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https://github.com/Findus23/collision-analyisis-and-interpolation.git
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61 lines
2.3 KiB
Python
61 lines
2.3 KiB
Python
import numpy as np
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from matplotlib import pyplot as plt, cm
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from CustomScaler import CustomScaler
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from config import water_fraction
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from interpolators.griddata import GriddataInterpolator
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from interpolators.rbf import RbfInterpolator
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from simulation_list import SimulationList
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def main():
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mcode, gamma, wt, wp = [10 ** 24, 0.6, 15 / 100, 15 / 100]
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simlist = SimulationList.jsonlines_load()
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# for s in simlist.simlist:
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# if s.type!="original":
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# continue
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# print(s.wpcode,s.projectile_water_fraction)
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# exit()
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data = simlist.X
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print("-----")
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print(len(data))
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# print(data[0])
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# exit()
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values = simlist.Y
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scaler = CustomScaler()
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scaler.fit(data)
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scaled_data = scaler.transform_data(data)
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# interpolator = RbfInterpolator(scaled_data, values)
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interpolator = GriddataInterpolator(scaled_data, values)
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alpharange = np.linspace(-0.5, 60.5, 300)
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vrange = np.linspace(0.5, 5.5, 300)
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grid_alpha, grid_v = np.meshgrid(alpharange, vrange)
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parameters = [grid_alpha, grid_v, mcode, gamma, wt, wp]
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scaled_parameters = list(scaler.transform_parameters(parameters))
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grid_result = interpolator.interpolate(*scaled_parameters)
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print("minmax")
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print(np.nanmin(grid_result), np.nanmax(grid_result))
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# plt.title("m={:3.0e}, gamma={:3.1f}, wt={:2.0f}%, wp={:2.0f}%\n".format(mcode, gamma, wt*100, wp*100))
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cmap = cm.Blues if water_fraction else cm.Oranges
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cmap.set_bad('white', 1.) # show nan white
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# plt.contourf(grid_alpha, grid_v, grid_result, 100, cmap="Blues", vmin=0, vmax=1)
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# plt.pcolormesh(grid_alpha, grid_v, grid_result, cmap="Blues", vmin=0, vmax=1)
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plt.imshow(grid_result, interpolation='none', cmap=cmap, aspect="auto", origin="lower", vmin=0, vmax=1,
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extent=[grid_alpha.min(), grid_alpha.max(), grid_v.min(), grid_v.max()])
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plt.colorbar().set_label("water retention fraction" if water_fraction else "core mass retention fraction")
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# plt.scatter(data[:, 0], data[:, 1], c=values, cmap="Blues")
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plt.xlabel("impact angle $\\alpha$ [$^{\circ}$]")
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plt.ylabel("velocity $v$ [$v_{esc}$]")
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plt.tight_layout()
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# plt.savefig("vis.png", transparent=True)
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plt.savefig("../arbeit/images/plots/mass_griddata2.pdf")
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plt.show()
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if __name__ == '__main__':
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main()
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