def __init__(self, lats, lons, times, values, variable=None, name=""):
'''Default Dataset constructor
:param lats: One dimensional numpy array of unique latitude values.
:type lats: numpy array
:param lons: One dimensional numpy array of unique longitude values.
:type lons: numpy array
:param times: One dimensional numpy array of unique python datetime
objects.
:type times: numpy array
:param values: Three dimensional numpy array of parameter values with
shape [timesLength, latsLength, lonsLength].
:type values: numpy array
:param variable: Name of the value variable.
:type variable: string
:param name: An optional string name for the Dataset.
:type variable: string
:raises: ValueError
'''
self._validate_inputs(lats, lons, times, values)
lats, lons, values = utils.normalize_lat_lon_values(lats, lons, values)
self.lats = lats
self.lons = lons
self.times = times
self.values = values
self.variable = variable
self.name = name
def test_lats_reversed(self):
lons2 = np.arange(-180, 180)
lats, lons, values = utils.normalize_lat_lon_values(self.lats[::-1],
lons2,
self.values[:, ::-1, :])
np.testing.assert_array_equal(lats, self.lats)
np.testing.assert_array_equal(values, self.values)
def __init__(self, lats, lons, times, values, variable=None, name=""):
'''Default Dataset constructor
:param lats: One dimensional numpy array of unique latitude values.
:type lats: numpy array
:param lons: One dimensional numpy array of unique longitude values.
:type lons: numpy array
:param times: One dimensional numpy array of unique python datetime
objects.
:type times: numpy array
:param values: Three dimensional numpy array of parameter values with
shape [timesLength, latsLength, lonsLength].
:type values: numpy array
:param variable: Name of the value variable.
:type variable: string
:param name: An optional string name for the Dataset.
:type variable: string
:raises: ValueError
'''
self._validate_inputs(lats, lons, times, values)
lats, lons, values = utils.normalize_lat_lon_values(lats, lons, values)
self.lats = lats
self.lons = lons
self.times = times
self.values = values
self.variable = variable
self.name = name
def test_lats_reversed(self):
lons2 = np.arange(-180, 180)
lats, lons, values = utils.normalize_lat_lon_values(self.lats[::-1],
lons2,
self.values[:, ::-1, :])
np.testing.assert_array_equal(lats, self.lats)
np.testing.assert_array_equal(values, self.values)
def test_shift_and_reversed(self):
expected_vals = np.array([[10, 11, 8, 9],
[6, 7, 4, 5],
[2, 3, 0, 1]])
lats, lons, values = utils.normalize_lat_lon_values(self.lats2[::-1],
self.lons2,
self.values2)
np.testing.assert_array_equal(values, expected_vals)
def test_shift_and_reversed(self):
expected_vals = np.array([[10, 11, 8, 9],
[6, 7, 4, 5],
[2, 3, 0, 1]])
lats, lons, values = utils.normalize_lat_lon_values(self.lats2[::-1],
self.lons2,
self.values2)
np.testing.assert_array_equal(values, expected_vals)
def test_lons_greater_than_180(self):
self.lons = np.array([190, 210, 230, 250])
self.lats = np.array([-30, 0, 30])
self.values = np.arange(12).reshape(3, 4)
expected_lons = np.array([-170, -150, -130, -110])
expected_values = np.array([[0, 1, 2, 3],
[4, 5, 6, 7],
[8, 9, 10, 11]])
lats, lons, values = utils.normalize_lat_lon_values(self.lats,
self.lons,
self.values)
np.testing.assert_array_equal(lons, expected_lons)
np.testing.assert_array_equal(expected_values, values)
def __init__(self,
lats,
lons,
times,
values,
variable=None,
units=None,
origin=None,
name=""):
'''Default Dataset constructor
:param lats: One dimensional numpy array of unique latitude values.
:type lats: :class:`numpy.ndarray`
:param lons: One dimensional numpy array of unique longitude values.
:type lons: :class:`numpy.ndarray`
:param times: One dimensional numpy array of unique python datetime
objects.
:type times: :class:`numpy.ndarray`
:param values: Three dimensional numpy array of parameter values with
shape [timesLength, latsLength, lonsLength].
:type values: :class:`numpy.ndarray`
:param variable: Name of the value variable.
:type variable: :mod:`string`
:param units: Name of the value units
:type units: :mod:`string`
:param name: An optional string name for the Dataset.
:type name: :mod:`string`
:param origin: An optional object used to specify information on where
this dataset was loaded from.
:type origin: :class:`dict`
:raises: ValueError
'''
self._validate_inputs(lats, lons, times, values)
lats, lons, values = utils.normalize_lat_lon_values(lats, lons, values)
self.lats = lats
self.lons = lons
self.times = times
self.values = values
self.variable = variable
self.units = units
self.name = name
self.origin = origin
def test_lons_reversed(self):
self.lats = np.arange(-10, 10)
self.lons = np.arange(40)
times = np.array([datetime.datetime(2000, x, 1) for x in range(1, 7)])
flat_array = np.arange(len(times) * len(self.lats) * len(self.lons))
self.variable = flat_array.reshape(len(times),
len(self.lats),
len(self.lons))
lats, lons, values = utils.normalize_lat_lon_values(self.lats,
self.lons[::-1],
self.values[:,
::,
::-1])
np.testing.assert_array_equal(lats, self.lats)
np.testing.assert_array_equal(values, self.values)
np.testing.assert_array_equal(lons, self.lons)
def __init__(self, lats, lons, times, values, variable=None, units=None,
origin=None, name=""):
'''Default Dataset constructor
:param lats: One dimensional numpy array of unique latitude values.
:type lats: :class:`numpy.ndarray`
:param lons: One dimensional numpy array of unique longitude values.
:type lons: :class:`numpy.ndarray`
:param times: One dimensional numpy array of unique python datetime
objects.
:type times: :class:`numpy.ndarray`
:param values: Three dimensional numpy array of parameter values with
shape [timesLength, latsLength, lonsLength].
:type values: :class:`numpy.ndarray`
:param variable: Name of the value variable.
:type variable: :mod:`string`
:param units: Name of the value units
:type units: :mod:`string`
:param name: An optional string name for the Dataset.
:type name: :mod:`string`
:param origin: An optional object used to specify information on where
this dataset was loaded from.
:type origin: :class:`dict`
:raises: ValueError
'''
self._validate_inputs(lats, lons, times, values)
lats, lons, values = utils.normalize_lat_lon_values(lats, lons, values)
self.lats = lats
self.lons = lons
self.times = times
self.values = values
self.variable = variable
self.units = units
self.name = name
self.origin = origin
def test_full_lons_shift(self):
lats, lons, values = utils.normalize_lat_lon_values(self.lats,
self.lons,
self.values)
np.testing.assert_array_equal(lons, np.arange(-180, 180))
def test_full_lons_shift(self):
lats, lons, values = utils.normalize_lat_lon_values(self.lats,
self.lons,
self.values)
np.testing.assert_array_equal(lons, np.arange(-180, 180))
