""" An experimental support for curvilinear grid. """ # TODO : # see if tick_iterator method can be simplified by reusing the parent method. import numpy as np from matplotlib import _api, cbook import matplotlib.patches as mpatches from matplotlib.path import Path import matplotlib.axes as maxes from mpl_toolkits.axes_grid1.parasite_axes import host_axes_class_factory from . import axislines, grid_helper_curvelinear from .axis_artist import AxisArtist from .grid_finder import ExtremeFinderSimple class FloatingAxisArtistHelper( grid_helper_curvelinear.FloatingAxisArtistHelper): pass class FixedAxisArtistHelper(grid_helper_curvelinear.FloatingAxisArtistHelper): def __init__(self, grid_helper, side, nth_coord_ticks=None): """ nth_coord = along which coordinate value varies. nth_coord = 0 -> x axis, nth_coord = 1 -> y axis """ value, nth_coord = grid_helper.get_data_boundary(side) super().__init__(grid_helper, nth_coord, value, axis_direction=side) if nth_coord_ticks is None: nth_coord_ticks = nth_coord self.nth_coord_ticks = nth_coord_ticks self.value = value self.grid_helper = grid_helper self._side = side def update_lim(self, axes): self.grid_helper.update_lim(axes) self._grid_info = self.grid_helper._grid_info def get_tick_iterators(self, axes): """tick_loc, tick_angle, tick_label, (optionally) tick_label""" grid_finder = self.grid_helper.grid_finder lat_levs, lat_n, lat_factor = self._grid_info["lat_info"] lon_levs, lon_n, lon_factor = self._grid_info["lon_info"] lon_levs, lat_levs = np.asarray(lon_levs), np.asarray(lat_levs) if lat_factor is not None: yy0 = lat_levs / lat_factor dy = 0.001 / lat_factor else: yy0 = lat_levs dy = 0.001 if lon_factor is not None: xx0 = lon_levs / lon_factor dx = 0.001 / lon_factor else: xx0 = lon_levs dx = 0.001 extremes = self.grid_helper._extremes xmin, xmax = sorted(extremes[:2]) ymin, ymax = sorted(extremes[2:]) def transform_xy(x, y): trf = grid_finder.get_transform() + axes.transData return trf.transform(np.column_stack([x, y])).T if self.nth_coord == 0: mask = (ymin <= yy0) & (yy0 <= ymax) yy0 = yy0[mask] xx0 = np.full_like(yy0, self.value) xx1, yy1 = transform_xy(xx0, yy0) xx00 = xx0.astype(float, copy=True) xx00[xx0 + dx > xmax] -= dx xx1a, yy1a = transform_xy(xx00, yy0) xx1b, yy1b = transform_xy(xx00 + dx, yy0) yy00 = yy0.astype(float, copy=True) yy00[yy0 + dy > ymax] -= dy xx2a, yy2a = transform_xy(xx0, yy00) xx2b, yy2b = transform_xy(xx0, yy00 + dy) labels = self._grid_info["lat_labels"] labels = [l for l, m in zip(labels, mask) if m] elif self.nth_coord == 1: mask = (xmin <= xx0) & (xx0 <= xmax) xx0 = xx0[mask] yy0 = np.full_like(xx0, self.value) xx1, yy1 = transform_xy(xx0, yy0) yy00 = yy0.astype(float, copy=True) yy00[yy0 + dy > ymax] -= dy xx1a, yy1a = transform_xy(xx0, yy00) xx1b, yy1b = transform_xy(xx0, yy00 + dy) xx00 = xx0.astype(float, copy=True) xx00[xx0 + dx > xmax] -= dx xx2a, yy2a = transform_xy(xx00, yy0) xx2b, yy2b = transform_xy(xx00 + dx, yy0) labels = self._grid_info["lon_labels"] labels = [l for l, m in zip(labels, mask) if m] def f1(): dd = np.arctan2(yy1b - yy1a, xx1b - xx1a) # angle normal dd2 = np.arctan2(yy2b - yy2a, xx2b - xx2a) # angle tangent mm = (yy1b - yy1a == 0) & (xx1b - xx1a == 0) # mask not defined dd dd[mm] = dd2[mm] + np.pi / 2 tick_to_axes = self.get_tick_transform(axes) - axes.transAxes for x, y, d, d2, lab in zip(xx1, yy1, dd, dd2, labels): c2 = tick_to_axes.transform((x, y)) delta = 0.00001 if 0-delta <= c2[0] <= 1+delta and 0-delta <= c2[1] <= 1+delta: d1, d2 = np.rad2deg([d, d2]) yield [x, y], d1, d2, lab return f1(), iter([]) def get_line(self, axes): self.update_lim(axes) k, v = dict(left=("lon_lines0", 0), right=("lon_lines0", 1), bottom=("lat_lines0", 0), top=("lat_lines0", 1))[self._side] xx, yy = self._grid_info[k][v] return Path(np.column_stack([xx, yy])) class ExtremeFinderFixed(ExtremeFinderSimple): # docstring inherited def __init__(self, extremes): """ This subclass always returns the same bounding box. Parameters ---------- extremes : (float, float, float, float) The bounding box that this helper always returns. """ self._extremes = extremes def __call__(self, transform_xy, x1, y1, x2, y2): # docstring inherited return self._extremes class GridHelperCurveLinear(grid_helper_curvelinear.GridHelperCurveLinear): def __init__(self, aux_trans, extremes, grid_locator1=None, grid_locator2=None, tick_formatter1=None, tick_formatter2=None): # docstring inherited self._extremes = extremes extreme_finder = ExtremeFinderFixed(extremes) super().__init__(aux_trans, extreme_finder, grid_locator1=grid_locator1, grid_locator2=grid_locator2, tick_formatter1=tick_formatter1, tick_formatter2=tick_formatter2) def get_data_boundary(self, side): """ Return v=0, nth=1. """ lon1, lon2, lat1, lat2 = self._extremes return dict(left=(lon1, 0), right=(lon2, 0), bottom=(lat1, 1), top=(lat2, 1))[side] def new_fixed_axis(self, loc, nth_coord=None, axis_direction=None, offset=None, axes=None): if axes is None: axes = self.axes if axis_direction is None: axis_direction = loc # This is not the same as the FixedAxisArtistHelper class used by # grid_helper_curvelinear.GridHelperCurveLinear.new_fixed_axis! _helper = FixedAxisArtistHelper( self, loc, nth_coord_ticks=nth_coord) axisline = AxisArtist(axes, _helper, axis_direction=axis_direction) # Perhaps should be moved to the base class? axisline.line.set_clip_on(True) axisline.line.set_clip_box(axisline.axes.bbox) return axisline # new_floating_axis will inherit the grid_helper's extremes. # def new_floating_axis(self, nth_coord, # value, # axes=None, # axis_direction="bottom" # ): # axis = super(GridHelperCurveLinear, # self).new_floating_axis(nth_coord, # value, axes=axes, # axis_direction=axis_direction) # # set extreme values of the axis helper # if nth_coord == 1: # axis.get_helper().set_extremes(*self._extremes[:2]) # elif nth_coord == 0: # axis.get_helper().set_extremes(*self._extremes[2:]) # return axis def _update_grid(self, x1, y1, x2, y2): if self._grid_info is None: self._grid_info = dict() grid_info = self._grid_info grid_finder = self.grid_finder extremes = grid_finder.extreme_finder(grid_finder.inv_transform_xy, x1, y1, x2, y2) lon_min, lon_max = sorted(extremes[:2]) lat_min, lat_max = sorted(extremes[2:]) lon_levs, lon_n, lon_factor = \ grid_finder.grid_locator1(lon_min, lon_max) lat_levs, lat_n, lat_factor = \ grid_finder.grid_locator2(lat_min, lat_max) grid_info["extremes"] = lon_min, lon_max, lat_min, lat_max # extremes grid_info["lon_info"] = lon_levs, lon_n, lon_factor grid_info["lat_info"] = lat_levs, lat_n, lat_factor grid_info["lon_labels"] = grid_finder.tick_formatter1("bottom", lon_factor, lon_levs) grid_info["lat_labels"] = grid_finder.tick_formatter2("bottom", lat_factor, lat_levs) if lon_factor is None: lon_values = np.asarray(lon_levs[:lon_n]) else: lon_values = np.asarray(lon_levs[:lon_n]/lon_factor) if lat_factor is None: lat_values = np.asarray(lat_levs[:lat_n]) else: lat_values = np.asarray(lat_levs[:lat_n]/lat_factor) lon_lines, lat_lines = grid_finder._get_raw_grid_lines( lon_values[(lon_min < lon_values) & (lon_values < lon_max)], lat_values[(lat_min < lat_values) & (lat_values < lat_max)], lon_min, lon_max, lat_min, lat_max) grid_info["lon_lines"] = lon_lines grid_info["lat_lines"] = lat_lines lon_lines, lat_lines = grid_finder._get_raw_grid_lines( # lon_min, lon_max, lat_min, lat_max) extremes[:2], extremes[2:], *extremes) grid_info["lon_lines0"] = lon_lines grid_info["lat_lines0"] = lat_lines def get_gridlines(self, which="major", axis="both"): grid_lines = [] if axis in ["both", "x"]: grid_lines.extend(self._grid_info["lon_lines"]) if axis in ["both", "y"]: grid_lines.extend(self._grid_info["lat_lines"]) return grid_lines @_api.deprecated("3.5") def get_boundary(self): """ Return (N, 2) array of (x, y) coordinate of the boundary. """ x0, x1, y0, y1 = self._extremes tr = self._aux_trans xx = np.linspace(x0, x1, 100) yy0 = np.full_like(xx, y0) yy1 = np.full_like(xx, y1) yy = np.linspace(y0, y1, 100) xx0 = np.full_like(yy, x0) xx1 = np.full_like(yy, x1) xxx = np.concatenate([xx[:-1], xx1[:-1], xx[-1:0:-1], xx0]) yyy = np.concatenate([yy0[:-1], yy[:-1], yy1[:-1], yy[::-1]]) t = tr.transform(np.array([xxx, yyy]).transpose()) return t class FloatingAxesBase: def __init__(self, *args, **kwargs): grid_helper = kwargs.get("grid_helper", None) if grid_helper is None: raise ValueError("FloatingAxes requires grid_helper argument") if not hasattr(grid_helper, "get_boundary"): raise ValueError("grid_helper must implement get_boundary method") super().__init__(*args, **kwargs) self.set_aspect(1.) self.adjust_axes_lim() def _gen_axes_patch(self): # docstring inherited # Using a public API to access _extremes. (x0, _), (x1, _), (y0, _), (y1, _) = map( self.get_grid_helper().get_data_boundary, ["left", "right", "bottom", "top"]) patch = mpatches.Polygon([(x0, y0), (x1, y0), (x1, y1), (x0, y1)]) patch.get_path()._interpolation_steps = 100 return patch def cla(self): super().cla() self.patch.set_transform( self.get_grid_helper().grid_finder.get_transform() + self.transData) # The original patch is not in the draw tree; it is only used for # clipping purposes. orig_patch = super()._gen_axes_patch() orig_patch.set_figure(self.figure) orig_patch.set_transform(self.transAxes) self.patch.set_clip_path(orig_patch) self.gridlines.set_clip_path(orig_patch) def adjust_axes_lim(self): bbox = self.patch.get_path().get_extents( # First transform to pixel coords, then to parent data coords. self.patch.get_transform() - self.transData) bbox = bbox.expanded(1.02, 1.02) self.set_xlim(bbox.xmin, bbox.xmax) self.set_ylim(bbox.ymin, bbox.ymax) floatingaxes_class_factory = cbook._make_class_factory( FloatingAxesBase, "Floating{}") FloatingAxes = floatingaxes_class_factory( host_axes_class_factory(axislines.Axes)) FloatingSubplot = maxes.subplot_class_factory(FloatingAxes)