Initialization and Dependencies

__init__.py

"""
A package for analysis, statistics and visualization of Calcium Imaging data,
specifically from including from Inscopix.
"""
from __future__ import annotations

import os
from inspect import getsourcefile

import yaml

from data.containers import CalciumData
from data.data_utils.file_handler import FileHandler
from graphs import *

__location__ = os.path.abspath(getsourcefile(lambda: 0))
ROOT_DIR = os.path.dirname(__location__)

_hard_dependencies = ["numpy",
                      "pandas"]  # let users know if theyre missing any vital deps
_missing_dependencies = []

for _dependency in _hard_dependencies:
    try:
        __import__(_dependency)
    except ImportError as _e:
        _missing_dependencies.append(f"{_dependency}: {_e}")

if _missing_dependencies:
    raise ImportError(
        "Unable to import required dependencies:\n" + "\n".join(_missing_dependencies)
    )
del _hard_dependencies, _dependency, _missing_dependencies


class Params:
    """@DynamicAttrs"""

    def __init__(self, parameter_dict):
        for key in parameter_dict:
            setattr(self, key, parameter_dict[key])


def get_parameters():
    with open(os.path.join(ROOT_DIR, 'params.yaml'),
              'rb') as f:
        parameters = yaml.safe_load(f.read())
    return Params(parameters)


def get_data():
    params = get_parameters()
    filehandler = FileHandler(
        params.Session['animal'],
        params.Session['date'],
        params.Directory['data'],
        params.Filenames['traces'],
        params.Filenames['events'],
        params.Filenames['gpio'],
        params.Filenames['eating'],
    )
    return CalciumData(filehandler,
                       doeating=params.Filenames['doeating'],
                       doevents=params.Filenames['doevents'],
                       color_dict=params.Colors,
                       adjust=params.Filenames['adjust'],
                       )


__doc__ = """
canalysis - A library for processing, manipulating, combining and visualizing Calcium 
Imaging datasets
=====================================================================
**canalysis** is a Python package that helps to process multivariate datasets. Calcium 
Imaging data can take many forms, generally 
you have a .csv/excel file with traces (values of how bright group of pixels is on a 
screen at any time), events (when a stimulus is presented
relative to the trace times). This library provides a backbone to combine and correlate 
these types in various ways. 
Main Features
-------------
Here are just a few of the things that canalysis does well:
  - Easy directory management to keep data clean and in the same place.
  - Process data for NaN's, outliers, and other issues.
  - Combine multiple datasets into one class for easy manipulations. 
  - Visualize data in various ways, including heatmaps, traces, and events. 
Calcium data can be very specific to the type of experiment being performed. This 
library can be easily modified to fit the type of data 
you need to process. 
"""

# Path: CalciumAnalysis/CalciumAnalysis/data/containers/calcium_data.py
__all__ = [
    "CalciumData",
    "FileHandler",
    "get_data",
    "Params",
    "graphs",
    "heatmaps",
]