sensospot_parser/README.md

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) == [
        'Analysis.Name', 
        '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'
    ]
```

## Constants

There is a `columns` module available, providing constans that define the column names.

```python

    import sensospot_data

    sensospot_data.columns.ANALYSIS_NAME == "Analysis.Name"
```


## Avaliable public functions:

from sensospot_data import parse_file, parse_folder  # noqa: F401
 - **parse_folder(path_to_folder)**
   Searches the folder for parsable Sensospot .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 a Sensospot csv file into a pandas data frame and will add some additional
   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: sensospot_parse [OPTIONS] SOURCE

Arguments:
  SOURCE:             Folder with Sensospot measurement

Options:
  -o, --outfile TEXT  Output file name, use a dash '-' for stdout, default:
                      'collected_data.csv'
  -q, --quiet         Ignore Sanity Check
  -r, --recurse       Recurse into folders one level down
  --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.