Python future_builtins.zip方法代码示例

# 需要导入模块: import future_builtins [as 别名]
# 或者: from future_builtins import zip [as 别名]
def test_traces_raw(openfn, kwargs):
    with openfn(**kwargs) as f:
        gen_traces = np.array(list(map(np.copy, f.trace)), dtype=np.single)

        raw_traces = f.trace.raw[:]
        assert np.array_equal(gen_traces, raw_traces)

        assert len(gen_traces) == f.tracecount
        assert len(raw_traces) == f.tracecount

        assert gen_traces[0][49] == raw_traces[0][49]
        assert gen_traces[1][49] == f.trace.raw[1][49]
        assert gen_traces[2][49] == raw_traces[2][49]

        assert np.array_equal(f.trace[10], f.trace.raw[10])

        for raw, gen in zip(f.trace.raw[::2], f.trace[::2]):
            assert np.array_equal(raw, gen)

        for raw, gen in zip(f.trace.raw[::-1], f.trace[::-1]):
            assert np.array_equal(raw, gen) 

# 需要导入模块: import future_builtins [as 别名]
# 或者: from future_builtins import zip [as 别名]
def test_group_single_key():
    with segyio.open(testdata / 'shot-gather.sgy', ignore_geometry = True) as f:
        group = f.group(segyio.su.fldr)
        assert len(group) == 4

        assert 2 in group
        assert 4 not in group

        expected_keys = [2, 3, 5, 8]

        for key, shot in zip(expected_keys, group.values()):
            assert key == shot.key

            for header in shot.header:
                assert key == header[segyio.su.fldr]

            for trace in shot.trace:
                assert key == trace[0] 

# 需要导入模块: import future_builtins [as 别名]
# 或者: from future_builtins import zip [as 别名]
def izip_records(seqarrays, fill_value=None, flatten=True):
    """
    Returns an iterator of concatenated items from a sequence of arrays.

    Parameters
    ----------
    seqarrays : sequence of arrays
        Sequence of arrays.
    fill_value : {None, integer}
        Value used to pad shorter iterables.
    flatten : {True, False},
        Whether to
    """
    # OK, that's a complete ripoff from Python2.6 itertools.izip_longest
    def sentinel(counter=([fill_value] * (len(seqarrays) - 1)).pop):
        "Yields the fill_value or raises IndexError"
        yield counter()
    #
    fillers = itertools.repeat(fill_value)
    iters = [itertools.chain(it, sentinel(), fillers) for it in seqarrays]
    # Should we flatten the items, or just use a nested approach
    if flatten:
        zipfunc = _izip_fields_flat
    else:
        zipfunc = _izip_fields
    #
    try:
        for tup in zip(*iters):
            yield tuple(zipfunc(tup))
    except IndexError:
        pass 

# 需要导入模块: import future_builtins [as 别名]
# 或者: from future_builtins import zip [as 别名]
def test_itertools(self):
        from itertools import imap, izip, ifilter
        # We will assume that the itertools functions work, so provided
        # that we've got identical coppies, we will work!
        self.assertEqual(map, imap)
        self.assertEqual(zip, izip)
        self.assertEqual(filter, ifilter)
        # Testing that filter(None, stuff) raises a warning lives in
        # test_py3kwarn.py 

# 需要导入模块: import future_builtins [as 别名]
# 或者: from future_builtins import zip [as 别名]
def izip_records(seqarrays, fill_value=None, flatten=True):
    """
    Returns an iterator of concatenated items from a sequence of arrays.

    Parameters
    ----------
    seqarray : sequence of arrays
        Sequence of arrays.
    fill_value : {None, integer}
        Value used to pad shorter iterables.
    flatten : {True, False},
        Whether to
    """
    # OK, that's a complete ripoff from Python2.6 itertools.izip_longest
    def sentinel(counter=([fill_value] * (len(seqarrays) - 1)).pop):
        "Yields the fill_value or raises IndexError"
        yield counter()
    #
    fillers = itertools.repeat(fill_value)
    iters = [itertools.chain(it, sentinel(), fillers) for it in seqarrays]
    # Should we flatten the items, or just use a nested approach
    if flatten:
        zipfunc = _izip_fields_flat
    else:
        zipfunc = _izip_fields
    #
    try:
        for tup in zip(*iters):
            yield tuple(zipfunc(tup))
    except IndexError:
        pass 

# 需要导入模块: import future_builtins [as 别名]
# 或者: from future_builtins import zip [as 别名]
def apply_all_cells(F, n_jobs=-1, disp=1, *fnn_args, **fnn_kwargs):
        """
        Run FNN deconvolution on multiple cells in parallel

        Arguments:
        -----------------------------------------------------------------------
        F: ndarray, [nc, nt] or [nc, npix, nt]
            measured fluorescence values

        n_jobs: int scalar
            number of jobs to process in parallel. if n_jobs == -1, all cores
            are used.

        *fnn_args, **fnn_kwargs
            additional arguments to pass to deconvolve()

        Returns:
        -----------------------------------------------------------------------
        n_hat_best: ndarray, [nc, nt]
            MAP estimate of the most likely spike train

        c_hat_best: ndarray, [nc, nt]
            estimated intracellular calcium concentration (A.U.)

        LL: ndarray, [nc,]
            posterior log-likelihood of F given n_hat_best and theta_best

        theta_best: tuple, [nc,]
            model parameters, updated according to learn_theta
        """

        pool = Parallel(n_jobs=n_jobs, verbose=disp, pre_dispatch='n_jobs * 2')

        results = pool(delayed(deconvolve)
                       (rr, *fnn_args, **fnn_kwargs) for rr in F)

        n_hat, c_hat, LL, theta = zip(*results)
        n_hat, c_hat, LL = (np.vstack(a) for a in (n_hat, c_hat, LL))

        return n_hat, c_hat, LL, theta 

# 需要导入模块: import future_builtins [as 别名]
# 或者: from future_builtins import zip [as 别名]
def test_fast_slow_dimensions(openfn, kwargs):
    with openfn(**kwargs) as f:
        for iline, fline in zip(f.iline, f.fast):
            assert np.array_equal(iline, fline)

        for xline, sline in zip(f.xline, f.slow):
            assert np.array_equal(xline, sline) 

# 需要导入模块: import future_builtins [as 别名]
# 或者: from future_builtins import zip [as 别名]
def test_create_sgy(small):
    orig = str(small.dirname + '/small.sgy')
    fresh = str(small.dirname + '/fresh.sgy')
    with segyio.open(orig) as src:
        spec = segyio.spec()
        spec.format = int(src.format)
        spec.sorting = int(src.sorting)
        spec.samples = src.samples
        spec.ilines = src.ilines
        spec.xlines = src.xlines

        with segyio.create(fresh, spec) as dst:
            dst.text[0] = src.text[0]
            dst.bin = src.bin

            # copy all headers
            dst.header = src.header

            for i, srctr in enumerate(src.trace):
                dst.trace[i] = srctr

            dst.trace = src.trace

            # this doesn't work yet, some restructuring is necessary
            # if it turns out to be a desired feature it's rather easy to do
            # for dsth, srch in zip(dst.header, src.header):
            #    dsth = srch

            # for dsttr, srctr in zip(dst.trace, src.trace):
            #    dsttr = srctr

    assert filecmp.cmp(orig, fresh) 

# 需要导入模块: import future_builtins [as 别名]
# 或者: from future_builtins import zip [as 别名]
def test_ref_sliced(small):
    with segyio.open(small, mode = 'r+') as f:
        expected = f.trace.raw[:]
        expected[10:15] += expected[:5]

        with f.trace.ref as ref:
            for x, y in zip(ref[10:15], f.trace[:]):
                np.copyto(x, x + y)

    with segyio.open(small) as f:
        npt.assert_array_almost_equal(expected, f.trace.raw[:]) 

# 需要导入模块: import future_builtins [as 别名]
# 或者: from future_builtins import zip [as 别名]
def test_gather_mode():
    with segyio.open(testdata / 'small-ps.sgy') as f:
        empty = np.empty(0, dtype=np.single)
        # should raise
        with pytest.raises(KeyError):
            assert np.array_equal(empty, f.gather[2, 3, 3])

        with pytest.raises(KeyError):
            assert np.array_equal(empty, f.gather[2, 5, 1])

        with pytest.raises(KeyError):
            assert np.array_equal(empty, f.gather[5, 2, 1])

        assert np.array_equal(f.trace[10], f.gather[2, 3, 1])
        assert np.array_equal(f.trace[11], f.gather[2, 3, 2])

        traces = segyio.tools.collect(f.trace[10:12])
        gather = f.gather[2, 3, :]
        assert np.array_equal(traces, gather)
        assert np.array_equal(traces, f.gather[2, 3])
        assert np.array_equal(empty, f.gather[2, 3, 1:0])
        assert np.array_equal(empty, f.gather[2, 3, 3:4])

        for g, line in zip(f.gather[1:3, 3, 1], f.iline[1:3]):
            assert 10 == len(g)
            assert (10,) == g.shape
            assert np.array_equal(line[2], g)

        for g, line in zip(f.gather[1:3, 3, :], f.iline[1:3]):
            assert 2 == len(g)
            assert (2, 10) == g.shape
            assert np.array_equal(line[2], g[0])

        for g, line in zip(f.gather[:, 2, 1], f.iline[:]):
            assert 10 == len(g)
            assert (10,) == g.shape
            assert np.array_equal(line[1], g)

        for g, line in zip(f.gather[1, :, 1], f.xline[:]):
            assert 10 == len(g)
            assert (10,) == g.shape
            assert np.array_equal(line[0], g)

        # overshoot the inlines, should still work
        for g, line in zip(f.gather[3:10, 3, 1], f.iline[3:]):
            assert 10 == len(g)
            assert (10,) == g.shape
            print(g)
            print(line[0])
            assert np.array_equal(line[2], g)

        for g, line in zip(f.gather[1, 1:3, :], f.xline[1:3]):
            assert 2 == len(g)
            assert (2, 10) == g.shape
            assert np.array_equal(line[0], g[0])

        for g, line in zip(f.gather[1, 1:3, 3:4], f.xline[1:3]):
            assert np.array_equal(empty, g) 

# 需要导入模块: import future_builtins [as 别名]
# 或者: from future_builtins import zip [as 别名]
def test_create_from_naught_prestack(endian, tmpdir):
    spec = segyio.spec()
    spec.format = 5
    #spec.sorting not set by test design
    spec.samples = range(7)
    spec.ilines = range(1, 4)
    spec.xlines = range(1, 3)
    spec.offsets = range(1, 6)
    spec.endian = endian

    with segyio.create(tmpdir / "mk-ps.sgy", spec) as dst:
        arr = np.arange(start=0.000,
                        stop=0.007,
                        step=0.001,
                        dtype=np.single)

        arr = np.concatenate([[arr + 0.01], [arr + 0.02]], axis=0)
        lines = [arr + i for i in spec.ilines]
        cube = [(off * 100) + line for line in lines for off in spec.offsets]

        dst.iline[:, :] = cube

        for of in spec.offsets:
            for il in spec.ilines:
                dst.header.iline[il, of] = {TraceField.INLINE_3D: il,
                                            TraceField.offset: of
                                            }
            for xl in spec.xlines:
                dst.header.xline[xl, of] = {TraceField.CROSSLINE_3D: xl}

    with segyio.open(tmpdir / "mk-ps.sgy", endian = endian) as f:
        assert 101.010 == approx(f.trace[0][0], abs=1e-4)
        assert 101.011 == approx(f.trace[0][1], abs=1e-4)
        assert 101.016 == approx(f.trace[0][-1], abs=1e-4)
        assert 503.025 == approx(f.trace[-1][5], abs=1e-4)
        assert f.header[0][TraceField.offset] != f.header[1][TraceField.offset]
        assert 1 == f.header[0][TraceField.offset]
        assert 2 == f.header[1][TraceField.offset]

        for x, y in zip(f.iline[:, :], cube):
            assert list(x.flatten()) == list(y.flatten())

        assert f.sorting == TraceSortingFormat.INLINE_SORTING 

# 需要导入模块: import future_builtins [as 别名]
# 或者: from future_builtins import zip [as 别名]
def test_group_multi_key_corret_index():
    with segyio.open(testdata / 'shot-gather.sgy', ignore_geometry = True) as f:
        group = f.group((segyio.su.fldr, segyio.su.grnofr))
        assert len(group) == 8

        expected_keys = [
            ((segyio.su.fldr, 2), (segyio.su.grnofr, 1)),
            ((segyio.su.fldr, 2), (segyio.su.grnofr, 2)),
            ((segyio.su.fldr, 3), (segyio.su.grnofr, 1)),
            ((segyio.su.fldr, 3), (segyio.su.grnofr, 2)),
            ((segyio.su.fldr, 5), (segyio.su.grnofr, 1)),
            ((segyio.su.fldr, 5), (segyio.su.grnofr, 2)),
            ((segyio.su.fldr, 8), (segyio.su.grnofr, 1)),
            ((segyio.su.fldr, 8), (segyio.su.grnofr, 2)),
        ]

        expected_keys = [frozenset(k) for k in expected_keys]

        indices = [
            # fldr = 2, grnofr = 1
            [0, 2, 4, 6, 8],
            # fldr = 2, grnofr = 2
            [1, 3, 5, 7, 9],

            # fldr = 3, grnofr = 1
            [10, 12, 14, 16, 18, 20],
            # fldr = 3, grnofr = 2
            [11, 13, 15, 17, 19, 21],

            # fldr = 5, grnofr = 1
            [22, 24, 26, 28, 30, 32, 34],
            # fldr = 5, grnofr = 2
            [23, 25, 27, 29, 31, 33],

            # fldr = 8, grnofr = 1
            [35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59],
            # fldr = 8, grnofr = 2
            [36, 38, 40, 42, 44, 46, 48, 50, 52, 54, 56, 58, 60],
        ]

        # this test checks that every individual group maps to the known index
        # it's supposed to model. it would be more elegant to represent the
        # indices as a key -> index dict, but that makes verifying that every
        # key/index pair is covered uglier
        assert len(expected_keys) == len(indices)

        for key, index, shot in zip(expected_keys, indices, group.values()):
            assert index == shot.index
            assert key == shot.key