Source code for mpl_toolkits.axisartist.floating_axes

"""
An experimental support for curvilinear grid.
"""

# TODO :
# see if tick_iterator method can be simplified by reusing the parent method.

import functools

import numpy as np

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


[docs]class FloatingAxisArtistHelper( grid_helper_curvelinear.FloatingAxisArtistHelper): pass
[docs]class FixedAxisArtistHelper(grid_helper_curvelinear.FloatingAxisArtistHelper):
[docs] 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
[docs] def update_lim(self, axes): self.grid_helper.update_lim(axes) self.grid_info = self.grid_helper.grid_info
[docs] 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): x1, y1 = grid_finder.transform_xy(x, y) x2, y2 = axes.transData.transform(np.array([x1, y1]).T).T return x2, y2 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([])
[docs] 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]))
[docs]class ExtremeFinderFixed(ExtremeFinderSimple): # docstring inherited
[docs] 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
[docs] def __call__(self, transform_xy, x1, y1, x2, y2): # docstring inherited return self._extremes
[docs]class GridHelperCurveLinear(grid_helper_curvelinear.GridHelperCurveLinear):
[docs] 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)
[docs] 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]
[docs] 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
[docs] 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
[docs] 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
[docs]class FloatingAxesBase:
[docs] 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") self._axes_class_floating.__init__(self, *args, **kwargs) self.set_aspect(1.) self.adjust_axes_lim()
def _gen_axes_patch(self): # docstring inherited grid_helper = self.get_grid_helper() t = grid_helper.get_boundary() return mpatches.Polygon(t)
[docs] def cla(self): self._axes_class_floating.cla(self) # HostAxes.cla(self) self.patch.set_transform(self.transData) patch = self._axes_class_floating._gen_axes_patch(self) patch.set_figure(self.figure) patch.set_visible(False) patch.set_transform(self.transAxes) self.patch.set_clip_path(patch) self.gridlines.set_clip_path(patch) self._original_patch = patch
[docs] def adjust_axes_lim(self): grid_helper = self.get_grid_helper() t = grid_helper.get_boundary() x, y = t[:, 0], t[:, 1] xmin, xmax = min(x), max(x) ymin, ymax = min(y), max(y) dx = (xmax-xmin) / 100 dy = (ymax-ymin) / 100 self.set_xlim(xmin-dx, xmax+dx) self.set_ylim(ymin-dy, ymax+dy)
[docs]@functools.lru_cache(None) def floatingaxes_class_factory(axes_class): return type("Floating %s" % axes_class.__name__, (FloatingAxesBase, axes_class), {'_axes_class_floating': axes_class})
FloatingAxes = floatingaxes_class_factory( host_axes_class_factory(axislines.Axes)) FloatingSubplot = maxes.subplot_class_factory(FloatingAxes)