trough
Example
Features
- Download Madrigal TEC, OMNI and DMSP SSUSI data
- Process datasets into more convenient
xarraydata structures and save as NetCDF - Automatically label main ionospheric trough
Usage
- Clone Repo
- create conda environment:
conda env create -f environment.yml -n trough python=3.9 conda activate troughpip install apexpy- if you get a numpy error when you try to import apexpy:
pip install --upgrade nump - install trough with
pip install -e . - copy
config.json.example-->config.jsonand change any options you want - run with
python -m trough config.json - wait for it to finish (can take several days if you are running 5+ years)
- add
import troughin your code and access the data usingtrough.get_data
Config
Main Options
| Config Option | Definition |
|---|---|
| base_dir | base directory of trough downloads and processing, directories for downloading and processing will be created from here |
| madrigal_user_name | name supplied to MadrigalWeb |
| madrigal_user_email | email supplied to MadrigalWeb |
| madrigal_user_affil | affiliation supplied to MadrigalWeb |
| nasa_spdf_download_method | "http" or "ftp" (default) |
| lat_res | latitude resolution of processed TEC maps (degrees Apex magnetic latitude) |
| lon_res | longitude resolution of processed TEC maps (degrees Apex magnetic longitude) |
| time_res_unit | time resolution units (passed to np.timedelta64) |
| time_res_n | time resolution in units specified above (passed to np.timedelta64) |
| script_name | which script to run, available scripts are in trough/scripts.py |
| start_date | start date of interval (YYYYMMDD, YYYYMMDD_hh, YYYYMMDD_hhmm, or YYYYMMDD_hhmmss) |
| end_date | end date of interval, see "start_date" for format |
| keep_download | whether or not to keep the downloaded files (not recommended) |
| trough_id_params | trough labeling algorithm parameters, see below |
Trough Labeling Options
| Config Option | Definition |
|---|---|
| bg_est_shape | background estimation filter size in pixels [time, latitude, longitude] |
| model_weight_max | maximum value of L2 regularization before multiplication by coefficient l2_weight |
| rbf_bw | RBF bandwidth, number of pixels to half weight |
| tv_hw | total variation horizontal weight |
| tv_vw | total variation vertical weight |
| l2_weight | L2 regularization coefficient |
| tv_weight | TV regularization coefficient |
| perimeter_th | minimum perimeter for a connected component in a label image |
| area_th | minimum area for a connected component in a label image |
| threshold | score threshold below which a pixel is not labeled as MIT |
| closing_rad | radius for disk structuring element passed to skimage.morphology.binary_closing |