Metadata-Version: 1.1
Name: biotracks
Version: 0.2.0b1
Summary: Data package representation for cell migration tracking data
Home-page: https://github.com/CellMigStandOrg/biotracks
Author: paola masuzzo
Author-email: paola.masuzzo@ugent.be
License: BSD
Description: A datapackage representation of cell migration-derived tracking files.
        ******************************************************************************
        
        .. image:: https://travis-ci.org/CellMigStandOrg/biotracks.svg?branch=master
            :target: https://travis-ci.org/CellMigStandOrg/biotracks
        
        .. image:: https://badge.fury.io/py/biotracks.svg
            :target: https://badge.fury.io/py/biotracks
        
        This Python project aims to create a simple Python package to produce data packages of cell migration tracking files. The final goal is to have a uniform, standardized way to represent these data, as in `Frictionless Data <http://frictionlessdata.io/>`_ and `Data Packages <http://frictionlessdata.io/data-packages/>`_ .
        
        Steps to follow to use the package:
        
        + **step 1** - Install the package (note it's Python 3 only at the moment):
        
        .. code-block::
        
           python setup.py install
        
        + **step 2** - create a ``biotracks.ini`` configuration file and place it in the same directory as your tracking file. The file must be structured as follows:
        
        .. code-block::
        
          [TOP_LEVEL_INFO]
          author = the author of the dp
          title = a title describing the dp
          name = a name for the dp
          author_institute = the insitute of the author
          author_email = a valid email address
        
          [TRACKING_DATA]
          x_coord_cmso = the column name pointing to the x coordinate
          y_coord_cmso = the column name pointing to the y coordinate
          z_coord_cmso = the column name pointing to the z coordinate
          frame_cmso = the column name pointing to the frame information
          object_id_cmso = the object identifier
          link_id_cmso = the link identifier
        
        
        +  **step 3** - move to the ``scripts`` directory and run:
        
        .. code-block:: python
        
          python create_dpkg.py your_tracking_file
        
        this will create a **dp** directory containing:
        
        + a *csv* file for the **objects** (i.e. cells)
        + a *csv* file for the **links** (i.e. a linear collection of objects)
        + and a **dp.json** file containing the *json* schemas of the two *csv* files.
        
        
        This last file will look something like this:
        
        .. code-block:: json
        
          {
              "resources": [{
                  "name": "objects_table",
                  "schema": {
                      "primaryKey": "SPOT_ID",
                      "fields": [{
                          "name": "SPOT_ID",
                          "title": "",
                          "description": "",
                          "constraints": {
                              "unique": true
                          },
                          "type": "integer",
                          "format": "default"
                      }, {
                          "type": "integer",
                          "name": "FRAME",
                          "title": "",
                          "format": "default",
                          "description": ""
                      }, {
                          "type": "number",
                          "name": "POSITION_X",
                          "title": "",
                          "format": "default",
                          "description": ""
                      }, {
                          "type": "number",
                          "name": "POSITION_Y",
                          "title": "",
                          "format": "default",
                          "description": ""
                      }]
                  },
                  "path": "objects.csv"
              }, {
                  "name": "links_table",
                  "schema": {
                      "foreignKeys": [{
                          "fields": "SPOT_ID",
                          "reference": {
                              "resource": "objects_table",
                              "fields": "SPOT_ID",
                              "datapackage": ""
                          }
                      }],
                      "fields": [{
                          "type": "integer",
                          "name": "LINK_ID",
                          "title": "",
                          "format": "default",
                          "description": ""
                      }, {
                          "type": "integer",
                          "name": "SPOT_ID",
                          "title": "",
                          "format": "default",
                          "description": ""
                      }]
                  },
                  "path": "links.csv"
              }],
              "name": "CMSO_tracks",
              "title": "A CMSO data package representation of cell tracking data",
              "author_email": "paola.masuzzo@email.com",
              "author_institute": "VIB",
              "author": "paola masuzzo"
          }
        
        Then, the datapackage is pushed to a **pandas** dataframe. At the moment, this dataframe is used to create simple visualizations of links and turning angles.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: BSD License
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Intended Audience :: Science/Research
