def addField(self,
fieldName,
fieldValue,
longName=None,
units=None,
**kwargs):
"""
Add a field to the sounding
.. _ndarray: http://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.htm
Parameters
----------
fieldName : str
Name of the field to be added. It supports abbreviations
(see :py:attr:`abbreviations`)
fieldValue : any
Corresponding field value. If the field value is an ndarray_ then
it will be converted to a :py:class:`~SkewTplus.sounding.soundingArray` with the corresponding
metadata.
longName : str, optional
Long name of the field
units : str , optional
units of the field
missingValue : float, optional
Value for missing data. Occurrences of this value will be masked.
The default missingValue can be change with :py:meth:`setMissingValue`
"""
missingValue = kwargs.pop('missingValue', self.missingValue)
fieldName = self._getFieldName(fieldName)
if isinstance(fieldValue, ndarray):
_fieldValue = masked_invalid(fieldValue)
_fieldValue = masked_values(_fieldValue, missingValue)
_fieldValue.harden_mask()
self._soundingData[fieldName] = soundingArray(
_fieldValue,
longName=longName,
units=units,
missingValue=missingValue)
else:
self._soundingData[fieldName] = fieldValue
def execute(Tlo, Plo, Thi, Phi):
C = 0.034167
Tratio = Thi/Tlo
Pratio = Phi/Plo
logTratio = log(Tratio)
logPratio = log(Pratio)
# Guard against divide-by-zero errors, again
logPratio = masked_values(logPratio, 0, copy=False)
result = C * logTratio / logPratio
return result
def test_matrix_indexing(self):
# Tests conversions and indexing
x1 = np.matrix([[1, 2, 3], [4, 3, 2]])
x2 = masked_array(x1, mask=[[1, 0, 0], [0, 1, 0]])
x3 = masked_array(x1, mask=[[0, 1, 0], [1, 0, 0]])
x4 = masked_array(x1)
# test conversion to strings
str(x2) # raises?
repr(x2) # raises?
# tests of indexing
assert_(type(x2[1, 0]) is type(x1[1, 0]))
assert_(x1[1, 0] == x2[1, 0])
assert_(x2[1, 1] is masked)
assert_equal(x1[0, 2], x2[0, 2])
assert_equal(x1[0, 1:], x2[0, 1:])
assert_equal(x1[:, 2], x2[:, 2])
assert_equal(x1[:], x2[:])
assert_equal(x1[1:], x3[1:])
x1[0, 2] = 9
x2[0, 2] = 9
assert_equal(x1, x2)
x1[0, 1:] = 99
x2[0, 1:] = 99
assert_equal(x1, x2)
x2[0, 1] = masked
assert_equal(x1, x2)
x2[0, 1:] = masked
assert_equal(x1, x2)
x2[0, :] = x1[0, :]
x2[0, 1] = masked
assert_(allequal(getmask(x2), np.array([[0, 1, 0], [0, 1, 0]])))
x3[1, :] = masked_array([1, 2, 3], [1, 1, 0])
assert_(allequal(getmask(x3)[1], masked_array([1, 1, 0])))
assert_(allequal(getmask(x3[1]), masked_array([1, 1, 0])))
x4[1, :] = masked_array([1, 2, 3], [1, 1, 0])
assert_(allequal(getmask(x4[1]), masked_array([1, 1, 0])))
assert_(allequal(x4[1], masked_array([1, 2, 3])))
x1 = np.matrix(np.arange(5) * 1.0)
x2 = masked_values(x1, 3.0)
assert_equal(x1, x2)
assert_(allequal(masked_array([0, 0, 0, 1, 0], dtype=MaskType),
x2.mask))
assert_equal(3.0, x2.fill_value)
def test_matrix_indexing(self):
# Tests conversions and indexing
x1 = np.matrix([[1, 2, 3], [4, 3, 2]])
x2 = masked_array(x1, mask=[[1, 0, 0], [0, 1, 0]])
x3 = masked_array(x1, mask=[[0, 1, 0], [1, 0, 0]])
x4 = masked_array(x1)
# test conversion to strings
str(x2) # raises?
repr(x2) # raises?
# tests of indexing
assert_(type(x2[1, 0]) is type(x1[1, 0]))
assert_(x1[1, 0] == x2[1, 0])
assert_(x2[1, 1] is masked)
assert_equal(x1[0, 2], x2[0, 2])
assert_equal(x1[0, 1:], x2[0, 1:])
assert_equal(x1[:, 2], x2[:, 2])
assert_equal(x1[:], x2[:])
assert_equal(x1[1:], x3[1:])
x1[0, 2] = 9
x2[0, 2] = 9
assert_equal(x1, x2)
x1[0, 1:] = 99
x2[0, 1:] = 99
assert_equal(x1, x2)
x2[0, 1] = masked
assert_equal(x1, x2)
x2[0, 1:] = masked
assert_equal(x1, x2)
x2[0, :] = x1[0, :]
x2[0, 1] = masked
assert_(allequal(getmask(x2), np.array([[0, 1, 0], [0, 1, 0]])))
x3[1, :] = masked_array([1, 2, 3], [1, 1, 0])
assert_(allequal(getmask(x3)[1], masked_array([1, 1, 0])))
assert_(allequal(getmask(x3[1]), masked_array([1, 1, 0])))
x4[1, :] = masked_array([1, 2, 3], [1, 1, 0])
assert_(allequal(getmask(x4[1]), masked_array([1, 1, 0])))
assert_(allequal(x4[1], masked_array([1, 2, 3])))
x1 = np.matrix(np.arange(5) * 1.0)
x2 = masked_values(x1, 3.0)
assert_equal(x1, x2)
assert_(allequal(masked_array([0, 0, 0, 1, 0], dtype=MaskType),
x2.mask))
assert_equal(3.0, x2.fill_value)
def getCleanSounding(self):
"""
Clean the sounding, when Temperature or pressure has a missing values,
removing that pressure level.
It returns the pressure in Pa and temperatures in Celsius
"""
pressure = self['pressure']
temperature = self['temperature']
dewPointTemperature = self['dewPointTemperature']
dewPointTemperature[getmaskarray(
dewPointTemperature)] = self.missingValue
if pressure.units is not None:
if pressure.units.lower() == 'hpa':
hPa = True
elif pressure.units.lower() == 'pa':
hPa = False
else:
raise fatalError(
"Error getting clean sounding plot",
"Pressure units not supported:%s" % pressure.units,
"Supported: hPa or Pa ")
else:
hPa = True
if temperature.units is not None:
if dewPointTemperature.units is not None:
if temperature.units.lower(
) != dewPointTemperature.units.lower():
raise fatalError(
"Error getting clean sounding plot",
"Temperature units: %s" % temperature.units,
"Dew Point Temp: %s" % dewPointTemperature.units)
if temperature.units.lower() == 'c':
celsius = True
elif temperature.units.lower() == 'k':
celsius = False
else:
raise fatalError(
"Error getting clean sounding plot",
"Temperature units not supported:%s" % temperature.units,
"Supported: C or K ")
else:
celsius = True
mask = ~mask_or(
getmaskarray(pressure), getmaskarray(temperature), shrink=False)
if hPa:
_pressure = pressure.data[mask]
else:
_pressure = pressure.data[mask] / 100
if celsius:
_temperature = temperature.data[mask]
_dewPointTemperature = masked_values(
dewPointTemperature.data[mask], self.missingValue)
else:
_temperature = temperature.data[mask] - 273.15
_dewPointTemperature = masked_values(
dewPointTemperature.data[mask], self.missingValue) - 273.15
return (_pressure, _temperature, _dewPointTemperature)
def __init__(self, inputData=None, fileFormat=None, stationId=None):
"""
Sounding Initialization
It supports 4 types of initialization:
* From a University of Wyoming txt file
* From a University of Wyoming Website
* Form an ARM sounding Netcdf file
* From a dictionary with the field names, field values pairs
All the field are added trough the :py:meth:`addField` method.
The fields names support abbreviations when they are set or get.
But internally the field names stored are not abbreviated.
See :py:attr:`SkewT.sounding.abbreviations`.
If the fileFormat keyword is not specified, it is assumed that
the input data correspond to a filePath and it will try determine the
format automatically.
.. _datetime:`https://docs.python.org/2/library/datetime.html`
Parameters
----------
inputData : str, datetime_ or dict
If inputData is a dictionary, the sounding fields are taken from the
dictionary (field names, field values pairs).
If fileFormat is "web", then the inputData is considered the date of the sounding.
See :py:meth:fetchFromWeb for date input format.
Otherwise, if inputData is an string, it is considered a file path.
If fileFormat is None (default) the initialization will
try to automatically detect the file format.
If inputData is None, the create instance correspond to an empty sounding.
fileFormat : str
File format. Supported values:
* 'txt', "wrf", "uw or "wyoming" : University of Wyoming
* "netcdf", "arm" : ARM netcdf soundings
* 'web' : University of Wyoming website
stationId : str
Station ID. Used only when "web" is selected as format. See :py:meth:fetchFromWeb
for more details.
"""
self._soundingData = dict()
self.missingValue = -9999.
self.addField('StationNumber', '(No Number)')
self.addField('SoundingDate', '(No Date)')
if inputData is not None:
if fileFormat == "web":
self.fetchFromWeb(inputData, stationId)
else:
if isinstance(inputData, str):
# A file path was given
if not isfile(inputData):
raise fatalError("The file does not exists: %s\n" %
(inputData))
if fileFormat is None:
# Try automatic detection of file format
try:
self.fetchFromARMFile(inputData)
except OSError:
# If it is not a NETCDF , try TXT
self.fetchFromTxtFile(inputData)
else:
# If the argument is an string assume that is
# in the university of wyoming format
if fileFormat.lower() in ('txt', "wrf", "uw",
"wyoming"):
self.fetchFromTxtFile(inputData)
elif fileFormat.lower() in ('netcdf', 'arm'):
self.fetchFromARMFile(inputData)
else:
raise fatalError(
"Error loading Sounding",
"Selected format not supported:%s" %
fileFormat, "Accepted formats:%s" % str(
('txt', "wrf", "uw", "wyoming", "netcdf")))
elif isinstance(inputData, dict):
for fieldName, fieldValue in inputData.items():
if isinstance(fieldValue, ndarray):
dataValues = masked_invalid(fieldValue)
dataValues = masked_values(fieldValue,
self.missingValue)
dataValues.harden_mask()
self.addField(fieldName, fieldValue)
else:
self.addField(fieldName, fieldValue)
else:
raise fatalError(
"Input Data not supported",
"type(inputData)=%s" % str(type(inputData)))
