Version 3.0.0
matplotlib
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Source code for mpl_toolkits.axisartist.grid_finder

import numpy as np
from matplotlib.transforms import Bbox
from . import clip_path
clip_line_to_rect = clip_path.clip_line_to_rect

import matplotlib.ticker as mticker
from matplotlib.transforms import Transform

# extremes finder

[docs]class ExtremeFinderSimple(object): def __init__(self, nx, ny): self.nx, self.ny = nx, ny def __call__(self, transform_xy, x1, y1, x2, y2): """ get extreme values. x1, y1, x2, y2 in image coordinates (0-based) nx, ny : number of division in each axis """ x_, y_ = np.linspace(x1, x2, self.nx), np.linspace(y1, y2, self.ny) x, y = np.meshgrid(x_, y_) lon, lat = transform_xy(np.ravel(x), np.ravel(y)) lon_min, lon_max = lon.min(), lon.max() lat_min, lat_max = lat.min(), lat.max() return self._add_pad(lon_min, lon_max, lat_min, lat_max) def _add_pad(self, lon_min, lon_max, lat_min, lat_max): """ a small amount of padding is added because the current clipping algorithms seems to fail when the gridline ends at the bbox boundary. """ dlon = (lon_max - lon_min) / self.nx dlat = (lat_max - lat_min) / self.ny lon_min, lon_max = lon_min - dlon, lon_max + dlon lat_min, lat_max = lat_min - dlat, lat_max + dlat return lon_min, lon_max, lat_min, lat_max
[docs]class GridFinderBase(object): def __init__(self, extreme_finder, grid_locator1, grid_locator2, tick_formatter1=None, tick_formatter2=None): """ the transData of the axes to the world coordinate. locator1, locator2 : grid locator for 1st and 2nd axis. Derived must define "transform_xy, inv_transform_xy" (may use update_transform) """ super().__init__() self.extreme_finder = extreme_finder self.grid_locator1 = grid_locator1 self.grid_locator2 = grid_locator2 self.tick_formatter1 = tick_formatter1 self.tick_formatter2 = tick_formatter2
[docs] def get_grid_info(self, x1, y1, x2, y2): """ lon_values, lat_values : list of grid values. if integer is given, rough number of grids in each direction. """ extremes = self.extreme_finder(self.inv_transform_xy, x1, y1, x2, y2) # min & max rage of lat (or lon) for each grid line will be drawn. # i.e., gridline of lon=0 will be drawn from lat_min to lat_max. lon_min, lon_max, lat_min, lat_max = extremes lon_levs, lon_n, lon_factor = \ self.grid_locator1(lon_min, lon_max) lat_levs, lat_n, lat_factor = \ self.grid_locator2(lat_min, lat_max) 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 = self._get_raw_grid_lines(lon_values, lat_values, lon_min, lon_max, lat_min, lat_max) ddx = (x2-x1)*1.e-10 ddy = (y2-y1)*1.e-10 bb = Bbox.from_extents(x1-ddx, y1-ddy, x2+ddx, y2+ddy) grid_info = {} grid_info["extremes"] = extremes grid_info["lon_lines"] = lon_lines grid_info["lat_lines"] = lat_lines grid_info["lon"] = self._clip_grid_lines_and_find_ticks(lon_lines, lon_values, lon_levs, bb) grid_info["lat"] = self._clip_grid_lines_and_find_ticks(lat_lines, lat_values, lat_levs, bb) tck_labels = grid_info["lon"]["tick_labels"] = dict() for direction in ["left", "bottom", "right", "top"]: levs = grid_info["lon"]["tick_levels"][direction] tck_labels[direction] = self.tick_formatter1(direction, lon_factor, levs) tck_labels = grid_info["lat"]["tick_labels"] = dict() for direction in ["left", "bottom", "right", "top"]: levs = grid_info["lat"]["tick_levels"][direction] tck_labels[direction] = self.tick_formatter2(direction, lat_factor, levs) return grid_info
def _get_raw_grid_lines(self, lon_values, lat_values, lon_min, lon_max, lat_min, lat_max): lons_i = np.linspace(lon_min, lon_max, 100) # for interpolation lats_i = np.linspace(lat_min, lat_max, 100) lon_lines = [self.transform_xy(np.zeros_like(lats_i) + lon, lats_i) for lon in lon_values] lat_lines = [self.transform_xy(lons_i, np.zeros_like(lons_i) + lat) for lat in lat_values] return lon_lines, lat_lines def _clip_grid_lines_and_find_ticks(self, lines, values, levs, bb): gi = { "values": [], "levels": [], "tick_levels": dict(left=[], bottom=[], right=[], top=[]), "tick_locs": dict(left=[], bottom=[], right=[], top=[]), "lines": [], } tck_levels = gi["tick_levels"] tck_locs = gi["tick_locs"] for (lx, ly), v, lev in zip(lines, values, levs): xy, tcks = clip_line_to_rect(lx, ly, bb) if not xy: continue gi["levels"].append(v) gi["lines"].append(xy) for tck, direction in zip(tcks, ["left", "bottom", "right", "top"]): for t in tck: tck_levels[direction].append(lev) tck_locs[direction].append(t) return gi
[docs] def update_transform(self, aux_trans): if isinstance(aux_trans, Transform): def transform_xy(x, y): ll1 = np.column_stack([x, y]) ll2 = aux_trans.transform(ll1) lon, lat = ll2[:,0], ll2[:,1] return lon, lat def inv_transform_xy(x, y): ll1 = np.column_stack([x, y]) ll2 = aux_trans.inverted().transform(ll1) lon, lat = ll2[:,0], ll2[:,1] return lon, lat else: transform_xy, inv_transform_xy = aux_trans self.transform_xy = transform_xy self.inv_transform_xy = inv_transform_xy
[docs] def update(self, **kw): for k in kw: if k in ["extreme_finder", "grid_locator1", "grid_locator2", "tick_formatter1", "tick_formatter2"]: setattr(self, k, kw[k]) else: raise ValueError("unknown update property '%s'" % k)
[docs]class GridFinder(GridFinderBase): def __init__(self, transform, extreme_finder=None, grid_locator1=None, grid_locator2=None, tick_formatter1=None, tick_formatter2=None): """ transform : transform from the image coordinate (which will be the transData of the axes to the world coordinate. or transform = (transform_xy, inv_transform_xy) locator1, locator2 : grid locator for 1st and 2nd axis. """ if extreme_finder is None: extreme_finder = ExtremeFinderSimple(20, 20) if grid_locator1 is None: grid_locator1 = MaxNLocator() if grid_locator2 is None: grid_locator2 = MaxNLocator() if tick_formatter1 is None: tick_formatter1 = FormatterPrettyPrint() if tick_formatter2 is None: tick_formatter2 = FormatterPrettyPrint() super().__init__( extreme_finder, grid_locator1, grid_locator2, tick_formatter1, tick_formatter2) self.update_transform(transform)
[docs]class MaxNLocator(mticker.MaxNLocator): def __init__(self, nbins=10, steps=None, trim=True, integer=False, symmetric=False, prune=None): # trim argument has no effect. It has been left for API compatibility mticker.MaxNLocator.__init__(self, nbins, steps=steps, integer=integer, symmetric=symmetric, prune=prune) self.create_dummy_axis() self._factor = None def __call__(self, v1, v2): if self._factor is not None: self.set_bounds(v1*self._factor, v2*self._factor) locs = mticker.MaxNLocator.__call__(self) return np.array(locs), len(locs), self._factor else: self.set_bounds(v1, v2) locs = mticker.MaxNLocator.__call__(self) return np.array(locs), len(locs), None
[docs] def set_factor(self, f): self._factor = f
[docs]class FixedLocator(object): def __init__(self, locs): self._locs = locs self._factor = None def __call__(self, v1, v2): if self._factor is None: v1, v2 = sorted([v1, v2]) else: v1, v2 = sorted([v1*self._factor, v2*self._factor]) locs = np.array([l for l in self._locs if v1 <= l <= v2]) return locs, len(locs), self._factor
[docs] def set_factor(self, f): self._factor = f
# Tick Formatter
[docs]class FormatterPrettyPrint(object): def __init__(self, useMathText=True): self._fmt = mticker.ScalarFormatter( useMathText=useMathText, useOffset=False) self._fmt.create_dummy_axis() self._ignore_factor = True def __call__(self, direction, factor, values): if not self._ignore_factor: if factor is None: factor = 1. values = [v/factor for v in values] #values = [v for v in values] self._fmt.set_locs(values) return [self._fmt(v) for v in values]
[docs]class DictFormatter(object): def __init__(self, format_dict, formatter=None): """ format_dict : dictionary for format strings to be used. formatter : fall-back formatter """ super().__init__() self._format_dict = format_dict self._fallback_formatter = formatter def __call__(self, direction, factor, values): """ factor is ignored if value is found in the dictionary """ if self._fallback_formatter: fallback_strings = self._fallback_formatter( direction, factor, values) else: fallback_strings = [""]*len(values) r = [self._format_dict.get(k, v) for k, v in zip(values, fallback_strings)] return r