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34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
import numpy as np
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from matplotlib import pyplot as plt
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from scipy.interpolate import griddata
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from simulation_list import SimulationList
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mcode, gamma, wt, wp = [24.0, 1, 10.0, 10.0]
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simlist = SimulationList.jsonlines_load()
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simulations = simlist.simlist
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print(simulations)
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simsubset = [sim for sim in simulations if
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sim.mcode == mcode and sim.gammacode == gamma and sim.wtcode == wt and sim.wpcode == wp]
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data = np.array([[s.alphacode, s.vcode] for s in simsubset])
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values = np.array([s.water_retention_both for s in simsubset])
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factor = 1
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grid_x, grid_y = np.mgrid[-0.5:60.5:100j, 0.5:5.5:100j]
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N = factor * np.arange(0., 1.01, 0.01)
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print(grid_x)
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grid_c = griddata(data, values, (grid_x, grid_y), method="linear")
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print(grid_c)
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plt.title("m={:3.0f}, gamma={:3.1f}, wt={:2.0f}, wp={:2.0f}\n".format(mcode, gamma, wt, wp))
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# plt.contourf(grid_x, grid_y, grid_c, N, cmap="Blues", vmin=0, vmax=1)
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plt.pcolormesh(grid_x, grid_y, grid_c, cmap="Blues", vmin=0, vmax=1)
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plt.colorbar().set_label("test")
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plt.scatter(data[:, 0], data[:, 1], c="black", cmap="Blues")
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plt.savefig("vis.png")
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plt.show()
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