Version 3.0.0
matplotlib
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Source code for mpl_toolkits.axisartist.angle_helper

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] def set_params(self, nbins=None): if nbins is not None: self.den = int(nbins)
[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.transform_xy = transform_xy #self.inv_transform_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