Introduce inferred labels in stacked bar charts #128

iantei · 2024-04-08T10:37:59Z

No description provided.

… Count and Proportion.

…etrics notebook.

…ed mode.

…metrics notebook.

…etrics notebook.

…e structure.

…data-sizex to 10 from 4 to adjust horizonatal length of the stacked bar charts. Update with new option values.

…s Text button for all 100% Stacked Bar Charts.

… description.

… process_notebook_data function.

… confirmed trips.

…e the users according to the include_test_users.

…pdate different strings for the 100% Stacked bar charts Y-axis labels.

… bar. 3. Shorten the plot title description.

…ate the text description for the Y-axis bar. 3. Shorten the plot title description.

…_data_for_cutoff with cutoff argument.

…e the text description for the Y-axis bar. 3. Shorten the plot title description.

…tion for the Y-axis bar. 3. Shorten the plot title description.

…. Update the text description for the Y-axis bar. 3. Shorten the plot title description.

…d bar. 2. Update the text description for the Y-axis bar. 3. Shorten the plot title description.

…r. 2. Update the text description for the Y-axis bar. 3. Shorten the plot title description.

…putation. 2. Update inferred bar. 3. Update the text description for the Y-axis bar. 4. Shorten the plot title description.

…placed mode.

…file name.

iantei · 2024-04-08T11:58:26Z

Test Scenario:

Dataset loaded: openpath_prod_cortezebikes & openpath_prod_usaid_laos_ev

docker-compose setup:

services:
  notebook-server:
    environment:
          - DB_HOST=mongodb://db/openpath_prod_cortezebikes
          - WEB_SERVER_HOST=0.0.0.0
          - CRON_MODE=TRUE
          - STUDY_CONFIG=cortezebikes

Execution of scripts for `energy_calculations`, `generic_metrics`, `generic_timeseries` and `mode_specific_timeseries` notebooks.

Generic Timeseries

(emission) root@038aa0a04710:/usr/src/app/saved-notebooks# PYTHONPATH=.. python bin/update_mappings.py mapping_dictionaries.ipynb
(emission) root@038aa0a04710:/usr/src/app/saved-notebooks# PYTHONPATH=.. python bin/generate_plots.py generic_timeseries.ipynb default 
/usr/src/app/saved-notebooks/bin/generate_plots.py:30: SyntaxWarning: "is not" with a literal. Did you mean "!="?
  if r.status_code is not 200:
About to download config from https://raw.githubusercontent.com/e-mission/nrel-openpath-deploy-configs/main/configs/cortezebikes.nrel-op.json
Successfully downloaded config with version 1 for Cortez 55+ eBike Program and data collection URL https://cortezebikes-openpath.nrel.gov/api/
label_options is unavailable for the dynamic_config in cortezebikes
Running at 2024-04-08T10:51:42.351144+00:00 with args Namespace(plot_notebook='generic_timeseries.ipynb', program='default', date=None) for range (<Arrow [2023-06-01T00:00:00+00:00]>, <Arrow [2024-04-01T00:00:00+00:00]>)
Running at 2024-04-08T10:51:42.388267+00:00 with params [Parameter('year', int), Parameter('month', int), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:51:51.019951+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=6), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:51:57.050658+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=7), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:52:03.870046+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=8), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:52:10.652408+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=9), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:52:16.913490+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=10), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
 Running at 2024-04-08T10:52:23.671309+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=11), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:52:31.107099+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=12), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:52:37.774468+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=1), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:52:44.086618+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=2), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:52:49.974567+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=3), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:52:55.826877+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=4), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]

Mode Specific Timeseries

(emission) root@038aa0a04710:/usr/src/app/saved-notebooks# PYTHONPATH=.. python bin/generate_plots.py mode_specific_timeseries.ipynb default 
/usr/src/app/saved-notebooks/bin/generate_plots.py:30: SyntaxWarning: "is not" with a literal. Did you mean "!="?
  if r.status_code is not 200:
About to download config from https://raw.githubusercontent.com/e-mission/nrel-openpath-deploy-configs/main/configs/cortezebikes.nrel-op.json
Successfully downloaded config with version 1 for Cortez 55+ eBike Program and data collection URL https://cortezebikes-openpath.nrel.gov/api/
label_options is unavailable for the dynamic_config in cortezebikes
Running at 2024-04-08T10:53:59.953298+00:00 with args Namespace(plot_notebook='mode_specific_timeseries.ipynb', program='default', date=None) for range (<Arrow [2023-06-01T00:00:00+00:00]>, <Arrow [2024-04-01T00:00:00+00:00]>)
Running at 2024-04-08T10:53:59.986064+00:00 with params [Parameter('year', int), Parameter('month', int), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:54:15.508127+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=6), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:54:23.829980+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=7), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:54:33.172350+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=8), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:54:42.309153+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=9), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:54:51.645116+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=10), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:55:01.004711+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=11), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:55:10.072507+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=12), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:55:18.948403+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=1), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:55:26.240539+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=2), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:55:33.416492+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=3), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:55:40.803762+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=4), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]

Energy Calculations:

(emission) root@038aa0a04710:/usr/src/app/saved-notebooks# PYTHONPATH=.. python bin/generate_plots.py energy_calculations.ipynb default
/usr/src/app/saved-notebooks/bin/generate_plots.py:30: SyntaxWarning: "is not" with a literal. Did you mean "!="?
  if r.status_code is not 200:
About to download config from https://raw.githubusercontent.com/e-mission/nrel-openpath-deploy-configs/main/configs/cortezebikes.nrel-op.json
Successfully downloaded config with version 1 for Cortez 55+ eBike Program and data collection URL https://cortezebikes-openpath.nrel.gov/api/
label_options is unavailable for the dynamic_config in cortezebikes
Running at 2024-04-08T10:56:15.621876+00:00 with args Namespace(plot_notebook='energy_calculations.ipynb', program='default', date=None) for range (<Arrow [2023-06-01T00:00:00+00:00]>, <Arrow [2024-04-01T00:00:00+00:00]>)
Running at 2024-04-08T10:56:15.661003+00:00 with params [Parameter('year', int), Parameter('month', int), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('is_debug_mode', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:56:21.786460+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=6), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('is_debug_mode', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:56:26.038191+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=7), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('is_debug_mode', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:56:30.782353+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=8), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('is_debug_mode', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:56:35.222316+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=9), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('is_debug_mode', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:56:39.650033+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=10), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('is_debug_mode', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:56:44.014215+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=11), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('is_debug_mode', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:56:48.250069+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=12), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('is_debug_mode', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:56:52.559431+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=1), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('is_debug_mode', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:56:56.832909+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=2), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('is_debug_mode', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:57:01.154644+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=3), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('is_debug_mode', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]
Running at 2024-04-08T10:57:05.049871+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=4), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('is_debug_mode', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True)]

Generic Metrics notebooks:

(emission) root@057703777f44:/usr/src/app/saved-notebooks# PYTHONPATH=.. python bin/update_mappings.py mapping_dictionaries.ipynb
(emission) root@057703777f44:/usr/src/app/saved-notebooks# PYTHONPATH=.. python bin/generate_plots.py generic_metrics.ipynb default
/usr/src/app/saved-notebooks/bin/generate_plots.py:30: SyntaxWarning: "is not" with a literal. Did you mean "!="?
  if r.status_code is not 200:
About to download config from https://raw.githubusercontent.com/e-mission/nrel-openpath-deploy-configs/main/configs/cortezebikes.nrel-op.json
Successfully downloaded config with version 1 for Cortez 55+ eBike Program and data collection URL https://cortezebikes-openpath.nrel.gov/api/
label_options is unavailable for the dynamic_config in cortezebikes
Running at 2024-04-08T11:22:54.911281+00:00 with args Namespace(plot_notebook='generic_metrics.ipynb', program='default', date=None) for range (<Arrow [2023-06-01T00:00:00+00:00]>, <Arrow [2024-04-01T00:00:00+00:00]>)
Running at 2024-04-08T11:22:54.953016+00:00 with params [Parameter('year', int), Parameter('month', int), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True), Parameter('sensed_algo_prefix', str, value='cleaned')]
Running at 2024-04-08T11:23:13.904960+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=6), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True), Parameter('sensed_algo_prefix', str, value='cleaned')]
Running at 2024-04-08T11:23:28.700717+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=7), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True), Parameter('sensed_algo_prefix', str, value='cleaned')]
Running at 2024-04-08T11:23:45.038579+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=8), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True), Parameter('sensed_algo_prefix', str, value='cleaned')]
Running at 2024-04-08T11:24:00.197543+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=9), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True), Parameter('sensed_algo_prefix', str, value='cleaned')]
Running at 2024-04-08T11:24:15.256795+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=10), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True), Parameter('sensed_algo_prefix', str, value='cleaned')]
Running at 2024-04-08T11:24:30.147444+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=11), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True), Parameter('sensed_algo_prefix', str, value='cleaned')]
Running at 2024-04-08T11:24:44.950058+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=12), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True), Parameter('sensed_algo_prefix', str, value='cleaned')]
Running at 2024-04-08T11:24:58.902453+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=1), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True), Parameter('sensed_algo_prefix', str, value='cleaned')]
Running at 2024-04-08T11:25:13.068264+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=2), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True), Parameter('sensed_algo_prefix', str, value='cleaned')]
Running at 2024-04-08T11:25:26.259429+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=3), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True), Parameter('sensed_algo_prefix', str, value='cleaned')]
Running at 2024-04-08T11:25:39.976348+00:00 with params [Parameter('year', int, value=2024), Parameter('month', int, value=4), Parameter('program', str, value='default'), Parameter('study_type', str, value='program'), Parameter('mode_of_interest', str, value='e-bike'), Parameter('include_test_users', bool, value=False), Parameter('dynamic_labels', dict, value={}), Parameter('use_imperial', bool, value=True), Parameter('sensed_algo_prefix', str, value='cleaned')]

Execution of notebook scripts: Generic Metrics and Generic Timeseries: For Laos

Generic Timeseries:

(emission) root@f779753ffc07:/usr/src/app/saved-notebooks# PYTHONPATH=.. python bin/update_mappings.py mapping_dictionaries.ipynb
(emission) root@f779753ffc07:/usr/src/app/saved-notebooks# PYTHONPATH=.. python bin/generate_plots.py generic_timeseries.ipynb default
/usr/src/app/saved-notebooks/bin/generate_plots.py:30: SyntaxWarning: "is not" with a literal. Did you mean "!="?
  if r.status_code is not 200:
About to download config from https://raw.githubusercontent.com/e-mission/nrel-openpath-deploy-configs/main/configs/usaid-laos-ev.nrel-op.json
Successfully downloaded config with version 1 for USAID-NREL Support for Electric Vehicle Readiness and data collection URL https://USAID-laos-EV-openpath.nrel.gov/api/
Dynamic labels download was successful for nrel-openpath-deploy-configs: usaid-laos-ev
Running at 2024-04-08T11:36:19.334927+00:00 with args Namespace(plot_notebook='generic_timeseries.ipynb', program='default', date=None) for range (<Arrow [2023-05-01T00:00:00+00:00]>, <Arrow [2024-04-01T00:00:00+00:00]>)
Running at 2024-04-08T11:36:19.369748+00:00 with params [Parameter('year', int), Parameter('month', int), Parameter('program', str, value='default'), Parameter('study_type', str, value='study'), Parameter('include_test_users', bool, value=True), Parameter('dynamic_labels', dict, value={'MODE': [{'value': 'walk', 'baseMode': 'WALKING', 'met_equivalent': 'WALKING', 'kgCo2PerKm': 0}, {'value': 'e-auto_rickshaw', 'baseMode': 'MOPED', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.085416859}, {'value': 'auto_rickshaw', 'baseMode': 'MOPED', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.231943784}, {'value': 'motorcycle', 'baseMode': 'MOPED', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.113143309}, {'value': 'e-bike', 'baseMode': 'E_BIKE', 'met': {'ALL': {'range': [0, -1], 'mets': 4.9}}, 'kgCo2PerKm': 0.00728}, {'value': 'bike', 'baseMode': 'BICYCLING', 'met_equivalent': 'BICYCLING', 'kgCo2PerKm': 0}, {'value': 'drove_alone', 'baseMode': 'CAR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.22031}, {'value': 'shared_ride', 'baseMode': 'CAR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.11015}, {'value': 'e_car_drove_alone', 'baseMode': 'E_CAR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.08216}, {'value': 'e_car_shared_ride', 'baseMode': 'E_CAR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.04108}, {'value': 'taxi', 'baseMode': 'TAXI', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.30741}, {'value': 'bus', 'baseMode': 'BUS', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.20727}, {'value': 'train', 'baseMode': 'TRAIN', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.12256}, {'value': 'free_shuttle', 'baseMode': 'BUS', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.20727}, {'value': 'air', 'baseMode': 'AIR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.09975}, {'value': 'not_a_trip', 'baseMode': 'UNKNOWN', 'met_equivalent': 'UNKNOWN', 'kgCo2PerKm': 0}, {'value': 'other', 'baseMode': 'OTHER', 'met_equivalent': 'UNKNOWN', 'kgCo2PerKm': 0}], 'PURPOSE': [{'value': 'home'}, {'value': 'work'}, {'value': 'at_work'}, {'value': 'school'}, {'value': 'transit_transfer'}, {'value': 'shopping'}, {'value': 'meal'}, {'value': 'pick_drop_person'}, {'value': 'pick_drop_item'}, {'value': 'personal_med'}, {'value': 'access_recreation'}, {'value': 'exercise'}, {'value': 'entertainment'}, {'value': 'religious'}, {'value': 'other'}], 'translations': {'en': {'walk': 'Walk', 'e-auto_rickshaw': 'E-tuk tuk', 'auto_rickshaw': 'Tuk Tuk', 'motorcycle': 'Motorcycle', 'e-bike': 'E-bike', 'bike': 'Bicycle', 'drove_alone': 'Car Drove Alone', 'shared_ride': 'Car Shared Ride', 'e_car_drove_alone': 'E-Car Drove Alone', 'e_car_shared_ride': 'E-Car Shared Ride', 'taxi': 'Taxi/Loca/inDrive', 'bus': 'Bus', 'train': 'Train', 'free_shuttle': 'Free Shuttle', 'air': 'Airplane', 'not_a_trip': 'Not a trip', 'home': 'Home', 'work': 'To Work', 'at_work': 'At Work', 'school': 'School', 'transit_transfer': 'Transit transfer', 'shopping': 'Shopping', 'meal': 'Meal', 'pick_drop_person': 'Pick-up/ Drop off Person', 'pick_drop_item': 'Pick-up/ Drop off Item', 'personal_med': 'Personal/ Medical', 'access_recreation': 'Access Recreation', 'exercise': 'Recreation/ Exercise', 'entertainment': 'Entertainment/ Social', 'religious': 'Religious', 'other': 'Other'}, 'lo': {'walk': 'ດ້ວຍການຍ່າງ', 'e-auto_rickshaw': 'ລົດ 3 ລໍ້ໄຟຟ້າ ຫລື ຕຸກຕຸກໄຟຟ້າ', 'auto_rickshaw': 'ເດີນທາດ້ວຍ ລົດຕຸກຕຸກ ຫລື ລົດສາມລໍ້', 'motorcycle': 'ລົດຈັກ', 'e-bike': 'ວຍລົດຈັກໄຟຟ້າ', 'bike': 'ລົດຖີບ', 'drove_alone': 'ເດີນທາງ ດ້ວຍລົດໃຫ່ຍ ເຊີ່ງເປັນລົດທີ່ຂັບເອງ', 'shared_ride': 'ເດີນທາງດ້ວຍລົດໃຫ່ຍ ຮ່ວມກັບລົດຄົນອຶ່ນ', 'e_car_drove_alone': 'ດ້ວຍການຂັບລົດໄຟຟ້າໄປເອງ', 'e_car_shared_ride': 'ດ້ວຍການຈ້າງລົດໄຟຟ້າໄປ', 'taxi': 'ແທັກຊີ', 'bus': 'ລົດເມ', 'train': 'ລົດໄຟ', 'free_shuttle': 'ລົດຮັບສົ່ງຟຣີ', 'air': 'ຍົນ', 'not_a_trip': 'ບໍ່ແມ່ນການເດີນທາງ', 'home': 'ບ້ານ', 'work': 'ໄປເຮັດວຽກ', 'at_work': 'ຢູ່ບ່ອນເຮັດວຽກ', 'school': 'ໄປໂຮງຮຽນ', 'transit_transfer': 'ການຖ່າຍໂອນການເດີນທາງ', 'shopping': 'ຊອບປິ້ງ', 'meal': 'ອາຫານ', 'pick_drop_person': 'ໄປຮັບ ຫລື ສົນ ຄົນ', 'pick_drop_item': 'ໄປຮັບ ຫລື ສົ່ງສິນຄ້າ', 'personal_med': 'ໄປຫາໝໍ', 'access_recreation': 'ເຂົ້າເຖິງການພັກຜ່ອນ', 'exercise': 'ພັກຜ່ອນ/ອອກກຳລັງກາຍ', 'entertainment': 'ບັນເທີງ/ສັງຄົມ', 'religious': 'ຈຸດປະສົງທາງສາດສະໜາ', 'other': 'ອື່ນໆ'}}}), Parameter('use_imperial', bool, value=False)]

Generic Metrics

(emission) root@f779753ffc07:/usr/src/app/saved-notebooks# PYTHONPATH=.. python bin/generate_plots.py generic_metrics.ipynb default
/usr/src/app/saved-notebooks/bin/generate_plots.py:30: SyntaxWarning: "is not" with a literal. Did you mean "!="?
  if r.status_code is not 200:
About to download config from https://raw.githubusercontent.com/e-mission/nrel-openpath-deploy-configs/main/configs/usaid-laos-ev.nrel-op.json
Successfully downloaded config with version 1 for USAID-NREL Support for Electric Vehicle Readiness and data collection URL https://USAID-laos-EV-openpath.nrel.gov/api/
Dynamic labels download was successful for nrel-openpath-deploy-configs: usaid-laos-ev
Running at 2024-04-08T11:38:53.648015+00:00 with args Namespace(plot_notebook='generic_metrics.ipynb', program='default', date=None) for range (<Arrow [2023-05-01T00:00:00+00:00]>, <Arrow [2024-04-01T00:00:00+00:00]>)
Running at 2024-04-08T11:38:53.686866+00:00 with params [Parameter('year', int), Parameter('month', int), Parameter('program', str, value='default'), Parameter('study_type', str, value='study'), Parameter('mode_of_interest', str), Parameter('include_test_users', bool, value=True), Parameter('dynamic_labels', dict, value={'MODE': [{'value': 'walk', 'baseMode': 'WALKING', 'met_equivalent': 'WALKING', 'kgCo2PerKm': 0}, {'value': 'e-auto_rickshaw', 'baseMode': 'MOPED', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.085416859}, {'value': 'auto_rickshaw', 'baseMode': 'MOPED', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.231943784}, {'value': 'motorcycle', 'baseMode': 'MOPED', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.113143309}, {'value': 'e-bike', 'baseMode': 'E_BIKE', 'met': {'ALL': {'range': [0, -1], 'mets': 4.9}}, 'kgCo2PerKm': 0.00728}, {'value': 'bike', 'baseMode': 'BICYCLING', 'met_equivalent': 'BICYCLING', 'kgCo2PerKm': 0}, {'value': 'drove_alone', 'baseMode': 'CAR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.22031}, {'value': 'shared_ride', 'baseMode': 'CAR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.11015}, {'value': 'e_car_drove_alone', 'baseMode': 'E_CAR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.08216}, {'value': 'e_car_shared_ride', 'baseMode': 'E_CAR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.04108}, {'value': 'taxi', 'baseMode': 'TAXI', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.30741}, {'value': 'bus', 'baseMode': 'BUS', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.20727}, {'value': 'train', 'baseMode': 'TRAIN', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.12256}, {'value': 'free_shuttle', 'baseMode': 'BUS', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.20727}, {'value': 'air', 'baseMode': 'AIR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.09975}, {'value': 'not_a_trip', 'baseMode': 'UNKNOWN', 'met_equivalent': 'UNKNOWN', 'kgCo2PerKm': 0}, {'value': 'other', 'baseMode': 'OTHER', 'met_equivalent': 'UNKNOWN', 'kgCo2PerKm': 0}], 'PURPOSE': [{'value': 'home'}, {'value': 'work'}, {'value': 'at_work'}, {'value': 'school'}, {'value': 'transit_transfer'}, {'value': 'shopping'}, {'value': 'meal'}, {'value': 'pick_drop_person'}, {'value': 'pick_drop_item'}, {'value': 'personal_med'}, {'value': 'access_recreation'}, {'value': 'exercise'}, {'value': 'entertainment'}, {'value': 'religious'}, {'value': 'other'}], 'translations': {'en': {'walk': 'Walk', 'e-auto_rickshaw': 'E-tuk tuk', 'auto_rickshaw': 'Tuk Tuk', 'motorcycle': 'Motorcycle', 'e-bike': 'E-bike', 'bike': 'Bicycle', 'drove_alone': 'Car Drove Alone', 'shared_ride': 'Car Shared Ride', 'e_car_drove_alone': 'E-Car Drove Alone', 'e_car_shared_ride': 'E-Car Shared Ride', 'taxi': 'Taxi/Loca/inDrive', 'bus': 'Bus', 'train': 'Train', 'free_shuttle': 'Free Shuttle', 'air': 'Airplane', 'not_a_trip': 'Not a trip', 'home': 'Home', 'work': 'To Work', 'at_work': 'At Work', 'school': 'School', 'transit_transfer': 'Transit transfer', 'shopping': 'Shopping', 'meal': 'Meal', 'pick_drop_person': 'Pick-up/ Drop off Person', 'pick_drop_item': 'Pick-up/ Drop off Item', 'personal_med': 'Personal/ Medical', 'access_recreation': 'Access Recreation', 'exercise': 'Recreation/ Exercise', 'entertainment': 'Entertainment/ Social', 'religious': 'Religious', 'other': 'Other'}, 'lo': {'walk': 'ດ້ວຍການຍ່າງ', 'e-auto_rickshaw': 'ລົດ 3 ລໍ້ໄຟຟ້າ ຫລື ຕຸກຕຸກໄຟຟ້າ', 'auto_rickshaw': 'ເດີນທາດ້ວຍ ລົດຕຸກຕຸກ ຫລື ລົດສາມລໍ້', 'motorcycle': 'ລົດຈັກ', 'e-bike': 'ວຍລົດຈັກໄຟຟ້າ', 'bike': 'ລົດຖີບ', 'drove_alone': 'ເດີນທາງ ດ້ວຍລົດໃຫ່ຍ ເຊີ່ງເປັນລົດທີ່ຂັບເອງ', 'shared_ride': 'ເດີນທາງດ້ວຍລົດໃຫ່ຍ ຮ່ວມກັບລົດຄົນອຶ່ນ', 'e_car_drove_alone': 'ດ້ວຍການຂັບລົດໄຟຟ້າໄປເອງ', 'e_car_shared_ride': 'ດ້ວຍການຈ້າງລົດໄຟຟ້າໄປ', 'taxi': 'ແທັກຊີ', 'bus': 'ລົດເມ', 'train': 'ລົດໄຟ', 'free_shuttle': 'ລົດຮັບສົ່ງຟຣີ', 'air': 'ຍົນ', 'not_a_trip': 'ບໍ່ແມ່ນການເດີນທາງ', 'home': 'ບ້ານ', 'work': 'ໄປເຮັດວຽກ', 'at_work': 'ຢູ່ບ່ອນເຮັດວຽກ', 'school': 'ໄປໂຮງຮຽນ', 'transit_transfer': 'ການຖ່າຍໂອນການເດີນທາງ', 'shopping': 'ຊອບປິ້ງ', 'meal': 'ອາຫານ', 'pick_drop_person': 'ໄປຮັບ ຫລື ສົນ ຄົນ', 'pick_drop_item': 'ໄປຮັບ ຫລື ສົ່ງສິນຄ້າ', 'personal_med': 'ໄປຫາໝໍ', 'access_recreation': 'ເຂົ້າເຖິງການພັກຜ່ອນ', 'exercise': 'ພັກຜ່ອນ/ອອກກຳລັງກາຍ', 'entertainment': 'ບັນເທີງ/ສັງຄົມ', 'religious': 'ຈຸດປະສົງທາງສາດສະໜາ', 'other': 'ອື່ນໆ'}}}), Parameter('use_imperial', bool, value=False), Parameter('sensed_algo_prefix', str, value='cleaned')]
Running at 2024-04-08T11:39:06.736910+00:00 with params [Parameter('year', int, value=2023), Parameter('month', int, value=5), Parameter('program', str, value='default'), Parameter('study_type', str, value='study'), Parameter('mode_of_interest', str), Parameter('include_test_users', bool, value=True), Parameter('dynamic_labels', dict, value={'MODE': [{'value': 'walk', 'baseMode': 'WALKING', 'met_equivalent': 'WALKING', 'kgCo2PerKm': 0}, {'value': 'e-auto_rickshaw', 'baseMode': 'MOPED', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.085416859}, {'value': 'auto_rickshaw', 'baseMode': 'MOPED', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.231943784}, {'value': 'motorcycle', 'baseMode': 'MOPED', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.113143309}, {'value': 'e-bike', 'baseMode': 'E_BIKE', 'met': {'ALL': {'range': [0, -1], 'mets': 4.9}}, 'kgCo2PerKm': 0.00728}, {'value': 'bike', 'baseMode': 'BICYCLING', 'met_equivalent': 'BICYCLING', 'kgCo2PerKm': 0}, {'value': 'drove_alone', 'baseMode': 'CAR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.22031}, {'value': 'shared_ride', 'baseMode': 'CAR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.11015}, {'value': 'e_car_drove_alone', 'baseMode': 'E_CAR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.08216}, {'value': 'e_car_shared_ride', 'baseMode': 'E_CAR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.04108}, {'value': 'taxi', 'baseMode': 'TAXI', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.30741}, {'value': 'bus', 'baseMode': 'BUS', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.20727}, {'value': 'train', 'baseMode': 'TRAIN', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.12256}, {'value': 'free_shuttle', 'baseMode': 'BUS', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.20727}, {'value': 'air', 'baseMode': 'AIR', 'met_equivalent': 'IN_VEHICLE', 'kgCo2PerKm': 0.09975}, {'value': 'not_a_trip', 'baseMode': 'UNKNOWN', 'met_equivalent': 'UNKNOWN', 'kgCo2PerKm': 0}, {'value': 'other', 'baseMode': 'OTHER', 'met_equivalent': 'UNKNOWN', 'kgCo2PerKm': 0}], 'PURPOSE': [{'value': 'home'}, {'value': 'work'}, {'value': 'at_work'}, {'value': 'school'}, {'value': 'transit_transfer'}, {'value': 'shopping'}, {'value': 'meal'}, {'value': 'pick_drop_person'}, {'value': 'pick_drop_item'}, {'value': 'personal_med'}, {'value': 'access_recreation'}, {'value': 'exercise'}, {'value': 'entertainment'}, {'value': 'religious'}, {'value': 'other'}], 'translations': {'en': {'walk': 'Walk', 'e-auto_rickshaw': 'E-tuk tuk', 'auto_rickshaw': 'Tuk Tuk', 'motorcycle': 'Motorcycle', 'e-bike': 'E-bike', 'bike': 'Bicycle', 'drove_alone': 'Car Drove Alone', 'shared_ride': 'Car Shared Ride', 'e_car_drove_alone': 'E-Car Drove Alone', 'e_car_shared_ride': 'E-Car Shared Ride', 'taxi': 'Taxi/Loca/inDrive', 'bus': 'Bus', 'train': 'Train', 'free_shuttle': 'Free Shuttle', 'air': 'Airplane', 'not_a_trip': 'Not a trip', 'home': 'Home', 'work': 'To Work', 'at_work': 'At Work', 'school': 'School', 'transit_transfer': 'Transit transfer', 'shopping': 'Shopping', 'meal': 'Meal', 'pick_drop_person': 'Pick-up/ Drop off Person', 'pick_drop_item': 'Pick-up/ Drop off Item', 'personal_med': 'Personal/ Medical', 'access_recreation': 'Access Recreation', 'exercise': 'Recreation/ Exercise', 'entertainment': 'Entertainment/ Social', 'religious': 'Religious', 'other': 'Other'}, 'lo': {'walk': 'ດ້ວຍການຍ່າງ', 'e-auto_rickshaw': 'ລົດ 3 ລໍ້ໄຟຟ້າ ຫລື ຕຸກຕຸກໄຟຟ້າ', 'auto_rickshaw': 'ເດີນທາດ້ວຍ ລົດຕຸກຕຸກ ຫລື ລົດສາມລໍ້', 'motorcycle': 'ລົດຈັກ', 'e-bike': 'ວຍລົດຈັກໄຟຟ້າ', 'bike': 'ລົດຖີບ', 'drove_alone': 'ເດີນທາງ ດ້ວຍລົດໃຫ່ຍ ເຊີ່ງເປັນລົດທີ່ຂັບເອງ', 'shared_ride': 'ເດີນທາງດ້ວຍລົດໃຫ່ຍ ຮ່ວມກັບລົດຄົນອຶ່ນ', 'e_car_drove_alone': 'ດ້ວຍການຂັບລົດໄຟຟ້າໄປເອງ', 'e_car_shared_ride': 'ດ້ວຍການຈ້າງລົດໄຟຟ້າໄປ', 'taxi': 'ແທັກຊີ', 'bus': 'ລົດເມ', 'train': 'ລົດໄຟ', 'free_shuttle': 'ລົດຮັບສົ່ງຟຣີ', 'air': 'ຍົນ', 'not_a_trip': 'ບໍ່ແມ່ນການເດີນທາງ', 'home': 'ບ້ານ', 'work': 'ໄປເຮັດວຽກ', 'at_work': 'ຢູ່ບ່ອນເຮັດວຽກ', 'school': 'ໄປໂຮງຮຽນ', 'transit_transfer': 'ການຖ່າຍໂອນການເດີນທາງ', 'shopping': 'ຊອບປິ້ງ', 'meal': 'ອາຫານ', 'pick_drop_person': 'ໄປຮັບ ຫລື ສົນ ຄົນ', 'pick_drop_item': 'ໄປຮັບ ຫລື ສົ່ງສິນຄ້າ', 'personal_med': 'ໄປຫາໝໍ', 'access_recreation': 'ເຂົ້າເຖິງການພັກຜ່ອນ', 'exercise': 'ພັກຜ່ອນ/ອອກກຳລັງກາຍ', 'entertainment': 'ບັນເທີງ/ສັງຄົມ', 'religious': 'ຈຸດປະສົງທາງສາດສະໜາ', 'other': 'ອື່ນໆ'}}}), Parameter('use_imperial', bool, value=False), Parameter('sensed_algo_prefix', str, value='cleaned')]

Mode_specific_metrics and energy_calculations are not being generated since this is STUDY.

Result:

Program/Study	Chart Type	Chart
Cortezebikes	Default Charts
Cortezebikes	All Stacked Charts
Cortezebikes	View Text
Laos	Default Charts
Laos	All Stacked Charts
Laos	View Text

Abby-Wheelis · 2024-04-08T15:28:28Z

Thank you for showing all of the images, this looks really good! I haven't looked at the code yet, but I noticed a couple of small things related to the charts:

the color-mode mapping is not consistent between all of the charts (like in the first image E-bike is blue in total trips but orange in total miles)
The 80th percentile chart seems to be the only one that does not have the "% of total trips" line in the bar labels, can you add it so it is consistent with the other charts?
In the "commute" chart, I think that it should say labeled 'To Work' by user in this case, since that is the label we're actually referring to, this is similar to the way that you'll select what purpose label means commute like this code was doing before you refactored - ideally the "commute" mode should show up in the purpose chart somewhere since its just based on the "work" mode in whatever labels (dynamic or default) that are being used

iantei · 2024-04-08T17:19:20Z

Thank you for showing all of the images, this looks really good! I haven't looked at the code yet, but I noticed a couple of small things related to the charts:

the color-mode mapping is not consistent between all of the charts (like in the first image E-bike is blue in total trips but orange in total miles)

The PR #117 is still under review, and yet to be merged. This will be addressed once we integrate this changes.

iantei · 2024-04-08T17:55:10Z

The 80th percentile chart seems to be the only one that does not have the "% of total trips" line in the bar labels, can you add it so it is consistent with the other charts?

Updated Chart for Under 80th percentile chart

iantei · 2024-08-16T19:30:28Z

@Abby-Wheelis @shankari
There has been a lot of changes introduced since this PR was last updated. Also, there are a few rollback commits here. So, instead of merging these with the newer updates, I have decided to incorporate these changes in a new PR #145.

iantei added 30 commits February 25, 2024 18:29

Function to create 100% Stacked Bar Chart

581b492

Add calculate_pct(labels, values) to calculate the proportion.

d6f1b82

Introduce a process_trip_data() to create a dataframe with cols Mode,…

5ddc396

… Count and Proportion.

Merge list of all dataframes into one.

1165562

Remove functions related with Pie Chart from plots.py.

2e9ad7d

Remove code and markdown blocks related with Pie Chart from generic_m…

a55e9f6

…etrics notebook.

Add sensed_algo_prefix for generic_metrics notebook.

7e71308

Added load_viz_notebook_sensor_inference_data() function in generic m…

45db963

…etrics notebook.

Filter for mode_of_interest.

ec9037b

Remove Generic Metrics markdown.

ebeb9dd

Markdown and code for 100% Stacked Bar Charts based on Number of Trips.

a1283bb

2. 100% Stacked Bar Charts representing 80th of number of trips.

441019c

3. 100% Stacked Bar Charts representing commute trips.

e53c0cc

Clean up.

eb3dcfc

4. 100% Stacked Bar Charts representing Distance by Mode.

e582011

5. 100% Stacked Bar Charts representing Count by Purpose.

5fedbb0

6. 100% Stacked Bar Charts representing Replaced mode.

f31e43e

Update markdown for 6.

7b6cef2

7. 100% Stacked Bar Charts representing Trip Distance based on Replac…

428982c

…ed mode.

Update Markdown text.

119d707

Copied the bar plots from generic_metrics_sensed notebook to generic_…

1c5e00a

…metrics notebook.

Copied the bar plots from mode_specific_metrics notebook to generic_m…

4d58d4c

…etrics notebook.

Added Store alt text function for stacked bar charts. Added html tabl…

7f31c5d

…e structure.

Added alt_text for stacked bar charts in generic metric notebook.

3388258

Retrieve htmlFile in index.html.

11345f6

Update data-sizex to 8 from 4 for ntrips_mode_confirm.

2f7b0da

Add X and Y axis labels.

c17027d

Update the quality text for sensed in scaffolding.py

5d83605

Update the default loaded configs.

f91f379

Remove older file names and option values associated with it. Update …

339f0cd

…data-sizex to 10 from 4 to adjust horizonatal length of the stacked bar charts. Update with new option values.

iantei added 21 commits April 8, 2024 02:38

Update the metrics options to list three options for replaced mode.

e76733b

1. Update the text from More Info to View as Text. 2. Show the View a…

0dd48e9

…s Text button for all 100% Stacked Bar Charts.

Introduce new function for filter_inferred_trips.

d0d19ba

Introduce expand_inferredlabels function.

a25dfb7

Introduce new quality data functions to return the values for the bar…

2a98e7a

… description.

1. Remove old implementation of load_viz_notebook_data, and introduce…

a8c4529

… process_notebook_data function.

Update load_viz_notebook_data with unified form for both inferred and…

e5deba0

… confirmed trips.

1. Update the load_viz_notebook_data() to return values_dict 2. Updat…

1ee4c94

…e the users according to the include_test_users.

1. Introduce data_eb_inferred. 2. Return the value for mode_dict. 3.U…

8d676aa

…pdate different strings for the 100% Stacked bar charts Y-axis labels.

1. Update inferred bar. 2. Update the text description for the Y-axis…

83ab16d

… bar. 3. Shorten the plot title description.

For Number of Trips for Replaced Mode: 1. Update inferred bar. 2. Upd…

98c5a28

…ate the text description for the Y-axis bar. 3. Shorten the plot title description.

Update the cutoff to consider just expanded_ct_sensed. Update process…

5b83d3f

…_data_for_cutoff with cutoff argument.

For 80th percentile number of trips: 1. Update inferred bar. 2. Updat…

b8fc519

…e the text description for the Y-axis bar. 3. Shorten the plot title description.

For commute trips: 1. Update inferred bar. 2. Update the text descrip…

5db935a

…tion for the Y-axis bar. 3. Shorten the plot title description.

For Total Trip Length covered by each mode: 1. Update inferred bar. 2…

16df1af

…. Update the text description for the Y-axis bar. 3. Shorten the plot title description.

For Total Trip Length covered by each mode in Land: 1. Update inferre…

091324d

…d bar. 2. Update the text description for the Y-axis bar. 3. Shorten the plot title description.

For Total Trip Length covered by replaced mode: 1. Update inferred ba…

735f32a

…r. 2. Update the text description for the Y-axis bar. 3. Shorten the plot title description.

For number of trips for each purpose: 1. Remove the mode_specific com…

9fa7652

…putation. 2. Update inferred bar. 3. Update the text description for the Y-axis bar. 4. Shorten the plot title description.

Add 100% stacked bar chart for number of trips for each purpose by re…

2885bfa

…placed mode.

Update the value from total_trip_ to total_trip_length_ to match the …

97b05ae

…file name.

Update the return values for updated load_viz_notebook_data().

c73583d

Adding % of total trips for 80th percentile charts.

7195dcc

iantei changed the base branch from main to fix_start_notebook_path April 18, 2024 17:28

iantei changed the base branch from fix_start_notebook_path to main April 18, 2024 17:28

Abby-Wheelis mentioned this pull request May 5, 2024

Change from pie charts to 100% stacked bar chart #123

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Introduce inferred labels in stacked bar charts #128

Introduce inferred labels in stacked bar charts #128

iantei commented Apr 8, 2024

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Introduce inferred labels in stacked bar charts #128

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Introduce inferred labels in stacked bar charts #128

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