395 lines
13 KiB
Python
395 lines
13 KiB
Python
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import numpy as np
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import math
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from mpl_toolkits.axisartist.grid_finder import ExtremeFinderSimple
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def select_step_degree(dv):
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degree_limits_ = [1.5, 3, 7, 13, 20, 40, 70, 120, 270, 520]
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degree_steps_ = [1, 2, 5, 10, 15, 30, 45, 90, 180, 360]
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degree_factors = [1.] * len(degree_steps_)
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minsec_limits_ = [1.5, 2.5, 3.5, 8, 11, 18, 25, 45]
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minsec_steps_ = [1, 2, 3, 5, 10, 15, 20, 30]
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minute_limits_ = np.array(minsec_limits_) / 60
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minute_factors = [60.] * len(minute_limits_)
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second_limits_ = np.array(minsec_limits_) / 3600
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second_factors = [3600.] * len(second_limits_)
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degree_limits = [*second_limits_, *minute_limits_, *degree_limits_]
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degree_steps = [*minsec_steps_, *minsec_steps_, *degree_steps_]
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degree_factors = [*second_factors, *minute_factors, *degree_factors]
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n = np.searchsorted(degree_limits, dv)
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step = degree_steps[n]
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factor = degree_factors[n]
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return step, factor
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def select_step_hour(dv):
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hour_limits_ = [1.5, 2.5, 3.5, 5, 7, 10, 15, 21, 36]
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hour_steps_ = [1, 2, 3, 4, 6, 8, 12, 18, 24]
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hour_factors = [1.] * len(hour_steps_)
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minsec_limits_ = [1.5, 2.5, 3.5, 4.5, 5.5, 8, 11, 14, 18, 25, 45]
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minsec_steps_ = [1, 2, 3, 4, 5, 6, 10, 12, 15, 20, 30]
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minute_limits_ = np.array(minsec_limits_) / 60
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minute_factors = [60.] * len(minute_limits_)
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second_limits_ = np.array(minsec_limits_) / 3600
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second_factors = [3600.] * len(second_limits_)
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hour_limits = [*second_limits_, *minute_limits_, *hour_limits_]
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hour_steps = [*minsec_steps_, *minsec_steps_, *hour_steps_]
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hour_factors = [*second_factors, *minute_factors, *hour_factors]
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n = np.searchsorted(hour_limits, dv)
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step = hour_steps[n]
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factor = hour_factors[n]
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return step, factor
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def select_step_sub(dv):
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# subarcsec or degree
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tmp = 10.**(int(math.log10(dv))-1.)
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factor = 1./tmp
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if 1.5*tmp >= dv:
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step = 1
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elif 3.*tmp >= dv:
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step = 2
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elif 7.*tmp >= dv:
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step = 5
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else:
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step = 1
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factor = 0.1*factor
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return step, factor
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def select_step(v1, v2, nv, hour=False, include_last=True,
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threshold_factor=3600.):
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if v1 > v2:
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v1, v2 = v2, v1
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dv = (v2 - v1) / nv
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if hour:
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_select_step = select_step_hour
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cycle = 24.
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else:
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_select_step = select_step_degree
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cycle = 360.
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# for degree
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if dv > 1 / threshold_factor:
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step, factor = _select_step(dv)
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else:
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step, factor = select_step_sub(dv*threshold_factor)
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factor = factor * threshold_factor
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levs = np.arange(np.floor(v1 * factor / step),
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np.ceil(v2 * factor / step) + 0.5,
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dtype=int) * step
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# n : number of valid levels. If there is a cycle, e.g., [0, 90, 180,
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# 270, 360], the grid line needs to be extended from 0 to 360, so
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# we need to return the whole array. However, the last level (360)
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# needs to be ignored often. In this case, so we return n=4.
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n = len(levs)
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# we need to check the range of values
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# for example, -90 to 90, 0 to 360,
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if factor == 1. and levs[-1] >= levs[0] + cycle: # check for cycle
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nv = int(cycle / step)
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if include_last:
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levs = levs[0] + np.arange(0, nv+1, 1) * step
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else:
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levs = levs[0] + np.arange(0, nv, 1) * step
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n = len(levs)
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return np.array(levs), n, factor
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def select_step24(v1, v2, nv, include_last=True, threshold_factor=3600):
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v1, v2 = v1 / 15, v2 / 15
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levs, n, factor = select_step(v1, v2, nv, hour=True,
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include_last=include_last,
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threshold_factor=threshold_factor)
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return levs * 15, n, factor
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def select_step360(v1, v2, nv, include_last=True, threshold_factor=3600):
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return select_step(v1, v2, nv, hour=False,
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include_last=include_last,
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threshold_factor=threshold_factor)
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class LocatorBase:
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def __init__(self, nbins, include_last=True):
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self.nbins = nbins
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self._include_last = include_last
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def set_params(self, nbins=None):
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if nbins is not None:
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self.nbins = int(nbins)
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class LocatorHMS(LocatorBase):
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def __call__(self, v1, v2):
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return select_step24(v1, v2, self.nbins, self._include_last)
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class LocatorHM(LocatorBase):
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def __call__(self, v1, v2):
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return select_step24(v1, v2, self.nbins, self._include_last,
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threshold_factor=60)
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class LocatorH(LocatorBase):
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def __call__(self, v1, v2):
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return select_step24(v1, v2, self.nbins, self._include_last,
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threshold_factor=1)
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class LocatorDMS(LocatorBase):
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def __call__(self, v1, v2):
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return select_step360(v1, v2, self.nbins, self._include_last)
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class LocatorDM(LocatorBase):
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def __call__(self, v1, v2):
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return select_step360(v1, v2, self.nbins, self._include_last,
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threshold_factor=60)
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class LocatorD(LocatorBase):
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def __call__(self, v1, v2):
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return select_step360(v1, v2, self.nbins, self._include_last,
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threshold_factor=1)
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class FormatterDMS:
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deg_mark = r"^{\circ}"
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min_mark = r"^{\prime}"
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sec_mark = r"^{\prime\prime}"
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fmt_d = "$%d" + deg_mark + "$"
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fmt_ds = r"$%d.%s" + deg_mark + "$"
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# %s for sign
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fmt_d_m = r"$%s%d" + deg_mark + r"\,%02d" + min_mark + "$"
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fmt_d_ms = r"$%s%d" + deg_mark + r"\,%02d.%s" + min_mark + "$"
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fmt_d_m_partial = "$%s%d" + deg_mark + r"\,%02d" + min_mark + r"\,"
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fmt_s_partial = "%02d" + sec_mark + "$"
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fmt_ss_partial = "%02d.%s" + sec_mark + "$"
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def _get_number_fraction(self, factor):
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## check for fractional numbers
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number_fraction = None
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# check for 60
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for threshold in [1, 60, 3600]:
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if factor <= threshold:
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break
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d = factor // threshold
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int_log_d = int(np.floor(np.log10(d)))
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if 10**int_log_d == d and d != 1:
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number_fraction = int_log_d
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factor = factor // 10**int_log_d
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return factor, number_fraction
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return factor, number_fraction
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def __call__(self, direction, factor, values):
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if len(values) == 0:
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return []
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ss = np.sign(values)
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signs = ["-" if v < 0 else "" for v in values]
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factor, number_fraction = self._get_number_fraction(factor)
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values = np.abs(values)
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if number_fraction is not None:
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values, frac_part = divmod(values, 10 ** number_fraction)
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frac_fmt = "%%0%dd" % (number_fraction,)
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frac_str = [frac_fmt % (f1,) for f1 in frac_part]
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if factor == 1:
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if number_fraction is None:
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return [self.fmt_d % (s * int(v),) for s, v in zip(ss, values)]
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else:
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return [self.fmt_ds % (s * int(v), f1)
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for s, v, f1 in zip(ss, values, frac_str)]
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elif factor == 60:
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deg_part, min_part = divmod(values, 60)
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if number_fraction is None:
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return [self.fmt_d_m % (s1, d1, m1)
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for s1, d1, m1 in zip(signs, deg_part, min_part)]
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else:
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return [self.fmt_d_ms % (s, d1, m1, f1)
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for s, d1, m1, f1
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in zip(signs, deg_part, min_part, frac_str)]
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elif factor == 3600:
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if ss[-1] == -1:
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inverse_order = True
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values = values[::-1]
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signs = signs[::-1]
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else:
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inverse_order = False
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l_hm_old = ""
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r = []
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deg_part, min_part_ = divmod(values, 3600)
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min_part, sec_part = divmod(min_part_, 60)
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if number_fraction is None:
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sec_str = [self.fmt_s_partial % (s1,) for s1 in sec_part]
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else:
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sec_str = [self.fmt_ss_partial % (s1, f1)
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for s1, f1 in zip(sec_part, frac_str)]
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for s, d1, m1, s1 in zip(signs, deg_part, min_part, sec_str):
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l_hm = self.fmt_d_m_partial % (s, d1, m1)
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if l_hm != l_hm_old:
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l_hm_old = l_hm
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l = l_hm + s1
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else:
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l = "$" + s + s1
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r.append(l)
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if inverse_order:
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return r[::-1]
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else:
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return r
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else: # factor > 3600.
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return [r"$%s^{\circ}$" % v for v in ss*values]
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class FormatterHMS(FormatterDMS):
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deg_mark = r"^\mathrm{h}"
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min_mark = r"^\mathrm{m}"
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sec_mark = r"^\mathrm{s}"
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fmt_d = "$%d" + deg_mark + "$"
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fmt_ds = r"$%d.%s" + deg_mark + "$"
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# %s for sign
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fmt_d_m = r"$%s%d" + deg_mark + r"\,%02d" + min_mark+"$"
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fmt_d_ms = r"$%s%d" + deg_mark + r"\,%02d.%s" + min_mark+"$"
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fmt_d_m_partial = "$%s%d" + deg_mark + r"\,%02d" + min_mark + r"\,"
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fmt_s_partial = "%02d" + sec_mark + "$"
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fmt_ss_partial = "%02d.%s" + sec_mark + "$"
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def __call__(self, direction, factor, values): # hour
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return super().__call__(direction, factor, np.asarray(values) / 15)
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class ExtremeFinderCycle(ExtremeFinderSimple):
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# docstring inherited
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def __init__(self, nx, ny,
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lon_cycle=360., lat_cycle=None,
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lon_minmax=None, lat_minmax=(-90, 90)):
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"""
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This subclass handles the case where one or both coordinates should be
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taken modulo 360, or be restricted to not exceed a specific range.
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Parameters
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----------
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nx, ny : int
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The number of samples in each direction.
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lon_cycle, lat_cycle : 360 or None
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If not None, values in the corresponding direction are taken modulo
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*lon_cycle* or *lat_cycle*; in theory this can be any number but
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the implementation actually assumes that it is 360 (if not None);
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other values give nonsensical results.
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This is done by "unwrapping" the transformed grid coordinates so
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that jumps are less than a half-cycle; then normalizing the span to
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no more than a full cycle.
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For example, if values are in the union of the [0, 2] and
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[358, 360] intervals (typically, angles measured modulo 360), the
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values in the second interval are normalized to [-2, 0] instead so
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that the values now cover [-2, 2]. If values are in a range of
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[5, 1000], this gets normalized to [5, 365].
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lon_minmax, lat_minmax : (float, float) or None
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If not None, the computed bounding box is clipped to the given
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range in the corresponding direction.
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"""
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self.nx, self.ny = nx, ny
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self.lon_cycle, self.lat_cycle = lon_cycle, lat_cycle
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self.lon_minmax = lon_minmax
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self.lat_minmax = lat_minmax
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def __call__(self, transform_xy, x1, y1, x2, y2):
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# docstring inherited
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x, y = np.meshgrid(
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np.linspace(x1, x2, self.nx), np.linspace(y1, y2, self.ny))
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lon, lat = transform_xy(np.ravel(x), np.ravel(y))
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# iron out jumps, but algorithm should be improved.
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# This is just naive way of doing and my fail for some cases.
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# Consider replacing this with numpy.unwrap
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# We are ignoring invalid warnings. They are triggered when
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# 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._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
|