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plot_error_extreme.py
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plot_error_extreme.py
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import os
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import utils
@plt.style.context('utils/small_fig_v2.mplstyle')
def plot_error_extreme(std_levels, errors, extra_errors=None, label_errors=None, label_extra_errors=None,
save_path=None, twinx=False, title=None):
label_errors = label_errors or 'Error'
label_extra_errors = label_extra_errors or 'Error'
save_path = save_path or os.path.join(os.getcwd(), 'error_extreme.pdf')
plt.rcParams['text.usetex'] = True
fig = plt.figure()
ax = fig.add_subplot(111)
h0 = ax.plot(std_levels, errors, label=label_errors, marker='s', color='tab:blue')
standard_std_level = std_levels[std_levels == 0.1]
standard_erros = errors[std_levels == 0.1]
ax.plot(standard_std_level, standard_erros, marker='*', color='tab:green')
if extra_errors is not None:
_ax = ax.twinx() if twinx else ax
h1 = _ax.plot(std_levels, extra_errors, label=label_extra_errors, marker='s', color='tab:red')
standard_extra_errors = extra_errors[std_levels == 0.1]
_ax.plot(standard_std_level, standard_extra_errors, marker='*', color='tab:green')
_ax.set_ylabel(label_extra_errors)
_ax.legend(loc='upper left', bbox_to_anchor=(0.0, -0.15, 1, 1))
# _ax.set_yscale('log')
ax.set_xlabel('Standard Deviation Levels')
if not twinx:
ax.set_ylabel('Error')
else:
ax.set_ylabel(label_errors)
# ax.set_yscale('log')
ax.legend(loc='upper left')
if title is not None:
ax.set_title(title)
ax.grid(True)
fig.savefig(save_path)
return fig
def main():
std_levels = np.array([0.05, 0.1, 0.2, 0.3, 0.4, 0.5])
# CASE 14
# de_vm_errors = np.array([2e-6, 2e-6, 3e-6, 5e-6, 9e-6, 1.5e-5])
# de_vm_errors = np.sqrt(de_vm_errors) # Vm (pu)
# de_va_errors = np.array([0.034828, 0.072657, 0.276021, 0.774585, 1.700192, 3.237581])
# de_va_errors = np.sqrt(de_va_errors) # Va (deg)
# CASE 118
# masked_l2_errors = np.array([0.0159, 0.0244, 0.0667, 0.2168, 0.5242, 1.0747])
# phys_errors = np.array([0.7883, 1.0601, 1.1612, 1.9435, 4.7033, 10.8349])
de_vm_errors = np.array([2e-6, 3e-6, 4e-6, 7e-6, 1.6e-5, 3.2e-5])
de_vm_errors = np.sqrt(de_vm_errors) # Vm (pu)
de_va_errors = np.array([0.7787, 1.2852, 6.4346, 24.3934, 60.2678, 117.9775])
de_va_errors = np.sqrt(de_va_errors) # Va (deg)
# CASE 6470rte
# de_vm_errors = np.array([0.000026, 0.000031, 0.000052, 0.000112, 0.000235, 0.000379])
# de_vm_errors = np.sqrt(de_vm_errors) # Vm (pu)
# de_va_errors = np.array([12.61, 39.4316, 272.9134, 1024.9236, 2492.5876, 3475.6005])
# de_va_errors = np.sqrt(de_va_errors) # Va (deg)
# plot_error_extreme(
# std_levels=std_levels,
# errors=masked_l2_errors,
# extra_errors=phys_errors,
# label_errors='Masked L2 error',
# label_extra_errors='Physical error',
# save_path='error_extreme_ml2_phys.pdf',
# )
plot_error_extreme(
std_levels=std_levels,
errors=de_vm_errors,
extra_errors=de_va_errors,
label_errors='$V^m$ RMSE (p.u.)',
label_extra_errors=r'$\theta$ RMSE (deg)',
save_path='error_extreme_vm_va.pdf',
twinx=True,
# title='Case 6470rte'
)
if __name__ == '__main__':
main()