text: """
  MIT License
  
  Copyright (c) 2019 Andrew Riha
  
  Permission is hereby granted, free of charge, to any person obtaining a copy
  of this software and associated documentation files (the "Software"), to deal
  in the Software without restriction, including without limitation the rights
  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  copies of the Software, and to permit persons to whom the Software is
  furnished to do so, subject to the following conditions:
  
  The above copyright notice and this permission notice shall be included in all
  copies or substantial portions of the Software.
  
  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  SOFTWARE.
  
  """
  
  import os
  import shutil
  from unittest import TestCase
  
  import numpy as np
  import pandas as pd
  from snps.io.reader import NORMALIZED_DTYPES
  
  from lineage import Lineage
  
  
  class BaseLineageTestCase(TestCase):
      def setUp(self):
          self.l = Lineage()
  
      def simulate_snps(
          self,
          ind,
          chrom="1",
          pos_start=1,
          pos_max=111700002,
          pos_step=10000,
          genotype="AA",
          insert_nulls=True,
          null_snp_step=101,
          complement_genotype_one_chrom=False,
          complement_genotype_two_chroms=False,
          complement_snp_step=50,
      ):
          ind._build = 37
  
          positions = np.arange(pos_start, pos_max, pos_step, dtype=np.int64)
          snps = pd.DataFrame(
              {"chrom": chrom},
              index=pd.Index(
                  ["rs" + str(x + 1) for x in range(len(positions))], name="rsid"
              ),
          )
          snps["pos"] = positions
          snps["genotype"] = genotype
  
          if insert_nulls:
              snps.loc[snps.iloc[0::null_snp_step, :].index, "genotype"] = np.nan
  
          indices = snps.iloc[0::complement_snp_step, :].index
          if complement_genotype_two_chroms:
              snps.loc[indices, "genotype"] = snps.loc[indices, "genotype"].apply(
                  self.complement_two_chroms
              )
          elif complement_genotype_one_chrom:
              snps.loc[indices, "genotype"] = snps.loc[indices, "genotype"].apply(
                  self.complement_one_chrom
              )
  
          ind._snps = snps
  
          return ind
  
      @staticmethod
      def get_complement(base):
          if base == "A":
              return "T"
          elif base == "G":
              return "C"
          elif base == "C":
              return "G"
          elif base == "T":
              return "A"
          else:
              return base
  
      def complement_one_chrom(self, genotype):
          if pd.isnull(genotype):
              return np.nan
  
          complement = ""
  
          for base in list(genotype):
              complement += self.get_complement(base)
              complement += genotype[1]
              return complement
  
      def complement_two_chroms(self, genotype):
          if pd.isnull(genotype):
              return np.nan
  
          complement = ""
  
          for base in list(genotype):
              complement += self.get_complement(base)
  
          return complement
  
      @staticmethod
      def create_snp_df(rsid, chrom, pos, genotype):
          df = pd.DataFrame(
              {"rsid": rsid, "chrom": chrom, "pos": pos, "genotype": genotype},
              columns=["rsid", "chrom", "pos", "genotype"],
          )
          df = df.astype(NORMALIZED_DTYPES)
          df = df.set_index("rsid")
          return df
  
      def generic_snps(self):
          return self.create_snp_df(
              rsid=["rs" + str(i) for i in range(1, 9)],
              chrom=["1"] * 8,
              pos=list(range(101, 109)),
              genotype=["AA", "CC", "GG", "TT", np.nan, "GC", "TC", "AT"],
          )
  
      @property
      def downloads_enabled(self):
          """ Property indicating if downloads are enabled.
  
          Only download from external resources when an environment variable named
          "DOWNLOADS_ENABLED" is set to "true".
  
          Returns
          -------
          bool
          """
          return True if os.getenv("DOWNLOADS_ENABLED") == "true" else False
  