## utdf2gmns: Introduction
This open-source package is a tool to convert utdf file to GMNS format.
## Required Data Input Files:
* [X] UTDF.csv
* [X] node.csv (GMNS format)
* [X] movement.csv (GMNS format)
## **Produced outputs**
**If input folder have UTDF.csv only, outputs are:**
* A dictionary store utdf data with keys: Networks, Node, Links, Timeplans, Lanes, and utdf_intersection_geo
* A file named utdf2gmns.pickle to store dictionary object.
**If input folder have extra node.csv and movement.csv, outputs are:**
* Two files named movement_utdf.csv and intersection_utdf.csv
* A file named utdf2gmns.pickle to store dictionary object.
## **Package dependencies**:
* [X] geocoder==1.38.1
* [X] numpy==1.23.3
* [X] openpyxl==3.0.10
* [X] pandas==1.4.4
## Data Conversion Steps:
Step 1: Read UTDF.csv file and perform geocoding, then produce utdf_geo, utdf_lane, and utdf_phase_timeplans.
Step 2: Match four files (utdf_geo, node, utdf_lane, utdf_pahse_timeplans, movement) to produce movement_utdf
## Installation
`pip install UTDF2GMNS`
## Example
```python
import utdf2gmns as ug
import pandas as pd
if__name__=="main":
city =" Bullhead City, AZ"
# option= 1, generate movement_utdf.csv directly
# option= 2, generate movement_utdf.csv step by step (more flexible)
option =1
if option ==1:
# NOTE: Option 1, generate movement_utdf.csv directly
path =r"C:\Users\roche\Desktop\coding\data_bullhead_seg4" # the fold contain UTDF.csv, node.csv and movement.csv
res = ug.generate_movement_utdf(path, city,isSave2csv=True)
if option ==2:
# NOTE: Option 2, generate movement_utdf.csv step by step (more flexible)
path_utdf =r"C:\Users\roche\Desktop\coding\data_bullhead_seg4\UTDF.csv"
path_node =r"C:\Users\roche\Desktop\coding\data_bullhead_seg4\node.csv"
path_movement =r"C:\Users\roche\Desktop\coding\data_bullhead_seg4\movement.csv"
# Step 1: read UTDF.csv
utdf_dict_data = ug.generate_utdf_dataframes(path_utdf, city)
# Step 1.1: get intersection data from UTDF.csv
df_intersection = utdf_dict_data["utdf_intersection"]
# Step 1.2: geocoding intersection data
df_intersection_geo = ug.generate_coordinates_from_intersection(df_intersection)
# Step 2: read node.csv and movement.csv
df_node = pd.read_csv(path_node)
df_movement = pd.read_csv(path_movement)
# Step 3: match intersection_geo and node
df_intersection_node = ug.match_intersection_node(df_intersection_geo, df_node)
# Step 4: match movement and intersection_node
df_movement_intersection = ug.match_movement_and_intersection_node(df_movement, df_intersection_node)
# Step 5: match movement and utdf_lane
df_movement_utdf_lane = ug.match_movement_utdf_lane(df_movement_intersection, utdf_dict_data)
# Step 6: match movement and utdf_phase_timeplans
df_movement_utdf_phase = ug.match_movement_utdf_phase_timeplans(df_movement_utdf_lane, utdf_dict_data)
```
## TODO LIST
* [X] Print out how many intersections being geocoded.
* [ ] Print out how many movements being matched or not matched for signalized intersecton nodes in osm2gmns files.
* [ ] Add cycle length and green time for each movement.
* [ ] Check reasonable capacity.
* [ ] Check each movement is reasonable (like 15s of green time...). other attributes.
* [ ] Check number of lanes correctness between osm2gmns file and synchro file per movements.
* [X] Print out check log.
* [X] Number of lanes of the movements from synchro file.
* [ ] Add signal info to micre-link.csv
* [X] Add function to verify whether geocoded for utdf_geo
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"description": "## utdf2gmns: Introduction\r\n\r\nThis open-source package is a tool to convert utdf file to GMNS format.\r\n\r\n## Required Data Input Files:\r\n\r\n* [X] UTDF.csv\r\n* [X] node.csv (GMNS format)\r\n* [X] movement.csv (GMNS format)\r\n\r\n## **Produced outputs**\r\n\r\n**If input folder have UTDF.csv only, outputs are:**\r\n\r\n* A dictionary store utdf data with keys: Networks, Node, Links, Timeplans, Lanes, and utdf_intersection_geo\r\n* A file named utdf2gmns.pickle to store dictionary object.\r\n\r\n**If input folder have extra node.csv and movement.csv, outputs are:**\r\n\r\n* Two files named movement_utdf.csv and intersection_utdf.csv\r\n* A file named utdf2gmns.pickle to store dictionary object.\r\n\r\n## **Package dependencies**:\r\n\r\n* [X] geocoder==1.38.1\r\n* [X] numpy==1.23.3\r\n* [X] openpyxl==3.0.10\r\n* [X] pandas==1.4.4\r\n\r\n## Data Conversion Steps:\r\n\r\nStep 1: Read UTDF.csv file and perform geocoding, then produce utdf_geo, utdf_lane, and utdf_phase_timeplans.\r\n\r\nStep 2: Match four files (utdf_geo, node, utdf_lane, utdf_pahse_timeplans, movement) to produce movement_utdf\r\n\r\n## Installation\r\n\r\n`pip install UTDF2GMNS`\r\n\r\n## Example\r\n\r\n```python\r\nimport utdf2gmns as ug\r\nimport pandas as pd\r\nif__name__==\"main\":\r\n city =\" Bullhead City, AZ\"\r\n # option= 1, generate movement_utdf.csv directly\r\n # option= 2, generate movement_utdf.csv step by step (more flexible)\r\n\r\n option =1\r\n\r\n if option ==1:\r\n # NOTE: Option 1, generate movement_utdf.csv directly\r\n path =r\"C:\\Users\\roche\\Desktop\\coding\\data_bullhead_seg4\" # the fold contain UTDF.csv, node.csv and movement.csv\r\n res = ug.generate_movement_utdf(path, city,isSave2csv=True)\r\n\r\n if option ==2:\r\n # NOTE: Option 2, generate movement_utdf.csv step by step (more flexible)\r\n path_utdf =r\"C:\\Users\\roche\\Desktop\\coding\\data_bullhead_seg4\\UTDF.csv\"\r\n path_node =r\"C:\\Users\\roche\\Desktop\\coding\\data_bullhead_seg4\\node.csv\"\r\n path_movement =r\"C:\\Users\\roche\\Desktop\\coding\\data_bullhead_seg4\\movement.csv\"\r\n\r\n # Step 1: read UTDF.csv\r\n utdf_dict_data = ug.generate_utdf_dataframes(path_utdf, city)\r\n\r\n # Step 1.1: get intersection data from UTDF.csv\r\n df_intersection = utdf_dict_data[\"utdf_intersection\"]\r\n\r\n # Step 1.2: geocoding intersection data\r\n df_intersection_geo = ug.generate_coordinates_from_intersection(df_intersection)\r\n\r\n # Step 2: read node.csv and movement.csv\r\n df_node = pd.read_csv(path_node)\r\n df_movement = pd.read_csv(path_movement)\r\n\r\n # Step 3: match intersection_geo and node\r\n df_intersection_node = ug.match_intersection_node(df_intersection_geo, df_node)\r\n\r\n # Step 4: match movement and intersection_node\r\n df_movement_intersection = ug.match_movement_and_intersection_node(df_movement, df_intersection_node)\r\n\r\n # Step 5: match movement and utdf_lane\r\n df_movement_utdf_lane = ug.match_movement_utdf_lane(df_movement_intersection, utdf_dict_data)\r\n\r\n # Step 6: match movement and utdf_phase_timeplans\r\n df_movement_utdf_phase = ug.match_movement_utdf_phase_timeplans(df_movement_utdf_lane, utdf_dict_data)\r\n\r\n```\r\n\r\n## TODO LIST\r\n\r\n* [X] Print out how many intersections being geocoded.\r\n* [ ] Print out how many movements being matched or not matched for signalized intersecton nodes in osm2gmns files.\r\n* [ ] Add cycle length and green time for each movement.\r\n* [ ] Check reasonable capacity.\r\n* [ ] Check each movement is reasonable (like 15s of green time...). other attributes.\r\n* [ ] Check number of lanes correctness between osm2gmns file and synchro file per movements.\r\n* [X] Print out check log.\r\n* [X] Number of lanes of the movements from synchro file.\r\n* [ ] Add signal info to micre-link.csv\r\n* [X] Add function to verify whether geocoded for utdf_geo\r\n",
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