<gh_stars>0
import pandas as pd


class GeneInfo:
    """This class stores information regarding a specific problem's
    biological parameters."""

    def __init__(self, frame_path, obj_list, com_size=100, fixed_list=[]):
        """Default constructor provides control over default EA parameters.

        Defaults are defined above in the function header.

        Parameters
        -------
        frame_path, string
            Load the frame_path string into a DataFrame.
            Should resolve to a pickled pandas DataFrame.
            See repository for documentation on what the format of the frame
            should be.
        obj_list, list of strings
            List of column identifiers to use as objectives for the GA.
        com_size, optional, integer
            Size of candidate communities to fix the problem to.
        fixed_list, optional, list
            List of genes to keep fixed in the candidate solutions.
            Should be of the form of the string labels of genes.
        """

        self.frame_path = frame_path
        self.data_frame = pd.read_pickle(frame_path)
        self.gene_count = self.data_frame.shape[0]
        self.obj_list = obj_list
        self.fixed_list = fixed_list
        self.fixed_list_ids = self.data_frame[
            self.data_frame['GeneName'].isin(fixed_list)].index.to_list()
        self.com_size = com_size
        self.frontier = [0 for x in range(self.gene_count)]

    def __str__(self):
        """Return params as string."""

        return "Frame path: {}\nGene Count: {}\nObjectives: {}\nCommunity {}" \
               "\nFixed Genes: {}".format(self.frame_path, self.gene_count,
                                          self.obj_list, self.com_size,
                                          self.fixed_list)

import pandas as pd


class GeneInfo:
    """This class stores information regarding a specific problem's
    biological parameters."""

    def __init__(self, frame_path, obj_list, com_size=100, fixed_list=[]):
        """Default constructor provides control over default EA parameters.

        Defaults are defined above in the function header.

        Parameters
        -------
        frame_path, string
            Load the frame_path string into a DataFrame.
            Should resolve to a pickled pandas DataFrame.
            See repository for documentation on what the format of the frame
            should be.
        obj_list, list of strings
            List of column identifiers to use as objectives for the GA.
        com_size, optional, integer
            Size of candidate communities to fix the problem to.
        fixed_list, optional, list
            List of genes to keep fixed in the candidate solutions.
            Should be of the form of the string labels of genes.
        """

        self.frame_path = frame_path
        self.data_frame = pd.read_pickle(frame_path)
        self.gene_count = self.data_frame.shape[0]
        self.obj_list = obj_list
        self.fixed_list = fixed_list
        self.fixed_list_ids = self.data_frame[
            self.data_frame['GeneName'].isin(fixed_list)].index.to_list()
        self.com_size = com_size
        self.frontier = [0 for x in range(self.gene_count)]

    def __str__(self):
        """Return params as string."""

        return "Frame path: {}\nGene Count: {}\nObjectives: {}\nCommunity {}" \
               "\nFixed Genes: {}".format(self.frame_path, self.gene_count,
                                          self.obj_list, self.com_size,
                                          self.fixed_list)
This class stores information regarding a specific problem's     biological parameters. Default constructor provides control over default EA parameters.          Defaults are defined above in the function header.          Parameters         -------         frame_path, string             Load the frame_path string into a DataFrame.             Should resolve to a pickled pandas DataFrame.             See repository for documentation on what the format of the frame             should be.         obj_list, list of strings             List of column identifiers to use as objectives for the GA.         com_size, optional, integer             Size of candidate communities to fix the problem to.         fixed_list, optional, list             List of genes to keep fixed in the candidate solutions.             Should be of the form of the string labels of genes. Return params as string.