Sensospot Data Parser
=====================

Parsing the numerical output from Sensovation Sensospot image analysis.

## Example:

```python

    import sensospot_data

    # read the raw data of a folder
    raw_data = sensospot_data.parse_folder(<path to results directory>)

    sorted(raw_data.columns) == [
        'Bkg.Area', 'Bkg.Mean', 'Bkg.Median', 'Bkg.StdDev', 'Bkg.Sum', 
        'Exposure.Id', 
        'Parameters.Channel', 'Parameters.Time', 
        'Pos.Id', 'Pos.Nom.X', 'Pos.Nom.Y', 'Pos.X', 'Pos.Y', 
        'Spot.Area', 'Spot.Diameter', 'Spot.Found', 'Spot.Mean', 'Spot.Median', 'Spot.Saturation', 'Spot.StdDev', 'Spot.Sum', 
        'Well.Column', 'Well.Name', 'Well.Row']
    ]
```

## Avaliable functions:

from .parser import parse_file, parse_folder  # noqa: F401
 - **parse_folder(path_to_folder)**
   Searches the folder for parsable .csv files, parses them into one big pandas
   data frame and will add additional meta data from parameters folder, if 
   it is present.
- **parse_file(path_to_csv_file)**
   Parses the csv file into a pandas data frame and will add additional some
   meta data from the file name. Is internally also used by `parse_folder()`


## CLI

For the (propably) most important function, there is even a cli command
```sh
Usage: parse_sensospot_data [OPTIONS] SOURCE

Arguments:
  SOURCE:             Folder with Sensospot measurement

Options:
  -o, --outfile TEXT  Output file name, relative to SOURCE, defaults to 'collected_data.csv'
  --help              Show this message and exit.
```

## Development

To install the development version of Sensovation Data Parser:

    git clone https://git.cpi.imtek.uni-freiburg.de/holgi/sensospot_data.git

    # create a virtual environment and install all required dev dependencies
    cd sensospot_data
    make devenv

To run the tests, use `make tests` (failing on first error) or `make coverage` for a complete report.