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Merge pull request #195 from sunya-ch/tekton-prerequisite
add isolate_from_data and train_from_data, with refactor entrypoint (tekton prerequisite)
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,113 @@ | ||
| import os | ||
| import sys | ||
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| cur_path = os.path.join(os.path.dirname(__file__), '.') | ||
| sys.path.append(cur_path) | ||
| src_path = os.path.join(os.path.dirname(__file__), '..', 'src') | ||
| sys.path.append(src_path) | ||
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| from util.prom_types import TIMESTAMP_COL | ||
| from util import PowerSourceMap | ||
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| def ts_plot(data, cols, title, output_folder, name, labels=None, subtitles=None, ylabel=None): | ||
| plot_height = 3 | ||
| plot_width = 10 | ||
| import matplotlib.pyplot as plt | ||
| import seaborn as sns | ||
| sns.set(font_scale=1.2) | ||
| fig, axes = plt.subplots(len(cols), 1, figsize=(plot_width, len(cols)*plot_height)) | ||
| for i in range(0, len(cols)): | ||
| if len(cols) == 1: | ||
| ax = axes | ||
| else: | ||
| ax = axes[i] | ||
| if isinstance(cols[i], list): | ||
| # multiple lines | ||
| for j in range(0, len(cols[i])): | ||
| sns.lineplot(data=data, x=TIMESTAMP_COL, y=cols[i][j], ax=ax, label=labels[j]) | ||
| ax.set_title(subtitles[i]) | ||
| else: | ||
| sns.lineplot(data=data, x=TIMESTAMP_COL, y=cols[i], ax=ax) | ||
| ax.set_title(cols[i]) | ||
| if ylabel is not None: | ||
| ax.set_ylabel(ylabel) | ||
| plt.suptitle(title, x=0.5, y=0.99) | ||
| plt.tight_layout() | ||
| filename = os.path.join(output_folder, name + ".png") | ||
| fig.savefig(filename) | ||
| plt.close() | ||
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| def feature_power_plot(data, model_id, output_type, energy_source, feature_cols, actual_power_cols, predicted_power_cols, output_folder, name): | ||
| plot_height = 5 | ||
| plot_width = 5 | ||
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| import matplotlib.pyplot as plt | ||
| import seaborn as sns | ||
| sns.set(font_scale=1.2) | ||
| row_num = len(feature_cols) | ||
| col_num = len(actual_power_cols) | ||
| width = max(10, col_num*plot_width) | ||
| fig, axes = plt.subplots(row_num, col_num, figsize=(width, row_num*plot_height)) | ||
| for xi in range(0, row_num): | ||
| feature_col = feature_cols[xi] | ||
| for yi in range(0, col_num): | ||
| if row_num == 1: | ||
| if col_num == 1: | ||
| ax = axes | ||
| else: | ||
| ax = axes[yi] | ||
| else: | ||
| if col_num == 1: | ||
| ax = axes[xi] | ||
| else: | ||
| ax = axes[xi][yi] | ||
| sorted_data = data.sort_values(by=[feature_col]) | ||
| sns.scatterplot(data=sorted_data, x=feature_col, y=actual_power_cols[yi], ax=ax, label="actual") | ||
| sns.lineplot(data=sorted_data, x=feature_col, y=predicted_power_cols[yi], ax=ax, label="predicted", color='C1') | ||
| if xi == 0: | ||
| ax.set_title(actual_power_cols[yi]) | ||
| if yi == 0: | ||
| ax.set_ylabel("Power (W)") | ||
| title = "{} {} prediction correlation \n by {}".format(energy_source, output_type, model_id) | ||
| plt.suptitle(title, x=0.5, y=0.99) | ||
| plt.tight_layout() | ||
| filename = os.path.join(output_folder, name + ".png") | ||
| fig.savefig(filename) | ||
| plt.close() | ||
|
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| def summary_plot(args, energy_source, summary_df, output_folder, name): | ||
| if len(summary_df) == 0: | ||
| print("no summary data to plot") | ||
| return | ||
|
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| plot_height = 3 | ||
| plot_width = 20 | ||
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| import matplotlib.pyplot as plt | ||
| import seaborn as sns | ||
| sns.set(font_scale=1.2) | ||
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| energy_components = PowerSourceMap[energy_source] | ||
| col_num = len(energy_components) | ||
| fig, axes = plt.subplots(col_num, 1, figsize=(plot_width, plot_height*col_num)) | ||
| for i in range(0, col_num): | ||
| component = energy_components[i] | ||
| data = summary_df[(summary_df["energy_source"]==energy_source) & (summary_df["energy_component"]==component)] | ||
| data = data.sort_values(by=["Feature Group", "MAE"]) | ||
| if col_num == 1: | ||
| ax = axes | ||
| else: | ||
| ax = axes[i] | ||
| sns.barplot(data=data, x="Feature Group", y="MAE", hue="Model", ax=ax) | ||
| ax.set_title(component) | ||
| ax.set_ylabel("MAE (Watt)") | ||
| ax.set_ylim((0, 100)) | ||
| if i < col_num-1: | ||
| ax.set_xlabel("") | ||
| ax.legend(bbox_to_anchor=(1.05, 1.05)) | ||
| plt.suptitle("{} {} error".format(energy_source, args.output_type)) | ||
| plt.tight_layout() | ||
| filename = os.path.join(output_folder, name + ".png") | ||
| fig.savefig(filename) | ||
| plt.close() |
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