Python numpy.int16() Examples

The following are 30 code examples for showing how to use numpy.int16(). These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.

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Example 1
Project: sklearn-audio-transfer-learning   Author: jordipons   File: utils.py    License: ISC License 6 votes vote down vote up
def wavefile_to_waveform(wav_file, features_type):
    data, sr = sf.read(wav_file)
    if features_type == 'vggish':
        tmp_name = str(int(np.random.rand(1)*1000000)) + '.wav'
        sf.write(tmp_name, data, sr, subtype='PCM_16')
        sr, wav_data = wavfile.read(tmp_name)
        os.remove(tmp_name)
        # sr, wav_data = wavfile.read(wav_file) # as done in VGGish Audioset
        assert wav_data.dtype == np.int16, 'Bad sample type: %r' % wav_data.dtype
        data = wav_data / 32768.0  # Convert to [-1.0, +1.0]
  
    # at least one second of samples, if not repead-pad
    src_repeat = data
    while (src_repeat.shape[0] < sr): 
        src_repeat = np.concatenate((src_repeat, data), axis=0)
        data = src_repeat[:sr]

    return data, sr 
Example 2
Project: pyscf   Author: pyscf   File: numpy_helper.py    License: Apache License 2.0 6 votes vote down vote up
def frompointer(pointer, count, dtype=float):
    '''Interpret a buffer that the pointer refers to as a 1-dimensional array.

    Args:
        pointer : int or ctypes pointer
            address of a buffer
        count : int
            Number of items to read.
        dtype : data-type, optional
            Data-type of the returned array; default: float.

    Examples:

    >>> s = numpy.ones(3, dtype=numpy.int32)
    >>> ptr = s.ctypes.data
    >>> frompointer(ptr, count=6, dtype=numpy.int16)
    [1, 0, 1, 0, 1, 0]
    '''
    dtype = numpy.dtype(dtype)
    count *= dtype.itemsize
    buf = (ctypes.c_char * count).from_address(pointer)
    a = numpy.ndarray(count, dtype=numpy.int8, buffer=buf)
    return a.view(dtype) 
Example 3
Project: me-ica   Author: ME-ICA   File: test_arraywriters.py    License: GNU Lesser General Public License v2.1 6 votes vote down vote up
def test_no_offset_scale():
    # Specific tests of no-offset scaling
    SAW = SlopeArrayWriter
    # Floating point
    for data in ((-128, 127),
                  (-128, 126),
                  (-128, -127),
                  (-128, 0),
                  (-128, -1),
                  (126, 127),
                  (-127, 127)):
        aw = SAW(np.array(data, dtype=np.float32), np.int8)
        assert_equal(aw.slope, 1.0)
    aw = SAW(np.array([-126, 127 * 2.0], dtype=np.float32), np.int8)
    assert_equal(aw.slope, 2)
    aw = SAW(np.array([-128 * 2.0, 127], dtype=np.float32), np.int8)
    assert_equal(aw.slope, 2)
    # Test that nasty abs behavior does not upset us
    n = -2**15
    aw = SAW(np.array([n, n], dtype=np.int16), np.uint8)
    assert_array_almost_equal(aw.slope, n / 255.0, 5) 
Example 4
Project: me-ica   Author: ME-ICA   File: test_arraywriters.py    License: GNU Lesser General Public License v2.1 6 votes vote down vote up
def test_writer_maker():
    arr = np.arange(10, dtype=np.float64)
    aw = make_array_writer(arr, np.float64)
    assert_true(isinstance(aw, SlopeInterArrayWriter))
    aw = make_array_writer(arr, np.float64, True, True)
    assert_true(isinstance(aw, SlopeInterArrayWriter))
    aw = make_array_writer(arr, np.float64, True, False)
    assert_true(isinstance(aw, SlopeArrayWriter))
    aw = make_array_writer(arr, np.float64, False, False)
    assert_true(isinstance(aw, ArrayWriter))
    assert_raises(ValueError, make_array_writer, arr, np.float64, False)
    assert_raises(ValueError, make_array_writer, arr, np.float64, False, True)
    # Does calc_scale get run by default?
    aw = make_array_writer(arr, np.int16, calc_scale=False)
    assert_equal((aw.slope, aw.inter), (1, 0))
    aw.calc_scale()
    slope, inter = aw.slope, aw.inter
    assert_false((slope, inter) == (1, 0))
    # Should run by default
    aw = make_array_writer(arr, np.int16)
    assert_equal((aw.slope, aw.inter), (slope, inter))
    aw = make_array_writer(arr, np.int16, calc_scale=True)
    assert_equal((aw.slope, aw.inter), (slope, inter)) 
Example 5
Project: me-ica   Author: ME-ICA   File: test_casting.py    License: GNU Lesser General Public License v2.1 6 votes vote down vote up
def test_able_int_type():
    # The integer type cabable of containing values
    for vals, exp_out in (
        ([0, 1], np.uint8),
        ([0, 255], np.uint8),
        ([-1, 1], np.int8),
        ([0, 256], np.uint16),
        ([-1, 128], np.int16),
        ([0.1, 1], None),
        ([0, 2**16], np.uint32),
        ([-1, 2**15], np.int32),
        ([0, 2**32], np.uint64),
        ([-1, 2**31], np.int64),
        ([-1, 2**64-1], None),
        ([0, 2**64-1], np.uint64),
        ([0, 2**64], None)):
        assert_equal(able_int_type(vals), exp_out) 
Example 6
Project: me-ica   Author: ME-ICA   File: test_spatialimages.py    License: GNU Lesser General Public License v2.1 6 votes vote down vote up
def test_isolation(self):
        # Test image isolated from external changes to header and affine
        img_klass = self.image_class
        arr = np.arange(3, dtype=np.int16)
        aff = np.eye(4)
        img = img_klass(arr, aff)
        assert_array_equal(img.get_affine(), aff)
        aff[0,0] = 99
        assert_false(np.all(img.get_affine() == aff))
        # header, created by image creation
        ihdr = img.get_header()
        # Pass it back in
        img = img_klass(arr, aff, ihdr)
        # Check modifying header outside does not modify image
        ihdr.set_zooms((4,))
        assert_not_equal(img.get_header(), ihdr) 
Example 7
Project: me-ica   Author: ME-ICA   File: test_scaling.py    License: GNU Lesser General Public License v2.1 6 votes vote down vote up
def test_calculate_scale():
    # Test for special cases in scale calculation
    npa = np.array
    # Here the offset handles it
    res = calculate_scale(npa([-2, -1], dtype=np.int8), np.uint8, True)
    assert_equal(res, (1.0, -2.0, None, None))
    # Not having offset not a problem obviously
    res = calculate_scale(npa([-2, -1], dtype=np.int8), np.uint8, 0)
    assert_equal(res, (-1.0, 0.0, None, None))
    # Case where offset handles scaling
    res = calculate_scale(npa([-1, 1], dtype=np.int8), np.uint8, 1)
    assert_equal(res, (1.0, -1.0, None, None))
    # Can't work for no offset case
    assert_raises(ValueError,
                  calculate_scale, npa([-1, 1], dtype=np.int8), np.uint8, 0)
    # Offset trick can't work when max is out of range
    res = calculate_scale(npa([-1, 255], dtype=np.int16), np.uint8, 1)
    assert_not_equal(res, (1.0, -1.0, None, None)) 
Example 8
Project: me-ica   Author: ME-ICA   File: test_utils.py    License: GNU Lesser General Public License v2.1 6 votes vote down vote up
def test_can_cast():
    tests = ((np.float32, np.float32, True, True, True),
             (np.float64, np.float32, True, True, True),
             (np.complex128, np.float32, False, False, False),
             (np.float32, np.complex128, True, True, True),
             (np.float32, np.uint8, False, True, True),
             (np.uint32, np.complex128, True, True, True),
             (np.int64, np.float32, True, True, True),
             (np.complex128, np.int16, False, False, False),
             (np.float32, np.int16, False, True, True),
             (np.uint8, np.int16, True, True, True),
             (np.uint16, np.int16, False, True, True),
             (np.int16, np.uint16, False, False, True),
             (np.int8, np.uint16, False, False, True),
             (np.uint16, np.uint8, False, True, True),
             )
    for intype, outtype, def_res, scale_res, all_res in tests:
        assert_equal(def_res, can_cast(intype, outtype))
        assert_equal(scale_res, can_cast(intype, outtype, False, True))
        assert_equal(all_res, can_cast(intype, outtype, True, True)) 
Example 9
Project: me-ica   Author: ME-ICA   File: test_arrayproxy.py    License: GNU Lesser General Public License v2.1 6 votes vote down vote up
def test_nifti1_init():
    bio = BytesIO()
    shape = (2,3,4)
    hdr = Nifti1Header()
    arr = np.arange(24, dtype=np.int16).reshape(shape)
    write_raw_data(arr, hdr, bio)
    hdr.set_slope_inter(2, 10)
    ap = ArrayProxy(bio, hdr)
    assert_true(ap.file_like == bio)
    assert_equal(ap.shape, shape)
    # Check there has been a copy of the header
    assert_false(ap.header is hdr)
    # Get the data
    assert_array_equal(np.asarray(ap), arr * 2.0 + 10)
    with InTemporaryDirectory():
        f = open('test.nii', 'wb')
        write_raw_data(arr, hdr, f)
        f.close()
        ap = ArrayProxy('test.nii', hdr)
        assert_true(ap.file_like == 'test.nii')
        assert_equal(ap.shape, shape)
        assert_array_equal(np.asarray(ap), arr * 2.0 + 10) 
Example 10
Project: hsds   Author: HDFGroup   File: hdf5dtypeTest.py    License: Apache License 2.0 6 votes vote down vote up
def testCreateBaseType(self):
        dt = hdf5dtype.createDataType('H5T_STD_U32BE')
        self.assertEqual(dt.name, 'uint32')
        self.assertEqual(dt.byteorder, '>')
        self.assertEqual(dt.kind, 'u')

        dt = hdf5dtype.createDataType('H5T_STD_I16LE')
        self.assertEqual(dt.name, 'int16')
        self.assertEqual(dt.kind, 'i')

        dt = hdf5dtype.createDataType('H5T_IEEE_F64LE')
        self.assertEqual(dt.name, 'float64')
        self.assertEqual(dt.kind, 'f')

        dt = hdf5dtype.createDataType('H5T_IEEE_F32LE')
        self.assertEqual(dt.name, 'float32')
        self.assertEqual(dt.kind, 'f')

        typeItem = { 'class': 'H5T_INTEGER', 'base': 'H5T_STD_I32BE' }
        typeSize = hdf5dtype.getItemSize(typeItem)
        dt = hdf5dtype.createDataType(typeItem)
        self.assertEqual(dt.name, 'int32')
        self.assertEqual(dt.kind, 'i')
        self.assertEqual(typeSize, 4) 
Example 11
Project: blow   Author: joansj   File: audio.py    License: Apache License 2.0 6 votes vote down vote up
def synthesize(frames,filename,stride,sr=16000,deemph=0,ymax=0.98,normalize=False):
    # Generate stream
    y=torch.zeros((len(frames)-1)*stride+len(frames[0]))
    for i,x in enumerate(frames):
        y[i*stride:i*stride+len(x)]+=x
    # To numpy & deemph
    y=y.numpy().astype(np.float32)
    if deemph>0:
        y=deemphasis(y,alpha=deemph)
    # Normalize
    if normalize:
        y-=np.mean(y)
        mx=np.max(np.abs(y))
        if mx>0:
            y*=ymax/mx
    else:
        y=np.clip(y,-ymax,ymax)
    # To 16 bit & save
    wavfile.write(filename,sr,np.array(y*32767,dtype=np.int16))
    return y

######################################################################################################################## 
Example 12
Project: Black-Box-Audio   Author: rtaori   File: run_audio_attack.py    License: MIT License 5 votes vote down vote up
def save_wav(audio, output_wav_file):
    wav.write(output_wav_file, 16000, np.array(np.clip(np.round(audio), -2**15, 2**15-1), dtype=np.int16))
    print('output dB', db(audio)) 
Example 13
Project: vergeml   Author: mme   File: env.py    License: MIT License 5 votes vote down vote up
def _convert(self, vals):
        res = {}
        for k, v in vals.items():
            if isinstance(v, (np.int, np.int8, np.int16, np.int32, np.int64)):
                v = int(v)
            elif isinstance(v, (np.float, np.float16, np.float32, np.float64)):
                v = float(v)
            elif isinstance(v, Labels):
                v = list(v)
            elif isinstance(v, np.ndarray):
                v = v.tolist()
            elif isinstance(v, dict):
                v = self._convert(v)
            res[k] = v
        return res 
Example 14
Project: vergeml   Author: mme   File: env.py    License: MIT License 5 votes vote down vote up
def _toscalar(v):
    if isinstance(v, (np.float16, np.float32, np.float64,
                      np.uint8, np.uint16, np.uint32, np.uint64,
                      np.int8, np.int16, np.int32, np.int64)):
        return np.asscalar(v)
    else:
        return v 
Example 15
Project: spectrum_painter   Author: polygon   File: radios.py    License: MIT License 5 votes vote down vote up
def convert(self, complex_iq):
        intlv = self._interleave(complex_iq)
        clipped = self._clip(intlv, limit=1.0)
        converted = 2047. * clipped
        bladerf_out = converted.astype(np.int16)
        return bladerf_out 
Example 16
Project: Griffin_lim   Author: candlewill   File: audio.py    License: MIT License 5 votes vote down vote up
def save_wav(wav, path):
    wav *= 32767 / max(0.01, np.max(np.abs(wav)))
    wavfile.write(path, hparams.sample_rate, wav.astype(np.int16)) 
Example 17
Project: Deep_VoiceChanger   Author: pstuvwx   File: gla_gpu.py    License: MIT License 5 votes vote down vote up
def save(path, bps, data):
        if data.dtype != np.int16:
            data = data.astype(np.int16)
        data = np.reshape(data, -1)
        wav.write(path, bps, data) 
Example 18
Project: Deep_VoiceChanger   Author: pstuvwx   File: gla_util.py    License: MIT License 5 votes vote down vote up
def save(path, bps, data):
        if data.dtype != np.int16:
            data = data.astype(np.int16)
        data = np.reshape(data, -1)
        wav.write(path, bps, data) 
Example 19
Project: Deep_VoiceChanger   Author: pstuvwx   File: dataset.py    License: MIT License 5 votes vote down vote up
def save(path, bps, data):
    if data.dtype != np.int16:
        data = data.astype(np.int16)
    data = np.reshape(data, -1)
    wav.write(path, bps, data) 
Example 20
Project: NiBetaSeries   Author: HBClab   File: conftest.py    License: MIT License 5 votes vote down vote up
def brainmask_file(deriv_dir,
                   deriv_mask_fname=deriv_mask_fname):
    brainmask_file = deriv_dir.ensure(deriv_mask_fname)
    bm_data = np.array([[[1, 1]]], dtype=np.int16)
    bm_img = nib.Nifti1Image(bm_data, np.eye(4))
    bm_img.to_filename(str(brainmask_file))
    return brainmask_file 
Example 21
Project: NiBetaSeries   Author: HBClab   File: conftest.py    License: MIT License 5 votes vote down vote up
def atlas_file(tmpdir_factory):
    atlas_file = tmpdir_factory.mktemp("atlas").join("atlas.nii.gz")
    atlas_data = np.array([[[1, 2]]], dtype=np.int16)
    atlas_img = nib.Nifti1Image(atlas_data, np.eye(4))
    atlas_img.to_filename(str(atlas_file))

    return atlas_file 
Example 22
Project: neuropythy   Author: noahbenson   File: images.py    License: GNU Affero General Public License v3.0 5 votes vote down vote up
def parse_type(self, hdat, dataobj=None):
        dtype = super(MGHImageType, self).parse_type(hdat, dataobj=dataobj)
        if   np.issubdtype(dtype, np.floating): dtype = np.float32
        elif np.issubdtype(dtype, np.int8):     dtype = np.int8
        elif np.issubdtype(dtype, np.int16):    dtype = np.int16
        elif np.issubdtype(dtype, np.integer):  dtype = np.int32
        else: raise ValueError('Could not deduce appropriate MGH type for dtype %s' % dtype)
        return dtype 
Example 23
Project: DeepLab_v3_plus   Author: songdejia   File: util.py    License: MIT License 5 votes vote down vote up
def encode_segmap(mask):
    """Encode segmentation label images as pascal classes
    Args:
        mask (np.ndarray): raw segmentation label image of dimension
          (M, N, 3), in which the Pascal classes are encoded as colours.
    Returns:
        (np.ndarray): class map with dimensions (M,N), where the value at
        a given location is the integer denoting the class index.
    """
    mask = mask.astype(int)
    label_mask = np.zeros((mask.shape[0], mask.shape[1]), dtype=np.int16)
    for ii, label in enumerate(get_pascal_labels()):
        label_mask[np.where(np.all(mask == label, axis=-1))[:2]] = ii
    label_mask = label_mask.astype(int)
    return label_mask 
Example 24
Project: GST-Tacotron   Author: KinglittleQ   File: cutoff.py    License: MIT License 5 votes vote down vote up
def cutoff(input_wav, output_wav):
    '''
    input_wav --- input wav file path
    output_wav --- output wav file path
    '''

    # read input wave file and get parameters.
    with wave.open(input_wav, 'r') as fw:
        params = fw.getparams()
        # print(params)
        nchannels, sampwidth, framerate, nframes = params[:4]

        strData = fw.readframes(nframes)
        waveData = np.fromstring(strData, dtype=np.int16)

        max_v = np.max(abs(waveData))
        for i in range(waveData.shape[0]):
            if abs(waveData[i]) > 0.08 * max_v:
                break

        for j in range(waveData.shape[0] - 1, 0, -1):
            if abs(waveData[j]) > 0.08 * max_v:
                break

    # write new wav file
    with wave.open(output_wav, 'w') as fw:
        params = list(params)
        params[3] = nframes - i - (waveData.shape[0] - 1 - j)
        fw.setparams(params)
        fw.writeframes(strData[2 * i:2 * (j + 1)]) 
Example 25
Project: QCElemental   Author: MolSSI   File: molecule.py    License: BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def atomic_numbers(self) -> Array[np.int16]:
        atomic_numbers = self.__dict__.get("atomic_numbers_")
        if atomic_numbers is None:
            atomic_numbers = np.array([periodictable.to_Z(x) for x in self.symbols])
        return atomic_numbers 
Example 26
Project: QCElemental   Author: MolSSI   File: molecule.py    License: BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def mass_numbers(self) -> Array[np.int16]:
        mass_numbers = self.__dict__.get("mass_numbers_")
        if mass_numbers is None:
            mass_numbers = np.array([periodictable.to_A(x) for x in self.symbols])
        return mass_numbers 
Example 27
Project: openISP   Author: cruxopen   File: hsc.py    License: MIT License 5 votes vote down vote up
def execute(self):
        lut_sin, lut_cos = self.lut()
        img_h = self.img.shape[0]
        img_w = self.img.shape[1]
        img_c = self.img.shape[2]
        hsc_img = np.empty((img_h, img_w, img_c), np.int16)
        for y in range(img_h):
            for x in range(img_w):
                hsc_img[y,x,0] = (self.img[y,x,0] - 128) * lut_cos[self.hue] + (self.img[y,x,1] - 128) * lut_sin[self.hue] + 128
                hsc_img[y,x,1] = (self.img[y,x,1] - 128) * lut_cos[self.hue] - (self.img[y,x,0] - 128) * lut_sin[self.hue] + 128
                hsc_img[y,x,0] = self.saturation * (self.img[y,x,0] - 128) / 256 + 128
                hsc_img[y,x,1] = self.saturation * (self.img[y,x,1] - 128) / 256 + 128
        self.img = hsc_img
        return self.clipping() 
Example 28
Project: openISP   Author: cruxopen   File: bcc.py    License: MIT License 5 votes vote down vote up
def execute(self):
        img_h = self.img.shape[0]
        img_w = self.img.shape[1]
        bcc_img = np.empty((img_h, img_w), np.int16)
        for y in range(img_h):
            for x in range(img_w):
                bcc_img[y,x] = self.img[y,x] + self.brightness
                bcc_img[y,x] = self.img[y,x] + (self.img[y,x] - 127) * self.contrast
        self.img = bcc_img
        return self.clipping() 
Example 29
Project: openISP   Author: cruxopen   File: eeh.py    License: MIT License 5 votes vote down vote up
def execute(self):
        img_pad = self.padding()
        img_h = self.img.shape[0]
        img_w = self.img.shape[1]
        ee_img = np.empty((img_h, img_w), np.int16)
        em_img = np.empty((img_h, img_w), np.int16)
        for y in range(img_pad.shape[0] - 2):
            for x in range(img_pad.shape[1] - 4):
                em_img[y,x] = np.sum(np.multiply(img_pad[y:y+3, x:x+5], self.edge_filter[:, :])) / 8
                ee_img[y,x] = img_pad[y+1,x+2] + self.emlut(em_img[y,x], self.thres, self.gain, self.emclip)
        self.img = ee_img
        return self.clipping(), em_img 
Example 30
Project: L3C-PyTorch   Author: fab-jul   File: images_loader.py    License: GNU General Public License v3.0 5 votes vote down vote up
def to_tensor_not_normalized(pic):
    """ copied from PyTorch functional.to_tensor, removed final .float().div(255.) """
    if isinstance(pic, np.ndarray):
        # handle numpy array
        img = torch.from_numpy(pic.transpose((2, 0, 1)))
        return img

    # handle PIL Image
    if pic.mode == 'I':
        img = torch.from_numpy(np.array(pic, np.int32, copy=False))
    elif pic.mode == 'I;16':
        img = torch.from_numpy(np.array(pic, np.int16, copy=False))
    elif pic.mode == 'F':
        img = torch.from_numpy(np.array(pic, np.float32, copy=False))
    elif pic.mode == '1':
        img = 255 * torch.from_numpy(np.array(pic, np.uint8, copy=False))
    else:
        img = torch.ByteTensor(torch.ByteStorage.from_buffer(pic.tobytes()))
    # PIL image mode: L, P, I, F, RGB, YCbCr, RGBA, CMYK
    if pic.mode == 'YCbCr':
        nchannel = 3
    elif pic.mode == 'I;16':
        nchannel = 1
    else:
        nchannel = len(pic.mode)
    img = img.view(pic.size[1], pic.size[0], nchannel)
    # put it from HWC to CHW format
    # yikes, this transpose takes 80% of the loading time/CPU
    img = img.transpose(0, 1).transpose(0, 2).contiguous()
    return img