def __init__(self):
"""default pyFileReader constructor
This initializer calls the base class initializer.
The variables dictionary is initialized here and is expected to be populated by the subclassing reader.
"""
super(pyFileReader, self).__init__()
self.variables = {} #created in subclass
self.variableIDs = {} #maps from variable string names to long ids
self.variableNames = {} #maps from long ids to string names
self.globalAttributes = OrderedDict(
) #maps from attribute str names to global attribute objects
self.globalAttributeNames = {} #maps from ids to str names
self.globalAttributeIDs = {} #maps from str names to ids
self.variableAttributes = {
} #maps from variable str names to dictionaries of variable attributes
self.variableAttributeNames = {} #maps from attribute IDs to name
self.variableAttributeIDs = {} #maps from attribute names to IDs
self.globalAttributes['model_name'] = Attribute(
'model_name', 'python_base_model')
self.globalAttributes['python_model'] = Attribute('python_model', 1)
self.debug = False
self.missing_value = -256. * -256. * -256. * -256. * -256. #same as ccmc::defaults::missingValue
self.dummy_variable = pyKameleon.vectorFloat()
self.dummy_variable.append(0)
def getVariable(self, variable, startIndex = None, count = None): '''copy float variable into memory''' var_name = self.getVariableName(variable) if self.debug: print "\tpyFileReader.getVariable returning variable", var_name if self.variables[var_name] is None: self.variables[var_name] = pyKameleon.vectorFloat() self.variables[var_name].extend(self.file_tree['variables'][var_name]['data'].flatten()) return self.variables[var_name]
def getVariable(self, variable, startIndex=None, count=None):
'''copy float variable into memory'''
var_name = self.getVariableName(variable)
if self.debug:
print "\tpyFileReader.getVariable returning variable", var_name
if self.variables[var_name] is None:
self.variables[var_name] = pyKameleon.vectorFloat()
self.variables[var_name].extend(
self.file_tree['variables'][var_name]['data'].flatten())
return self.variables[var_name]
def fillRandom(type='float', count=30):
import random
if type == 'float':
vector = pyKameleon.vectorFloat()
for i in range(count):
vector.append(random.random())
return vector
if type == 'int':
vector = pyKameleon.vectorInt()
for i in range(count):
vector.append(int(5 * random.random()))
return vector
def fillRandom(type = 'float', count = 30): import random if type == 'float': vector = pyKameleon.vectorFloat() for i in range(count): vector.append(random.random()) return vector if type == 'int': vector = pyKameleon.vectorInt() for i in range(count): vector.append(int(5*random.random())) return vector
def read_binary_file(variable_file):
""" Reads an rcm binary file. All RCM data files include a label for each record before the variable data
This is RCM's definition of the label structure (bytes sum to 240):
TYPE :: label_def
INTEGER (iprec) :: intg (20)
REAL (rprec) :: real (20)
CHARACTER(LEN=80) :: char
"""
# dt = numpy.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))])
f = open()
x = numpy.fromfile()
vector = pyKameleon.vectorFloat()
return vector
'''
def read_binary_file(variable_file):
""" Reads an rcm binary file. All RCM data files include a label for each record before the variable data
This is RCM's definition of the label structure (bytes sum to 240):
TYPE :: label_def
INTEGER (iprec) :: intg (20)
REAL (rprec) :: real (20)
CHARACTER(LEN=80) :: char
"""
# dt = numpy.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))])
f = open()
x = numpy.fromfile()
vector = pyKameleon.vectorFloat()
return vector
'''
def __init__(self):
"""default pyFileReader constructor
This initializer calls the base class initializer.
The variables dictionary is initialized here and is expected to be populated by the subclassing reader.
"""
super(pyFileReader, self).__init__()
self.variables = {} #created in subclass
self.variableIDs = {} #maps from variable string names to long ids
self.variableNames = {} #maps from long ids to string names
self.globalAttributes = OrderedDict() #maps from attribute str names to global attribute objects
self.globalAttributeNames = {} #maps from ids to str names
self.globalAttributeIDs = {} #maps from str names to ids
self.variableAttributes = {} #maps from variable str names to dictionaries of variable attributes
self.variableAttributeNames = {} #maps from attribute IDs to name
self.variableAttributeIDs = {} #maps from attribute names to IDs
self.globalAttributes['model_name'] = Attribute('model_name', 'python_base_model')
self.globalAttributes['python_model'] = Attribute('python_model',1)
self.debug = False
self.missing_value = -256.*-256.*-256.*-256.*-256. #same as ccmc::defaults::missingValue
self.dummy_variable = pyKameleon.vectorFloat()
self.dummy_variable.append(0)
def readVariableFromFile(filename, variable): vector = pyKameleon.vectorFloat() for i in range(30): vector.append(random.random()) return vector
def readVariableFromFile(filename, variable): vector = pyKameleon.vectorFloat() for i in range(30): vector.append(random.random()) return vector
