# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
This file defines the classes used to represent a 'coordinate', which includes
axes, ticks, tick labels, and grid lines.
"""
import warnings
import numpy as np
from matplotlib import rcParams
from matplotlib.patches import PathPatch
from matplotlib.path import Path
from matplotlib.transforms import Affine2D, ScaledTranslation
from astropy import units as u
from astropy.utils.exceptions import AstropyDeprecationWarning
from .axislabels import AxisLabels
from .formatter_locator import AngleFormatterLocator, ScalarFormatterLocator
from .frame import EllipticalFrame, RectangularFrame1D
from .grid_paths import get_gridline_path, get_lon_lat_path
from .ticklabels import TickLabels
from .ticks import Ticks
from .utils import MATPLOTLIB_LT_3_8
__all__ = ["CoordinateHelper"]
# Matplotlib's gridlines use Line2D, but ours use PathPatch.
# Patches take a slightly different format of linestyle argument.
LINES_TO_PATCHES_LINESTYLE = {
"-": "solid",
"--": "dashed",
"-.": "dashdot",
":": "dotted",
"none": "none",
"None": "none",
" ": "none",
"": "none",
}
def wrap_angle_at(values, coord_wrap):
# On ARM processors, np.mod emits warnings if there are NaN values in the
# array, although this doesn't seem to happen on other processors.
with np.errstate(invalid="ignore"):
return np.mod(values - coord_wrap, 360.0) - (360.0 - coord_wrap)
[docs]
class CoordinateHelper:
"""
Helper class to control one of the coordinates in the
:class:`~astropy.visualization.wcsaxes.WCSAxes`.
Parameters
----------
parent_axes : :class:`~astropy.visualization.wcsaxes.WCSAxes`
The axes the coordinate helper belongs to.
parent_map : :class:`~astropy.visualization.wcsaxes.CoordinatesMap`
The :class:`~astropy.visualization.wcsaxes.CoordinatesMap` object this
coordinate belongs to.
transform : `~matplotlib.transforms.Transform`
The transform corresponding to this coordinate system.
coord_index : int
The index of this coordinate in the
:class:`~astropy.visualization.wcsaxes.CoordinatesMap`.
coord_type : {'longitude', 'latitude', 'scalar'}
The type of this coordinate, which is used to determine the wrapping and
boundary behavior of coordinates. Longitudes wrap at ``coord_wrap``,
latitudes have to be in the range -90 to 90, and scalars are unbounded
and do not wrap.
coord_unit : `~astropy.units.Unit`
The unit that this coordinate is in given the output of transform.
format_unit : `~astropy.units.Unit`, optional
The unit to use to display the coordinates.
coord_wrap : `astropy.units.Quantity`
The angle at which the longitude wraps (defaults to 360 degrees).
frame : `~astropy.visualization.wcsaxes.frame.BaseFrame`
The frame of the :class:`~astropy.visualization.wcsaxes.WCSAxes`.
default_label : str, optional
The axis label to show by default if none is set later.
"""
def __init__(
self,
parent_axes=None,
parent_map=None,
transform=None,
coord_index=None,
coord_type="scalar",
coord_unit=None,
coord_wrap=None,
frame=None,
format_unit=None,
default_label=None,
):
# Keep a reference to the parent axes and the transform
self._parent_axes = parent_axes
self._parent_map = parent_map
self._transform = transform
self._coord_index = coord_index
self._coord_unit = coord_unit
self._format_unit = format_unit
self._frame = frame
self._default_label = default_label or ""
self._auto_axislabel = True
self._axislabel_set = False
self._custom_formatter = None
# Disable auto label for elliptical frames as it puts labels in
# annoying places.
if issubclass(self.parent_axes.frame_class, EllipticalFrame):
self._auto_axislabel = False
self.set_coord_type(coord_type, coord_wrap)
# Initialize ticks
self.dpi_transform = Affine2D()
self.offset_transform = ScaledTranslation(0, 0, self.dpi_transform)
self._ticks = Ticks(
frame=self.frame, transform=parent_axes.transData + self.offset_transform
)
# Initialize tick labels
self._ticklabels = TickLabels(
self.frame,
transform=None, # display coordinates
figure=parent_axes.get_figure(),
)
self._ticks.display_minor_ticks(rcParams["xtick.minor.visible"])
self._minor_frequency = 5
# Initialize axis labels
self._axislabels = AxisLabels(
self.frame,
transform=None, # display coordinates
figure=parent_axes.get_figure(),
)
# Initialize container for the grid lines
self._grid_lines = []
# Initialize grid style. Take defaults from matplotlib.rcParams.
# Based on matplotlib.axis.YTick._get_gridline.
self._grid_lines_kwargs = {
"visible": False,
"facecolor": "none",
"edgecolor": rcParams["grid.color"],
"linestyle": LINES_TO_PATCHES_LINESTYLE[rcParams["grid.linestyle"]],
"linewidth": rcParams["grid.linewidth"],
"alpha": rcParams["grid.alpha"],
"transform": self.parent_axes.transData,
}
@property
def parent_axes(self):
"""
The axes the coordinate helper belongs to.
"""
return self._parent_axes
@parent_axes.setter
def parent_axes(self, value):
warnings.warn(
"Setting CoordinateHelper.parent_axes directly is deprecated",
AstropyDeprecationWarning,
)
self._parent_axes = value
@property
def parent_map(self):
"""
The :class:`~astropy.visualization.wcsaxes.CoordinatesMap` object this
coordinate belongs to.
"""
return self._parent_map
@parent_map.setter
def parent_map(self, value):
warnings.warn(
"Setting CoordinateHelper.parent_map directly is deprecated",
AstropyDeprecationWarning,
)
self._parent_map = value
@property
def transform(self):
"""
The transform corresponding to this coordinate system.
"""
return self._transform
@transform.setter
def transform(self, value):
warnings.warn(
"Setting CoordinateHelper.transform directly is deprecated",
AstropyDeprecationWarning,
)
self._transform = value
@property
def coord_index(self):
"""
The index of this coordinate in the
:class:`~astropy.visualization.wcsaxes.CoordinatesMap`.
"""
return self._coord_index
@coord_index.setter
def coord_index(self, value):
warnings.warn(
"Setting CoordinateHelper.coord_index directly is deprecated",
AstropyDeprecationWarning,
)
self._coord_index = value
@property
def coord_type(self):
"""
The type of this coordinate (e.g., ``'longitude'``)
"""
return self._coord_type
@coord_type.setter
def coord_type(self, value):
warnings.warn(
"Setting CoordinateHelper.coord_type directly is deprecated, use CoordinateHelper.set_coord_type instead",
AstropyDeprecationWarning,
)
self._coord_type = value
@property
def coord_unit(self):
"""
The unit that this coordinate is in given the output of transform.
"""
return self._coord_unit
@coord_unit.setter
def coord_unit(self, value):
warnings.warn(
"Setting CoordinateHelper.coord_unit directly is deprecated",
AstropyDeprecationWarning,
)
self._coord_unit = value
@property
def coord_wrap(self):
"""
The angle at which the longitude wraps (defaults to 360 degrees).
"""
return self._coord_wrap
@coord_wrap.setter
def coord_wrap(self, value):
warnings.warn(
"Setting CoordinateHelper.coord_wrap directly is deprecated, use CoordinateHelper.set_coord_type instead",
AstropyDeprecationWarning,
)
self._coord_wrap = value
@property
def frame(self):
"""
The frame of the :class:`~astropy.visualization.wcsaxes.WCSAxes`.
"""
return self._frame
@frame.setter
def frame(self, value):
warnings.warn(
"Setting CoordinateHelper.frame directly is deprecated",
AstropyDeprecationWarning,
)
self._frame = value
@property
def default_label(self):
"""
The axis label to show by default if none is set later.
"""
return self._default_label
@default_label.setter
def default_label(self, value):
warnings.warn(
"Setting CoordinateHelper.default_label directly is deprecated",
AstropyDeprecationWarning,
)
self._default_label = value
@property
def ticks(self):
warnings.warn(
"CoordinateHelper.ticks should not be accessed directly and is deprecated",
AstropyDeprecationWarning,
)
return self._ticks
@ticks.setter
def ticks(self, value):
warnings.warn(
"Setting CoordinateHelper.ticks directly is deprecated",
AstropyDeprecationWarning,
)
self._ticks = value
@property
def ticklabels(self):
warnings.warn(
"CoordinateHelper.ticklabels should not be accessed directly and is deprecated",
AstropyDeprecationWarning,
)
return self._ticklabels
@ticklabels.setter
def ticklabels(self, value):
warnings.warn(
"Setting CoordinateHelper.ticklabels directly is deprecated",
AstropyDeprecationWarning,
)
self._ticklabels = value
@property
def axislabels(self):
warnings.warn(
"CoordinateHelper.axislabels should not be accessed directly and is deprecated",
AstropyDeprecationWarning,
)
return self._axislabels
@axislabels.setter
def axislabels(self, value):
warnings.warn(
"Setting CoordinateHelper.axislabels directly is deprecated",
AstropyDeprecationWarning,
)
self._axislabels = value
[docs]
def grid(self, draw_grid=True, grid_type=None, **kwargs):
"""
Plot grid lines for this coordinate.
Standard matplotlib appearance options (color, alpha, etc.) can be
passed as keyword arguments.
Parameters
----------
draw_grid : bool
Whether to show the gridlines
grid_type : {'lines', 'contours'}
Whether to plot the contours by determining the grid lines in
world coordinates and then plotting them in world coordinates
(``'lines'``) or by determining the world coordinates at many
positions in the image and then drawing contours
(``'contours'``). The first is recommended for 2-d images, while
for 3-d (or higher dimensional) cubes, the ``'contours'`` option
is recommended. By default, 'lines' is used if the transform has
an inverse, otherwise 'contours' is used.
"""
if grid_type == "lines" and not self.transform.has_inverse:
raise ValueError(
"The specified transform has no inverse, so the "
"grid cannot be drawn using grid_type='lines'"
)
if grid_type is None:
grid_type = "lines" if self.transform.has_inverse else "contours"
if grid_type in ("lines", "contours"):
self._grid_type = grid_type
else:
raise ValueError("grid_type should be 'lines' or 'contours'")
if "color" in kwargs:
kwargs["edgecolor"] = kwargs.pop("color")
self._grid_lines_kwargs.update(kwargs)
if draw_grid is None:
draw_grid = True
self._grid_lines_kwargs["visible"] = draw_grid
[docs]
def set_coord_type(self, coord_type, coord_wrap=None):
"""
Set the coordinate type for the axis.
Parameters
----------
coord_type : str
One of 'longitude', 'latitude' or 'scalar'
coord_wrap : `~astropy.units.Quantity`, optional
The value to wrap at for angular coordinates.
"""
self._coord_type = coord_type
if coord_wrap is not None and not isinstance(coord_wrap, u.Quantity):
warnings.warn(
"Passing 'coord_wrap' as a number is deprecated. Use a Quantity with units convertible to angular degrees instead.",
AstropyDeprecationWarning,
)
coord_wrap = coord_wrap * u.deg
if coord_type == "longitude" and coord_wrap is None:
self._coord_wrap = 360 * u.deg
elif coord_type != "longitude" and coord_wrap is not None:
raise NotImplementedError(
"coord_wrap is not yet supported for non-longitude coordinates"
)
else:
self._coord_wrap = coord_wrap
# Initialize tick formatter/locator
if coord_type == "scalar":
self._coord_scale_to_deg = None
self._formatter_locator = ScalarFormatterLocator(unit=self.coord_unit)
elif coord_type in ["longitude", "latitude"]:
if self.coord_unit is u.deg:
self._coord_scale_to_deg = None
else:
self._coord_scale_to_deg = self.coord_unit.to(u.deg)
self._formatter_locator = AngleFormatterLocator(
unit=self.coord_unit, format_unit=self._format_unit
)
else:
raise ValueError(
"coord_type should be one of 'scalar', 'longitude', or 'latitude'"
)
[docs]
def set_separator(self, separator):
"""
Set the separator to use for the angle major tick labels.
Parameters
----------
separator : str or tuple or None
The separator between numbers in sexagesimal representation. Can be
either a string or a tuple (or `None` for default).
"""
if not (self._formatter_locator.__class__ == AngleFormatterLocator):
raise TypeError("Separator can only be specified for angle coordinates")
if isinstance(separator, (str, tuple)) or separator is None:
self._formatter_locator.sep = separator
else:
raise TypeError("separator should be a string, a tuple, or None")
[docs]
def set_ticks(
self,
values=None,
spacing=None,
number=None,
size=None,
width=None,
color=None,
alpha=None,
direction=None,
exclude_overlapping=None,
):
"""
Set the location and properties of the ticks.
At most one of the options from ``values``, ``spacing``, or
``number`` can be specified.
Parameters
----------
values : iterable, optional
The coordinate values at which to show the ticks.
spacing : float, optional
The spacing between ticks.
number : float, optional
The approximate number of ticks shown.
size : float, optional
The length of the ticks in points
color : str or tuple, optional
A valid Matplotlib color for the ticks
alpha : float, optional
The alpha value (transparency) for the ticks.
direction : {'in','out'}, optional
Whether the ticks should point inwards or outwards.
"""
if sum([values is None, spacing is None, number is None]) < 2:
raise ValueError(
"At most one of values, spacing, or number should be specified"
)
if values is not None:
self._formatter_locator.values = values
elif spacing is not None:
self._formatter_locator.spacing = spacing
elif number is not None:
self._formatter_locator.number = number
if size is not None:
self._ticks.set_ticksize(size)
if width is not None:
self._ticks.set_linewidth(width)
if color is not None:
self._ticks.set_color(color)
if alpha is not None:
self._ticks.set_alpha(alpha)
if direction is not None:
if direction in ("in", "out"):
self._ticks.set_tick_out(direction == "out")
else:
raise ValueError("direction should be 'in' or 'out'")
if exclude_overlapping is not None:
warnings.warn(
"exclude_overlapping= should be passed to "
"set_ticklabel instead of set_ticks",
AstropyDeprecationWarning,
)
self._ticklabels.set_exclude_overlapping(exclude_overlapping)
[docs]
def set_ticks_position(self, position):
"""
Set where ticks should appear.
Parameters
----------
position : str or list
The axes on which the ticks for this coordinate should appear.
Should be a sequence containing zero or more of ``'b'``, ``'t'``,
``'l'``, ``'r'``. For example, ``'lb'`` will lead the ticks to be
shown on the left and bottom axis. In addition, if ``'#'`` is
included in the sequence, the position will be considered dynamic and
will be updated at draw-time in order to show the ticks on the same
axes as the tick labels are shown.
"""
self._ticks.set_visible_axes(position)
[docs]
def get_ticks_position(self):
"""
Get where tick labels will appear.
"""
return list(self._ticks.get_visible_axes())
[docs]
def set_ticks_visible(self, visible):
"""
Set whether ticks are visible or not.
Parameters
----------
visible : bool
The visibility of ticks. Setting as ``False`` will hide ticks
along this coordinate.
"""
self._ticks.set_visible(visible)
[docs]
def set_ticklabel(
self,
color=None,
size=None,
pad=None,
exclude_overlapping=None,
*,
simplify=True,
**kwargs,
):
"""
Set the visual properties for the tick labels.
Parameters
----------
size : float, optional
The size of the ticks labels in points
color : str or tuple, optional
A valid Matplotlib color for the tick labels
pad : float, optional
Distance in points between tick and label.
exclude_overlapping : bool, optional
Whether to exclude tick labels that overlap over each other.
simplify : bool, optional
Whether to remove repeated parts of tick labels.
**kwargs
Other keyword arguments are passed to :class:`matplotlib.text.Text`.
"""
if size is not None:
self._ticklabels.set_size(size)
if color is not None:
self._ticklabels.set_color(color)
if pad is not None:
self._ticklabels.set_pad(pad)
if exclude_overlapping is not None:
self._ticklabels.set_exclude_overlapping(exclude_overlapping)
self._ticklabels.set_simplify(simplify)
self._ticklabels.set(**kwargs)
[docs]
def set_ticklabel_position(self, position):
"""
Set where tick labels should appear.
Parameters
----------
position : str or list
The axes on which the tick labels for this coordinate should
appear. Should be a sequence containing zero or more of ``'b'``,
``'t'``, ``'l'``, ``'r'``. For example, ``'lb'`` will lead the
tick labels to be shown on the left and bottom axis. In addition,
if ``'#'`` is included in the sequence, the position will be
considered dynamic and will be updated at draw-time in order to
attempt to optimize the layout of all the coordinates.
"""
self._ticklabels.set_visible_axes(position)
[docs]
def get_ticklabel_position(self):
"""
Get where tick labels will appear.
"""
return list(self._ticklabels.get_visible_axes())
[docs]
def set_ticklabel_visible(self, visible):
"""
Set whether the tick labels are visible or not.
Parameters
----------
visible : bool
The visibility of ticks. Setting as ``False`` will hide this
coordinate's tick labels.
"""
self._ticklabels.set_visible(visible)
[docs]
def set_axislabel(self, text, minpad=1, **kwargs):
"""
Set the text and optionally visual properties for the axis label.
Parameters
----------
text : str
The axis label text.
minpad : float, optional
The padding for the label in terms of axis label font size.
**kwargs
Keywords are passed to :class:`matplotlib.text.Text`. These
can include keywords to set the ``color``, ``size``, ``weight``, and
other text properties.
"""
fontdict = kwargs.pop("fontdict", None)
# NOTE: When using plt.xlabel/plt.ylabel, minpad can get set explicitly
# to None so we need to make sure that in that case we change to a
# default numerical value.
if minpad is None:
minpad = 1
self._axislabel_set = True
self._axislabels.set_text(text)
self._axislabels.set_minpad(minpad)
self._axislabels.set(**kwargs)
if fontdict is not None:
self._axislabels.update(fontdict)
[docs]
def get_axislabel(self):
"""
Get the text for the axis label.
Returns
-------
label : str
The axis label
"""
if self._auto_axislabel and not self._axislabel_set:
return self._get_default_axislabel()
else:
return self._axislabels.get_text()
[docs]
def set_auto_axislabel(self, auto_label):
"""
Render default axis labels if no explicit label is provided.
Parameters
----------
auto_label : `bool`
`True` if default labels will be rendered.
"""
self._auto_axislabel = bool(auto_label)
[docs]
def get_auto_axislabel(self):
"""
Render default axis labels if no explicit label is provided.
Returns
-------
auto_axislabel : `bool`
`True` if default labels will be rendered.
"""
return self._auto_axislabel
def _get_default_axislabel(self):
unit = self.get_format_unit() or self.coord_unit
if not unit or unit is u.one or self.coord_type in ("longitude", "latitude"):
return f"{self.default_label}"
else:
return f"{self.default_label} [{unit:latex}]"
[docs]
def set_axislabel_position(self, position):
"""
Set where axis labels should appear.
Parameters
----------
position : str or list
The axes on which the axis label for this coordinate should
appear. Should be a sequence containing zero or more of ``'b'``,
``'t'``, ``'l'``, ``'r'``. For example, ``'lb'`` will lead the
axis label to be shown on the left and bottom axis. In addition, if
``'#'`` is included in the sequence, the position will be considered
dynamic and will be updated at draw-time in order to show the axis
label on the same axes as the tick labels are shown.
"""
self._axislabels.set_visible_axes(position)
[docs]
def get_axislabel_position(self):
"""
Get where axis labels will appear.
"""
return list(self._axislabels.get_visible_axes())
[docs]
def set_axislabel_visibility_rule(self, rule):
"""
Set the rule used to determine when the axis label is drawn.
Parameters
----------
rule : str
If the rule is 'always' axis labels will always be drawn on the
axis. If the rule is 'ticks' the label will only be drawn if ticks
were drawn on that axis. If the rule is 'labels' the axis label
will only be drawn if tick labels were drawn on that axis.
"""
self._axislabels.set_visibility_rule(rule)
[docs]
def get_axislabel_visibility_rule(self, rule):
"""
Get the rule used to determine when the axis label is drawn.
"""
return self._axislabels.get_visibility_rule()
@property
def locator(self):
return self._formatter_locator.locator
@property
def formatter(self):
return self._custom_formatter or self._formatter_locator.formatter
def _draw_grid(self, renderer):
renderer.open_group("grid lines")
if self._grid_lines_kwargs["visible"]:
if isinstance(self.frame, RectangularFrame1D):
self._update_grid_lines_1d()
else:
if self._grid_type == "lines":
self._update_grid_lines()
else:
self._update_grid_contour()
if self._grid_type == "lines":
frame_patch = self.frame.patch
for path in self._grid_lines:
p = PathPatch(path, **self._grid_lines_kwargs)
p.set_clip_path(frame_patch)
p.draw(renderer)
elif self._grid is not None:
if MATPLOTLIB_LT_3_8:
for line in self._grid.collections:
line.set(**self._grid_lines_kwargs)
line.draw(renderer)
else:
self._grid.set(**self._grid_lines_kwargs)
self._grid.draw(renderer)
renderer.close_group("grid lines")
def _draw_ticks(self, renderer, existing_bboxes):
"""
Draw all ticks and ticklabels.
Parameters
----------
existing_bboxes : list[Bbox]
All bboxes for ticks that have already been drawn by other
coordinates.
"""
renderer.open_group("ticks")
self._ticks.draw(renderer)
self._ticklabels._tick_out_size = self._ticks.out_size
self._ticklabels._set_existing_bboxes(existing_bboxes)
self._ticklabels.draw(renderer)
renderer.close_group("ticks")
def _draw_axislabels(self, renderer, bboxes, ticklabels_bbox, visible_ticks):
# Render the default axis label if no axis label is set.
if self._auto_axislabel and not self._axislabel_set:
self.set_axislabel(self._get_default_axislabel())
renderer.open_group("axis labels")
self._axislabels.draw(
renderer,
bboxes=bboxes,
ticklabels_bbox=ticklabels_bbox,
coord_ticklabels_bbox=ticklabels_bbox[self],
ticks_locs=self._ticks.ticks_locs,
visible_ticks=visible_ticks,
)
renderer.close_group("axis labels")
def _update_ticks(self):
if self.coord_index is None:
return
# TODO: this method should be optimized for speed
# Here we determine the location and rotation of all the ticks. For
# each axis, we can check the intersections for the specific
# coordinate and once we have the tick positions, we can use the WCS
# to determine the rotations.
coord_range = self.parent_map._coord_range
# First find the ticks we want to show
tick_world_coordinates, self._fl_spacing = self.locator(
*coord_range[self.coord_index]
)
if self._ticks.get_display_minor_ticks():
minor_ticks_w_coordinates = self._formatter_locator.minor_locator(
self._fl_spacing,
self.get_minor_frequency(),
*coord_range[self.coord_index],
)
# We want to allow non-standard rectangular frames, so we just rely on
# the parent axes to tell us what the bounding frame is.
from . import conf
frame = self.frame.sample(conf.frame_boundary_samples)
self._ticks.clear()
self._ticklabels.clear()
self._lblinfo = []
self._lbl_world = []
# Look up parent axes' transform from data to figure coordinates.
#
# See:
# https://matplotlib.org/stable/tutorials/advanced/transforms_tutorial.html#the-transformation-pipeline
transData = self.parent_axes.transData
invertedTransLimits = transData.inverted()
for axis, spine in frame.items():
if spine.data.size == 0:
continue
if not isinstance(self.frame, RectangularFrame1D):
# Determine tick rotation in display coordinates and compare to
# the normal angle in display coordinates.
pixel0 = spine.data
world0 = spine.world[:, self.coord_index]
if np.isnan(world0).all():
continue
axes0 = transData.transform(pixel0)
# Advance 2 pixels in figure coordinates
pixel1 = axes0.copy()
pixel1[:, 0] += 2.0
pixel1 = invertedTransLimits.transform(pixel1)
with np.errstate(invalid="ignore"):
world1 = self.transform.transform(pixel1)[:, self.coord_index]
# Advance 2 pixels in figure coordinates
pixel2 = axes0.copy()
pixel2[:, 1] += 2.0 if self.frame.origin == "lower" else -2.0
pixel2 = invertedTransLimits.transform(pixel2)
with np.errstate(invalid="ignore"):
world2 = self.transform.transform(pixel2)[:, self.coord_index]
dx = world1 - world0
dy = world2 - world0
# Rotate by 90 degrees
dx, dy = -dy, dx
if self.coord_type == "longitude":
if self._coord_scale_to_deg is not None:
dx *= self._coord_scale_to_deg
dy *= self._coord_scale_to_deg
# Here we wrap at 180 not self.coord_wrap since we want to
# always ensure abs(dx) < 180 and abs(dy) < 180
dx = wrap_angle_at(dx, 180.0)
dy = wrap_angle_at(dy, 180.0)
tick_angle = np.degrees(np.arctan2(dy, dx))
normal_angle_full = np.hstack(
[spine.normal_angle, spine.normal_angle[-1]]
)
with np.errstate(invalid="ignore"):
reset = ((normal_angle_full - tick_angle) % 360 > 90.0) & (
(tick_angle - normal_angle_full) % 360 > 90.0
)
tick_angle[reset] -= 180.0
else:
rotation = 90 if axis == "b" else -90
tick_angle = np.zeros((conf.frame_boundary_samples,)) + rotation
# We find for each interval the starting and ending coordinate,
# ensuring that we take wrapping into account correctly for
# longitudes.
w1 = spine.world[:-1, self.coord_index]
w2 = spine.world[1:, self.coord_index]
if self.coord_type == "longitude":
if self._coord_scale_to_deg is not None:
w1 = w1 * self._coord_scale_to_deg
w2 = w2 * self._coord_scale_to_deg
w1 = wrap_angle_at(w1, self.coord_wrap.to_value(u.deg))
w2 = wrap_angle_at(w2, self.coord_wrap.to_value(u.deg))
with np.errstate(invalid="ignore"):
w1[w2 - w1 > 180.0] += 360
w2[w1 - w2 > 180.0] += 360
if self._coord_scale_to_deg is not None:
w1 = w1 / self._coord_scale_to_deg
w2 = w2 / self._coord_scale_to_deg
# For longitudes, we need to check ticks as well as ticks + 360,
# since the above can produce pairs such as 359 to 361 or 0.5 to
# 1.5, both of which would match a tick at 0.75. Otherwise we just
# check the ticks determined above.
self._compute_ticks(tick_world_coordinates, spine, axis, w1, w2, tick_angle)
if self._ticks.get_display_minor_ticks():
self._compute_ticks(
minor_ticks_w_coordinates,
spine,
axis,
w1,
w2,
tick_angle,
ticks="minor",
)
# format tick labels, add to scene
text = self.formatter(
self._lbl_world * tick_world_coordinates.unit, spacing=self._fl_spacing
)
for kwargs, txt in zip(self._lblinfo, text):
self._ticklabels.add(text=txt, **kwargs)
def _compute_ticks(
self, tick_world_coordinates, spine, axis, w1, w2, tick_angle, ticks="major"
):
if self.coord_type == "longitude":
tick_world_coordinates_values = tick_world_coordinates.to_value(u.deg)
tick_world_coordinates_values = np.hstack(
[tick_world_coordinates_values, tick_world_coordinates_values + 360]
)
tick_world_coordinates_values *= u.deg.to(self.coord_unit)
else:
tick_world_coordinates_values = tick_world_coordinates.to_value(
self.coord_unit
)
for t in tick_world_coordinates_values:
# Find steps where a tick is present. We have to check
# separately for the case where the tick falls exactly on the
# frame points, otherwise we'll get two matches, one for w1 and
# one for w2.
with np.errstate(invalid="ignore"):
intersections = np.hstack(
[
np.nonzero((t - w1) == 0)[0],
np.nonzero(((t - w1) * (t - w2)) < 0)[0],
]
)
# But we also need to check for intersection with the last w2
if t - w2[-1] == 0:
intersections = np.append(intersections, len(w2) - 1)
# Loop over ticks, and find exact pixel coordinates by linear
# interpolation
for imin in intersections:
imax = imin + 1
if np.allclose(w1[imin], w2[imin], rtol=1.0e-13, atol=1.0e-13):
continue # tick is exactly aligned with frame
else:
frac = (t - w1[imin]) / (w2[imin] - w1[imin])
x_data_i = spine.data[imin, 0] + frac * (
spine.data[imax, 0] - spine.data[imin, 0]
)
y_data_i = spine.data[imin, 1] + frac * (
spine.data[imax, 1] - spine.data[imin, 1]
)
delta_angle = tick_angle[imax] - tick_angle[imin]
if delta_angle > 180.0:
delta_angle -= 360.0
elif delta_angle < -180.0:
delta_angle += 360.0
angle_i = tick_angle[imin] + frac * delta_angle
if self.coord_type == "longitude":
if self._coord_scale_to_deg is not None:
t *= self._coord_scale_to_deg
world = wrap_angle_at(t, self.coord_wrap.to_value(u.deg))
if self._coord_scale_to_deg is not None:
world /= self._coord_scale_to_deg
else:
world = t
if ticks == "major":
self._ticks.add(
axis=axis,
pixel=(x_data_i, y_data_i),
world=world,
angle=angle_i,
axis_displacement=imin + frac,
)
# store information to pass to ticklabels.add
# it's faster to format many ticklabels at once outside
# of the loop
self._lblinfo.append(
dict(
axis=axis,
data=(x_data_i, y_data_i),
world=world,
angle=spine.normal_angle[imin],
axis_displacement=imin + frac,
)
)
self._lbl_world.append(world)
else:
self._ticks.add_minor(
minor_axis=axis,
minor_pixel=(x_data_i, y_data_i),
minor_world=world,
minor_angle=angle_i,
minor_axis_displacement=imin + frac,
)
[docs]
def display_minor_ticks(self, display_minor_ticks):
"""
Display minor ticks for this coordinate.
Parameters
----------
display_minor_ticks : bool
Whether or not to display minor ticks.
"""
self._ticks.display_minor_ticks(display_minor_ticks)
[docs]
def get_minor_frequency(self):
return self._minor_frequency
[docs]
def set_minor_frequency(self, frequency):
"""
Set the frequency of minor ticks per major ticks.
Parameters
----------
frequency : int
The number of minor ticks per major ticks.
"""
self._minor_frequency = frequency
def _update_grid_lines_1d(self):
if self.coord_index is None:
return
x_ticks_pos = [a[0] for a in self._ticks.pixel["b"]]
ymin, ymax = self.parent_axes.get_ylim()
self._grid_lines = []
for x_coord in x_ticks_pos:
pixel = [[x_coord, ymin], [x_coord, ymax]]
self._grid_lines.append(Path(pixel))
def _update_grid_lines(self):
# For 3-d WCS with a correlated third axis, the *proper* way of
# drawing a grid should be to find the world coordinates of all pixels
# and drawing contours. What we are doing here assumes that we can
# define the grid lines with just two of the coordinates (and
# therefore assumes that the other coordinates are fixed and set to
# the value in the slice). Here we basically assume that if the WCS
# had a third axis, it has been abstracted away in the transformation.
if self.coord_index is None:
return
coord_range = self.parent_map._coord_range
tick_world_coordinates, spacing = self.locator(*coord_range[self.coord_index])
tick_world_coordinates_values = tick_world_coordinates.to_value(self.coord_unit)
n_coord = len(tick_world_coordinates_values)
if n_coord == 0:
return
from . import conf
n_samples = conf.grid_samples
xy_world = np.zeros((n_samples * n_coord, 2))
self._grid_lines = []
for iw, w in enumerate(tick_world_coordinates_values):
subset = slice(iw * n_samples, (iw + 1) * n_samples)
if self.coord_index == 0:
xy_world[subset, 0] = np.repeat(w, n_samples)
xy_world[subset, 1] = np.linspace(
coord_range[1][0], coord_range[1][1], n_samples
)
else:
xy_world[subset, 0] = np.linspace(
coord_range[0][0], coord_range[0][1], n_samples
)
xy_world[subset, 1] = np.repeat(w, n_samples)
# We now convert all the world coordinates to pixel coordinates in a
# single go rather than doing this in the gridline to path conversion
# to fully benefit from vectorized coordinate transformations.
# Transform line to pixel coordinates
pixel = self.transform.inverted().transform(xy_world)
# Create round-tripped values for checking
xy_world_round = self.transform.transform(pixel)
for iw in range(n_coord):
subset = slice(iw * n_samples, (iw + 1) * n_samples)
self._grid_lines.append(
self._get_gridline(
xy_world[subset], pixel[subset], xy_world_round[subset]
)
)
[docs]
def add_tickable_gridline(self, name, constant):
"""
Define a gridline that can be used for ticks and labels.
This gridline is not itself drawn, but instead can be specified in calls to
methods such as
:meth:`~astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper.set_ticklabel_position`
for drawing ticks and labels. Since the gridline has a constant value in this
coordinate, and thus would not have any ticks or labels for the same coordinate,
the call to
:meth:`~astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper.set_ticklabel_position`
would typically be made on the complementary coordinate.
Parameters
----------
name : str
The name for the gridline, usually a single character, but can be longer
constant : `~astropy.units.Quantity`
The constant coordinate value of the gridline
Notes
-----
A limitation is that the tickable part of the gridline must be contiguous. If
the gridline consists of more than one disconnected segment within the plot
extent, only one of those segments will be made tickable.
"""
if self.coord_index is None:
return
if name in self.frame:
raise ValueError(f"The frame already has a spine with the name '{name}'")
coord_range = self.parent_map.get_coord_range()
constant = constant.to_value(self.coord_unit)
from . import conf
n_samples = conf.grid_samples
# See comment in _update_grid_lines() about a WCS with more than 2 axes
xy_world = np.zeros((n_samples, 2))
xy_world[:, self.coord_index] = np.repeat(constant, n_samples)
# If the complementary coordinate is longitude, we attempt to close the gridline
# If such closure is a discontinuity, it will be filtered out later
if self.parent_map[1 - self.coord_index].coord_type == "longitude":
xy_world[:-1, 1 - self.coord_index] = np.linspace(
coord_range[1 - self.coord_index][0],
coord_range[1 - self.coord_index][1],
n_samples - 1,
)
xy_world[-1, 1 - self.coord_index] = coord_range[1 - self.coord_index][0]
else:
xy_world[:, 1 - self.coord_index] = np.linspace(
coord_range[1 - self.coord_index][0],
coord_range[1 - self.coord_index][1],
n_samples,
)
# Transform line to pixel coordinates
pixel = self.transform.inverted().transform(xy_world)
# Create round-tripped values for checking
xy_world_round = self.transform.transform(pixel)
# Get the path of the gridline, which masks hidden parts
gridline = self._get_gridline(xy_world, pixel, xy_world_round)
def data_for_spine(spine):
vertices = gridline.vertices.copy()
codes = gridline.codes.copy()
# Retain the parts of the gridline within the rectangular plot bounds.
# We ought to use the potentially non-rectangular plot frame, but
# calculating that patch requires updating all spines first, which is a
# catch-22.
xmin, xmax = spine.parent_axes.get_xlim()
ymin, ymax = spine.parent_axes.get_ylim()
keep = (
(vertices[:, 0] >= xmin)
& (vertices[:, 0] <= xmax)
& (vertices[:, 1] >= ymin)
& (vertices[:, 1] <= ymax)
)
codes[~keep] = Path.MOVETO
codes[1:][~keep[:-1]] = Path.MOVETO
# We isolate the last segment (the last run of LINETOs), which must be preceded
# by at least one MOVETO and may be succeeded by MOVETOs.
# We have to account for longitude wrapping as well.
# Bail out if there is no visible segment
lineto = np.flatnonzero(codes == Path.LINETO)
if np.size(lineto) == 0:
return np.zeros((0, 2))
# Find the start of the last segment (the last MOVETO before the LINETOs)
last_segment = np.flatnonzero(codes[: lineto[-1]] == Path.MOVETO)[-1]
# Double the gridline if it is closed (i.e., spans all longitudes)
if vertices[0, 0] == vertices[-1, 0] and vertices[0, 1] == vertices[-1, 1]:
codes = np.concatenate([codes, codes[1:]])
vertices = np.vstack([vertices, vertices[1:, :]])
# Stop the last segment before any trailing MOVETOs
moveto = np.flatnonzero(codes[last_segment + 1 :] == Path.MOVETO)
if np.size(moveto) > 0:
return vertices[last_segment : last_segment + moveto[0] + 1, :]
else:
return vertices[last_segment:n_samples, :]
self.frame[name] = self.frame.spine_class(
self.frame.parent_axes, self.frame.transform, data_func=data_for_spine
)
def _get_gridline(self, xy_world, pixel, xy_world_round):
if self.coord_type == "scalar":
return get_gridline_path(xy_world, pixel)
else:
return get_lon_lat_path(xy_world, pixel, xy_world_round)
def _clear_grid_contour(self):
if hasattr(self, "_grid") and self._grid:
if MATPLOTLIB_LT_3_8:
for line in self._grid.collections:
line.remove()
else:
self._grid.remove()
def _update_grid_contour(self):
if self.coord_index is None:
return
xmin, xmax = self.parent_axes.get_xlim()
ymin, ymax = self.parent_axes.get_ylim()
from . import conf
res = conf.contour_grid_samples
x, y = np.meshgrid(np.linspace(xmin, xmax, res), np.linspace(ymin, ymax, res))
pixel = np.array([x.ravel(), y.ravel()]).T
world = self.transform.transform(pixel)
field = world[:, self.coord_index].reshape(res, res).T
coord_range = self.parent_map._coord_range
tick_world_coordinates, spacing = self.locator(*coord_range[self.coord_index])
# tick_world_coordinates is a Quantities array and we only needs its values
tick_world_coordinates_values = tick_world_coordinates.value
if self.coord_type == "longitude":
# Find biggest gap in tick_world_coordinates and wrap in middle
# For now just assume spacing is equal, so any mid-point will do
mid = 0.5 * (
tick_world_coordinates_values[0] + tick_world_coordinates_values[1]
)
field = wrap_angle_at(field, mid)
tick_world_coordinates_values = wrap_angle_at(
tick_world_coordinates_values, mid
)
# Replace wraps by NaN
with np.errstate(invalid="ignore"):
reset = (np.abs(np.diff(field[:, :-1], axis=0)) > 180) | (
np.abs(np.diff(field[:-1, :], axis=1)) > 180
)
field[:-1, :-1][reset] = np.nan
field[1:, :-1][reset] = np.nan
field[:-1, 1:][reset] = np.nan
field[1:, 1:][reset] = np.nan
if len(tick_world_coordinates_values) > 0:
with np.errstate(invalid="ignore"):
self._grid = self.parent_axes.contour(
x,
y,
field.transpose(),
levels=np.sort(tick_world_coordinates_values),
)
else:
self._grid = None
[docs]
def tick_params(self, which="both", **kwargs):
"""
Method to set the tick and tick label parameters in the same way as the
:meth:`~matplotlib.axes.Axes.tick_params` method in Matplotlib.
This is provided for convenience, but the recommended API is to use
:meth:`~astropy.visualization.wcsaxes.CoordinateHelper.set_ticks`,
:meth:`~astropy.visualization.wcsaxes.CoordinateHelper.set_ticklabel`,
:meth:`~astropy.visualization.wcsaxes.CoordinateHelper.set_ticks_position`,
:meth:`~astropy.visualization.wcsaxes.CoordinateHelper.set_ticklabel_position`,
and :meth:`~astropy.visualization.wcsaxes.CoordinateHelper.grid`.
Parameters
----------
which : {'both', 'major', 'minor'}, optional
Which ticks to apply the settings to. By default, setting are
applied to both major and minor ticks. Note that if ``'minor'`` is
specified, only the length of the ticks can be set currently.
direction : {'in', 'out'}, optional
Puts ticks inside the axes, or outside the axes.
length : float, optional
Tick length in points.
width : float, optional
Tick width in points.
color : color, optional
Tick color (accepts any valid Matplotlib color)
pad : float, optional
Distance in points between tick and label.
labelsize : float or str, optional
Tick label font size in points or as a string (e.g., 'large').
labelcolor : color, optional
Tick label color (accepts any valid Matplotlib color)
colors : color, optional
Changes the tick color and the label color to the same value
(accepts any valid Matplotlib color).
bottom, top, left, right : bool, optional
Where to draw the ticks. Note that this will not work correctly if
the frame is not rectangular.
labelbottom, labeltop, labelleft, labelright : bool, optional
Where to draw the tick labels. Note that this will not work
correctly if the frame is not rectangular.
grid_color : color, optional
The color of the grid lines (accepts any valid Matplotlib color).
grid_alpha : float, optional
Transparency of grid lines: 0 (transparent) to 1 (opaque).
grid_linewidth : float, optional
Width of grid lines in points.
grid_linestyle : str, optional
The style of the grid lines (accepts any valid Matplotlib line
style).
"""
# First do some sanity checking on the keyword arguments
# colors= is a fallback default for color and labelcolor
if "colors" in kwargs:
if "color" not in kwargs:
kwargs["color"] = kwargs["colors"]
if "labelcolor" not in kwargs:
kwargs["labelcolor"] = kwargs["colors"]
# The only property that can be set *specifically* for minor ticks is
# the length. In future we could consider having a separate Ticks instance
# for minor ticks so that e.g. the color can be set separately.
if which == "minor":
if len(set(kwargs) - {"length"}) > 0:
raise ValueError(
"When setting which='minor', the only "
"property that can be set at the moment is "
"'length' (the minor tick length)"
)
else:
if "length" in kwargs:
self._ticks.set_minor_ticksize(kwargs["length"])
return
# At this point, we can now ignore the 'which' argument.
# Set the tick arguments
self.set_ticks(
size=kwargs.get("length"),
width=kwargs.get("width"),
color=kwargs.get("color"),
direction=kwargs.get("direction"),
)
# Set the tick position
position = None
for arg in ("bottom", "left", "top", "right"):
if arg in kwargs and position is None:
position = ""
if kwargs.get(arg):
position += arg[0]
if position is not None:
self.set_ticks_position(position)
# Set the tick label arguments.
self.set_ticklabel(
color=kwargs.get("labelcolor"),
size=kwargs.get("labelsize"),
pad=kwargs.get("pad"),
)
# Set the tick label position
position = None
for arg in ("bottom", "left", "top", "right"):
if "label" + arg in kwargs and position is None:
position = ""
if kwargs.get("label" + arg):
position += arg[0]
if position is not None:
self.set_ticklabel_position(position)
# And the grid settings
if "grid_color" in kwargs:
self._grid_lines_kwargs["edgecolor"] = kwargs["grid_color"]
if "grid_alpha" in kwargs:
self._grid_lines_kwargs["alpha"] = kwargs["grid_alpha"]
if "grid_linewidth" in kwargs:
self._grid_lines_kwargs["linewidth"] = kwargs["grid_linewidth"]
if "grid_linestyle" in kwargs:
if kwargs["grid_linestyle"] in LINES_TO_PATCHES_LINESTYLE:
self._grid_lines_kwargs["linestyle"] = LINES_TO_PATCHES_LINESTYLE[
kwargs["grid_linestyle"]
]
else:
self._grid_lines_kwargs["linestyle"] = kwargs["grid_linestyle"]
