Version 2.2.5
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
import math
from mpl_toolkits.axisartist.grid_finder import ExtremeFinderSimple
[docs]def select_step_degree(dv):
degree_limits_ = [1.5, 3, 7, 13, 20, 40, 70, 120, 270, 520]
degree_steps_ = [ 1, 2, 5, 10, 15, 30, 45, 90, 180, 360]
degree_factors = [1.] * len(degree_steps_)
minsec_limits_ = [1.5, 2.5, 3.5, 8, 11, 18, 25, 45]
minsec_steps_ = [1, 2, 3, 5, 10, 15, 20, 30]
minute_limits_ = np.array(minsec_limits_) / 60
minute_factors = [60.] * len(minute_limits_)
second_limits_ = np.array(minsec_limits_) / 3600
second_factors = [3600.] * len(second_limits_)
degree_limits = np.concatenate([second_limits_,
minute_limits_,
degree_limits_])
degree_steps = np.concatenate([minsec_steps_,
minsec_steps_,
degree_steps_])
degree_factors = np.concatenate([second_factors,
minute_factors,
degree_factors])
n = degree_limits.searchsorted(dv)
step = degree_steps[n]
factor = degree_factors[n]
return step, factor
[docs]def select_step_hour(dv):
hour_limits_ = [1.5, 2.5, 3.5, 5, 7, 10, 15, 21, 36]
hour_steps_ = [1, 2 , 3, 4, 6, 8, 12, 18, 24]
hour_factors = [1.] * len(hour_steps_)
minsec_limits_ = [1.5, 2.5, 3.5, 4.5, 5.5, 8, 11, 14, 18, 25, 45]
minsec_steps_ = [1, 2, 3, 4, 5, 6, 10, 12, 15, 20, 30]
minute_limits_ = np.array(minsec_limits_) / 60
minute_factors = [60.] * len(minute_limits_)
second_limits_ = np.array(minsec_limits_) / 3600
second_factors = [3600.] * len(second_limits_)
hour_limits = np.concatenate([second_limits_,
minute_limits_,
hour_limits_])
hour_steps = np.concatenate([minsec_steps_,
minsec_steps_,
hour_steps_])
hour_factors = np.concatenate([second_factors,
minute_factors,
hour_factors])
n = hour_limits.searchsorted(dv)
step = hour_steps[n]
factor = hour_factors[n]
return step, factor
[docs]def select_step_sub(dv):
# subarcsec or degree
tmp = 10.**(int(math.log10(dv))-1.)
factor = 1./tmp
if 1.5*tmp >= dv:
step = 1
elif 3.*tmp >= dv:
step = 2
elif 7.*tmp >= dv:
step = 5
else:
step = 1
factor = 0.1*factor
return step, factor
[docs]def select_step(v1, v2, nv, hour=False, include_last=True,
threshold_factor=3600.):
if v1 > v2:
v1, v2 = v2, v1
dv = (v2 - v1) / nv
if hour:
_select_step = select_step_hour
cycle = 24.
else:
_select_step = select_step_degree
cycle = 360.
# for degree
if dv > 1./threshold_factor:
step, factor = _select_step(dv)
else:
step, factor = select_step_sub(dv*threshold_factor)
factor = factor * threshold_factor
f1, f2, fstep = v1*factor, v2*factor, step/factor
levs = np.arange(np.floor(f1/step), np.ceil(f2/step)+0.5, dtype=int) * step
# n : number of valid levels. If there is a cycle, e.g., [0, 90, 180,
# 270, 360], the grid line needs to be extended from 0 to 360, so
# we need to return the whole array. However, the last level (360)
# needs to be ignored often. In this case, so we return n=4.
n = len(levs)
# we need to check the range of values
# for example, -90 to 90, 0 to 360,
if factor == 1. and (levs[-1] >= levs[0]+cycle): # check for cycle
nv = int(cycle / step)
if include_last:
levs = levs[0] + np.arange(0, nv+1, 1) * step
else:
levs = levs[0] + np.arange(0, nv, 1) * step
n = len(levs)
return np.array(levs), n, factor
[docs]def select_step24(v1, v2, nv, include_last=True, threshold_factor=3600):
v1, v2 = v1/15., v2/15.
levs, n, factor = select_step(v1, v2, nv, hour=True,
include_last=include_last,
threshold_factor=threshold_factor)
return levs*15., n, factor
[docs]def select_step360(v1, v2, nv, include_last=True, threshold_factor=3600):
return select_step(v1, v2, nv, hour=False,
include_last=include_last,
threshold_factor=threshold_factor)
[docs]class LocatorBase(object):
def __init__(self, den, include_last=True):
self.den = den
self._include_last = include_last
@property
def nbins(self):
return self.den
@nbins.setter
def nbins(self, v):
self.den = v
[docs]class LocatorHMS(LocatorBase):
def __call__(self, v1, v2):
return select_step24(v1, v2, self.den, self._include_last)
[docs]class LocatorHM(LocatorBase):
def __call__(self, v1, v2):
return select_step24(v1, v2, self.den, self._include_last,
threshold_factor=60)
[docs]class LocatorH(LocatorBase):
def __call__(self, v1, v2):
return select_step24(v1, v2, self.den, self._include_last,
threshold_factor=1)
[docs]class LocatorDMS(LocatorBase):
def __call__(self, v1, v2):
return select_step360(v1, v2, self.den, self._include_last)
[docs]class LocatorDM(LocatorBase):
def __call__(self, v1, v2):
return select_step360(v1, v2, self.den, self._include_last,
threshold_factor=60)
[docs]class LocatorD(LocatorBase):
def __call__(self, v1, v2):
return select_step360(v1, v2, self.den, self._include_last,
threshold_factor=1)
[docs]class FormatterDMS(object):
deg_mark = r"^{\circ}"
min_mark = r"^{\prime}"
sec_mark = r"^{\prime\prime}"
fmt_d = "$%d" + deg_mark + "$"
fmt_ds = r"$%d.%s" + deg_mark + "$"
# %s for sign
fmt_d_m = r"$%s%d" + deg_mark + r"\,%02d" + min_mark + "$"
fmt_d_ms = r"$%s%d" + deg_mark + r"\,%02d.%s" + min_mark + "$"
fmt_d_m_partial = "$%s%d" + deg_mark + r"\,%02d" + min_mark + r"\,"
fmt_s_partial = "%02d" + sec_mark + "$"
fmt_ss_partial = "%02d.%s" + sec_mark + "$"
def _get_number_fraction(self, factor):
## check for fractional numbers
number_fraction = None
# check for 60
for threshold in [1, 60, 3600]:
if factor <= threshold:
break
d = factor // threshold
int_log_d = int(np.floor(np.log10(d)))
if 10**int_log_d == d and d != 1:
number_fraction = int_log_d
factor = factor // 10**int_log_d
return factor, number_fraction
return factor, number_fraction
def __call__(self, direction, factor, values):
if len(values) == 0:
return []
#ss = [[-1, 1][v>0] for v in values] #not py24 compliant
values = np.asarray(values)
ss = np.where(values>0, 1, -1)
sign_map = {(-1, True):"-"}
signs = [sign_map.get((s, v!=0), "") for s, v in zip(ss, values)]
factor, number_fraction = self._get_number_fraction(factor)
values = np.abs(values)
if number_fraction is not None:
values, frac_part = divmod(values, 10**number_fraction)
frac_fmt = "%%0%dd" % (number_fraction,)
frac_str = [frac_fmt % (f1,) for f1 in frac_part]
if factor == 1:
if number_fraction is None:
return [self.fmt_d % (s*int(v),) for (s, v) in zip(ss, values)]
else:
return [self.fmt_ds % (s*int(v), f1)
for (s, v, f1) in zip(ss, values, frac_str)]
elif factor == 60:
deg_part, min_part = divmod(values, 60)
if number_fraction is None:
return [self.fmt_d_m % (s1, d1, m1)
for s1, d1, m1 in zip(signs, deg_part, min_part)]
else:
return [self.fmt_d_ms % (s, d1, m1, f1)
for s, d1, m1, f1 in zip(signs, deg_part, min_part, frac_str)]
elif factor == 3600:
if ss[-1] == -1:
inverse_order = True
values = values[::-1]
signs = signs[::-1]
else:
inverse_order = False
l_hm_old = ""
r = []
deg_part, min_part_ = divmod(values, 3600)
min_part, sec_part = divmod(min_part_, 60)
if number_fraction is None:
sec_str = [self.fmt_s_partial % (s1,) for s1 in sec_part]
else:
sec_str = [self.fmt_ss_partial % (s1, f1) for s1, f1 in zip(sec_part, frac_str)]
for s, d1, m1, s1 in zip(signs, deg_part, min_part, sec_str):
l_hm = self.fmt_d_m_partial % (s, d1, m1)
if l_hm != l_hm_old:
l_hm_old = l_hm
l = l_hm + s1 #l_s
else:
l = "$" + s + s1
r.append(l)
if inverse_order:
return r[::-1]
else:
return r
else: # factor > 3600.
return [r"$%s^{\circ}$" % (str(v),) for v in ss*values]
[docs]class FormatterHMS(FormatterDMS):
deg_mark = r"^\mathrm{h}"
min_mark = r"^\mathrm{m}"
sec_mark = r"^\mathrm{s}"
fmt_d = "$%d" + deg_mark + "$"
fmt_ds = r"$%d.%s" + deg_mark + "$"
# %s for sign
fmt_d_m = r"$%s%d" + deg_mark + r"\,%02d" + min_mark+"$"
fmt_d_ms = r"$%s%d" + deg_mark + r"\,%02d.%s" + min_mark+"$"
fmt_d_m_partial = "$%s%d" + deg_mark + r"\,%02d" + min_mark + r"\,"
fmt_s_partial = "%02d" + sec_mark + "$"
fmt_ss_partial = "%02d.%s" + sec_mark + "$"
def __call__(self, direction, factor, values): # hour
return FormatterDMS.__call__(self, direction, factor, np.asarray(values)/15.)
[docs]class ExtremeFinderCycle(ExtremeFinderSimple):
"""
When there is a cycle, e.g., longitude goes from 0-360.
"""
def __init__(self,
nx, ny,
lon_cycle = 360.,
lat_cycle = None,
lon_minmax = None,
lat_minmax = (-90, 90)
):
#self.transfrom_xy = transform_xy
#self.inv_transfrom_xy = inv_transform_xy
self.nx, self.ny = nx, ny
self.lon_cycle, self.lat_cycle = lon_cycle, lat_cycle
self.lon_minmax = lon_minmax
self.lat_minmax = lat_minmax
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 divisions 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))
# iron out jumps, but algorithm should be improved.
# This is just naive way of doing and my fail for some cases.
# Consider replacing this with numpy.unwrap
# We are ignoring invalid warnings. They are triggered when
# comparing arrays with NaNs using > We are already handling
# that correctly using np.nanmin and np.nanmax
with np.errstate(invalid='ignore'):
if self.lon_cycle is not None:
lon0 = np.nanmin(lon)
lon -= 360. * ((lon - lon0) > 180.)
if self.lat_cycle is not None:
lat0 = np.nanmin(lat)
lat -= 360. * ((lat - lat0) > 180.)
lon_min, lon_max = np.nanmin(lon), np.nanmax(lon)
lat_min, lat_max = np.nanmin(lat), np.nanmax(lat)
lon_min, lon_max, lat_min, lat_max = \
self._adjust_extremes(lon_min, lon_max, lat_min, lat_max)
return lon_min, lon_max, lat_min, lat_max
def _adjust_extremes(self, lon_min, lon_max, lat_min, lat_max):
lon_min, lon_max, lat_min, lat_max = \
self._add_pad(lon_min, lon_max, lat_min, lat_max)
# check cycle
if self.lon_cycle:
lon_max = min(lon_max, lon_min + self.lon_cycle)
if self.lat_cycle:
lat_max = min(lat_max, lat_min + self.lat_cycle)
if self.lon_minmax is not None:
min0 = self.lon_minmax[0]
lon_min = max(min0, lon_min)
max0 = self.lon_minmax[1]
lon_max = min(max0, lon_max)
if self.lat_minmax is not None:
min0 = self.lat_minmax[0]
lat_min = max(min0, lat_min)
max0 = self.lat_minmax[1]
lat_max = min(max0, lat_max)
return lon_min, lon_max, lat_min, lat_max