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1f9c9653c5
The class currently just reads the main data section and does not process any of the headers or log information.
197 lines
7.4 KiB
Python
197 lines
7.4 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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from os import SEEK_SET, SEEK_CUR
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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', '<u8'),
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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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"""
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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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data_module, = (m for m in modules if m['shortname'] == b'VMP data ')
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## There is 100 bytes of data before the main array starts
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self.data = np.frombuffer(data_module['data'], dtype=VMPdata_dtype,
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offset=100)
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