_angle > 90: text_angle -= 180 elif text_angle < -90: text_angle += 180 text_angle += user_angle self.label1.set_rotation(text_angle) self.label2.set_rotation(text_angle) # This extra padding helps preserve the look from previous releases but # is also needed because labels are anchored to their center. pad = self._pad + 7 self._update_padding(pad, self._loc * axes.get_theta_direction() + axes.get_theta_offset()) class ThetaAxis(maxis.XAxis): """ A theta Axis. This overrides certain properties of an `.XAxis` to provide special-casing for an angular axis. """ __name__ = 'thetaaxis' axis_name = 'theta' #: Read-only name identifying the axis. _tick_class = ThetaTick def _wrap_locator_formatter(self): self.set_major_locator(ThetaLocator(self.get_major_locator())) self.set_major_formatter(ThetaFormatter()) self.isDefault_majloc = True self.isDefault_majfmt = True def clear(self): # docstring inherited super().clear() self.set_ticks_position('none') self._wrap_locator_formatter() def _set_scale(self, value, **kwargs): if value != 'linear': raise NotImplementedError( "The xscale cannot be set on a polar plot") super()._set_scale(value, **kwargs) # LinearScale.set_default_locators_and_formatters just set the major # locator to be an AutoLocator, so we customize it here to have ticks # at sensible degree multiples. self.get_major_locator().set_params(steps=[1, 1.5, 3, 4.5, 9, 10]) self._wrap_locator_formatter() def _copy_tick_props(self, src, dest): """Copy the props from src tick to dest tick.""" if src is None or dest is None: return super()._copy_tick_props(src, dest) # Ensure that tick transforms are independent so that padding works. trans = dest._get_text1_transform()[0] dest.label1.set_transform(trans + dest._text1_translate) trans = dest._get_text2_transform()[0] dest.label2.set_transform(trans + dest._text2_translate) class RadialLocator(mticker.Locator): """ Used to locate radius ticks. Ensures that all ticks are strictly positive. For all other tasks, it delegates to the base `.Locator` (which may be different depending on the scale of the *r*-axis). """ def __init__(self, base, axes=None): self.base = base self._axes = axes def set_axis(self, axis): self.base.set_axis(axis) def __call__(self): # Ensure previous behaviour with full circle non-annular views. if self._axes: if _is_full_circle_rad(*self._axes.viewLim.intervalx): rorigin = self._axes.get_rorigin() * self._axes.get_rsign() if self._axes.get_rmin() <= rorigin: return [tick for tick in self.base() if tick > rorigin] return self.base() def _zero_in_bounds(self): """ Return True if zero is within the valid values for the scale of the radial axis. """ vmin, vmax = self._axes.yaxis._scale.limit_range_for_scale(0, 1, 1e-5) return vmin == 0 def nonsingular(self, vmin, vmax): # docstring inherited if self._zero_in_bounds() and (vmin, vmax) == (-np.inf, np.inf): # Initial view limits return (0, 1) else: return self.base.nonsingular(vmin, vmax) def view_limits(self, vmin, vmax): vmin, vmax = self.base.view_limits(vmin, vmax) if self._zero_in_bounds() and vmax > vmin: # this allows inverted r/y-lims vmin = min(0, vmin) return mtransforms.nonsingular(vmin, vmax) class _ThetaShift(mtransforms.ScaledTranslation): """ Apply a padding shift based on axes theta limits. This is used to create padding for radial ticks. Parameters ---------- axes : `~matplotlib.axes.Axes` The owning Axes; used to determine limits. pad : float The padding to apply, in points. mode : {'min', 'max', 'rlabel'} Whether to shift away from the start (``'min'``) or the end (``'max'``) of the axes, or using the rlabel position (``'rlabel'``). """ def __init__(self, axes, pad, mode): super().__init__(pad, pad, axes.figure.dpi_scale_trans) self.set_children(axes._realViewLim) self.axes = axes self.mode = mode self.pad = pad __str__ = mtransforms._make_str_method("axes", "pad", "mode") def get_matrix(self): if self._invalid: if self.mode == 'rlabel': angle = ( np.deg2rad(self.axes.get_rlabel_position() * self.axes.get_theta_direction()) + self.axes.get_theta_offset() - np.pi / 2 ) elif self.mode == 'min': angle = self.axes._realViewLim.xmin - np.pi / 2 elif self.mode == 'max': angle = self.axes._realViewLim.xmax + np.pi / 2 self._t = (self.pad * np.cos(angle) / 72, self.pad * np.sin(angle) / 72) return super().get_matrix() class RadialTick(maxis.YTick): """ A radial-axis tick. This subclass of `.YTick` provides radial ticks with some small modification to their re-positioning such that ticks are rotated based on axes limits. This results in ticks that are correctly perpendicular to the spine. Labels are also rotated to be perpendicular to the spine, when 'auto' rotation is enabled. """ def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.label1.set_rotation_mode('anchor') self.label2.set_rotation_mode('anchor') def _determine_anchor(self, mode, angle, start): # Note: angle is the (spine angle - 90) because it's used for the tick # & text setup, so all numbers below are -90 from (normed) spine angle. if mode == 'auto': if start: if -90 <= angle <= 90: return 'left', 'center' else: return 'right', 'center' else: if -90 <= angle <= 90: return 'right', 'center' else: return 'left', 'center' else: if start: if angle < -68.5: return 'center', 'top' elif angle < -23.5: return 'left', 'top' elif angle < 22.5: return 'left', 'center' elif angle < 67.5: return 'left', 'bottom' elif angle < 112.5: return 'center', 'bottom' elif angle < 157.5: return 'right', 'bottom' elif angle < 202.5: return 'right', 'center' elif angle < 247.5: return 'right', 'top' else: return 'center', 'top' else: if angle < -68.5: return 'center', 'bottom' elif angle < -23.5: return 'right', 'bottom' elif angle < 22.5: return 'right', 'center' elif angle < 67.5: return 'right', 'top' elif angle < 112.5: return 'center', 'top' elif angle < 157.5: return 'left', 'top' elif angle < 202.5: return 'left', 'center' elif angle < 247.5: return 'left', 'bottom' else: return 'center', 'bottom' def update_position(self, loc): super().update_position(loc) axes = self.axes thetamin = axes.get_thetamin() thetamax = axes.get_thetamax() direction = axes.get_theta_direction() offset_rad = axes.get_theta_offset() offset = np.rad2deg(offset_rad) full = _is_full_circle_deg(thetamin, thetamax) if full: angle = (axes.get_rlabel_position() * direction + offset) % 360 - 90 tick_angle = 0 else: angle = (thetamin * direction + offset) % 360 - 90 if direction > 0: tick_angle = np.deg2rad(angle) else: tick_angle = np.deg2rad(angle + 180) text_angle = (angle + 90) % 180 - 90 # between -90 and +90. mode, user_angle = self._labelrotation if mode == 'auto': text_angle += user_angle else: text_angle = user_angle if full: ha = self.label1.get_horizontalalignment() va = self.label1.get_verticalalignment() else: ha, va = self._determine_anchor(mode, angle, direction > 0) self.label1.set_horizontalalignment(ha) self.label1.set_verticalalignment(va) self.label1.set_rotation(text_angle) marker = self.tick1line.get_marker() if marker == mmarkers.TICKLEFT: trans = mtransforms.Affine2D().rotate(tick_angle) elif marker == '_': trans = mtransforms.Affine2D().rotate(tick_angle + np.pi / 2) elif marker == mmarkers.TICKRIGHT: trans = mtransforms.Affine2D().scale(-1, 1).rotate(tick_angle) else: # Don't modify custom tick line markers. trans = self.tick1line._marker._transform self.tick1line._marker._transform = trans if full: self.label2.set_visible(False) self.tick2line.set_visible(False) angle = (thetamax * direction + offset) % 360 - 90 if direction > 0: tick_angle = np.deg2rad(angle) else: tick_angle = np.deg2rad(angle + 180) text_angle = (angle + 90) % 180 - 90 # between -90 and +90. mode, user_angle = self._labelrotation if mode == 'auto': text_angle += user_angle else: text_angle = user_angle ha, va = self._determine_anchor(mode, angle, direction < 0) self.label2.set_ha(ha) self.label2.set_va(va) self.label2.set_rotation(text_angle) marker = self.tick2line.get_marker() if marker == mmarkers.TICKLEFT: trans = mtransforms.Affine2D().rotate(tick_angle) elif marker == '_': trans = mtransforms.Affine2D().rotate(tick_angle + np.pi / 2) elif marker == mmarkers.TICKRIGHT: trans = mtransforms.Affine2D().scale(-1, 1).rotate(tick_angle) else: # Don't modify custom tick line markers. trans = self.tick2line._marker._transform self.tick2line._marker._transform = trans class RadialAxis(maxis.YAxis): """ A radial Axis. This overrides certain properties of a `.YAxis` to provide special-casing for a radial axis. """ __name__ = 'radialaxis' axis_name = 'radius' #: Read-only name identifying the axis. _tick_class = RadialTick def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.sticky_edges.y.append(0) def _wrap_locator_formatter(self): self.set_major_locator(RadialLocator(self.get_major_locator(), self.axes)) self.isDefault_majloc = True def clear(self): # docstring inherited super().clear() self.set_ticks_position('none') self._wrap_locator_formatter() def _set_scale(self, value, **kwargs): super()._set_scale(value, **kwargs) self._wrap_locator_formatter() def _is_full_circle_deg(thetamin, thetamax): """ Determine if a wedge (in degrees) spans the full circle. The condition is derived from :class:`~matplotlib.patches.Wedge`. """ return abs(abs(thetamax - thetamin) - 360.0) < 1e-12 def _is_full_circle_rad(thetamin, thetamax): """ Determine if a wedge (in radians) spans the full circle. The condition is derived from :class:`~matplotlib.patches.Wedge`. """ return abs(abs(thetamax - thetamin) - 2 * np.pi) < 1.74e-14 class _WedgeBbox(mtransforms.Bbox): """ Transform (theta, r) wedge Bbox into Axes bounding box. Parameters ---------- center : (float, float) Center of the wedge viewLim : `~matplotlib.transforms.Bbox` Bbox determining the boundaries of the wedge originLim : `~matplotlib.transforms.Bbox` Bbox determining the origin for the wedge, if different from *viewLim* """ def __init__(self, center, viewLim, originLim, **kwargs): super().__init__([[0, 0], [1, 1]], **kwargs) self._center = center self._viewLim = viewLim self._originLim = originLim self.set_children(viewLim, originLim) __str__ = mtransforms._make_str_method("_center", "_viewLim", "_originLim") def get_points(self): # docstring inherited if self._invalid: points = self._viewLim.get_points().copy() # Scale angular limits to work with Wedge. points[:, 0] *= 180 / np.pi if points[0, 0] > points[1, 0]: points[:, 0] = points[::-1, 0] # Scale radial limits based on origin radius. points[:, 1] -= self._originLim.y0 # Scale radial limits to match axes limits. rscale = 0.5 / points[1, 1] points[:, 1] *= rscale width = min(points[1, 1] - points[0, 1], 0.5) # Generate bounding box for wedge. wedge = mpatches.Wedge(self._center, points[1, 1], points[0, 0], points[1, 0], width=width) self.update_from_path(wedge.get_path()) # Ensure equal aspect ratio. w, h = self._points[1] - self._points[0] deltah = max(w - h, 0) / 2 deltaw = max(h - w, 0) / 2 self._points += np.array([[-deltaw, -deltah], [deltaw, deltah]]) self._invalid = 0 return self._points class PolarAxes(Axes): """ A polar graph projection, where the input dimensions are *theta*, *r*. Theta starts pointing east and goes anti-clockwise. """ name = 'polar' def __init__(self, *args, theta_offset=0, theta_direction=1, rlabel_position=22.5, **kwargs): # docstring inherited self._default_theta_offset = theta_offset self._default_theta_direction = theta_direction self._default_rlabel_position = np.deg2rad(rlabel_position) super().__init__(*args, **kwargs) self.use_sticky_edges = True self.set_aspect('equal', adjustable='box', anchor='C') self.clear() def clear(self): # docstring inherited super().clear() self.title.set_y(1.05) start = self.spines.get('start', None) if start: start.set_visible(False) end = self.spines.get('end', None) if end: end.set_visible(False) self.set_xlim(0.0, 2 * np.pi) self.grid(mpl.rcParams['polaraxes.grid']) inner = self.spines.get('inner', None) if inner: inner.set_visible(False) self.set_rorigin(None) self.set_theta_offset(self._default_theta_offset) self.set_theta_direction(self._default_theta_direction) def _init_axis(self): # This is moved out of __init__ because non-separable axes don't use it self.xaxis = ThetaAxis(self, clear=False) self.yaxis = RadialAxis(self, clear=False) self.spines['polar'].register_axis(self.yaxis) def _set_lim_and_transforms(self): # A view limit where the minimum radius can be locked if the user # specifies an alternate origin. self._originViewLim = mtransforms.LockableBbox(self.viewLim) # Handle angular offset and direction. self._direction = mtransforms.Affine2D() \ .scale(self._default_theta_direction, 1.0) self._theta_offset = mtransforms.Affine2D() \ .translate(self._default_theta_offset, 0.0) self.transShift = self._direction + self._theta_offset # A view limit shifted to the correct location after accounting for # orientation and offset. self._realViewLim = mtransforms.TransformedBbox(self.viewLim, self.transShift) # Transforms the x and y axis separately by a scale factor # It is assumed that this part will have non-linear components self.transScale = mtransforms.TransformWrapper( mtransforms.IdentityTransform()) # Scale view limit into a bbox around the selected wedge. This may be # smaller than the usual unit axes rectangle if not plotting the full # circle. self.axesLim = _WedgeBbox((0.5, 0.5), self._realViewLim, self._originViewLim) # Scale the wedge to fill the axes. self.transWedge = mtransforms.BboxTransformFrom(self.axesLim) # Scale the axes to fill the figure. self.transAxes = mtransforms.BboxTransformTo(self.bbox) # A (possibly non-linear) projection on the (already scaled) # data. This one is aware of rmin self.transProjection = self.PolarTransform( self, apply_theta_transforms=False, scale_transform=self.transScale ) # Add dependency on rorigin. self.transProjection.set_children(self._originViewLim) # An affine transformation on the data, generally to limit the # range of the axes self.transProjectionAffine = self.PolarAffine(self.transScale, self._originViewLim) # The complete data transformation stack -- from data all the # way to display coordinates # # 1. Remove any radial axis scaling (e.g. log scaling) # 2. Shift data in the theta direction # 3. Project the data from polar to cartesian values # (with the origin in the same place) # 4. Scale and translate the cartesian values to Axes coordinates # (here the origin is moved to the lower left of the Axes) # 5. Move and scale to fill the Axes # 6. Convert from Axes coordinates to Figure coordinates self.transData = ( self.transScale + self.transShift + self.transProjection + ( self.transProjectionAffine + self.transWedge + self.transAxes ) ) # This is the transform for theta-axis ticks. It is # equivalent to transData, except it always puts r == 0.0 and r == 1.0 # at the edge of the axis circles. self._xaxis_transform = ( mtransforms.blended_transform_factory( mtransforms.IdentityTransform(), mtransforms.BboxTransformTo(self.viewLim)) + self.transData) # The theta labels are flipped along the radius, so that text 1 is on # the outside by default. This should work the same as before. flipr_transform = mtransforms.Affine2D() \ .translate(0.0, -0.5) \ .scale(1.0, -1.0) \ .translate(0.0, 0.5) self._xaxis_text_transform = flipr_transform + self._xaxis_transform # This is the transform for r-axis ticks. It scales the theta # axis so the gridlines from 0.0 to 1.0, now go from thetamin to # thetamax. self._yaxis_transform = ( mtransforms.blended_transform_factory( mtransforms.BboxTransformTo(self.viewLim), mtransforms.IdentityTransform()) + self.transData) # The r-axis labels are put at an angle and padded in the r-direction self._r_label_position = mtransforms.Affine2D() \ .translate(self._default_rlabel_position, 0.0) self._yaxis_text_transform = mtransforms.TransformWrapper( self._r_label_position + self.transData) def get_xaxis_transform(self, which='grid'): _api.check_in_list(['tick1', 'tick2', 'grid'], which=which) return self._xaxis_transform def get_xaxis_text1_transform(self, pad): return self._xaxis_text_transform, 'center', 'center' def get_xaxis_text2_transform(self, pad): return self._xaxis_text_transform, 'center', 'center' def get_yaxis_transform(self, which='grid'): if which in ('tick1', 'tick2'): return self._yaxis_text_transform elif which == 'grid': return self._yaxis_transform else: _api.check_in_list(['tick1', 'tick2', 'grid'], which=which) def get_yaxis_text1_transform(self, pad): thetamin, thetamax = self._realViewLim.intervalx if _is_full_circle_rad(thetamin, thetamax): return self._yaxis_text_transform, 'bottom', 'left' elif self.get_theta_direction() > 0: halign = 'left' pad_shift = _ThetaShift(self, pad, 'min') else: halign = 'right' pad_shift = _ThetaShift(self, pad, 'max') return self._yaxis_text_transform + pad_shift, 'center', halign def get_yaxis_text2_transform(self, pad): if self.get_theta_direction() > 0: halign = 'right' pad_shift = _ThetaShift(self, pad, 'max') else: halign = 'left' pad_shift = _ThetaShift(self, pad, 'min') return self._yaxis_text_transform + pad_shift, 'center', halign def draw(self, renderer): self._unstale_viewLim() thetamin, thetamax = np.rad2deg(self._realViewLim.intervalx) if thetamin > thetamax: thetamin, thetamax = thetamax, thetamin rmin, rmax = ((self._realViewLim.intervaly - self.get_rorigin()) * self.get_rsign()) if isinstance(self.patch, mpatches.Wedge): # Backwards-compatibility: Any subclassed Axes might override the # patch to not be the Wedge that PolarAxes uses. center = self.transWedge.transform((0.5, 0.5)) self.patch.set_center(center) self.patch.set_theta1(thetamin) self.patch.set_theta2(thetamax) edge, _ = self.transWedge.transform((1, 0)) radius = edge - center[0] width = min(radius * (rmax - rmin) / rmax, radius) self.patch.set_radius(radius) self.patch.set_width(width) inner_width = radius - width inner = self.spines.get('inner', None) if inner: inner.set_visible(inner_width != 0.0) visible = not _is_full_circle_deg(thetamin, thetamax) # For backwards compatibility, any subclassed Axes might override the # spines to not include start/end that PolarAxes uses. start = self.spines.get('start', None) end = self.spines.get('end', None) if start: start.set_visible(visible) if end: end.set_visible(visible) if visible: yaxis_text_transform = self._yaxis_transform else: yaxis_text_transform = self._r_label_position + self.transData if self._yaxis_text_transform != yaxis_text_transform: self._yaxis_text_transform.set(yaxis_text_transform) self.yaxis.reset_ticks() self.yaxis.set_clip_path(self.patch) super().draw(renderer) def _gen_axes_patch(self): return mpatches.Wedge((0.5, 0.5), 0.5, 0.0, 360.0) def _gen_axes_spines(self): spines = { 'polar': Spine.arc_spine(self, 'top', (0.5, 0.5), 0.5, 0, 360), 'start': Spine.linear_spine(self, 'left'), 'end': Spine.linear_spine(self, 'right'), 'inner': Spine.arc_spine(self, 'bottom', (0.5, 0.5), 0.0, 0, 360), } spines['polar'].set_transform(self.transWedge + self.transAxes) spines['inner'].set_transform(self.transWedge + self.transAxes) spines['start'].set_transform(self._yaxis_transform) spines['end'].set_transform(self._yaxis_transform) return spines def set_thetamax(self, thetamax): """Set the maximum theta limit in degrees.""" self.viewLim.x1 = np.deg2rad(thetamax) def get_thetamax(self): """Return the maximum theta limit in degrees.""" return np.rad2deg(self.viewLim.xmax) def set_thetamin(self, thetamin): """Set the minimum theta limit in degrees.""" self.viewLim.x0 = np.deg2rad(thetamin) def get_thetamin(self): """Get the minimum theta limit in degrees.""" return np.rad2deg(self.viewLim.xmin) def set_thetalim(self, *args, **kwargs): r""" Set the minimum and maximum theta values. Can take the following signatures: - ``set_thetalim(minval, maxval)``: Set the limits in radians. - ``set_thetalim(thetamin=minval, thetamax=maxval)``: Set the limits in degrees. where minval and maxval are the minimum and maximum limits. Values are wrapped in to the range :math:`[0, 2\pi]` (in radians), so for example it is possible to do ``set_thetalim(-np.pi / 2, np.pi / 2)`` to have an axis symmetric around 0. A ValueError is raised if the absolute angle difference is larger than a full circle. """ orig_lim = self.get_xlim() # in radians if 'thetamin' in kwargs: kwargs['xmin'] = np.deg2rad(kwargs.pop('thetamin')) if 'thetamax' in kwargs: kwargs['xmax'] = np.deg2rad(kwargs.pop('thetamax')) new_min, new_max = self.set_xlim(*args, **kwargs) # Parsing all permutations of *args, **kwargs is tricky; it is simpler # to let set_xlim() do it and then validate the limits. if abs(new_max - new_min) > 2 * np.pi: self.set_xlim(orig_lim) # un-accept the change raise ValueError("The angle range must be less than a full circle") return tuple(np.rad2deg((new_min, new_max))) def set_theta_offset(self, offset): """ Set the offset for the location of 0 in radians. """ mtx = self._theta_offset.get_matrix() mtx[0, 2] = offset self._theta_offset.invalidate() def get_theta_offset(self): """ Get the offset for the location of 0 in radians. """ return self._theta_offset.get_matrix()[0, 2] def set_theta_zero_location(self, loc, offset=0.0): """ Set the location of theta's zero. This simply calls `set_theta_offset` with the correct value in radians. Parameters ---------- loc : str May be one of "N", "NW", "W", "SW", "S", "SE", "E", or "NE". offset : float, default: 0 An offset in degrees to apply from the specified *loc*. **Note:** this offset is *always* applied counter-clockwise regardless of the direction setting. """ mapping = { 'N': np.pi * 0.5, 'NW': np.pi * 0.75, 'W': np.pi, 'SW': np.pi * 1.25, 'S': np.pi * 1.5, 'SE': np.pi * 1.75, 'E': 0, 'NE': np.pi * 0.25} return self.set_theta_offset(mapping[loc] + np.deg2rad(offset)) def set_theta_direction(self, direction): """ Set the direction in which theta increases. clockwise, -1: Theta increases in the clockwise direction counterclockwise, anticlockwise, 1: Theta increases in the counterclockwise direction """ mtx = self._direction.get_matrix() if direction in ('clockwise', -1): mtx[0, 0] = -1 elif direction in ('counterclockwise', 'anticlockwise', 1): mtx[0, 0] = 1 else: _api.check_in_list( [-1, 1, 'clockwise', 'counterclockwise', 'anticlockwise'], direction=direction) self._direction.invalidate() def get_theta_direction(self): """ Get the direction in which theta increases. -1: Theta increases in the clockwise direction 1: Theta increases in the counterclockwise direction """ return self._direction.get_matrix()[0, 0] def set_rmax(self, rmax): """ Set the outer radial limit. Parameters ---------- rmax : float """ self.viewLim.y1 = rmax def get_rmax(self): """ Returns ------- float Outer radial limit. """ return self.viewLim.ymax def set_rmin(self, rmin): """ Set the inner radial limit. Parameters ---------- rmin : float """ self.viewLim.y0 = rmin def get_rmin(self): """ Returns ------- float The inner radial limit. """ return self.viewLim.ymin def set_rorigin(self, rorigin): """ Update the radial origin. Parameters ---------- rorigin : float """ self._originViewLim.locked_y0 = rorigin def get_rorigin(self): """ Returns ------- float """ return self._originViewLim.y0 def get_rsign(self): return np.sign(self._originViewLim.y1 - self._originViewLim.y0) def set_rlim(self, bottom=None, top=None, *, emit=True, auto=False, **kwargs): """ Set the radial axis view limits. This function behaves like `.Axes.set_ylim`, but additionally supports *rmin* and *rmax* as aliases for *bottom* and *top*. See Also -------- .Axes.set_ylim """ if 'rmin' in kwargs: if bottom is None: bottom = kwargs.pop('rmin') else: raise ValueError('Cannot supply both positional "bottom"' 'argument and kwarg "rmin"') if 'rmax' in kwargs: if top is None: top = kwargs.pop('rmax') else: raise ValueError('Cannot supply both positional "top"' 'argument and kwarg "rmax"') return self.set_ylim(bottom=bottom, top=top, emit=emit, auto=auto, **kwargs) def get_rlabel_position(self): """ Returns ------- float The theta position of the radius labels in degrees. """ return np.rad2deg(self._r_label_position.get_matrix()[0, 2]) def set_rlabel_position(self, value): """ Update the theta position of the radius labels. Parameters ---------- value : number The angular position of the radius labels in degrees. """ self._r_label_position.clear().translate(np.deg2rad(value), 0.0) def set_yscale(self, *args, **kwargs): super().set_yscale(*args, **kwargs) self.yaxis.set_major_locator( self.RadialLocator(self.yaxis.get_major_locator(), self)) def set_rscale(self, *args, **kwargs): return Axes.set_yscale(self, *args, **kwargs) def set_rticks(self, *args, **kwargs): return Axes.set_yticks(self, *args, **kwargs) def set_thetagrids(self, angles, labels=None, fmt=None, **kwargs): """ Set the theta gridlines in a polar plot. Parameters ---------- angles : tuple with floats, degrees The angles of the theta gridlines. labels : tuple with strings or None The labels to use at each theta gridline. The `.projections.polar.ThetaFormatter` will be used if None. fmt : str or None Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'. Note that the angle that is used is in radians. Returns ------- lines : list of `.lines.Line2D` The theta gridlines. labels : list of `.text.Text` The tick labels. Other Parameters ---------------- **kwargs *kwargs* are optional `.Text` properties for the labels. .. warning:: This only sets the properties of the current ticks. Ticks are not guaranteed to be persistent. Various operations can create, delete and modify the Tick instances. There is an imminent risk that these settings can get lost if you work on the figure further (including also panning/zooming on a displayed figure). Use `.set_tick_params` instead if possible. See Also -------- .PolarAxes.set_rgrids .Axis.get_gridlines .Axis.get_ticklabels """ # Make sure we take into account unitized data angles = self.convert_yunits(angles) angles = np.deg2rad(angles) self.set_xticks(angles) if labels is not None: self.set_xticklabels(labels) elif fmt is not None: self.xaxis.set_major_formatter(mticker.FormatStrFormatter(fmt)) for t in self.xaxis.get_ticklabels(): t._internal_update(kwargs) return self.xaxis.get_ticklines(), self.xaxis.get_ticklabels() def set_rgrids(self, radii, labels=None, angle=None, fmt=None, **kwargs): """ Set the radial gridlines on a polar plot. Parameters ---------- radii : tuple with floats The radii for the radial gridlines labels : tuple with strings or None The labels to use at each radial gridline. The `matplotlib.ticker.ScalarFormatter` will be used if None. angle : float The angular position of the radius labels in degrees. fmt : str or None Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'. Returns ------- lines : list of `.lines.Line2D` The radial gridlines. labels : list of `.text.Text` The tick labels. Other Parameters ---------------- **kwargs *kwargs* are optional `.Text` properties for the labels. .. warning:: This only sets the properties of the current ticks. Ticks are not guaranteed to be persistent. Various operations can create, delete and modify the Tick instances. There is an imminent risk that these settings can get lost if you work on the figure further (including also panning/zooming on a displayed figure). Use `.set_tick_params` instead if possible. See Also -------- .PolarAxes.set_thetagrids .Axis.get_gridlines .Axis.get_ticklabels """ # Make sure we take into account unitized data radii = self.convert_xunits(radii) radii = np.asarray(radii) self.set_yticks(radii) if labels is not None: self.set_yticklabels(labels) elif fmt is not None: self.yaxis.set_major_formatter(mticker.FormatStrFormatter(fmt)) if angle is None: angle = self.get_rlabel_position() self.set_rlabel_position(angle) for t in self.yaxis.get_ticklabels(): t._internal_update(kwargs) return self.yaxis.get_gridlines(), self.yaxis.get_ticklabels() def format_coord(self, theta, r): # docstring inherited screen_xy = self.transData.transform((theta, r)) screen_xys = screen_xy + np.stack( np.meshgrid([-1, 0, 1], [-1, 0, 1])).reshape((2, -1)).T ts, rs = self.transData.inverted().transform(screen_xys).T delta_t = abs((ts - theta + np.pi) % (2 * np.pi) - np.pi).max() delta_t_halfturns = delta_t / np.pi delta_t_degrees = delta_t_halfturns * 180 delta_r = abs(rs - r).max() if theta < 0: theta += 2 * np.pi theta_halfturns = theta / np.pi theta_degrees = theta_halfturns * 180 # See ScalarFormatter.format_data_short. For r, use #g-formatting # (as for linear axes), but for theta, use f-formatting as scientific # notation doesn't make sense and the trailing dot is ugly. def format_sig(value, delta, opt, fmt): # For "f", only count digits after decimal point. prec = (max(0, -math.floor(math.log10(delta))) if fmt == "f" else cbook._g_sig_digits(value, delta)) return f"{value:-{opt}.{prec}{fmt}}" return ('\N{GREEK SMALL LETTER THETA}={}\N{GREEK SMALL LETTER PI} ' '({}\N{DEGREE SIGN}), r={}').format( format_sig(theta_halfturns, delta_t_halfturns, "", "f"), format_sig(theta_degrees, delta_t_degrees, "", "f"), format_sig(r, delta_r, "#", "g"), ) def get_data_ratio(self): """ Return the aspect ratio of the data itself. For a polar plot, this should always be 1.0 """ return 1.0 # # # Interactive panning def can_zoom(self): """ Return whether this Axes supports the zoom box button functionality. A polar Axes does not support zoom boxes. """ return False def can_pan(self): """ Return whether this Axes supports the pan/zoom button functionality. For a polar Axes, this is slightly misleading. Both panning and zooming are performed by the same button. Panning is performed in azimuth while zooming is done along the radial. """ return True def start_pan(self, x, y, button): angle = np.deg2rad(self.get_rlabel_position()) mode = '' if button == 1: epsilon = np.pi / 45.0 t, r = self.transData.inverted().transform((x, y)) if angle - epsilon <= t <= angle + epsilon: mode = 'drag_r_labels' elif button == 3: mode = 'zoom' self._pan_start = types.SimpleNamespace( rmax=self.get_rmax(), trans=self.transData.frozen(), trans_inverse=self.transData.inverted().frozen(), r_label_angle=self.get_rlabel_position(), x=x, y=y, mode=mode) def end_pan(self): del self._pan_start def drag_pan(self, button, key, x, y): p = self._pan_start if p.mode == 'drag_r_labels': (startt, startr), (t, r) = p.trans_inverse.transform( [(p.x, p.y), (x, y)]) # Deal with theta dt = np.rad2deg(startt - t) self.set_rlabel_position(p.r_label_angle - dt) trans, vert1, horiz1 = self.get_yaxis_text1_transform(0.0) trans, vert2, horiz2 = self.get_yaxis_text2_transform(0.0) for t in self.yaxis.majorTicks + self.yaxis.minorTicks: t.label1.set_va(vert1) t.label1.set_ha(horiz1) t.label2.set_va(vert2) t.label2.set_ha(horiz2) elif p.mode == 'zoom': (startt, startr), (t, r) = p.trans_inverse.transform( [(p.x, p.y), (x, y)]) # Deal with r scale = r / startr self.set_rmax(p.rmax / scale) # To keep things all self-contained, we can put aliases to the Polar classes # defined above. This isn't strictly necessary, but it makes some of the # code more readable, and provides a backwards compatible Polar API. In # particular, this is used by the :doc:`/gallery/specialty_plots/radar_chart` # example to override PolarTransform on a PolarAxes subclass, so make sure that # that example is unaffected before changing this. PolarAxes.PolarTransform = PolarTransform PolarAxes.PolarAffine = PolarAffine PolarAxes.InvertedPolarTransform = InvertedPolarTransform PolarAxes.ThetaFormatter = ThetaFormatter PolarAxes.RadialLocator = RadialLocator PolarAxes.ThetaLocator = ThetaLocator