numpy.fromfile - python examples

Here are the examples of the python api numpy.fromfile taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.

145 Examples 7

3 View Complete Implementation : test_vq.py
Copyright MIT License
Author : ktraunmueller
    def test_kmeans2_init(self):
        """Testing that kmeans2 init methods work."""
        data = np.fromfile(DATAFILE1, sep=", ")
        data = data.reshape((200, 2))

        kmeans2(data, 3, minit='points')
        kmeans2(data[:, :1], 3, minit='points')  # special case (1-D)

        # minit='random' can give warnings, filter those
        warn_ctx = WarningManager()
        warn_ctx.__enter__()
        try:
            warnings.filterwarnings('ignore',
                        message="One of the clusters is empty. Re-run")
            kmeans2(data, 3, minit='random')
            kmeans2(data[:, :1], 3, minit='random')  # special case (1-D)
        finally:
            warn_ctx.__exit__()

3 View Complete Implementation : test_vq.py
Copyright MIT License
Author : ktraunmueller
    def test_kmeans2_rank1(self):
        """Testing simple call to kmeans2 with rank 1 data."""
        data = np.fromfile(DATAFILE1, sep=", ")
        data = data.reshape((200, 2))
        data1 = data[:, 0]
        data2 = data[:, 1]

        initc = data1[:3]
        code = initc.copy()
        code1 = kmeans2(data1, code, iter=1)[0]
        code2 = kmeans2(data1, code, iter=2)[0]

3 View Complete Implementation : test_vq.py
Copyright MIT License
Author : ktraunmueller
    def test_kmeans2_init(self):
        """Testing that kmeans2 init methods work."""
        data = np.fromfile(DATAFILE1, sep=", ")
        data = data.reshape((200, 2))

        kmeans2(data, 3, minit='points')
        kmeans2(data[:, :1], 3, minit='points')  # special case (1-D)

        # minit='random' can give warnings, filter those
        warn_ctx = WarningManager()
        warn_ctx.__enter__()
        try:
            warnings.filterwarnings('ignore',
                        message="One of the clusters is empty. Re-run")
            kmeans2(data, 3, minit='random')
            kmeans2(data[:, :1], 3, minit='random')  # special case (1-D)
        finally:
            warn_ctx.__exit__()

3 View Complete Implementation : test_vq.py
Copyright MIT License
Author : ktraunmueller
    def test_kmeans2_rank1(self):
        """Testing simple call to kmeans2 with rank 1 data."""
        data = np.fromfile(DATAFILE1, sep=", ")
        data = data.reshape((200, 2))
        data1 = data[:, 0]
        data2 = data[:, 1]

        initc = data1[:3]
        code = initc.copy()
        code1 = kmeans2(data1, code, iter=1)[0]
        code2 = kmeans2(data1, code, iter=2)[0]

3 View Complete Implementation : test_vq.py
Copyright MIT License
Author : ktraunmueller
    def test_kmeans_lost_cluster(self):
        """This will cause kmean to have a cluster with no points."""
        data = np.fromfile(DATAFILE1, sep=", ")
        data = data.reshape((200, 2))
        initk = np.array([[-1.8127404, -0.67128041],
                         [2.04621601, 0.07401111],
                         [-2.31149087,-0.05160469]])

        res = kmeans(data, initk)

        warn_ctx = WarningManager()
        warn_ctx.__enter__()
        try:
            warnings.simplefilter('ignore', UserWarning)
            res = kmeans2(data, initk, missing='warn')
        finally:
            warn_ctx.__exit__()

        astert_raises(ClusterError, kmeans2, data, initk, missing='raise')

3 View Complete Implementation : test_vq.py
Copyright MIT License
Author : ktraunmueller
    def test_kmeans_lost_cluster(self):
        """This will cause kmean to have a cluster with no points."""
        data = np.fromfile(DATAFILE1, sep=", ")
        data = data.reshape((200, 2))
        initk = np.array([[-1.8127404, -0.67128041],
                         [2.04621601, 0.07401111],
                         [-2.31149087,-0.05160469]])

        res = kmeans(data, initk)

        warn_ctx = WarningManager()
        warn_ctx.__enter__()
        try:
            warnings.simplefilter('ignore', UserWarning)
            res = kmeans2(data, initk, missing='warn')
        finally:
            warn_ctx.__exit__()

        astert_raises(ClusterError, kmeans2, data, initk, missing='raise')

3 View Complete Implementation : seviri_l1b_hrit.py
Copyright GNU General Public License v3.0
Author : pytroll
    def read_prologue(self):
        """Read the prologue metadata."""
        with open(self.filename, "rb") as fp_:
            fp_.seek(self.mda['total_header_length'])
            data = np.fromfile(fp_, dtype=hrit_prologue, count=1)
            self.prologue.update(recarray2dict(data))
            try:
                impf = np.fromfile(fp_, dtype=impf_configuration, count=1)[0]
            except IndexError:
                logger.info('No IMPF configuration field found in prologue.')
            else:
                self.prologue.update(recarray2dict(impf))

3 View Complete Implementation : seviri_l1b_native.py
Copyright GNU General Public License v3.0
Author : pytroll
    def _read_trailer(self):

        hdr_size = native_header.itemsize
        data_size = (self._get_data_dtype().itemsize *
                     self.mda['number_of_lines'])

        with open(self.filename) as fp:

            fp.seek(hdr_size + data_size)
            data = np.fromfile(fp, dtype=native_trailer, count=1)

        self.trailer.update(recarray2dict(data))

3 View Complete Implementation : test_vq.py
Copyright MIT License
Author : ktraunmueller
    def test_kmeans2_rank1_2(self):
        """Testing simple call to kmeans2 with rank 1 data."""
        data = np.fromfile(DATAFILE1, sep=", ")
        data = data.reshape((200, 2))
        data1 = data[:, 0]

        code1 = kmeans2(data1, 2, iter=1)

3 View Complete Implementation : test_vq.py
Copyright MIT License
Author : ktraunmueller
    def test_kmeans2_rank1_2(self):
        """Testing simple call to kmeans2 with rank 1 data."""
        data = np.fromfile(DATAFILE1, sep=", ")
        data = data.reshape((200, 2))
        data1 = data[:, 0]

        code1 = kmeans2(data1, 2, iter=1)