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https://github.com/Findus23/collision-analyisis-and-interpolation.git
synced 2024-09-18 14:03:51 +02:00
50 lines
1.5 KiB
Python
50 lines
1.5 KiB
Python
import numpy as np
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from matplotlib import pyplot as plt
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from matplotlib.axes import Axes
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from pathlib import Path
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from simulation_list import SimulationList
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plt.style.use('dark_background')
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simulations = SimulationList.jsonlines_load(Path("rsmc_dataset.jsonl"))
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np.set_printoptions(linewidth=1000, edgeitems=4)
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x = simulations.as_matrix
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labels = ["impact angle $\\alpha$", " collision speed $v$", "projectile mass", "mass fraction $\\gamma$",
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"target water fraction", "projectile water fraction"]
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matrixlabels = labels + ["water retention"]
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print(x)
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print(x.shape)
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corr = np.corrcoef(x.T)
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print(np.cov(x.T))
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X = np.copy(x)
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X -= X.mean(axis=0)
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manual = np.dot(X.T, X.conj()) / (x.shape[0] - 1)
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assert np.allclose(manual, np.cov(x.T))
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print(corr.shape)
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simple_cov = corr[-1, :-1]
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# plot correclation matrix
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plt.matshow(corr)
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# plt.xticks(range(len(matrixlabels)), matrixlabels, rotation=90)
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# plt.yticks(range(len(matrixlabels)), matrixlabels)
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# plt.colorbar()
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# plt.savefig("correlation.pdf", transparent=True)
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# plt.tight_layout()
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# plt.show()
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plt.close()
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ax = plt.gca() # type:Axes
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print(len(labels), len(simple_cov))
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print(simple_cov)
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plt.barh(range(len(simple_cov)), simple_cov,color="#B3DE69")
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# ax.set_xticks(index + bar_width / 2)
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ax.set_yticklabels([0] + labels)
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ax2 = ax.twinx() # type:Axes
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ax2.set_yticklabels([0] + ["({:.2f})".format(a) for a in simple_cov])
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ax2.set_ylim(ax.get_ylim())
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plt.tight_layout()
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plt.savefig("../arbeit/images/cov.pdf",transparent=True)
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plt.show()
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