Source code for mdf_reader.properties

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""


"""
import glob
import os
import io
import pandas as pd


# Supported formats, sources and internal data models -------------------------
[docs]schema_path = os.path.join(os.path.dirname(__file__),'data_models','lib')
[docs]supported_data_models = [ os.path.basename(x).split(".")[0] for x in glob.glob(schema_path + '/*/*.json') if os.path.basename(x).split(".")[0] == os.path.dirname(x).split("/")[-1]]
# Data types ------------------------------------------------------------------
[docs]numpy_integers = ['int8','int16','int32','int64','uint8','uint16','uint32','uint64']
[docs]numpy_floats = ['float16','float32','float64']
[docs]pandas_nan_integers = {'int8':'Int8','int16':'Int16','int32':'Int32', 'int64':'Int64','uint8':'UInt8','uint16':'UInt16', 'uint32':'UInt32','uint64':'UInt64'}
[docs]numeric_types = numpy_integers.copy()
numeric_types.extend(numpy_floats) numeric_types.extend(pandas_nan_integers.values())
[docs]object_types = ['str','object','key','datetime']
[docs]data_types = object_types.copy()
data_types.extend(numpy_integers) data_types.extend(numpy_floats)
[docs]pandas_dtypes = {}
for dtype in object_types: pandas_dtypes[dtype] = 'object' pandas_dtypes.update({ x:x for x in numeric_types }) # ....and how they are managed
[docs]data_type_conversion_args = {}
for dtype in numeric_types: data_type_conversion_args[dtype] = ['scale','offset'] data_type_conversion_args['str'] = ['disable_white_strip'] data_type_conversion_args['object'] = ['disable_white_strip'] data_type_conversion_args['key'] = ['disable_white_strip'] data_type_conversion_args['datetime'] = ['datetime_format'] # Misc ------------------------------------------------------------------------
[docs]tol = 1E-10
[docs]dummy_level = '_SECTION_'
# Length of reports in initial read
[docs]MAX_FULL_REPORT_WIDTH = 100000
# This is a delimiter internally used when writing to buffers # It is the Unicode Character 'END OF TEXT' # It is supposed to be safe because we don;t expect it in a string # It's UTF-8 encoding lenght is not > 1, so it is supported by pandas 'c' # engine, which is faster than the python engine.
[docs]internal_delimiter = u"\u0003"