# -*- coding: utf-8 -*-
"""
Class for reading/writing data from micromed (.trc).
Inspired by the Matlab code for EEGLAB from Rami K. Niazy.

Completed with matlab Guillaume BECQ code.

Supported : Read

Author: sgarcia
"""

import datetime
import os
import struct

from io import open, BufferedReader

import numpy as np
import quantities as pq

from neo.io.baseio import BaseIO
from neo.core import Segment, AnalogSignal, Epoch, Event


class StructFile(BufferedReader):
    def read_f(self, fmt):
        return struct.unpack(fmt, self.read(struct.calcsize(fmt)))


class MicromedIO(BaseIO):
    """
    Class for reading  data from micromed (.trc).

    Usage:
        >>> from neo import io
        >>> r = io.MicromedIO(filename='File_micromed_1.TRC')
        >>> seg = r.read_segment(lazy=False, cascade=True)
        >>> print seg.analogsignals # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
        [<AnalogSignal(array([ -1.77246094e+02,  -2.24707031e+02,
            -2.66015625e+02, ...
    """
    is_readable = True
    is_writable = False

    supported_objects = [Segment, AnalogSignal, Event, Epoch]
    readable_objects = [Segment]
    writeable_objects = []

    has_header = False
    is_streameable = False
    read_params = {Segment: []}
    write_params = None

    name = None
    extensions = ['TRC']

    mode = 'file'

    def __init__(self, filename=None):
        """
        This class read a micromed TRC file.

        Arguments:
            filename : the filename to read
        """
        BaseIO.__init__(self)
        self.filename = filename

    def read_segment(self, cascade=True, lazy=False, ):
        """
        Arguments:
        """
        f = StructFile(open(self.filename, 'rb'))

        # Name
        f.seek(64, 0)
        surname = f.read(22).decode('ascii')
        while surname[-1] == ' ':
            if len(surname) == 0:
                break
            surname = surname[:-1]
        firstname = f.read(20).decode('ascii')
        while firstname[-1] == ' ':
            if len(firstname) == 0:
                break
            firstname = firstname[:-1]

        #Date
        f.seek(128, 0)
        day, month, year, hour, minute, sec = f.read_f('bbbbbb')
        rec_datetime = datetime.datetime(year + 1900, month, day, hour, minute,
                                         sec)

        f.seek(138, 0)
        Data_Start_Offset, Num_Chan, Multiplexer, Rate_Min, Bytes = f.read_f(
            'IHHHH')
        #~ print Num_Chan, Bytes

        #header version
        f.seek(175, 0)
        header_version, = f.read_f('b')
        assert header_version == 4

        seg = Segment(name=str(firstname + ' ' + surname),
                      file_origin=os.path.basename(self.filename))
        seg.annotate(surname=surname)
        seg.annotate(firstname=firstname)
        seg.annotate(rec_datetime=rec_datetime)

        if not cascade:
            f.close()
            return seg

        # area
        f.seek(176, 0)
        zone_names = ['ORDER', 'LABCOD', 'NOTE', 'FLAGS', 'TRONCA', 'IMPED_B',
                      'IMPED_E', 'MONTAGE',
                      'COMPRESS', 'AVERAGE', 'HISTORY', 'DVIDEO', 'EVENT A',
                      'EVENT B', 'TRIGGER']
        zones = {}
        for zname in zone_names:
            zname2, pos, length = f.read_f('8sII')
            zones[zname] = zname2, pos, length
            #~ print zname2, pos, length

        # reading raw data
        if not lazy:
            f.seek(Data_Start_Offset, 0)
            rawdata = np.fromstring(f.read(), dtype='u' + str(Bytes))
            rawdata = rawdata.reshape((-1, Num_Chan))

        # Reading Code Info
        zname2, pos, length = zones['ORDER']
        f.seek(pos, 0)
        code = np.fromstring(f.read(Num_Chan*2), dtype='u2', count=Num_Chan)

        units = {-1: pq.nano * pq.V, 0: pq.uV, 1: pq.mV, 2: 1, 100: pq.percent,
                 101: pq.dimensionless, 102: pq.dimensionless}

        for c in range(Num_Chan):
            zname2, pos, length = zones['LABCOD']
            f.seek(pos + code[c] * 128 + 2, 0)

            label = f.read(6).strip(b"\x00").decode('ascii')
            ground = f.read(6).strip(b"\x00").decode('ascii')
            (logical_min, logical_max, logical_ground, physical_min,
             physical_max) = f.read_f('iiiii')
            k, = f.read_f('h')
            if k in units.keys():
                unit = units[k]
            else:
                unit = pq.uV

            f.seek(8, 1)
            sampling_rate, = f.read_f('H') * pq.Hz
            sampling_rate *= Rate_Min

            if lazy:
                signal = [] * unit
            else:
                factor = float(physical_max - physical_min) / float(
                    logical_max - logical_min + 1)
                signal = (rawdata[:, c].astype(
                    'f') - logical_ground) * factor * unit

            ana_sig = AnalogSignal(signal, sampling_rate=sampling_rate,
                                   name=str(label), channel_index=c)
            if lazy:
                ana_sig.lazy_shape = None
            ana_sig.annotate(ground=ground)

            seg.analogsignals.append(ana_sig)

        sampling_rate = np.mean(
            [ana_sig.sampling_rate for ana_sig in seg.analogsignals]) * pq.Hz

        # Read trigger and notes
        for zname, label_dtype in [('TRIGGER', 'u2'), ('NOTE', 'S40')]:
            zname2, pos, length = zones[zname]
            f.seek(pos, 0)
            triggers = np.fromstring(f.read(length), dtype=[('pos', 'u4'), (
                'label', label_dtype)])
            if not lazy:
                keep = (triggers['pos'] >= triggers['pos'][0]) & (
                    triggers['pos'] < rawdata.shape[0]) & (
                    triggers['pos'] != 0)
                triggers = triggers[keep]
                ea = Event(name=zname[0] + zname[1:].lower(),
                           labels=triggers['label'].astype('S'),
                           times=(triggers['pos'] / sampling_rate).rescale('s'))
            else:
                ea = Event(name=zname[0] + zname[1:].lower())
                ea.lazy_shape = triggers.size
            seg.events.append(ea)

        # Read Event A and B
        # Not so well  tested
        for zname in ['EVENT A', 'EVENT B']:
            zname2, pos, length = zones[zname]
            f.seek(pos, 0)
            epochs = np.fromstring(f.read(length),
                                   dtype=[('label', 'u4'), ('start', 'u4'),
                                          ('stop', 'u4'), ])
            ep = Epoch(name=zname[0] + zname[1:].lower())
            if not lazy:
                keep = (epochs['start'] > 0) & (
                    epochs['start'] < rawdata.shape[0]) & (
                    epochs['stop'] < rawdata.shape[0])
                epochs = epochs[keep]
                ep = Epoch(name=zname[0] + zname[1:].lower(),
                           labels=epochs['label'].astype('S'),
                           times=(epochs['start'] / sampling_rate).rescale('s'),
                           durations=((epochs['stop'] - epochs['start']) / sampling_rate).rescale('s'))
            else:
                ep = Epoch(name=zname[0] + zname[1:].lower())
                ep.lazy_shape = triggers.size
            seg.epochs.append(ep)

        seg.create_many_to_one_relationship()
        f.close()
        return seg
