# Path: simdna/simdnautil/util.py
# DEFAULT_LETTER_TO_INDEX = {'A': 0, 'C': 1, 'G': 2, 'T': 3}
# DEFAULT_BACKGROUND_FREQ = OrderedDict(
#     [('A', 0.3), ('C', 0.2), ('G', 0.2), ('T', 0.3)])
# DEFAULT_DINUC_FREQ = OrderedDict([
#  ('AA',0.095),
#  ('AC',0.050),
#  ('AG',0.071),
#  ('AT',0.075),
#  ('CA',0.073),
#  ('CC',0.054),
#  ('CG',0.010),
#  ('CT',0.072),
#  ('GA',0.060),
#  ('GC',0.044),
#  ('GG',0.054),
#  ('GT',0.050),
#  ('TA',0.064),
#  ('TC',0.060),
#  ('TG',0.073),
#  ('TT',0.095),
# ])
# DEFAULT_BASE_DISCRETE_DISTRIBUTION = DiscreteDistribution(
#     DEFAULT_BACKGROUND_FREQ)
# class DiscreteDistribution(object):
# class VariableWrapper():
#     class Enum(object):
# class FileNameParts(object):
# class ArgumentToAdd(object):
# class FloatArgument(ArgumentToAdd):
# class BooleanArgument(ArgumentToAdd):
# class CoreFileNameArgument(ArgumentToAdd):
# class ArrArgument(ArgumentToAdd):
# class ArrOfFileNamesArgument(ArrArgument):
#     def __init__(self, valToFreq):
#     def sample(self):
# def get_file_handle(filename, mode="r"):
# def default_tab_seppd(s):
# def trim_newline(s):
# def perform_action_on_each_line_of_file(
#     file_handle, action, transformation=default_tab_seppd, ignore_input_title=False):
# def process_line(line, i, ignore_input_title,
#                  transformation, action):
#     def __init__(self, var):
# def enum(**enums):
# def combine_enums(*enums):
# def sampleFromProbsArr(arrWithProbs):
# def reverseComplement(sequence):
# def sampleWithoutReplacement(arr, numToSample):
# def swapIndices(arr, idx1, idx2):
# def get_file_name_parts(file_name):
#     def __init__(self, directory, core_file_name, extension):
#     def get_full_path(self):
#     def get_core_file_name_and_extension(self):
#     def get_transformed_core_file_name(self, transformation, extension=None):
#     def get_transformed_file_path(self, transformation, extension=None):
# def format_as_json(jsonable_data):
#     def __init__(self, val, argumentName=None, argNameAndValSep="-"):
#     def argNamePrefix(self):
#     def transform(self):
#     def __init__(self, val, argumentName=None, argNameAndValSep="-"):
#     def argNamePrefix(self):
#     def transform(self):
#     def transform(self):
#     def transform(self):
#     def __init__(self, val, argumentName, sep="+", toStringFunc=str):
#     def transform(self):
#     def __init__(self, val, argumentName, sep="+"):
# def addArguments(string, args, joiner="_"):


from simdna.simdnautil import util
from collections import OrderedDict
            from simdna.synthetic.embeddables import StringEmbeddable
import numpy as np
import re
import itertools
    ofh.write(util.format_as_json(sequenceSetGenerator.getJsonableObject()))
    ofh.close()


def read_simdata_file(simdata_file, ids_to_load=None):
    """
    Read a simdata file and extract all simdata info as an enum
    :param simdata_file: str, path to file
    :param ids_to_load: list of ints, ids of sequences to load
    :return: enum of sequences, the embedded elements in each
             sequence, and any labels for those sequences
    """
    ids = []
    sequences = []
    embeddings = []
    labels = []
    if (ids_to_load is not None):
        ids_to_load = set(ids_to_load)

    def action(inp, line_number):
        if (line_number > 1):
            if (ids_to_load is None or (inp[0] in ids_to_load)):
                ids.append(inp[0])
                sequences.append(inp[1])
                embeddings.append(getEmbeddingsFromString(inp[2]))
                labels.append([int(x) for x in inp[3:]])

    util.perform_action_on_each_line_of_file(
        file_handle=util.get_file_handle(simdata_file),
        action=action,

# Path: simdna/simdnautil/util.py
# DEFAULT_LETTER_TO_INDEX = {'A': 0, 'C': 1, 'G': 2, 'T': 3}
# DEFAULT_BACKGROUND_FREQ = OrderedDict(
#     [('A', 0.3), ('C', 0.2), ('G', 0.2), ('T', 0.3)])
# DEFAULT_DINUC_FREQ = OrderedDict([
#  ('AA',0.095),
#  ('AC',0.050),
#  ('AG',0.071),
#  ('AT',0.075),
#  ('CA',0.073),
#  ('CC',0.054),
#  ('CG',0.010),
#  ('CT',0.072),
#  ('GA',0.060),
#  ('GC',0.044),
#  ('GG',0.054),
#  ('GT',0.050),
#  ('TA',0.064),
#  ('TC',0.060),
#  ('TG',0.073),
#  ('TT',0.095),
# ])
# DEFAULT_BASE_DISCRETE_DISTRIBUTION = DiscreteDistribution(
#     DEFAULT_BACKGROUND_FREQ)
# class DiscreteDistribution(object):
# class VariableWrapper():
#     class Enum(object):
# class FileNameParts(object):
# class ArgumentToAdd(object):
# class FloatArgument(ArgumentToAdd):
# class BooleanArgument(ArgumentToAdd):
# class CoreFileNameArgument(ArgumentToAdd):
# class ArrArgument(ArgumentToAdd):
# class ArrOfFileNamesArgument(ArrArgument):
#     def __init__(self, valToFreq):
#     def sample(self):
# def get_file_handle(filename, mode="r"):
# def default_tab_seppd(s):
# def trim_newline(s):
# def perform_action_on_each_line_of_file(
#     file_handle, action, transformation=default_tab_seppd, ignore_input_title=False):
# def process_line(line, i, ignore_input_title,
#                  transformation, action):
#     def __init__(self, var):
# def enum(**enums):
# def combine_enums(*enums):
# def sampleFromProbsArr(arrWithProbs):
# def reverseComplement(sequence):
# def sampleWithoutReplacement(arr, numToSample):
# def swapIndices(arr, idx1, idx2):
# def get_file_name_parts(file_name):
#     def __init__(self, directory, core_file_name, extension):
#     def get_full_path(self):
#     def get_core_file_name_and_extension(self):
#     def get_transformed_core_file_name(self, transformation, extension=None):
#     def get_transformed_file_path(self, transformation, extension=None):
# def format_as_json(jsonable_data):
#     def __init__(self, val, argumentName=None, argNameAndValSep="-"):
#     def argNamePrefix(self):
#     def transform(self):
#     def __init__(self, val, argumentName=None, argNameAndValSep="-"):
#     def argNamePrefix(self):
#     def transform(self):
#     def transform(self):
#     def transform(self):
#     def __init__(self, val, argumentName, sep="+", toStringFunc=str):
#     def transform(self):
#     def __init__(self, val, argumentName, sep="+"):
# def addArguments(string, args, joiner="_"):


# Path: simdna/synthetic/core.py
from simdna.simdnautil import util
from collections import OrderedDict
            from simdna.synthetic.embeddables import StringEmbeddable
import numpy as np
import re
import itertools

    ofh.write(util.format_as_json(sequenceSetGenerator.getJsonableObject()))
    ofh.close()


def read_simdata_file(simdata_file, ids_to_load=None):
    """
    Read a simdata file and extract all simdata info as an enum
    :param simdata_file: str, path to file
    :param ids_to_load: list of ints, ids of sequences to load
    :return: enum of sequences, the embedded elements in each
             sequence, and any labels for those sequences
    """
    ids = []
    sequences = []
    embeddings = []
    labels = []
    if (ids_to_load is not None):
        ids_to_load = set(ids_to_load)

    def action(inp, line_number):
        if (line_number > 1):
            if (ids_to_load is None or (inp[0] in ids_to_load)):
                ids.append(inp[0])
                sequences.append(inp[1])
                embeddings.append(getEmbeddingsFromString(inp[2]))
                labels.append([int(x) for x in inp[3:]])

    util.perform_action_on_each_line_of_file(
        file_handle=util.get_file_handle(simdata_file),
        action=action,

        transformation=util.default_tab_seppd)