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153 lines
4.6 KiB
153 lines
4.6 KiB
import numpy as num
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import logging
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import math
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from pyrocko import plot
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from pyrocko.guts import Tuple, Float
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from matplotlib import pyplot as plt
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from matplotlib import lines
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from matplotlib.ticker import FuncFormatter
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from grond.plot.config import PlotConfig
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guts_prefix = 'grond'
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km = 1e3
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d2r = math.pi / 180.
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logger = logging.getLogger('targets.plot')
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class StationDistributionPlot(PlotConfig):
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''' Plot showing all waveform fits for the ensemble of solutions'''
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name = 'seismic_stations_base'
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size_cm = Tuple.T(
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2, Float.T(),
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default=(16., 13.),
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help='width and length of the figure in cm')
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font_size = Float.T(
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default=10,
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help='font size of all text, except station labels')
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font_size_labels = Float.T(
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default=6,
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help='font size of station labels')
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def plot_station_distribution(
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self, azimuths, distances, weights, labels=None,
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scatter_kwargs=dict(), annotate_kwargs=dict(), maxsize=10**2):
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invalid_color = plot.mpl_color('aluminium3')
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scatter_default = {
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'alpha': .5,
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'zorder': 10,
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'c': plot.mpl_color('skyblue2'),
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}
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annotate_default = {
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'alpha': .8,
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'color': 'k',
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'fontsize': self.font_size_labels,
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'ha': 'right',
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'va': 'top',
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'xytext': (-5, -5),
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'textcoords': 'offset points'
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}
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scatter_default.update(scatter_kwargs)
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annotate_default.update(annotate_kwargs)
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fig = plt.figure(figsize=self.size_inch)
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plot.mpl_margins(
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fig, nw=1, nh=1, left=3., right=10., top=3., bottom=3.,
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units=self.font_size)
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ax = fig.add_subplot(111, projection='polar')
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valid = num.isfinite(weights)
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valid[valid] = num.logical_and(valid[valid], weights[valid] > 0.0)
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weights = weights.copy()
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if num.sum(valid) == 0:
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weights[:] = 1.0
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weights_ref = 1.0
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else:
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weights[~valid] = weights[valid].min()
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weights_ref = plot.nice_value(weights[valid].max())
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if weights_ref == 0.:
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weights_ref = 1.0
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colors = [scatter_default['c'] if s else invalid_color
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for s in valid]
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scatter_default.pop('c')
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weights_scaled = (weights / weights_ref) * maxsize
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stations = ax.scatter(
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azimuths*d2r, distances, s=weights_scaled, c=colors,
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**scatter_default)
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if len(labels) < 30: # TODO: remove after impl. of collision detection
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if labels is not None:
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for ilbl, label in enumerate(labels):
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ax.annotate(
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label, (azimuths[ilbl]*d2r, distances[ilbl]),
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**annotate_default)
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ax.set_theta_zero_location('N')
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ax.set_theta_direction(-1)
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ax.tick_params('y', labelsize=self.font_size, labelcolor='gray')
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ax.grid(alpha=.3)
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ax.set_ylim(0, distances.max()*1.1)
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ax.yaxis.set_major_locator(plt.MaxNLocator(4))
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ax.yaxis.set_major_formatter(
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FuncFormatter(lambda x, pos: '%d km' % (x/km)))
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# Legend
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entries = 4
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valid_marker = num.argmax(valid)
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ecl = stations.get_edgecolor()
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fc = tuple(stations.get_facecolor()[valid_marker])
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ec = tuple(ecl[min(valid_marker, len(ecl)-1)])
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def get_min_precision(values):
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sig_prec = num.floor(
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num.isfinite(num.log10(values[values > 0])))
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if sig_prec.size == 0:
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return 1
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return int(abs(sig_prec.min())) + 1
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legend_artists = [
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lines.Line2D(
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[0], [0], ls='none',
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marker='o', ms=num.sqrt(rad), mfc=fc, mec=ec)
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for rad in num.linspace(maxsize, .1*maxsize, entries)
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]
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sig_prec = get_min_precision(weights)
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legend_annot = [
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'{value:.{prec}f}'.format(value=val, prec=sig_prec)
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for val in num.linspace(weights_ref, .1*weights_ref, entries)
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]
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if not num.all(valid):
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legend_artists.append(
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lines.Line2D(
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[0], [0], ls='none',
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marker='o', ms=num.sqrt(maxsize),
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mfc=invalid_color, mec=invalid_color))
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legend_annot.append('Excluded')
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legend = fig.legend(
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legend_artists, legend_annot,
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fontsize=self.font_size, loc=4,
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markerscale=1, numpoints=1,
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frameon=False)
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return fig, ax, legend
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