Python ma.getdata方法代码示例

# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import getdata [as 别名]
def masked_rec_array_to_mgr(data, index, columns, dtype, copy):
    """
    Extract from a masked rec array and create the manager.
    """

    # essentially process a record array then fill it
    fill_value = data.fill_value
    fdata = ma.getdata(data)
    if index is None:
        index = get_names_from_index(fdata)
        if index is None:
            index = ibase.default_index(len(data))
    index = ensure_index(index)

    if columns is not None:
        columns = ensure_index(columns)
    arrays, arr_columns = to_arrays(fdata, columns)

    # fill if needed
    new_arrays = []
    for fv, arr, col in zip(fill_value, arrays, arr_columns):
        mask = ma.getmaskarray(data[col])
        if mask.any():
            arr, fv = maybe_upcast(arr, fill_value=fv, copy=True)
            arr[mask] = fv
        new_arrays.append(arr)

    # create the manager
    arrays, arr_columns = reorder_arrays(new_arrays, arr_columns, columns)
    if columns is None:
        columns = arr_columns

    mgr = arrays_to_mgr(arrays, arr_columns, index, columns, dtype)

    if copy:
        mgr = mgr.copy()
    return mgr


# ---------------------------------------------------------------------
# DataFrame Constructor Interface 

# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import getdata [as 别名]
def _masked_rec_array_to_mgr(data, index, columns, dtype, copy):
    """ extract from a masked rec array and create the manager """

    # essentially process a record array then fill it
    fill_value = data.fill_value
    fdata = ma.getdata(data)
    if index is None:
        index = _get_names_from_index(fdata)
        if index is None:
            index = _default_index(len(data))
    index = _ensure_index(index)

    if columns is not None:
        columns = _ensure_index(columns)
    arrays, arr_columns = _to_arrays(fdata, columns)

    # fill if needed
    new_arrays = []
    for fv, arr, col in zip(fill_value, arrays, arr_columns):
        mask = ma.getmaskarray(data[col])
        if mask.any():
            arr, fv = _maybe_upcast(arr, fill_value=fv, copy=True)
            arr[mask] = fv
        new_arrays.append(arr)

    # create the manager
    arrays, arr_columns = _reorder_arrays(new_arrays, arr_columns, columns)
    if columns is None:
        columns = arr_columns

    mgr = _arrays_to_mgr(arrays, arr_columns, index, columns)

    if copy:
        mgr = mgr.copy()
    return mgr 

# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import getdata [as 别名]
def getDataOnly(array1d):
    '''
    Removes redundant no data slots in a 1D array
    Note that sometimes data is missing within the array, so in the majority of cases, the array just needs to be shortened, but in a small number of cases, the 'within array' no data needs to be replaced
    :param array1d:
    :return: Simple array of numbers
    '''

    if np.any(ma.getmask(array1d)):
        mymask = np.invert(ma.getmask(array1d))
        outarray = ma.getdata(array1d)[mymask]
    else:
        outarray = ma.getdata(array1d)

    return outarray 

# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import getdata [as 别名]
def update_json(props, varname, data, datatype):
    """
    Adds an extra field to the properties of a feature in a geojson file. Provides a consistent way to handle different data types
    :param props: dictionary of properties
    :param varname: string variable name
    :param data: the data to add
    :param datatype: datatype
    :return: updated props
    """

    if isinstance(data, ma.MaskedArray) and (data.shape == ()) and ('int' in str(datatype)):
        props.update({varname: np.int(ma.getdata(data))})

    elif isinstance(data, ma.MaskedArray) and (data.shape == ()) and ('float' in str(datatype)):
        props.update({varname: np.float(ma.getdata(data))})

    elif isinstance(data, np.float32) or isinstance(data, np.float):
        props.update({varname: float(data)})

    elif isinstance(data, np.int) or isinstance(data, np.uint16):
        props.update({varname: int(data)})

    elif str(datatype) == 'string':
        props.update({varname: str(data)})

    else:
        return 

# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import getdata [as 别名]
def test_set_fields(self):
        # Tests setting fields.
        base = self.base.copy()
        mbase = base.view(mrecarray)
        mbase = mbase.copy()
        mbase.fill_value = (999999, 1e20, 'N/A')
        # Change the data, the mask should be conserved
        mbase.a._data[:] = 5
        assert_equal(mbase['a']._data, [5, 5, 5, 5, 5])
        assert_equal(mbase['a']._mask, [0, 1, 0, 0, 1])
        # Change the elements, and the mask will follow
        mbase.a = 1
        assert_equal(mbase['a']._data, [1]*5)
        assert_equal(ma.getmaskarray(mbase['a']), [0]*5)
        # Use to be _mask, now it's recordmask
        assert_equal(mbase.recordmask, [False]*5)
        assert_equal(mbase._mask.tolist(),
                     np.array([(0, 0, 0),
                               (0, 1, 1),
                               (0, 0, 0),
                               (0, 0, 0),
                               (0, 1, 1)],
                              dtype=bool))
        # Set a field to mask ........................
        mbase.c = masked
        # Use to be mask, and now it's still mask !
        assert_equal(mbase.c.mask, [1]*5)
        assert_equal(mbase.c.recordmask, [1]*5)
        assert_equal(ma.getmaskarray(mbase['c']), [1]*5)
        assert_equal(ma.getdata(mbase['c']), [b'N/A']*5)
        assert_equal(mbase._mask.tolist(),
                     np.array([(0, 0, 1),
                               (0, 1, 1),
                               (0, 0, 1),
                               (0, 0, 1),
                               (0, 1, 1)],
                              dtype=bool))
        # Set fields by slices .......................
        mbase = base.view(mrecarray).copy()
        mbase.a[3:] = 5
        assert_equal(mbase.a, [1, 2, 3, 5, 5])
        assert_equal(mbase.a._mask, [0, 1, 0, 0, 0])
        mbase.b[3:] = masked
        assert_equal(mbase.b, base['b'])
        assert_equal(mbase.b._mask, [0, 1, 0, 1, 1])
        # Set fields globally..........................
        ndtype = [('alpha', '|S1'), ('num', int)]
        data = ma.array([('a', 1), ('b', 2), ('c', 3)], dtype=ndtype)
        rdata = data.view(MaskedRecords)
        val = ma.array([10, 20, 30], mask=[1, 0, 0])

        rdata['num'] = val
        assert_equal(rdata.num, val)
        assert_equal(rdata.num.mask, [1, 0, 0]) 

# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import getdata [as 别名]
def test_set_fields(self):
        # Tests setting fields.
        base = self.base.copy()
        mbase = base.view(mrecarray)
        mbase = mbase.copy()
        mbase.fill_value = (999999, 1e20, 'N/A')
        # Change the data, the mask should be conserved
        mbase.a._data[:] = 5
        assert_equal(mbase['a']._data, [5, 5, 5, 5, 5])
        assert_equal(mbase['a']._mask, [0, 1, 0, 0, 1])
        # Change the elements, and the mask will follow
        mbase.a = 1
        assert_equal(mbase['a']._data, [1]*5)
        assert_equal(ma.getmaskarray(mbase['a']), [0]*5)
        # Use to be _mask, now it's recordmask
        assert_equal(mbase.recordmask, [False]*5)
        assert_equal(mbase._mask.tolist(),
                     np.array([(0, 0, 0),
                               (0, 1, 1),
                               (0, 0, 0),
                               (0, 0, 0),
                               (0, 1, 1)],
                              dtype=bool))
        # Set a field to mask ........................
        mbase.c = masked
        # Use to be mask, and now it's still mask !
        assert_equal(mbase.c.mask, [1]*5)
        assert_equal(mbase.c.recordmask, [1]*5)
        assert_equal(ma.getmaskarray(mbase['c']), [1]*5)
        assert_equal(ma.getdata(mbase['c']), [asbytes('N/A')]*5)
        assert_equal(mbase._mask.tolist(),
                     np.array([(0, 0, 1),
                               (0, 1, 1),
                               (0, 0, 1),
                               (0, 0, 1),
                               (0, 1, 1)],
                              dtype=bool))
        # Set fields by slices .......................
        mbase = base.view(mrecarray).copy()
        mbase.a[3:] = 5
        assert_equal(mbase.a, [1, 2, 3, 5, 5])
        assert_equal(mbase.a._mask, [0, 1, 0, 0, 0])
        mbase.b[3:] = masked
        assert_equal(mbase.b, base['b'])
        assert_equal(mbase.b._mask, [0, 1, 0, 1, 1])
        # Set fields globally..........................
        ndtype = [('alpha', '|S1'), ('num', int)]
        data = ma.array([('a', 1), ('b', 2), ('c', 3)], dtype=ndtype)
        rdata = data.view(MaskedRecords)
        val = ma.array([10, 20, 30], mask=[1, 0, 0])

        rdata['num'] = val
        assert_equal(rdata.num, val)
        assert_equal(rdata.num.mask, [1, 0, 0]) 

# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import getdata [as 别名]
def test_set_fields(self):
        # Tests setting fields.
        base = self.base.copy()
        mbase = base.view(mrecarray)
        mbase = mbase.copy()
        mbase.fill_value = (999999, 1e20, 'N/A')
        # Change the data, the mask should be conserved
        mbase.a._data[:] = 5
        assert_equal(mbase['a']._data, [5, 5, 5, 5, 5])
        assert_equal(mbase['a']._mask, [0, 1, 0, 0, 1])
        # Change the elements, and the mask will follow
        mbase.a = 1
        assert_equal(mbase['a']._data, [1]*5)
        assert_equal(ma.getmaskarray(mbase['a']), [0]*5)
        # Use to be _mask, now it's recordmask
        assert_equal(mbase.recordmask, [False]*5)
        assert_equal(mbase._mask.tolist(),
                     np.array([(0, 0, 0),
                               (0, 1, 1),
                               (0, 0, 0),
                               (0, 0, 0),
                               (0, 1, 1)],
                              dtype=bool))
        # Set a field to mask ........................
        mbase.c = masked
        # Use to be mask, and now it's still mask !
        assert_equal(mbase.c.mask, [1]*5)
        assert_equal(mbase.c.recordmask, [1]*5)
        assert_equal(ma.getmaskarray(mbase['c']), [1]*5)
        assert_equal(ma.getdata(mbase['c']), [asbytes('N/A')]*5)
        assert_equal(mbase._mask.tolist(),
                     np.array([(0, 0, 1),
                               (0, 1, 1),
                               (0, 0, 1),
                               (0, 0, 1),
                               (0, 1, 1)],
                              dtype=bool))
        # Set fields by slices .......................
        mbase = base.view(mrecarray).copy()
        mbase.a[3:] = 5
        assert_equal(mbase.a, [1, 2, 3, 5, 5])
        assert_equal(mbase.a._mask, [0, 1, 0, 0, 0])
        mbase.b[3:] = masked
        assert_equal(mbase.b, base['b'])
        assert_equal(mbase.b._mask, [0, 1, 0, 1, 1])
        # Set fields globally..........................
        ndtype = [('alpha', '|S1'), ('num', int)]
        data = ma.array([('a', 1), ('b', 2), ('c', 3)], dtype=ndtype)
        rdata = data.view(MaskedRecords)
        val = ma.array([10, 20, 30], mask=[1, 0, 0])

        with warnings.catch_warnings():
            warnings.simplefilter("ignore")
            rdata['num'] = val
            assert_equal(rdata.num, val)
            assert_equal(rdata.num.mask, [1, 0, 0]) 

# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import getdata [as 别名]
def test_set_fields(self):
        "Tests setting fields."
        base = self.base.copy()
        mbase = base.view(mrecarray)
        mbase = mbase.copy()
        mbase.fill_value = (999999, 1e20, 'N/A')
        # Change the data, the mask should be conserved
        mbase.a._data[:] = 5
        assert_equal(mbase['a']._data, [5, 5, 5, 5, 5])
        assert_equal(mbase['a']._mask, [0, 1, 0, 0, 1])
        # Change the elements, and the mask will follow
        mbase.a = 1
        assert_equal(mbase['a']._data, [1]*5)
        assert_equal(ma.getmaskarray(mbase['a']), [0]*5)
        # Use to be _mask, now it's recordmask
        assert_equal(mbase.recordmask, [False]*5)
        assert_equal(mbase._mask.tolist(),
                     np.array([(0, 0, 0), (0, 1, 1), (0, 0, 0), (0, 0, 0), (0, 1, 1)],
                              dtype=bool))
        # Set a field to mask ........................
        mbase.c = masked
        # Use to be mask, and now it's still mask !
        assert_equal(mbase.c.mask, [1]*5)
        assert_equal(mbase.c.recordmask, [1]*5)
        assert_equal(ma.getmaskarray(mbase['c']), [1]*5)
        assert_equal(ma.getdata(mbase['c']), [asbytes('N/A')]*5)
        assert_equal(mbase._mask.tolist(),
                     np.array([(0, 0, 1), (0, 1, 1), (0, 0, 1), (0, 0, 1), (0, 1, 1)],
                              dtype=bool))
        # Set fields by slices .......................
        mbase = base.view(mrecarray).copy()
        mbase.a[3:] = 5
        assert_equal(mbase.a, [1, 2, 3, 5, 5])
        assert_equal(mbase.a._mask, [0, 1, 0, 0, 0])
        mbase.b[3:] = masked
        assert_equal(mbase.b, base['b'])
        assert_equal(mbase.b._mask, [0, 1, 0, 1, 1])
        # Set fields globally..........................
        ndtype = [('alpha', '|S1'), ('num', int)]
        data = ma.array([('a', 1), ('b', 2), ('c', 3)], dtype=ndtype)
        rdata = data.view(MaskedRecords)
        val = ma.array([10, 20, 30], mask=[1, 0, 0])
        #
        with warnings.catch_warnings():
            warnings.simplefilter("ignore")
            rdata['num'] = val
            assert_equal(rdata.num, val)
            assert_equal(rdata.num.mask, [1, 0, 0]) 

# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import getdata [as 别名]
def test_set_fields(self):
        # Tests setting fields.
        base = self.base.copy()
        mbase = base.view(mrecarray)
        mbase = mbase.copy()
        mbase.fill_value = (999999, 1e20, 'N/A')
        # Change the data, the mask should be conserved
        mbase.a._data[:] = 5
        assert_equal(mbase['a']._data, [5, 5, 5, 5, 5])
        assert_equal(mbase['a']._mask, [0, 1, 0, 0, 1])
        # Change the elements, and the mask will follow
        mbase.a = 1
        assert_equal(mbase['a']._data, [1]*5)
        assert_equal(ma.getmaskarray(mbase['a']), [0]*5)
        # Use to be _mask, now it's recordmask
        assert_equal(mbase.recordmask, [False]*5)
        assert_equal(mbase._mask.tolist(),
                     np.array([(0, 0, 0),
                               (0, 1, 1),
                               (0, 0, 0),
                               (0, 0, 0),
                               (0, 1, 1)],
                              dtype=bool))
        # Set a field to mask ........................
        mbase.c = masked
        # Use to be mask, and now it's still mask !
        assert_equal(mbase.c.mask, [1]*5)
        assert_equal(mbase.c.recordmask, [1]*5)
        assert_equal(ma.getmaskarray(mbase['c']), [1]*5)
        assert_equal(ma.getdata(mbase['c']), [asbytes('N/A')]*5)
        assert_equal(mbase._mask.tolist(),
                     np.array([(0, 0, 1),
                               (0, 1, 1),
                               (0, 0, 1),
                               (0, 0, 1),
                               (0, 1, 1)],
                              dtype=bool))
        # Set fields by slices .......................
        mbase = base.view(mrecarray).copy()
        mbase.a[3:] = 5
        assert_equal(mbase.a, [1, 2, 3, 5, 5])
        assert_equal(mbase.a._mask, [0, 1, 0, 0, 0])
        mbase.b[3:] = masked
        assert_equal(mbase.b, base['b'])
        assert_equal(mbase.b._mask, [0, 1, 0, 1, 1])
        # Set fields globally..........................
        ndtype = [('alpha', '|S1'), ('num', int)]
        data = ma.array([('a', 1), ('b', 2), ('c', 3)], dtype=ndtype)
        rdata = data.view(MaskedRecords)
        val = ma.array([10, 20, 30], mask=[1, 0, 0])
        #
        with warnings.catch_warnings():
            warnings.simplefilter("ignore")
            rdata['num'] = val
            assert_equal(rdata.num, val)
            assert_equal(rdata.num.mask, [1, 0, 0])