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Merge pull request e-mission#148 from iantei/Integrate_base_mode_colors
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Integrate common base mode colors into public dashboard
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@shankari
shankari authored Sep 21, 2024
2 parents e28ce6e + 3cbd76b commit de20f12
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Showing 9 changed files with 125 additions and 67 deletions.
2 changes: 1 addition & 1 deletion viz_scripts/energy_calculations.ipynb
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Expand Up @@ -106,7 +106,7 @@
},
"outputs": [],
"source": [
"expanded_ct, file_suffix, quality_text, debug_df = scaffolding.load_viz_notebook_data(year,\n",
"expanded_ct, file_suffix, quality_text, debug_df = await scaffolding.load_viz_notebook_data(year,\n",
" month,\n",
" program,\n",
" study_type,\n",
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35 changes: 18 additions & 17 deletions viz_scripts/generic_metrics.ipynb
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Expand Up @@ -90,7 +90,8 @@
"metadata": {},
"outputs": [],
"source": [
"colors_mode, colors_purpose, colors_sensed = scaffolding.mapping_color_labels(dynamic_labels, dic_re, dic_pur)"
"colors_mode, colors_replaced, colors_purpose, colors_sensed, colors_ble = await scaffolding.mapping_color_labels(dynamic_labels)\n",
"values_to_translations, value_to_translations_purpose, values_to_translations_replaced = await scaffolding.translate_values_to_labels(dynamic_labels)"
]
},
{
Expand All @@ -108,7 +109,7 @@
"metadata": {},
"outputs": [],
"source": [
"expanded_ct, file_suffix, quality_text, debug_df = scaffolding.load_viz_notebook_data(year,\n",
"expanded_ct, file_suffix, quality_text, debug_df = await scaffolding.load_viz_notebook_data(year,\n",
" month,\n",
" program,\n",
" study_type,\n",
Expand Down Expand Up @@ -207,8 +208,8 @@
" # We will have text results corresponding to the axes for simplicity and consistency\n",
" text_results = [[\"Unmodified Alt Text\", \"Unmodified HTML\"], [\"Unmodified Alt Text\", \"Unmodified HTML\"]]\n",
" \n",
" plot_and_text_stacked_bar_chart(expanded_ct, lambda df: (df.groupby(\"Mode_confirm\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False)), \n",
" \"Labeled by user\\n\"+stacked_bar_quality_text_labeled, ax[0], text_results[0], colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(expanded_ct, lambda df: (df.groupby(\"mode_confirm_w_other\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False)), \n",
" \"Labeled by user\\n\"+stacked_bar_quality_text_labeled, ax[0], text_results[0], colors_mode, debug_df, values_to_translations)\n",
" plot_and_text_stacked_bar_chart(expanded_ct_sensed, lambda df: (df.groupby(\"primary_mode\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False)), \n",
" \"Sensed by OpenPATH\\n\"+stacked_bar_quality_text_sensed, ax[1], text_results[1], colors_sensed, debug_df_sensed)\n",
" \n",
Expand Down Expand Up @@ -258,8 +259,8 @@
" # Plot entries\n",
" fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15,2*1), sharex=True) \n",
" text_results = [\"Unmodified Alt Text\", \"Unmodified HTML\"]\n",
" plot_and_text_stacked_bar_chart(expanded_ct_commute, lambda df: df.groupby(\"Mode_confirm\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n (Confirmed trips)\", ax, text_results, colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(expanded_ct_commute, lambda df: df.groupby(\"mode_confirm_w_other\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n (Confirmed trips)\", ax, text_results, colors_mode, debug_df, values_to_translations)\n",
" set_title_and_save(fig, text_results, plot_title, file_name)\n",
"except (AttributeError, KeyError, pd.errors.UndefinedVariableError) as e:\n",
" plt.clf()\n",
Expand Down Expand Up @@ -291,8 +292,8 @@
"try:\n",
" fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15,2*1), sharex=True)\n",
" text_results = [\"Unmodified Alt Text\", \"Unmodified HTML\"]\n",
" plot_and_text_stacked_bar_chart(expanded_ct, lambda df: df.groupby(\"Trip_purpose\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+stacked_bar_quality_text_labeled, ax, text_results, colors_purpose, debug_df)\n",
" plot_and_text_stacked_bar_chart(expanded_ct, lambda df: df.groupby(\"purpose_confirm_w_other\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+stacked_bar_quality_text_labeled, ax, text_results, colors_purpose, debug_df, value_to_translations_purpose)\n",
" set_title_and_save(fig, text_results, plot_title_no_quality, file_name)\n",
"except (AttributeError, KeyError, pd.errors.UndefinedVariableError) as e:\n",
" plt.clf()\n",
Expand Down Expand Up @@ -335,16 +336,16 @@
"\n",
" ## We do an existence check for the labeled df because we want to display the sensed value even if we don't have the labeled value\n",
" ## but we don't need to have an existence check for sensed because in that case we will have no data to display\n",
" expanded_ct_u80 = expanded_ct.loc[(expanded_ct['distance'] <= cutoff)] if \"Mode_confirm\" in expanded_ct.columns else None\n",
" expanded_ct_u80 = expanded_ct.loc[(expanded_ct['distance'] <= cutoff)] if \"mode_confirm_w_other\" in expanded_ct.columns else None\n",
" expanded_ct_sensed_u80 = expanded_ct_sensed.loc[(expanded_ct_sensed['distance'] <= cutoff)]\n",
" sensed_u80_quality_text = f\"{len(expanded_ct_sensed_u80)} trips ({round(len(expanded_ct_sensed_u80)/len(expanded_ct_sensed)*100)}% of all trips)\\nfrom {scaffolding.unique_users(expanded_ct_sensed_u80)} {sensed_match.group(3)}\"\n",
" labeled_u80_quality_text = f\"{len(expanded_ct_u80)} trips ({round(len(expanded_ct_u80)/len(expanded_ct)*100)}% of all labeled,\\n{round(len(expanded_ct_u80)/len(expanded_ct_sensed)*100)}% of all trips)\\nfrom {scaffolding.unique_users(expanded_ct_u80)} {sensed_match.group(3)}\" if \"Mode_confirm\" in expanded_ct.columns else \"0 labeled trips\"\n",
" \n",
" # Plot entries\n",
" fig, ax = plt.subplots(nrows=2, ncols=1, figsize=(15,2*2), sharex=True)\n",
" text_results = [[\"Unmodified Alt Text\", \"Unmodified HTML\"], [\"Unmodified Alt Text\", \"Unmodified HTML\"]]\n",
" plot_and_text_stacked_bar_chart(expanded_ct_u80, lambda df: df.groupby(\"Mode_confirm\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+labeled_u80_quality_text, ax[0], text_results[0], colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(expanded_ct_u80, lambda df: df.groupby(\"mode_confirm_w_other\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+labeled_u80_quality_text, ax[0], text_results[0], colors_mode, debug_df, values_to_translations)\n",
" plot_and_text_stacked_bar_chart(expanded_ct_sensed_u80, lambda df: df.groupby(\"primary_mode\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" \"Sensed by OpenPATH\\n\"+sensed_u80_quality_text, ax[1], text_results[1], colors_sensed, debug_df_sensed)\n",
" set_title_and_save(fig, text_results, plot_title_no_quality, file_name)\n",
Expand Down Expand Up @@ -383,8 +384,8 @@
" fig, ax = plt.subplots(nrows=2, ncols=1, figsize=(15,2*2), sharex=True)\n",
" \n",
" text_results = [[\"Unmodified Alt Text\", \"Unmodified HTML\"], [\"Unmodified Alt Text\", \"Unmodified HTML\"]]\n",
" plot_and_text_stacked_bar_chart(expanded_ct, lambda df: df.groupby(\"Mode_confirm\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+stacked_bar_quality_text_labeled, ax[0], text_results[0], colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(expanded_ct, lambda df: df.groupby(\"mode_confirm_w_other\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+stacked_bar_quality_text_labeled, ax[0], text_results[0], colors_mode, debug_df, values_to_translations)\n",
" plot_and_text_stacked_bar_chart(expanded_ct_sensed, lambda df: df.groupby(\"primary_mode\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Sensed by OpenPATH\\n\"+stacked_bar_quality_text_sensed, ax[1], text_results[1], colors_sensed, debug_df_sensed)\n",
" set_title_and_save(fig, text_results, plot_title_no_quality, file_name) \n",
Expand Down Expand Up @@ -419,15 +420,15 @@
"try:\n",
" ## We do an existence check for the labeled df because we want to display the sensed value even if we don't have the labeled value\n",
" ## but we don't need to have an existence check for sensed because in that case we will have no data to display\n",
" labeled_land_trips_df = expanded_ct[expanded_ct['mode_confirm'] != \"air\"] if \"mode_confirm\" in expanded_ct.columns else None\n",
" labeled_land_trips_df = expanded_ct[expanded_ct['mode_confirm_w_other'] != \"air\"] if \"mode_confirm_w_other\" in expanded_ct.columns else None\n",
" sensed_land_trips_df = expanded_ct_sensed[expanded_ct_sensed['primary_mode'] != \"AIR_OR_HSR\"]\n",
" \n",
" sensed_land_quality_text = f\"{len(sensed_land_trips_df)} trips ({round(len(sensed_land_trips_df)/len(expanded_ct_sensed)*100)}% of all trips)\\nfrom {scaffolding.unique_users(sensed_land_trips_df)} {sensed_match.group(3)}\"\n",
" labeled_land_quality_text = f\"{len(labeled_land_trips_df)} trips ({round(len(labeled_land_trips_df)/len(expanded_ct)*100)}% of all labeled,\\n{round(len(labeled_land_trips_df)/len(expanded_ct_sensed)*100)}%) of all trips)\\nfrom {scaffolding.unique_users(labeled_land_trips_df)} {sensed_match.group(3)}\" if \"Mode_confirm\" in expanded_ct.columns else \"0 labeled trips\"\n",
" labeled_land_quality_text = f\"{len(labeled_land_trips_df)} trips ({round(len(labeled_land_trips_df)/len(expanded_ct)*100)}% of all labeled,\\n{round(len(labeled_land_trips_df)/len(expanded_ct_sensed)*100)}%) of all trips)\\nfrom {scaffolding.unique_users(labeled_land_trips_df)} {sensed_match.group(3)}\" if \"mode_confirm_w_other\" in expanded_ct.columns else \"0 labeled trips\"\n",
"\n",
" fig, ax = plt.subplots(nrows=2, ncols=1, figsize=(15,2*2), sharex=True)\n",
" plot_and_text_stacked_bar_chart(labeled_land_trips_df, lambda df: df.groupby(\"Mode_confirm\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+labeled_land_quality_text, ax[0], text_results[0], colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(labeled_land_trips_df, lambda df: df.groupby(\"mode_confirm_w_other\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n\"+labeled_land_quality_text, ax[0], text_results[0], colors_mode, debug_df, values_to_translations)\n",
" plot_and_text_stacked_bar_chart(sensed_land_trips_df, lambda df: df.groupby(\"primary_mode\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Sensed by OpenPATH\\n\"+sensed_land_quality_text, ax[1], text_results[1], colors_sensed, debug_df_sensed)\n",
" set_title_and_save(fig, text_results, plot_title_no_quality, file_name) \n",
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4 changes: 2 additions & 2 deletions viz_scripts/generic_metrics_sensed.ipynb
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Expand Up @@ -96,8 +96,8 @@
" expanded_ct[\"primary_mode\"] = expanded_ct.ble_sensed_summary.apply(lambda md: max(md[\"distance\"], key=md[\"distance\"].get))\n",
" unique_keys = expanded_ct.groupby(\"primary_mode\").agg({distance_col: \"count\"}).index\n",
" print(unique_keys)\n",
" colors_mode, colors_purpose, colors_sensed = scaffolding.mapping_color_labels({}, dict(zip(unique_keys, unique_keys)), {})\n",
" colors_sensed = colors_mode\n",
" colors_mode, colors_replaced, colors_purpose, colors_sensed, colors_ble = await scaffolding.mapping_color_labels(unique_keys) #Extract ble color mapping\n",
" colors_sensed = colors_ble\n",
"except ValueError as e:\n",
" print(\"Got ValueError \", e)"
]
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2 changes: 1 addition & 1 deletion viz_scripts/generic_timeseries.ipynb
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Expand Up @@ -87,7 +87,7 @@
},
"outputs": [],
"source": [
"expanded_ct, file_suffix, quality_text, debug_df = scaffolding.load_viz_notebook_data(year,\n",
"expanded_ct, file_suffix, quality_text, debug_df = await scaffolding.load_viz_notebook_data(year,\n",
" month,\n",
" program,\n",
" study_type,\n",
Expand Down
17 changes: 9 additions & 8 deletions viz_scripts/mode_specific_metrics.ipynb
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Expand Up @@ -103,7 +103,8 @@
"metadata": {},
"outputs": [],
"source": [
"colors_mode, colors_purpose, colors_sensed = scaffolding.mapping_color_labels(dynamic_labels, dic_re, dic_pur)"
"colors_mode, colors_replaced, colors_purpose, colors_sensed, colors_ble = await scaffolding.mapping_color_labels(dynamic_labels)\n",
"values_to_translations, value_to_translations_purpose, value_to_translations_replaced = await scaffolding.translate_values_to_labels(dynamic_labels)"
]
},
{
Expand All @@ -121,7 +122,7 @@
"metadata": {},
"outputs": [],
"source": [
"expanded_ct, file_suffix, quality_text, debug_df = scaffolding.load_viz_notebook_data(year,\n",
"expanded_ct, file_suffix, quality_text, debug_df = await scaffolding.load_viz_notebook_data(year,\n",
" month,\n",
" program,\n",
" study_type,\n",
Expand Down Expand Up @@ -193,8 +194,8 @@
"try:\n",
" fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15,2*1), sharex=True)\n",
" text_results = [\"Unmodified Alt Text\", \"Unmodified HTML\"]\n",
" plot_and_text_stacked_bar_chart(data_eb, lambda df: df.groupby(\"Trip_purpose\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False),\n",
" f\"Labeled `{mode_of_interest}` by user\", ax, text_results, colors_purpose, debug_df)\n",
" plot_and_text_stacked_bar_chart(data_eb, lambda df: df.groupby(\"purpose_confirm_w_other\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False),\n",
" f\"Labeled `{mode_of_interest}` by user\", ax, text_results, colors_purpose, debug_df, value_to_translations_purpose)\n",
" plot_title = plot_title_no_quality + \"\\n\" + f\"For {mode_of_interest}: \" + quality_text\n",
" set_title_and_save(fig, text_results, plot_title, file_name)\n",
"except (AttributeError, KeyError, pd.errors.UndefinedVariableError) as e:\n",
Expand Down Expand Up @@ -228,8 +229,8 @@
"try:\n",
" fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15,2*1), sharex=True)\n",
" text_results = [\"Unmodified Alt Text\", \"Unmodified HTML\"]\n",
" plot_and_text_stacked_bar_chart(data_eb, lambda df: df.groupby(\"Replaced_mode\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n (Trip distance)\", ax, text_results, colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(data_eb, lambda df: df.groupby(\"replaced_mode_w_other\").agg({distance_col: 'sum'}).sort_values(by=distance_col, ascending=False), \n",
" \"Labeled by user\\n (Trip distance)\", ax, text_results, colors_replaced, debug_df, value_to_translations_replaced)\n",
" plot_title = plot_title_no_quality + \"\\n\" + f\"For {mode_of_interest}: \" + quality_text\n",
" set_title_and_save(fig, text_results, plot_title, file_name)\n",
"except (AttributeError, KeyError, pd.errors.UndefinedVariableError) as e:\n",
Expand Down Expand Up @@ -263,8 +264,8 @@
"try:\n",
" fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15,2*1), sharex=True)\n",
" text_results = [\"Unmodified Alt Text\", \"Unmodified HTML\"]\n",
" plot_and_text_stacked_bar_chart(data_eb, lambda df: df.groupby(\"Replaced_mode\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" f\"Labeled `{mode_of_interest}` by user\", ax, text_results, colors_mode, debug_df)\n",
" plot_and_text_stacked_bar_chart(data_eb, lambda df: df.groupby(\"replaced_mode_w_other\").agg({distance_col: 'count'}).sort_values(by=distance_col, ascending=False), \n",
" f\"Labeled `{mode_of_interest}` by user\", ax, text_results, colors_replaced, debug_df, value_to_translations_replaced)\n",
" plot_title = plot_title_no_quality + \"\\n\" + f\"For {mode_of_interest}: \" + quality_text\n",
" set_title_and_save(fig, text_results, plot_title, file_name)\n",
"except (AttributeError, KeyError, pd.errors.UndefinedVariableError) as e:\n",
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2 changes: 1 addition & 1 deletion viz_scripts/mode_specific_timeseries.ipynb
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Expand Up @@ -96,7 +96,7 @@
"metadata": {},
"outputs": [],
"source": [
"expanded_ct, file_suffix, quality_text, debug_df = scaffolding.load_viz_notebook_data(year,\n",
"expanded_ct, file_suffix, quality_text, debug_df = await scaffolding.load_viz_notebook_data(year,\n",
" month,\n",
" program,\n",
" study_type,\n",
Expand Down
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