Version 2.2.3
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
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(GridFinderBase, self).__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 = dict()
gi["values"] = []
gi["levels"] = []
gi["tick_levels"] = dict(left=[], bottom=[], right=[], top=[])
gi["tick_locs"] = dict(left=[], bottom=[], right=[], top=[])
gi["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):
x, y = np.asarray(x), np.asarray(y)
ll1 = np.concatenate((x[:,np.newaxis], y[:,np.newaxis]), 1)
ll2 = aux_trans.transform(ll1)
lon, lat = ll2[:,0], ll2[:,1]
return lon, lat
def inv_transform_xy(x, y):
x, y = np.asarray(x), np.asarray(y)
ll1 = np.concatenate((x[:,np.newaxis], y[:,np.newaxis]), 1)
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(GridFinder, self).__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]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) and (l <= v2))])
return locs, len(locs), self._factor
# 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(DictFormatter, self).__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