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nb_utils.py
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"""Notebook utils."""
import numpy as np
import matplotlib.pyplot as plt
from skimage.filters import gaussian
def loss_plot(loss, logscale=False, save=None):
"""Loss plot."""
fig, ax = plt.subplots(1, figsize=(10, 5))
fig.patch.set_facecolor('xkcd:white')
if logscale:
plt.semilogy(loss, lw=3)
else:
plt.plot(loss, lw=3)
plt.xlabel('Iterations', fontsize=18)
plt.ylabel('Loss function value', fontsize=18)
ax.tick_params(axis='both', labelsize=18)
plt.tight_layout()
if save is not None:
plt.savefig(save)
plt.show()
def hist_plots(rock, connect, save=None):
"""Historgams of the correction factors."""
fig, ax = plt.subplots(1, 2, figsize=(12, 5))
fig.patch.set_facecolor('xkcd:white')
ax[0].hist(rock, bins=30, range=(-1, 1), density=True)
ax[0].axvline(rock.mean(), c='r', lw=3)
ax[0].set_title('Rock corrections', fontsize=22)
ax[0].tick_params(axis='both', labelsize=18)
ax[1].hist(connect, bins=30, range=(-1, 3), density=True)
ax[1].set_title('Connectivity corrections', fontsize=22)
ax[1].tick_params(axis='both', labelsize=18)
plt.tight_layout()
if save is not None:
plt.savefig(save)
plt.show()
def slice_view(initial_params, final_params, well_mask, z_ind,
name='values', cv=1.5, save=None):
"""Plot z-slice of 3D arrays."""
fig, ax = plt.subplots(1, 3, figsize=(15, 6))
fig.patch.set_facecolor('xkcd:white')
# initial properties
ax[0].imshow(gaussian(initial_params[:, :, z_ind], 1),
cmap='bwr', vmax=cv, vmin=-cv)
ax[0].set_title('Initial {}'.format(name), fontsize=22)
ax[0].set_ylabel('Y', fontsize=18)
# final properties
ax[1].imshow(gaussian(final_params[:, :, z_ind], 1),
cmap='bwr', vmax=cv, vmin=-cv)
ax[1].set_title('Final {}'.format(name), fontsize=22)
# difference
diff = final_params[:, :, z_ind] - initial_params[:, :, z_ind]
im = ax[2].imshow(gaussian(diff, 1), cmap='bwr', vmax=cv, vmin=-cv)
ax[2].set_title('Difference', fontsize=22)
# wells position
for i in range(3):
ax[i].scatter(*np.where(well_mask[:, :, z_ind].T), c='black', s=60)
ax[i].set_xlabel('X', fontsize=18)
ax[i].tick_params(axis='x', labelsize=18)
ax[i].tick_params(axis='y', labelsize=18)
fig.subplots_adjust(bottom=0.21)
cbar_ax = fig.add_axes([0.278, 0.05, 0.5, 0.03])
cbar_ax.tick_params(axis='x', labelsize=18)
fig.colorbar(im, cax=cbar_ax, orientation='horizontal')
if save is not None:
plt.savefig(save)
plt.show()
def cumulative_plots(target_rates, pred_rates, phases, vline=None, save=None):
"""Cumulative rates plot."""
target_cum = np.cumsum(target_rates, axis=0)
pred_cum = np.cumsum(pred_rates, axis=0)
fig, ax = plt.subplots(1, 3, figsize=(15, 5))
fig.patch.set_facecolor('xkcd:white')
for i, k in enumerate(phases):
ax[i].plot(target_cum[:, i], label='Target', lw=4)
ax[i].plot(pred_cum[:, i], label='HM', lw=4)
ax[i].set_title(k, fontsize=22)
ax[i].legend(fontsize=18)
ax[i].set_xlabel('Days', fontsize=18)
if vline is not None:
ax[i].axvline(vline, c='gray')
ax[i].tick_params(axis='x', labelsize=18)
ax[i].tick_params(axis='y', labelsize=18)
ax[i].ticklabel_format(style='sci', axis='y', scilimits=(0, 0))
ax[0].set_ylabel('Cumulative volume', fontsize=18)
plt.tight_layout()
if save is not None:
plt.savefig(save)
plt.show()
def corr_plots(target_rates, pred_rates, phases, mark_well=None, save=None):
"""Scatterplot target vs predicted."""
fig, ax = plt.subplots(1, 3, figsize=(15, 5))
fig.patch.set_facecolor('xkcd:white')
colors = ['b'] * len(target_rates)
if mark_well is not None:
colors[mark_well] = 'r'
for i, k in enumerate(phases):
x = pred_rates[..., i].sum(axis=1)
y = target_rates[..., i].sum(axis=1)
ax[i].scatter(x, y, c=colors, s=90)
ax[i].set_xlabel('Cumulative predicted', fontsize=18)
ax[i].plot([0, x.max()], [0, x.max()], c='k')
corr = np.corrcoef(x, y)[0, 1]
ax[i].set_title(k + ', R={:.2f}'.format(corr), fontsize=22)
ax[i].ticklabel_format(style='sci', axis='both', scilimits=(0, 0))
ax[i].tick_params(axis='x', labelsize=18)
ax[i].tick_params(axis='y', labelsize=18)
ax[i].set_aspect('equal')
ax[0].set_ylabel('Cumulative target', fontsize=18)
if save is not None:
plt.savefig(save, bbox_inches='tight')
plt.show()
def gas_oil_plot(gas_targ, gas_pred, oil_targ, oil_pred, vline=None, save=None):
"""Gas/oil ratio plot."""
fig, ax = plt.subplots(1, 1, figsize=(7, 5))
fig.patch.set_facecolor('xkcd:white')
ax.plot(gas_targ/oil_targ, label='Target', lw=4)
ax.plot(gas_pred/oil_pred, label='HM', lw=4)
ax.set_title('Gas/oil ratio', fontsize=22)
ax.legend(fontsize=18)
ax.set_xlabel('Days', fontsize=18)
if vline is not None:
ax.axvline(vline, c='gray', lw=2)
ax.tick_params(axis='x', labelsize=18)
ax.tick_params(axis='y', labelsize=18)
ax.ticklabel_format(style='sci', axis='y', scilimits=(0, 0))
plt.tight_layout()
if save is not None:
plt.savefig(save)
plt.show()