Source code for astropy.visualization.wcsaxes.core

# Licensed under a 3-clause BSD style license - see LICENSE.rst

from functools import partial
from collections import defaultdict

import numpy as np

from matplotlib import rcParams
from matplotlib.artist import Artist
from matplotlib.axes import Axes, subplot_class_factory
from matplotlib.transforms import Affine2D, Bbox, Transform

import astropy.units as u
from astropy.coordinates import SkyCoord, BaseCoordinateFrame
from astropy.wcs import WCS
from astropy.wcs.wcsapi import BaseHighLevelWCS

from .transforms import CoordinateTransform
from .coordinates_map import CoordinatesMap
from .utils import get_coord_meta, transform_contour_set_inplace
from .frame import RectangularFrame, RectangularFrame1D
from .wcsapi import IDENTITY, transform_coord_meta_from_wcs


__all__ = ['WCSAxes', 'WCSAxesSubplot']

VISUAL_PROPERTIES = ['facecolor', 'edgecolor', 'linewidth', 'alpha', 'linestyle']


class _WCSAxesArtist(Artist):
    """This is a dummy artist to enforce the correct z-order of axis ticks,
    tick labels, and gridlines.

    FIXME: This is a bit of a hack. ``Axes.draw`` sorts the artists by zorder
    and then renders them in sequence. For normal Matplotlib axes, the ticks,
    tick labels, and gridlines are included in this list of artists and hence
    are automatically drawn in the correct order. However, ``WCSAxes`` disables
    the native ticks, labels, and gridlines. Instead, ``WCSAxes.draw`` renders
    ersatz ticks, labels, and gridlines by explicitly calling the functions
    ``CoordinateHelper._draw_ticks``, ``CoordinateHelper._draw_grid``, etc.
    This hack would not be necessary if ``WCSAxes`` drew ticks, tick labels,
    and gridlines in the standary way."""

    def draw(self, renderer, *args, **kwargs):
        self.axes.draw_wcsaxes(renderer)


[docs]class WCSAxes(Axes): """ The main axes class that can be used to show world coordinates from a WCS. Parameters ---------- fig : `~matplotlib.figure.Figure` The figure to add the axes to rect : list The position of the axes in the figure in relative units. Should be given as ``[left, bottom, width, height]``. wcs : :class:`~astropy.wcs.WCS`, optional The WCS for the data. If this is specified, ``transform`` cannot be specified. transform : `~matplotlib.transforms.Transform`, optional The transform for the data. If this is specified, ``wcs`` cannot be specified. coord_meta : dict, optional A dictionary providing additional metadata when ``transform`` is specified. This should include the keys ``type``, ``wrap``, and ``unit``. Each of these should be a list with as many items as the dimension of the WCS. The ``type`` entries should be one of ``longitude``, ``latitude``, or ``scalar``, the ``wrap`` entries should give, for the longitude, the angle at which the coordinate wraps (and `None` otherwise), and the ``unit`` should give the unit of the coordinates as :class:`~astropy.units.Unit` instances. This can optionally also include a ``format_unit`` entry giving the units to use for the tick labels (if not specified, this defaults to ``unit``). transData : `~matplotlib.transforms.Transform`, optional Can be used to override the default data -> pixel mapping. slices : tuple, optional For WCS transformations with more than two dimensions, we need to choose which dimensions are being shown in the 2D image. The slice should contain one ``x`` entry, one ``y`` entry, and the rest of the values should be integers indicating the slice through the data. The order of the items in the slice should be the same as the order of the dimensions in the :class:`~astropy.wcs.WCS`, and the opposite of the order of the dimensions in Numpy. For example, ``(50, 'x', 'y')`` means that the first WCS dimension (last Numpy dimension) will be sliced at an index of 50, the second WCS and Numpy dimension will be shown on the x axis, and the final WCS dimension (first Numpy dimension) will be shown on the y-axis (and therefore the data will be plotted using ``data[:, :, 50].transpose()``) frame_class : type, optional The class for the frame, which should be a subclass of :class:`~astropy.visualization.wcsaxes.frame.BaseFrame`. The default is to use a :class:`~astropy.visualization.wcsaxes.frame.RectangularFrame` """ def __init__(self, fig, rect, wcs=None, transform=None, coord_meta=None, transData=None, slices=None, frame_class=None, **kwargs): """ """ super().__init__(fig, rect, **kwargs) self._bboxes = [] if frame_class is not None: self.frame_class = frame_class elif (wcs is not None and (wcs.pixel_n_dim == 1 or (slices is not None and 'y' not in slices))): self.frame_class = RectangularFrame1D else: self.frame_class = RectangularFrame if not (transData is None): # User wants to override the transform for the final # data->pixel mapping self.transData = transData self.reset_wcs(wcs=wcs, slices=slices, transform=transform, coord_meta=coord_meta) self._hide_parent_artists() self.format_coord = self._display_world_coords self._display_coords_index = 0 fig.canvas.mpl_connect('key_press_event', self._set_cursor_prefs) self.patch = self.coords.frame.patch self._wcsaxesartist = _WCSAxesArtist() self.add_artist(self._wcsaxesartist) self._drawn = False def _display_world_coords(self, x, y): if not self._drawn: return "" if self._display_coords_index == -1: return f"{x} {y} (pixel)" pixel = np.array([x, y]) coords = self._all_coords[self._display_coords_index] world = coords._transform.transform(np.array([pixel]))[0] coord_strings = [] for idx, coord in enumerate(coords): if coord.coord_index is not None: coord_strings.append(coord.format_coord(world[coord.coord_index], format='ascii')) coord_string = ' '.join(coord_strings) if self._display_coords_index == 0: system = "world" else: system = f"world, overlay {self._display_coords_index}" coord_string = f"{coord_string} ({system})" return coord_string def _set_cursor_prefs(self, event, **kwargs): if event.key == 'w': self._display_coords_index += 1 if self._display_coords_index + 1 > len(self._all_coords): self._display_coords_index = -1 def _hide_parent_artists(self): # Turn off spines and current axes for s in self.spines.values(): s.set_visible(False) self.xaxis.set_visible(False) if self.frame_class is not RectangularFrame1D: self.yaxis.set_visible(False) # We now overload ``imshow`` because we need to make sure that origin is # set to ``lower`` for all images, which means that we need to flip RGB # images.
[docs] def imshow(self, X, *args, **kwargs): """ Wrapper to Matplotlib's :meth:`~matplotlib.axes.Axes.imshow`. If an RGB image is passed as a PIL object, it will be flipped vertically and ``origin`` will be set to ``lower``, since WCS transformations - like FITS files - assume that the origin is the lower left pixel of the image (whereas RGB images have the origin in the top left). All arguments are passed to :meth:`~matplotlib.axes.Axes.imshow`. """ origin = kwargs.pop('origin', 'lower') # plt.imshow passes origin as None, which we should default to lower. if origin is None: origin = 'lower' elif origin == 'upper': raise ValueError("Cannot use images with origin='upper' in WCSAxes.") # To check whether the image is a PIL image we can check if the data # has a 'getpixel' attribute - this is what Matplotlib's AxesImage does try: from PIL.Image import Image, FLIP_TOP_BOTTOM except ImportError: # We don't need to worry since PIL is not installed, so user cannot # have passed RGB image. pass else: if isinstance(X, Image) or hasattr(X, 'getpixel'): X = X.transpose(FLIP_TOP_BOTTOM) return super().imshow(X, *args, origin=origin, **kwargs)
[docs] def contour(self, *args, **kwargs): """ Plot contours. This is a custom implementation of :meth:`~matplotlib.axes.Axes.contour` which applies the transform (if specified) to all contours in one go for performance rather than to each contour line individually. All positional and keyword arguments are the same as for :meth:`~matplotlib.axes.Axes.contour`. """ # In Matplotlib, when calling contour() with a transform, each # individual path in the contour map is transformed separately. However, # this is much too slow for us since each call to the transforms results # in an Astropy coordinate transformation, which has a non-negligible # overhead - therefore a better approach is to override contour(), call # the Matplotlib one with no transform, then apply the transform in one # go to all the segments that make up the contour map. transform = kwargs.pop('transform', None) cset = super().contour(*args, **kwargs) if transform is not None: # The transform passed to self.contour will normally include # a transData component at the end, but we can remove that since # we are already working in data space. transform = transform - self.transData transform_contour_set_inplace(cset, transform) return cset
[docs] def contourf(self, *args, **kwargs): """ Plot filled contours. This is a custom implementation of :meth:`~matplotlib.axes.Axes.contourf` which applies the transform (if specified) to all contours in one go for performance rather than to each contour line individually. All positional and keyword arguments are the same as for :meth:`~matplotlib.axes.Axes.contourf`. """ # See notes for contour above. transform = kwargs.pop('transform', None) cset = super().contourf(*args, **kwargs) if transform is not None: # The transform passed to self.contour will normally include # a transData component at the end, but we can remove that since # we are already working in data space. transform = transform - self.transData transform_contour_set_inplace(cset, transform) return cset
[docs] def plot_coord(self, *args, **kwargs): """ Plot `~astropy.coordinates.SkyCoord` or `~astropy.coordinates.BaseCoordinateFrame` objects onto the axes. The first argument to :meth:`~astropy.visualization.wcsaxes.WCSAxes.plot_coord` should be a coordinate, which will then be converted to the first two parameters to `matplotlib.axes.Axes.plot`. All other arguments are the same as `matplotlib.axes.Axes.plot`. If not specified a ``transform`` keyword argument will be created based on the coordinate. Parameters ---------- coordinate : `~astropy.coordinates.SkyCoord` or `~astropy.coordinates.BaseCoordinateFrame` The coordinate object to plot on the axes. This is converted to the first two arguments to `matplotlib.axes.Axes.plot`. See Also -------- matplotlib.axes.Axes.plot : This method is called from this function with all arguments passed to it. """ if isinstance(args[0], (SkyCoord, BaseCoordinateFrame)): # Extract the frame from the first argument. frame0 = args[0] if isinstance(frame0, SkyCoord): frame0 = frame0.frame native_frame = self._transform_pixel2world.frame_out # Transform to the native frame of the plot frame0 = frame0.transform_to(native_frame) plot_data = [] for coord in self.coords: if coord.coord_type == 'longitude': plot_data.append(frame0.spherical.lon.to_value(u.deg)) elif coord.coord_type == 'latitude': plot_data.append(frame0.spherical.lat.to_value(u.deg)) else: raise NotImplementedError("Coordinates cannot be plotted with this " "method because the WCS does not represent longitude/latitude.") if 'transform' in kwargs.keys(): raise TypeError("The 'transform' keyword argument is not allowed," " as it is automatically determined by the input coordinate frame.") transform = self.get_transform(native_frame) kwargs.update({'transform': transform}) args = tuple(plot_data) + args[1:] return super().plot(*args, **kwargs)
[docs] def reset_wcs(self, wcs=None, slices=None, transform=None, coord_meta=None): """ Reset the current Axes, to use a new WCS object. """ # Here determine all the coordinate axes that should be shown. if wcs is None and transform is None: self.wcs = IDENTITY else: # We now force call 'set', which ensures the WCS object is # consistent, which will only be important if the WCS has been set # by hand. For example if the user sets a celestial WCS by hand and # forgets to set the units, WCS.wcs.set() will do this. if wcs is not None: # Check if the WCS object is an instance of `astropy.wcs.WCS` # This check is necessary as only `astropy.wcs.WCS` supports # wcs.set() method if isinstance(wcs, WCS): wcs.wcs.set() if isinstance(wcs, BaseHighLevelWCS): wcs = wcs.low_level_wcs self.wcs = wcs # If we are making a new WCS, we need to preserve the path object since # it may already be used by objects that have been plotted, and we need # to continue updating it. CoordinatesMap will create a new frame # instance, but we can tell that instance to keep using the old path. if hasattr(self, 'coords'): previous_frame = {'path': self.coords.frame._path, 'color': self.coords.frame.get_color(), 'linewidth': self.coords.frame.get_linewidth()} else: previous_frame = {'path': None} if self.wcs is not None: transform, coord_meta = transform_coord_meta_from_wcs(self.wcs, self.frame_class, slices=slices) self.coords = CoordinatesMap(self, transform=transform, coord_meta=coord_meta, frame_class=self.frame_class, previous_frame_path=previous_frame['path']) self._transform_pixel2world = transform if previous_frame['path'] is not None: self.coords.frame.set_color(previous_frame['color']) self.coords.frame.set_linewidth(previous_frame['linewidth']) self._all_coords = [self.coords] # Common default settings for Rectangular Frame for ind, pos in enumerate(coord_meta.get('default_axislabel_position', ['b', 'l'])): self.coords[ind].set_axislabel_position(pos) for ind, pos in enumerate(coord_meta.get('default_ticklabel_position', ['b', 'l'])): self.coords[ind].set_ticklabel_position(pos) for ind, pos in enumerate(coord_meta.get('default_ticks_position', ['bltr', 'bltr'])): self.coords[ind].set_ticks_position(pos) if rcParams['axes.grid']: self.grid()
[docs] def draw_wcsaxes(self, renderer): if not self.axison: return # Here need to find out range of all coordinates, and update range for # each coordinate axis. For now, just assume it covers the whole sky. self._bboxes = [] # This generates a structure like [coords][axis] = [...] ticklabels_bbox = defaultdict(partial(defaultdict, list)) ticks_locs = defaultdict(partial(defaultdict, list)) visible_ticks = [] for coords in self._all_coords: coords.frame.update() for coord in coords: coord._draw_grid(renderer) for coords in self._all_coords: for coord in coords: coord._draw_ticks(renderer, bboxes=self._bboxes, ticklabels_bbox=ticklabels_bbox[coord], ticks_locs=ticks_locs[coord]) visible_ticks.extend(coord.ticklabels.get_visible_axes()) for coords in self._all_coords: for coord in coords: coord._draw_axislabels(renderer, bboxes=self._bboxes, ticklabels_bbox=ticklabels_bbox, ticks_locs=ticks_locs[coord], visible_ticks=visible_ticks) self.coords.frame.draw(renderer)
[docs] def draw(self, renderer, inframe=False): # In Axes.draw, the following code can result in the xlim and ylim # values changing, so we need to force call this here to make sure that # the limits are correct before we update the patch. locator = self.get_axes_locator() if locator: pos = locator(self, renderer) self.apply_aspect(pos) else: self.apply_aspect() if self._axisbelow is True: self._wcsaxesartist.set_zorder(0.5) elif self._axisbelow is False: self._wcsaxesartist.set_zorder(2.5) else: # 'line': above patches, below lines self._wcsaxesartist.set_zorder(1.5) # We need to make sure that that frame path is up to date self.coords.frame._update_patch_path() super().draw(renderer, inframe=inframe) self._drawn = True
# MATPLOTLIB_LT_30: The ``kwargs.pop('label', None)`` is to ensure # compatibility with Matplotlib 2.x (which has label) and 3.x (which has # xlabel). While these are meant to be a single positional argument, # Matplotlib internally sometimes specifies e.g. set_xlabel(xlabel=...).
[docs] def set_xlabel(self, xlabel=None, labelpad=1, **kwargs): if xlabel is None: xlabel = kwargs.pop('label', None) if xlabel is None: raise TypeError("set_xlabel() missing 1 required positional argument: 'xlabel'") for coord in self.coords: if 'b' in coord.axislabels.get_visible_axes(): coord.set_axislabel(xlabel, minpad=labelpad, **kwargs) break
[docs] def set_ylabel(self, ylabel=None, labelpad=1, **kwargs): if ylabel is None: ylabel = kwargs.pop('label', None) if ylabel is None: raise TypeError("set_ylabel() missing 1 required positional argument: 'ylabel'") if self.frame_class is RectangularFrame1D: return super().set_ylabel(ylabel, labelpad=labelpad, **kwargs) for coord in self.coords: if 'l' in coord.axislabels.get_visible_axes(): coord.set_axislabel(ylabel, minpad=labelpad, **kwargs) break
[docs] def get_xlabel(self): for coord in self.coords: if 'b' in coord.axislabels.get_visible_axes(): return coord.get_axislabel()
[docs] def get_ylabel(self): if self.frame_class is RectangularFrame1D: return super().get_ylabel() for coord in self.coords: if 'l' in coord.axislabels.get_visible_axes(): return coord.get_axislabel()
[docs] def get_coords_overlay(self, frame, coord_meta=None): # Here we can't use get_transform because that deals with # pixel-to-pixel transformations when passing a WCS object. if isinstance(frame, WCS): transform, coord_meta = transform_coord_meta_from_wcs(frame, self.frame_class) else: transform = self._get_transform_no_transdata(frame) if coord_meta is None: coord_meta = get_coord_meta(frame) coords = CoordinatesMap(self, transform=transform, coord_meta=coord_meta, frame_class=self.frame_class) self._all_coords.append(coords) # Common settings for overlay coords[0].set_axislabel_position('t') coords[1].set_axislabel_position('r') coords[0].set_ticklabel_position('t') coords[1].set_ticklabel_position('r') self.overlay_coords = coords return coords
[docs] def get_transform(self, frame): """ Return a transform from the specified frame to display coordinates. This does not include the transData transformation Parameters ---------- frame : :class:`~astropy.wcs.WCS` or :class:`~matplotlib.transforms.Transform` or str The ``frame`` parameter can have several possible types: * :class:`~astropy.wcs.WCS` instance: assumed to be a transformation from pixel to world coordinates, where the world coordinates are the same as those in the WCS transformation used for this ``WCSAxes`` instance. This is used for example to show contours, since this involves plotting an array in pixel coordinates that are not the final data coordinate and have to be transformed to the common world coordinate system first. * :class:`~matplotlib.transforms.Transform` instance: it is assumed to be a transform to the world coordinates that are part of the WCS used to instantiate this ``WCSAxes`` instance. * ``'pixel'`` or ``'world'``: return a transformation that allows users to plot in pixel/data coordinates (essentially an identity transform) and ``world`` (the default world-to-pixel transformation used to instantiate the ``WCSAxes`` instance). * ``'fk5'`` or ``'galactic'``: return a transformation from the specified frame to the pixel/data coordinates. * :class:`~astropy.coordinates.BaseCoordinateFrame` instance. """ return self._get_transform_no_transdata(frame).inverted() + self.transData
def _get_transform_no_transdata(self, frame): """ Return a transform from data to the specified frame """ if isinstance(frame, WCS): transform, coord_meta = transform_coord_meta_from_wcs(frame, self.frame_class) transform_world2pixel = transform.inverted() if self._transform_pixel2world.frame_out == transform_world2pixel.frame_in: return self._transform_pixel2world + transform_world2pixel else: return (self._transform_pixel2world + CoordinateTransform(self._transform_pixel2world.frame_out, transform_world2pixel.frame_in) + transform_world2pixel) elif frame == 'pixel': return Affine2D() elif isinstance(frame, Transform): return self._transform_pixel2world + frame else: if frame == 'world': return self._transform_pixel2world else: coordinate_transform = CoordinateTransform(self._transform_pixel2world.frame_out, frame) if coordinate_transform.same_frames: return self._transform_pixel2world else: return self._transform_pixel2world + coordinate_transform
[docs] def get_tightbbox(self, renderer, *args, **kwargs): # FIXME: we should determine what to do with the extra arguments here. # Note that the expected signature of this method is different in # Matplotlib 3.x compared to 2.x. if not self.get_visible(): return bb = [b for b in self._bboxes if b and (b.width != 0 or b.height != 0)] if bb: _bbox = Bbox.union(bb) return _bbox else: return self.get_window_extent(renderer)
[docs] def grid(self, b=None, axis='both', *, which='major', **kwargs): """ Plot gridlines for both coordinates. Standard matplotlib appearance options (color, alpha, etc.) can be passed as keyword arguments. This behaves like `matplotlib.axes.Axes` except that if no arguments are specified, the grid is shown rather than toggled. Parameters ---------- b : bool Whether to show the gridlines. """ if not hasattr(self, 'coords'): return if which != 'major': raise NotImplementedError('Plotting the grid for the minor ticks is ' 'not supported.') if axis == 'both': self.coords.grid(draw_grid=b, **kwargs) elif axis == 'x': self.coords[0].grid(draw_grid=b, **kwargs) elif axis == 'y': self.coords[1].grid(draw_grid=b, **kwargs) else: raise ValueError('axis should be one of x/y/both')
[docs] def tick_params(self, axis='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 ---------- axis : int or str, optional Which axis to apply the parameters to. This defaults to 'both' but this can also be set to an `int` or `str` that refers to the axis to apply it to, following the valid values that can index ``ax.coords``. Note that ``'x'`` and ``'y``' are also accepted in the case of rectangular axes. 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 can only be given if a specific coordinate is specified via the ``axis`` argument, and it 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 can only be given if a specific coordinate is specified via the ``axis`` argument, and it 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). """ if not hasattr(self, 'coords'): # Axes haven't been fully initialized yet, so just ignore, as # Axes.__init__ calls this method return if axis == 'both': for pos in ('bottom', 'left', 'top', 'right'): if pos in kwargs: raise ValueError(f"Cannot specify {pos}= when axis='both'") if 'label' + pos in kwargs: raise ValueError(f"Cannot specify label{pos}= when axis='both'") for coord in self.coords: coord.tick_params(**kwargs) elif axis in self.coords: self.coords[axis].tick_params(**kwargs) elif axis in ('x', 'y') and self.frame_class is RectangularFrame: spine = 'b' if axis == 'x' else 'l' for coord in self.coords: if spine in coord.axislabels.get_visible_axes(): coord.tick_params(**kwargs)
# In the following, we put the generated subplot class in a temporary class and # we then inherit it - if we don't do this, the generated class appears to # belong in matplotlib, not in WCSAxes, from the API's point of view.
[docs]class WCSAxesSubplot(subplot_class_factory(WCSAxes)): """ A subclass class for WCSAxes """ pass