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Generate colored graphs of time-series data
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timelag-graphgen
.gitignore
LICENSE
README.md
render_wave_3.sh
render_wave_3_mod.sh
requirements.txt
wave3_states.txt

README.md

timelag-graphgen

Generate colored graphs/animations of time-series data

Installation

This program uses python 3. To install all of the dependencies, run:

pip install -r requirements.txt --user

Usage

Call python timelag-graphgen/main.py ARGS, where ARGS are

  • -i INPUT_FILE (required)
    • The input data file to use
  • -f FORMAT (required)
    • The file format that the input data file is in
      • weekss - Single state, weekly (csv format) - don't know if this still works?
        • Start of interval
        • Time
        • Entries_KIN_t0
        • Exits_KIN_t0
        • Entries_FC_t0
        • Exits_FC_t0
        • Entries_CC_t0
        • Exits_CC_t0
      • dayss - Single state, daily - do not use
      • dayssp - Single state, daily, preprocessed - output of preprocess scripts
      • weekssp - Single state, weekly, preprocessed - output of preprocess scripts
      • weekms - Multistate week file (stata format)
        • state
        • county
        • caretype
        • year
        • admitcount
        • exitcount
        • week2
        • week4
        • geo
        • geo1
      • dayms - Multistate day file (csv format, | delimited)
        • date
        • state
        • county
        • caretype
        • admitcount
        • exitcount
        • year
  • -s STATE_ID (required)
    • The ID of the state (e.g. CA)
  • --coloring COLORING (required)
    • The coloring type to use; can be one of:
      • linear_all_time
      • linear_seasonal
      • discrete_months
      • discrete_months_split_markers
      • discrete_months_polygons
  • --limit LIMIT (optional, defaults to autoscale)
    • The maximum limit to use
  • --caretype CARETYPE (required)
    • The caretype to view
  • --render OUTPUT_FILE (optional, defaults to none)
    • Whether to render to an output file, and if so, where
    • If none, then will show interactive animation
    • If mp4, will render animation to mp4 output file
    • If image (only png tested), will render final step to image file
  • --lag LAG_LEN (optional, defaults to 1)
    • The number of lag steps to use, always in the current time unit
    • e.g. for weekly data --lag 1 means a lag of 1 week, for daily data it means lag of 1 day
  • --dropyearly (optional, defaults to false)
    • Whether to drop all data more than a year before the current animation time
  • --lowess (optional, defaults to false)
    • Whether to use the residuals from lowess smoothing
  • --ppf POINTS_PER_FRAME (optional, defaults to false)
    • Points to animate per frame - can vastly help in reducing render times (7 for daily data recommended)

Other useful files

  • render_wave_3.sh: script used to render wave 3, might be useful to look over
  • preprocess_multi.py and preprocess_mult_daily.py: preprocess multistate files into state-level files
    • Use weekms and dayms files, respectively
    • arg1: input file
    • arg2: output directory
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