mirror of
https://github.com/pim-n/pg-rad
synced 2026-03-23 21:58:12 +01:00
101 lines
2.7 KiB
Python
101 lines
2.7 KiB
Python
from matplotlib import pyplot as plt
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from matplotlib.gridspec import GridSpec
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from .landscape_plotter import LandscapeSlicePlotter
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from pg_rad.simulator.outputs import SimulationOutput
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from pg_rad.landscape.landscape import Landscape
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class ResultPlotter:
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def __init__(self, landscape: Landscape, output: SimulationOutput):
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self.landscape = landscape
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self.count_rate_res = output.count_rate
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self.source_res = output.sources
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def plot(self, landscape_z: float = 0):
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fig = plt.figure(figsize=(12, 10), constrained_layout=True)
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fig.suptitle(self.landscape.name)
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gs = GridSpec(
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3,
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2,
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width_ratios=[0.5, 0.5],
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height_ratios=[0.7, 0.15, 0.15],
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hspace=0.2)
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ax1 = fig.add_subplot(gs[0, 0])
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self._draw_count_rate(ax1)
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ax2 = fig.add_subplot(gs[0, 1])
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self._plot_landscape(ax2, landscape_z)
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ax3 = fig.add_subplot(gs[1, :])
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self._draw_table(ax3)
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ax4 = fig.add_subplot(gs[2, :])
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self._draw_source_table(ax4)
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plt.tight_layout()
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plt.show()
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def _plot_landscape(self, ax, z):
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lp = LandscapeSlicePlotter()
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ax = lp.plot(landscape=self.landscape, z=z, ax=ax, show=False)
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return ax
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def _draw_count_rate(self, ax):
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x = self.count_rate_res.arc_length
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y = self.count_rate_res.count_rate
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ax.plot(x, y, label='Count rate', color='r')
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ax.set_title('Count rate')
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ax.set_xlabel('Arc length s [m]')
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ax.set_ylabel('Counts')
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ax.legend()
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def _draw_table(self, ax):
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ax.set_axis_off()
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ax.set_title('Simulation parameters')
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cols = ('Parameter', 'Value')
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data = [
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["Air density (kg/m^3)", round(self.landscape.air_density, 3)],
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["Total path length (m)", round(self.landscape.path.length, 3)]
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]
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ax.table(
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cellText=data,
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colLabels=cols,
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loc='center'
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)
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return ax
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def _draw_source_table(self, ax):
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ax.set_axis_off()
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ax.set_title('Point sources')
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cols = (
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'Name',
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'Isotope',
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'Activity (MBq)',
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'Position (m)',
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'Dist. to path (m)'
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)
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# this formats position to tuple
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data = [
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[
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s.name,
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s.isotope,
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s.activity,
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"("+", ".join(f"{val:.2f}" for val in s.position)+")",
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round(s.dist_from_path, 2)
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]
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for s in self.source_res
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]
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ax.table(
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cellText=data,
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colLabels=cols,
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loc='center'
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)
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return ax
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