Python Raw._data[:,:]方法代码示例

# 需要导入模块: from mne.io import Raw [as 别名]
# 或者: from mne.io.Raw import _data[:,:] [as 别名]
def test_io_raw():
    """Test IO for raw data (Neuromag + CTF + gz)
    """
    tempdir = _TempDir()
    # test unicode io
    for chars in [b'\xc3\xa4\xc3\xb6\xc3\xa9', b'a']:
        with Raw(fif_fname) as r:
            assert_true('Raw' in repr(r))
            assert_true(op.basename(fif_fname) in repr(r))
            desc1 = r.info['description'] = chars.decode('utf-8')
            temp_file = op.join(tempdir, 'raw.fif')
            r.save(temp_file, overwrite=True)
            with Raw(temp_file) as r2:
                desc2 = r2.info['description']
            assert_equal(desc1, desc2)

    # Let's construct a simple test for IO first
    raw = Raw(fif_fname).crop(0, 3.5, False)
    raw.load_data()
    # put in some data that we know the values of
    data = rng.randn(raw._data.shape[0], raw._data.shape[1])
    raw._data[:, :] = data
    # save it somewhere
    fname = op.join(tempdir, 'test_copy_raw.fif')
    raw.save(fname, buffer_size_sec=1.0)
    # read it in, make sure the whole thing matches
    raw = Raw(fname)
    assert_allclose(data, raw[:, :][0], rtol=1e-6, atol=1e-20)
    # let's read portions across the 1-sec tag boundary, too
    inds = raw.time_as_index([1.75, 2.25])
    sl = slice(inds[0], inds[1])
    assert_allclose(data[:, sl], raw[:, sl][0], rtol=1e-6, atol=1e-20)

    # now let's do some real I/O
    fnames_in = [fif_fname, test_fif_gz_fname, ctf_fname]
    fnames_out = ['raw.fif', 'raw.fif.gz', 'raw.fif']
    for fname_in, fname_out in zip(fnames_in, fnames_out):
        fname_out = op.join(tempdir, fname_out)
        raw = Raw(fname_in)

        nchan = raw.info['nchan']
        ch_names = raw.info['ch_names']
        meg_channels_idx = [k for k in range(nchan)
                            if ch_names[k][0] == 'M']
        n_channels = 100
        meg_channels_idx = meg_channels_idx[:n_channels]
        start, stop = raw.time_as_index([0, 5])
        data, times = raw[meg_channels_idx, start:(stop + 1)]
        meg_ch_names = [ch_names[k] for k in meg_channels_idx]

        # Set up pick list: MEG + STI 014 - bad channels
        include = ['STI 014']
        include += meg_ch_names
        picks = pick_types(raw.info, meg=True, eeg=False, stim=True,
                           misc=True, ref_meg=True, include=include,
                           exclude='bads')

        # Writing with drop_small_buffer True
        raw.save(fname_out, picks, tmin=0, tmax=4, buffer_size_sec=3,
                 drop_small_buffer=True, overwrite=True)
        raw2 = Raw(fname_out)

        sel = pick_channels(raw2.ch_names, meg_ch_names)
        data2, times2 = raw2[sel, :]
        assert_true(times2.max() <= 3)

        # Writing
        raw.save(fname_out, picks, tmin=0, tmax=5, overwrite=True)

        if fname_in == fif_fname or fname_in == fif_fname + '.gz':
            assert_equal(len(raw.info['dig']), 146)

        raw2 = Raw(fname_out)

        sel = pick_channels(raw2.ch_names, meg_ch_names)
        data2, times2 = raw2[sel, :]

        assert_allclose(data, data2, rtol=1e-6, atol=1e-20)
        assert_allclose(times, times2)
        assert_allclose(raw.info['sfreq'], raw2.info['sfreq'], rtol=1e-5)

        # check transformations
        for trans in ['dev_head_t', 'dev_ctf_t', 'ctf_head_t']:
            if raw.info[trans] is None:
                assert_true(raw2.info[trans] is None)
            else:
                assert_array_equal(raw.info[trans]['trans'],
                                   raw2.info[trans]['trans'])

                # check transformation 'from' and 'to'
                if trans.startswith('dev'):
                    from_id = FIFF.FIFFV_COORD_DEVICE
                else:
                    from_id = FIFF.FIFFV_MNE_COORD_CTF_HEAD
                if trans[4:8] == 'head':
                    to_id = FIFF.FIFFV_COORD_HEAD
                else:
                    to_id = FIFF.FIFFV_MNE_COORD_CTF_HEAD
                for raw_ in [raw, raw2]:
                    assert_equal(raw_.info[trans]['from'], from_id)
#.........这里部分代码省略.........

# 需要导入模块: from mne.io import Raw [as 别名]
# 或者: from mne.io.Raw import _data[:,:] [as 别名]
def test_io_raw():
    """Test IO for raw data (Neuromag + CTF + gz)
    """
    # test unicode io
    for chars in [b"\xc3\xa4\xc3\xb6\xc3\xa9", b"a"]:
        with Raw(fif_fname) as r:
            desc1 = r.info["description"] = chars.decode("utf-8")
            temp_file = op.join(tempdir, "raw.fif")
            r.save(temp_file, overwrite=True)
            with Raw(temp_file) as r2:
                desc2 = r2.info["description"]
            assert_equal(desc1, desc2)

    # Let's construct a simple test for IO first
    raw = Raw(fif_fname, preload=True)
    raw.crop(0, 3.5)
    # put in some data that we know the values of
    data = np.random.randn(raw._data.shape[0], raw._data.shape[1])
    raw._data[:, :] = data
    # save it somewhere
    fname = op.join(tempdir, "test_copy_raw.fif")
    raw.save(fname, buffer_size_sec=1.0)
    # read it in, make sure the whole thing matches
    raw = Raw(fname)
    assert_true(np.allclose(data, raw[:, :][0], 1e-6, 1e-20))
    # let's read portions across the 1-sec tag boundary, too
    inds = raw.time_as_index([1.75, 2.25])
    sl = slice(inds[0], inds[1])
    assert_true(np.allclose(data[:, sl], raw[:, sl][0], 1e-6, 1e-20))

    # now let's do some real I/O
    fnames_in = [fif_fname, fif_gz_fname, ctf_fname]
    fnames_out = ["raw.fif", "raw.fif.gz", "raw.fif"]
    for fname_in, fname_out in zip(fnames_in, fnames_out):
        fname_out = op.join(tempdir, fname_out)
        raw = Raw(fname_in)

        nchan = raw.info["nchan"]
        ch_names = raw.info["ch_names"]
        meg_channels_idx = [k for k in range(nchan) if ch_names[k][0] == "M"]
        n_channels = 100
        meg_channels_idx = meg_channels_idx[:n_channels]
        start, stop = raw.time_as_index([0, 5])
        data, times = raw[meg_channels_idx, start : (stop + 1)]
        meg_ch_names = [ch_names[k] for k in meg_channels_idx]

        # Set up pick list: MEG + STI 014 - bad channels
        include = ["STI 014"]
        include += meg_ch_names
        picks = pick_types(
            raw.info, meg=True, eeg=False, stim=True, misc=True, ref_meg=True, include=include, exclude="bads"
        )

        # Writing with drop_small_buffer True
        raw.save(fname_out, picks, tmin=0, tmax=4, buffer_size_sec=3, drop_small_buffer=True, overwrite=True)
        raw2 = Raw(fname_out, preload=True)

        sel = pick_channels(raw2.ch_names, meg_ch_names)
        data2, times2 = raw2[sel, :]
        assert_true(times2.max() <= 3)

        # Writing
        raw.save(fname_out, picks, tmin=0, tmax=5, overwrite=True)

        if fname_in == fif_fname or fname_in == fif_fname + ".gz":
            assert_true(len(raw.info["dig"]) == 146)

        raw2 = Raw(fname_out)

        sel = pick_channels(raw2.ch_names, meg_ch_names)
        data2, times2 = raw2[sel, :]

        assert_true(np.allclose(data, data2, 1e-6, 1e-20))
        assert_allclose(times, times2)
        assert_allclose(raw.info["sfreq"], raw2.info["sfreq"], rtol=1e-5)

        # check transformations
        for trans in ["dev_head_t", "dev_ctf_t", "ctf_head_t"]:
            if raw.info[trans] is None:
                assert_true(raw2.info[trans] is None)
            else:
                assert_array_equal(raw.info[trans]["trans"], raw2.info[trans]["trans"])

                # check transformation 'from' and 'to'
                if trans.startswith("dev"):
                    from_id = FIFF.FIFFV_COORD_DEVICE
                else:
                    from_id = FIFF.FIFFV_MNE_COORD_CTF_HEAD
                if trans[4:8] == "head":
                    to_id = FIFF.FIFFV_COORD_HEAD
                else:
                    to_id = FIFF.FIFFV_MNE_COORD_CTF_HEAD
                for raw_ in [raw, raw2]:
                    assert_true(raw_.info[trans]["from"] == from_id)
                    assert_true(raw_.info[trans]["to"] == to_id)

        if fname_in == fif_fname or fname_in == fif_fname + ".gz":
            assert_allclose(raw.info["dig"][0]["r"], raw2.info["dig"][0]["r"])

    # test warnings on bad filenames
#.........这里部分代码省略.........