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242 lines
9.7 KiB
Python
242 lines
9.7 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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from os import SEEK_SET, SEEK_CUR
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import time
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from datetime import date
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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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VMPmodule_hdr = np.dtype([('shortname', 'S10'),
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('longname', 'S25'),
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('length', '<u4'),
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('version', '<u4'),
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('date', 'S8')])
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VMPdata_dtype = np.dtype([('flags', 'u1'),
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("time/s", '<f8'),
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("control/V/mA", '<f4'),
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("Ewe/V", '<f4'),
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("dQ/mA.h", '<f8'),
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("P/W", '<f4')])
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def read_VMP_modules(fileobj, read_module_data=True):
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"""Reads in module headers in the VMPmodule_hdr format. Yields a dict with
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the headers and offset for each module.
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N.B. the offset yielded is the offset to the start of the data i.e. after
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the end of the header. The data runs from (offset) to (offset+length)"""
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while True:
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module_magic = fileobj.read(len(b'MODULE'))
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if len(module_magic) == 0: # end of file
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raise StopIteration
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elif module_magic != b'MODULE':
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raise ValueError("Found %r, expecting start of new VMP MODULE" % module_magic)
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hdr_bytes = fileobj.read(VMPmodule_hdr.itemsize)
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if len(hdr_bytes) < VMPmodule_hdr.itemsize:
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raise IOError("Unexpected end of file while reading module header")
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hdr = np.fromstring(hdr_bytes, dtype=VMPmodule_hdr, count=1)
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hdr_dict = dict(((n, hdr[n][0]) for n in VMPmodule_hdr.names))
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hdr_dict['offset'] = fileobj.tell()
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if read_module_data:
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hdr_dict['data'] = fileobj.read(hdr_dict['length'])
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if len(hdr_dict['data']) != hdr_dict['length']:
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raise IOError("""Unexpected end of file while reading data
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current module: %s
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length read: %d
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length expected: %d""" % (hdr_dict['longname'],
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len(hdr_dict['data']),
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hdr_dict['length']))
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yield hdr_dict
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else:
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yield hdr_dict
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fileobj.seek(hdr_dict['offset'] + hdr_dict['length'], SEEK_SET)
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class MPRfile:
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"""Bio-Logic .mpr file
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The file format is not specified anywhere and has therefore been reverse
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engineered. Not all the fields are known.
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Attributes
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==========
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modules - A list of dicts containing basic information about the 'modules'
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of which the file is composed.
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data - numpy record array of type VMPdata_dtype containing the main data
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array of the file.
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startdate - The date when the experiment started
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enddate - The date when the experiment finished
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"""
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def __init__(self, file_or_path):
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if isinstance(file_or_path, str):
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mpr_file = open(file_or_path, 'rb')
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else:
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mpr_file = file_or_path
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mpr_magic = b'BIO-LOGIC MODULAR FILE\x1a \x00\x00\x00\x00'
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magic = mpr_file.read(len(mpr_magic))
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if magic != mpr_magic:
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raise ValueError('Invalid magic for .mpr file: %s' % magic)
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modules = list(read_VMP_modules(mpr_file))
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self.modules = modules
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settings_mod, = (m for m in modules if m['shortname'] == b'VMP Set ')
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data_module, = (m for m in modules if m['shortname'] == b'VMP data ')
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log_module, = (m for m in modules if m['shortname'] == b'VMP LOG ')
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n_data_points = np.fromstring(data_module['data'][:4], dtype='<u4')
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## not actually sure if this is the number of columns or if it means
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## something else:
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n_columns = int(data_module['data'][4])
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if data_module['version'] == 0:
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## There is 100 bytes of data before the main array starts
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column_types = np.fromstring(data_module['data'][5:], dtype='u1',
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count=n_columns)
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assert(data_module['length'] - 100 ==
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VMPdata_dtype.itemsize * n_data_points)
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self.data = np.frombuffer(data_module['data'], dtype=VMPdata_dtype,
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offset=100)
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elif data_module['version'] == 2:
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## There is 405 bytes of data before the main array starts
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column_types = np.fromstring(data_module['data'][5:], dtype='<u2',
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count=n_columns)
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assert(data_module['length'] - 405 ==
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VMPdata_dtype.itemsize * n_data_points)
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self.data = np.frombuffer(data_module['data'], dtype=VMPdata_dtype,
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offset=405)
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else:
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raise ValueError("Unrecognised version for data module: %d" %
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data_module['version'])
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## No idea what these 'column types' mean or even if they are actually
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## column types at all
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np.testing.assert_array_equal(column_types,
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[1, 2, 3, 21, 31, 65, 4, 5, 6, 7, 70])
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tm = time.strptime(str(settings_mod['date'], encoding='ascii'),
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'%m/%d/%y')
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self.startdate = date(tm.tm_year, tm.tm_mon, tm.tm_mday)
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tm = time.strptime(str(log_module['date'], encoding='ascii'),
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'%m/%d/%y')
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self.enddate = date(tm.tm_year, tm.tm_mon, tm.tm_mday)
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