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