Rewrote instructions to make more clear based on feedback.

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).