Metadata-Version: 2.1
Name: floweaver-path
Version: 0.0.3
Summary: floweaver extension to handle the path visualization
Home-page: https://github.com/fullflu/floweaver-path
Author: fullflu
Author-email: k.takayama0902@gmail.com
License: MIT
Description: # floweaver-path
        
        ## Description
        
        ![Demo](https://github.com/fullflu/floweaver-path/blob/master/demo/floweaver_path_demo.gif)
        
        This library (floweaver-path) is an extension of the [floweaver](https://sankeyview.readthedocs.io/en/latest/) to handle the visualization of paths that pass through a selected node.
        
        We focus on the visualization of longitudinal data.
        
        The idea of our visualization is based on [pathSankey](https://bl.ocks.org/jeinarsson/e37aa55c3b0e11ae6fa1), that is an extension of [d3-sankey](https://github.com/d3/d3-sankey).
        
        The color of paths that pass through a selected node is yellow-green (highlighted), and that of other paths is gray.
        
        You can interactively select a node by using dropdowns in jupyter notebook.
        
        We have two technical contributions to the field of visualization using Sankey diagrams.
        
        One is to extend the layer number:
        - Ordinary Sankey diagrams can only visualize paths between 2 layers.
        - pathSankey can only visualize paths between 3 layers.
        - We can visualize the comparison of paths between two layers before and after (up to 5 layers).
        
        The other is to create a notebook that can interact with users. We integrate several functions of ipywidgets into floweaver.
        
        ## Requirement
        
        ### installation using docker
        - docker (installs two libraries: floweaver(==2.0.0a5), ipysankeywidget==0.2.5)
        - input file (`*.csv, *.pickle or *.xlsx` should be put in `interaction/data` directory if you do not specify the data directory)
        
        ### installation using pip
        - pip
        - python (3.6)
        - input file (`*.csv, *.pickle or *.xlsx` should be put in `interaction/data` directory if you do not specify the data directory)
        
        Two libraries (floweaver>=2.0.0a5, ipysankeywidget>=0.2.5) will be installed.
        
        ## Setup (when you install using docker)
        
        ### build
        
        `scripts/build`
        
        ### run notebook
        
        `scripts/run-notebooks`
        
        Run docker, and connect `interaction` to `work`.
        
        Data and notebooks are shared between a docker image and your local system.
        
        ### use notebooks in browser
        
        Open a new browser tab and type `localhost: 10001` in the URL.
        
        Copy and paste a token to use notebooks. The token you can use is displayed in your terminal as follows:
        
        `http://(<id> or 127.0.0.1):8888/?token=<token>`
        
        ## Setup (when you install using pip)
        
        You can install floweaver_path by the ordinary installation command
        
        ```
        pip install floweaver_path
        ```
        
        You might need to execute the following commands
        
        ```
        jupyter nbextension install --py widgetsnbextension --user
        jupyter nbextension install --py ipysankeywidget --user
        jupyter nbextension enable widgetsnbextension --user --py
        jupyter nbextension enable ipysankeywidget --user --py
        ```
        
        ## Usage
        
        ### prepare data
        
        If you install floweaver_path using docker, you need to put your local file under the `interaction` directory. You can use the jupyter notebook to upload your local file. You can also directly put your local file under the `interaction` directory.
        
        If you install floweaver_path using pip, you do not need to move your local file because you can specify the all local paths.
        
        We focus on longitudinal data. The format of your file should be as follows:
        ```
           index  date  value1  value2
        0        1      2016/04/01   1   3
        1        2      2016/10/01   3   2
        2        1      2016/04/01   4   1
        ```
        
        - index: This variable is handled as user id.
        - date: This variable is handled as the date and visualized in the x-axis (in terms of sankey diagrams, `layer`). Data should not be duplicated with respect to a pair of (index, date).
        - value[n] (<img src="https://latex.codecogs.com/gif.latex?n&space;\in&space;\mathbb{N}">): These variables are handled as target variables. One of those variables is visualized in the y-axis (in terms of sankey diagrams, `node` in each layer).
        
        The name of each variable can be changed between files. You can select which variable to use interactively.
        
        Note that we support three types of file extensions: `.csv`, `.xlsx` and `.pickle`
        Please check the details of the data by loading `data/template_data.csv`.
        
        ### launch a working notebook
        
        The template notebook (`template.ipynb`) should not be changed.
        I recommend you to duplicate the template notebook and work on the duplicated notebook.
        
        ### call the visualizer
        
        You can import the visualizer and call it as follows.
        
        ```
        from floweaver_path import visualizer
        visualizer()
        ```
        
        The `visualizer` function has 5 arguments:
        - data_dir (default='./data'): where you put your local files
        - width (default=1070): the width of visualized figures
        - height (default=500): the width of visualized figures
        - target_color (default='yellowgreen'): the color of paths that pass through a selected node.
        - base_color (default='gray'): the width of paths that do not pass through a selected node.
        
        
        ### select a target node
        
        We prepare 7 dropdowns for users to interact with floweaver.
        - multiple display?: whether this library displays multiple images or not.
        - file path: data to be analyzed.
        - index column: column name that contains id information (e.g., user_id).
        - date column: column name that contains date information (handled as a `layer` and visualized in the x-axis).
        - target varible: column name that you want to analyze (handled as a `node` in each layer and visualized in the y-axis).
        - target date: value name that you want to select as the value of your target date.
        - target value: value name that you want to select as the value of your target variable.
        
        The dependence between the dropdowns is updated as soon as you select each value.
        
        
        ## Authors
        
        - [@fullflu](https://github.com/fullflu) proposed to create this library and prepared basic scripts.
        - [@adamist](https://github.com/adamist) created `Dockerfile`, `build` and `run-notebook` scripts.
        
        
        ## Contributors
        
        Please feel free to create issues or to contribute to floweaver-path!
        It would be useful to contribute to the original [floweaver](https://github.com/ricklupton/floweaver/blob/master/CONTRIBUTING.md) library.
        
        ## License
        
        [MIT](https://github.com/fullflu/floweaver-path/blob/master/LICENSE)
        
        
        ## Structure
        
        ```
        ├── Dockerfile
        ├── LICENSE
        ├── README.md
        ├── demo
        │   └── floweaver_path_demo.gif
        ├── interaction
        │   ├── data
        │   │   └── template_data.csv
        │   └── template.ipynb
        ├── requirements.txt
        ├── scripts
        │   ├── build
        │   └── run-notebook
        ├── setup.py
        ├── src
        │   ├── floweaver_path
        │   │   ├── __init__.py
        │   │   ├── lib
        │   │   │   ├── __init__.py
        │   │   │   ├── ts_sankey.py
        │   │   │   └── utils.py
        │   │   └── visualizer.py
        │   └── template
        │       ├── data
        │       │   └── template.csv
        │       └── notebooks
        │           └── template.ipynb
        └── tests
            ├── test_extract_files.py
            └── test_load_file.py
        ```
Keywords: floweaver-path
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
