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d909305b74
Realised that comparing numpy arrays read in from the binary .mpr files to a csv.DictReader would be more work than just writing a new function to read in a record array.
122 lines
4.4 KiB
Python
122 lines
4.4 KiB
Python
# -*- coding: utf-8 -*-
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"""Code to read in data files from Bio-Logic instruments"""
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__all__ = ['MPTfileCSV', 'MPTfile']
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import re
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import csv
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import numpy as np
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def fieldname_to_dtype(fieldname):
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"""Converts a column header from the MPT file into a tuple of
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canonical name and appropriate numpy dtype"""
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if fieldname == 'mode':
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return ('mode', np.uint8)
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elif fieldname in ("ox/red", "error", "control changes", "Ns changes",
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"counter inc."):
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return (fieldname, np.bool_)
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elif fieldname in ("time/s", "Ewe/V", "P/W", "(Q-Qo)/mA.h", "x"):
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return (fieldname, np.float_)
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elif fieldname in ("dq/mA.h", "dQ/mA.h"):
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return ("dQ/mA.h", np.float_)
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elif fieldname in ("I/mA", "<I>/mA"):
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return ("I/mA", np.float_)
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elif fieldname in ("control/V", "control/V/mA"):
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return ("control/V/mA", np.float_)
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else:
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raise ValueError("Invalid column header: %s" % fieldname)
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def MPTfile(file_or_path):
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"""Opens .mpt files as numpy record arrays
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Checks for the correct headings, skips any comments and returns a
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numpy record array object and a list of comments
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"""
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if isinstance(file_or_path, str):
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mpt_file = open(file_or_path, 'rb')
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else:
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mpt_file = file_or_path
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magic = next(mpt_file)
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if magic != b'EC-Lab ASCII FILE\r\n':
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raise ValueError("Bad first line for EC-Lab file: '%s'" % magic)
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nb_headers_match = re.match(b'Nb header lines : (\d+)\s*$', next(mpt_file))
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nb_headers = int(nb_headers_match.group(1))
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if nb_headers < 3:
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raise ValueError("Too few header lines: %d" % nb_headers)
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## The 'magic number' line, the 'Nb headers' line and the column headers
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## make three lines. Every additional line is a comment line.
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comments = [next(mpt_file) for i in range(nb_headers - 3)]
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fieldnames = next(mpt_file).decode('ascii').strip().split('\t')
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expected_fieldnames = (
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["mode", "ox/red", "error", "control changes", "Ns changes",
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"counter inc.", "time/s", "control/V/mA", "Ewe/V", "dq/mA.h",
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"P/W", "<I>/mA", "(Q-Qo)/mA.h", "x"],
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["mode", "ox/red", "error", "control changes", "Ns changes",
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"counter inc.", "time/s", "control/V", "Ewe/V", "I/mA",
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"dQ/mA.h", "P/W"],
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["mode", "ox/red", "error", "control changes", "Ns changes",
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"counter inc.", "time/s", "control/V", "Ewe/V", "<I>/mA",
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"dQ/mA.h", "P/W"])
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if fieldnames not in expected_fieldnames:
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raise ValueError("Unrecognised headers for MPT file format %s" %
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fieldnames)
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record_type = np.dtype(list(map(fieldname_to_dtype, fieldnames)))
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mpt_array = np.loadtxt(mpt_file, dtype=record_type)
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return mpt_array, comments
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def MPTfileCSV(file_or_path):
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"""Simple function to open MPT files as csv.DictReader objects
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Checks for the correct headings, skips any comments and returns a
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csv.DictReader object and a list of comments
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"""
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if isinstance(file_or_path, str):
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mpt_file = open(file_or_path, 'r')
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else:
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mpt_file = file_or_path
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magic = next(mpt_file)
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if magic != 'EC-Lab ASCII FILE\n':
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raise ValueError("Bad first line for EC-Lab file: '%s'" % magic)
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nb_headers_match = re.match('Nb header lines : (\d+)\s*$', next(mpt_file))
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nb_headers = int(nb_headers_match.group(1))
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if nb_headers < 3:
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raise ValueError("Too few header lines: %d" % nb_headers)
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## The 'magic number' line, the 'Nb headers' line and the column headers
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## make three lines. Every additional line is a comment line.
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comments = [next(mpt_file) for i in range(nb_headers - 3)]
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mpt_csv = csv.DictReader(mpt_file, dialect='excel-tab')
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expected_fieldnames = (
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["mode", "ox/red", "error", "control changes", "Ns changes",
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"counter inc.", "time/s", "control/V/mA", "Ewe/V", "dq/mA.h",
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"P/W", "<I>/mA", "(Q-Qo)/mA.h", "x"],
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["mode", "ox/red", "error", "control changes", "Ns changes",
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"counter inc.", "time/s", "control/V", "Ewe/V", "I/mA",
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"dQ/mA.h", "P/W"],
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["mode", "ox/red", "error", "control changes", "Ns changes",
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"counter inc.", "time/s", "control/V", "Ewe/V", "<I>/mA",
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"dQ/mA.h", "P/W"])
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if mpt_csv.fieldnames not in expected_fieldnames:
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raise ValueError("Unrecognised headers for MPT file format")
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return mpt_csv, comments
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