(self, stacked_data, days_to_plot=(0,10),
plot_sample=True, plot_original=True, plot_upper_lower_bounds=True, plot_points_of_distribution=False,
plot_daily_maxes=False, plot_parabolas=False, month_xticks=False)
| 530 | return new_stacked_data |
| 531 | |
| 532 | def plot(self, stacked_data, days_to_plot=(0,10), |
| 533 | plot_sample=True, plot_original=True, plot_upper_lower_bounds=True, plot_points_of_distribution=False, |
| 534 | plot_daily_maxes=False, plot_parabolas=False, month_xticks=False): |
| 535 | |
| 536 | if isinstance(stacked_data, pd.DataFrame): |
| 537 | stacked_data = stacked_data.squeeze() |
| 538 | |
| 539 | if not isinstance(stacked_data, pd.Series): |
| 540 | if plot_sample: |
| 541 | print('Warning: stacked_data is an arbitrary sample. Must be pd.Series to plot passed stacked_data, is ' |
| 542 | '{}'.format((type(stacked_data)))) |
| 543 | stacked_data = self.sample() |
| 544 | |
| 545 | indices = slice(24 * days_to_plot[0], 24 * days_to_plot[1]) |
| 546 | daily_slice = slice(*days_to_plot) |
| 547 | if plot_sample: |
| 548 | plt.plot(stacked_data[indices].index, stacked_data[indices].values, label='Sample') |
| 549 | |
| 550 | if plot_original: |
| 551 | plt.plot(stacked_data[indices].index, self.unmunged_data[indices].values, label='Original') |
| 552 | |
| 553 | if plot_upper_lower_bounds: |
| 554 | plt.plot(stacked_data[indices].index, |
| 555 | self.most_light_curve_eval('max', cumulative_hours=stacked_data[indices].index), color='k', |
| 556 | label='Parabola distribution UB') |
| 557 | |
| 558 | plt.plot(stacked_data[indices].index, |
| 559 | self.most_light_curve_eval('min', cumulative_hours=stacked_data[indices].index), color='c', |
| 560 | label='Parabola distribution LB') |
| 561 | |
| 562 | if plot_points_of_distribution: |
| 563 | if self.distribution_bounds is None: |
| 564 | raise RuntimeError('Could not find distribution bounds, must call \'sample\' at least once to plot') |
| 565 | else: |
| 566 | lower_distribution_bounds, upper_distribution_bounds = self.distribution_bounds |
| 567 | |
| 568 | plt.scatter(self.daily_maxes['cumulative_hr'].iloc[daily_slice], lower_distribution_bounds[daily_slice], |
| 569 | marker='.', color='r') |
| 570 | plt.scatter(self.daily_maxes['cumulative_hr'].iloc[daily_slice], upper_distribution_bounds[daily_slice], |
| 571 | marker='.', color='r') |
| 572 | |
| 573 | if plot_daily_maxes: |
| 574 | plt.scatter(self.daily_maxes['cumulative_hr'].iloc[daily_slice],self.daily_maxes['max_GHI'].iloc[daily_slice], |
| 575 | marker='.', color='r', label='Underlying daily max pv') |
| 576 | if plot_parabolas: |
| 577 | parabolas = self.parabolic_baseline.transpose().stack().squeeze() |
| 578 | print(parabolas) |
| 579 | plt.plot(stacked_data[indices].index, parabolas.iloc[indices],color='c',label='Parabolic Baseline') |
| 580 | if month_xticks: |
| 581 | print(plt.xticks()) |
| 582 | locs = [j*30*24 for j in range(13) if j*12>=days_to_plot[0] and j*12<=days_to_plot[1]] |
| 583 | ticks = [j for j in range(13) if j*12>=days_to_plot[0] and j*12<=days_to_plot[1]] |
| 584 | print(locs) |
| 585 | print(ticks) |
| 586 | plt.xticks(locs, ticks) |
| 587 | |
| 588 | plt.xlabel('Month') |
| 589 | plt.ylabel('PV') |
no test coverage detected