From c93c5caa40ab8fe10aec1d655db40aaeffd550bd Mon Sep 17 00:00:00 2001 From: Joe Flood Date: Thu, 15 Aug 2024 09:23:22 -0700 Subject: [PATCH] Rewrote instructions to make more clear based on feedback. --- README.md | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 0bf9879..9c522c8 100644 --- a/README.md +++ b/README.md @@ -20,13 +20,12 @@ A dictionary of the settings in config.yaml can be found [here](settings_diction ## To easily run all steps 1. Gain access to the database RP2025 on the server DGISWSQL22 from GIS. -2. Create a directory to run in. Create folders called "parking_inputs" and "parking_outputs." +2. Create a directory to run in and clone the repo into the directory. Create folders in the clone called "parking_inputs" and "parking_outputs." 3. Copy the the files auxiliary.csv and micro_mobility.csv from T:\ABM\data\sr15_inputs\landuse_prep into the directory. 4. Copy the contents of T:\ABM\data\sr15_inputs\landuse_prep\parking_inputs into the parking_inputs folder ("old" folder not needed). 5. Copy ParkingPolicies_[YEAR].csv from T:\ABM\data\sr15_inputs\landuse_prep\parking_outputs into the parking_outputs folder. -6. Clone the repo into the directory. -7. Open up config.yaml and do a find and replace searching for "T:\ABM\data\sr15_inputs\landuse_prep" and replacing them with the directory you created. -8. Within config.yaml, update `scenario_year` and `ff_year` to be the year of the scenario that you're preparing the land use for. -9. Edit the setting `EF_dir` and `base_lu` to be the directory with the outputs from Estimates and Forecasts that the land use prep tool will process. -10. Open Anaconda prompt, navigate into the cloned repo and create an Anaconda environment using the environment.yml file. -11. Activate the environment and run run_landuse_preprocessing.bat. The files will be created in the specified `output_dir` (the clone of the repo if that is unchanged). +6. Open up config.yaml and do a find and replace searching for "T:\ABM\data\sr15_inputs\landuse_prep" and replacing them with the directory you created. +7. Within config.yaml, update `scenario_year` and `ff_year` to be the year of the scenario that you're preparing the land use for. +8. Edit the setting `EF_dir` and `base_lu` to be the directory with the outputs from Estimates and Forecasts that the land use prep tool will process. +9. Open Anaconda prompt, navigate into the cloned repo and create an Anaconda environment using the environment.yml file. +10. Activate the environment and run run_landuse_preprocessing.bat. The files will be created in the specified `output_dir` (the clone of the repo if that is unchanged).