def test_GDF_get_descriptor(self):
"Test GDF get_descriptor function"
#TODO: Define tests which check DB contents
test_gdf = GDF() # Test default configuration
descriptor = test_gdf.get_descriptor(self.TEST_3D_PARAMETER)
descriptor = test_gdf.get_descriptor(self.TEST_2D_PARAMETER)
descriptor = test_gdf.get_descriptor()
def test_GDF_get_descriptor(self):
"Test GDF get_descriptor function"
#TODO: Define tests which check DB contents
test_gdf = GDF() # Test default configuration
descriptor = test_gdf.get_descriptor(self.TEST_3D_PARAMETER)
descriptor = test_gdf.get_descriptor(self.TEST_2D_PARAMETER)
descriptor = test_gdf.get_descriptor()
def main():
# Testing stuff
g = GDF(opendap=True)
# g.debug = True
# pprint(g.storage_config['LS5TM'])
# pprint(dict(g.storage_config['LS5TM']['dimensions']))
# pprint(dict(g.storage_config['LS5TM']['measurement_types']))
# pprint(g.storage_config['LS8OLI'])
# pprint(dict(g.storage_config['LS8OLI']['dimensions']))
# pprint(dict(g.storage_config['LS8OLI']['measurement_types']))
data_request_descriptor = {
"storage_type": "LS5TM",
"variables": ("B30",),
"dimensions": {
"X": {"range": (147.968, 148.032)},
"Y": {"range": (-36.032, -35.968)},
"T": {"range": (1262304000.0, 1325375999.999999)}, # 2010-01-01 00:00:00.0 - 2011-12-31 23:59:59.999999
},
}
t0 = datetime.now()
print "Starting 256 x 256 single-band cross-boundary descriptor at ", t0
d = g.get_descriptor(data_request_descriptor)
t1 = datetime.now()
print "Finishing 256 x 256 cross-boundary descriptor at %s (Elapsed time %s)" % (t1, t1 - t0)
pprint(d)
t0 = datetime.now()
print "Starting 256 x 256 single-band cross-boundary selection at ", t0
a = g.get_data(data_request_descriptor)
t1 = datetime.now()
print "Finishing 256 x 256 cross-boundary selection at %s (Elapsed time %s)" % (t1, t1 - t0)
pprint(a)
def main():
# Testing stuff
g = GDF()
# g.debug = True
# pprint(g.storage_config['LS5TM'])
# pprint(dict(g.storage_config['LS5TM']['dimensions']))
# pprint(dict(g.storage_config['LS5TM']['measurement_types']))
# pprint(g.storage_config['LS8OLI'])
# pprint(dict(g.storage_config['LS8OLI']['dimensions']))
# pprint(dict(g.storage_config['LS8OLI']['measurement_types']))
data_request_descriptor = {'storage_type': 'LS5TM',
'variables': ('B30',),
'dimensions': {'X': {'range': (147.968, 148.032)},
'Y': {'range': (-36.032, -35.968)},
'T': {'range': (1262304000.0, 1325375999.999999)}, # 2010-01-01 00:00:00.0 - 2011-12-31 23:59:59.999999
}
}
t0 = datetime.now()
print 'Starting 256 x 256 single-band cross-boundary descriptor at ', t0
d = g.get_descriptor(data_request_descriptor)
t1 = datetime.now()
print 'Finishing 256 x 256 cross-boundary descriptor at %s (Elapsed time %s)' % (t1, t1 - t0)
pprint(d)
t0 = datetime.now()
print 'Starting 256 x 256 single-band cross-boundary selection at ', t0
a = g.get_data(data_request_descriptor)
t1 = datetime.now()
print 'Finishing 256 x 256 cross-boundary selection at %s (Elapsed time %s)' % (t1, t1 - t0)
pprint(a)
class Analytics(object):
SUPPORTED_OUTPUT_TYPES = ['netcdf-cf', 'geotiff']
OPERATORS_SENSOR_SPECIFIC_BANDMATH = \
{
'ndvi': \
{
'sensors': \
{
'LS5TM' : { 'input': ['B40', 'B30'], 'function': 'ndvi'},
'LS7ETM' : { 'input': ['B40', 'B30'], 'function': 'ndvi'},
'LS8OLI' : { 'input': ['B5', 'B4'], 'function': 'ndvi'},
'LS8OLITIRS' : { 'input': ['B5', 'B4'], 'function': 'ndvi'},
},
'functions': \
{
'ndvi' : '((array1 - array2) / (array1 + array2))'
}
}
}
OPERATORS_REDUCTION = \
{
'median': 'median(array1)'
}
def __init__(self):
logger.debug('Initialise Analytics Module.')
self.gdf = GDF()
self.gdf.debug = False
self.plan = []
self.planDict = {}
def task(self, name):
return self.plan[self.planDict[name]]
def add_to_plan(self, name, task):
self.plan.append( { name : task })
size = len(self.plan)
self.planDict[name] = size-1
return self.plan[size-1]
def createArray(self, storage_type, variables, dimensions, name):
query_parameters = {}
query_parameters['storage_type'] = storage_type
query_parameters['dimensions'] = dimensions
query_parameters['variables'] = ()
for array in variables:
query_parameters['variables'] += (array,)
arrayDescriptors = self.gdf.get_descriptor(query_parameters)
if storage_type not in arrayDescriptors.keys():
raise AssertionError(storage_type, "not present in descriptor")
logger.debug('storage_type = %s', storage_type)
arrayResults = []
for variable in variables:
if variable not in arrayDescriptors[storage_type]['variables']:
raise AssertionError(variable, "not present in", storage_type, "descriptor")
logger.debug('variable = %s', variable)
arrayResult = {}
arrayResult['storage_type'] = storage_type
arrayResult['variable'] = variable
arrayResult['dimensions_order'] = arrayDescriptors[storage_type]['dimensions']
arrayResult['dimensions'] = dimensions
arrayResult['shape'] = arrayDescriptors[storage_type]['result_shape']
arrayResult['data_type'] = arrayDescriptors[storage_type]['variables'][variable]['numpy_datatype_name']
arrayResult['no_data_value'] = arrayDescriptors[storage_type]['variables'][variable]['nodata_value']
arrayResults.append({variable : arrayResult})
task = {}
task['array_input'] = arrayResults
task['array_output'] = copy.deepcopy(arrayResult)
task['array_output']['variable'] = 'data'
task['function'] = 'get_data'
task['orig_function'] = 'get_data'
return self.add_to_plan(name, task)
def applyCloudMask(self, arrays, mask, name):
size = len(arrays)
if size == 0:
raise AssertionError("Input array is empty")
task = {}
task['array_input'] = []
for array in arrays.keys():
task['array_input'].append(array)
task['array_mask'] = mask.keys()[0]
task['orig_function'] = 'apply_cloud_mask'
task['function'] = 'apply_cloud_mask'
task['array_output'] = copy.deepcopy(arrays.values()[0]['array_output'])
task['array_output']['variable'] = name
return self.add_to_plan(name, task)
# generic version
def applyBandMath(self, arrays, function, name):
# Arrays is a list
# output Array is same shape as input array
size = len(arrays)
if size == 0:
raise AssertionError("Input array is empty")
variables = []
if size == 1: # 1 input
if arrays.values()[0]['function'] == 'get_data':
# check shape is same for all input arrays
shape = arrays.values()[0]['array_input'][0].values()[0]['shape']
for variable in arrays.values()[0]['array_input']:
if shape != variable.values()[0]['shape']:
raise AssertionError("Shape is different")
variables.append(variable.keys()[0])
else:
variables.append(arrays.keys()[0])
orig_function = function
logger.debug('function before = %s', function)
count = 1
for variable in variables:
function = function.replace('array'+str(count), variable)
count += 1
logger.debug('function after = %s', function)
task = {}
task['array_input'] = []
task['array_input'].append(arrays.keys()[0])
task['orig_function'] = orig_function
task['function'] = function
task['array_output'] = copy.deepcopy(arrays.values()[0]['array_output'])
task['array_output']['variable'] = name
return self.add_to_plan(name, task)
else: # multi-dependencies
pprint(arrays)
for array in arrays:
variables.append(array.keys()[0])
orig_function = function
logger.debug('function before = %s', function)
count = 1
for variable in variables:
function = function.replace('array'+str(count), variable)
count += 1
logger.debug('function after = %s', function)
task = {}
task['array_input'] = []
for array in arrays:
task['array_input'].append(array.keys()[0])
task['orig_function'] = orig_function
task['function'] = function
task['array_output'] = copy.deepcopy(arrays[0].values()[0]['array_output'])
task['array_output']['variable'] = name
return self.add_to_plan(name, task)
# sensor specific version
def applySensorSpecificBandMath(self, storage_types, function, dimensions, name_data, name_result):
variables = self.getPredefinedInputs(storage_types, function)
arrays = self.createArray(storage_types, variables, dimensions, name_data)
function_text = self.getPredefinedFunction(storage_types, function)
return self.applyBandMath(arrays, function_text, name_result)
def applyReduction(self, array1, dimensions, function, name):
function = self.OPERATORS_REDUCTION.get(function)
return self.applyGenericReductionFunction(array1, dimensions, function, name)
def applyGenericReduction(self, arrays, dimensions, function, name):
size = len(arrays)
if size != 1:
raise AssertionError("Input array should be 1")
if arrays.values()[0]['function'] == 'get_data':
variable = arrays.values()[0]['array_input'][0].values()[0]['variable']
orig_function = function
logger.debug('function before = %s', function)
function = function.replace('array1', variable)
logger.debug('function after = %s', function)
task = {}
task['array_input'] = []
task['array_input'].append(arrays.keys()[0])
task['orig_function'] = orig_function
task['function'] = function
task['dimension'] = copy.deepcopy(dimensions)
task['array_output'] = copy.deepcopy(arrays.values()[0]['array_output'])
task['array_output']['variable'] = name
task['array_output']['dimensions_order'] = self.diffList(arrays.values()[0]['array_input'][0].values()[0]['dimensions_order'], dimensions)
result = ()
for value in task['array_output']['dimensions_order']:
input_task = self.task(task['array_input'][0])
index = input_task.values()[0]['array_output']['dimensions_order'].index(value)
value = input_task.values()[0]['array_output']['shape'][index]
result += (value,)
task['array_output']['shape'] = result
return self.add_to_plan(name, task)
else:
variable = arrays.keys()[0]
orig_function = function
logger.debug('function before = %s', function)
function = function.replace('array1', variable)
logger.debug('function after = %s', function)
task = {}
task['array_input'] = []
task['array_input'].append(variable)
task['orig_function'] = orig_function
task['function'] = function
task['dimension'] = copy.deepcopy(dimensions)
task['array_output'] = copy.deepcopy(arrays.values()[0]['array_output'])
task['array_output']['variable'] = name
task['array_output']['dimensions_order'] = self.diffList(arrays.values()[0]['array_output']['dimensions_order'], dimensions)
result = ()
for value in task['array_output']['dimensions_order']:
input_task = self.task(task['array_input'][0])
pprint(input_task)
index = input_task.values()[0]['array_output']['dimensions_order'].index(value)
value = input_task.values()[0]['array_output']['shape'][index]
result += (value,)
task['array_output']['shape'] = result
return self.add_to_plan(name, task)
def diffList(self, list1, list2):
list2 = set(list2)
return [result for result in list1 if result not in list2]
def getPredefinedInputs(self, storage_type, function):
return self.OPERATORS_SENSOR_SPECIFIC_BANDMATH.get(function).get('sensors').get(storage_type).get('input')
def getPredefinedFunction(self, storage_type, function):
function_id = self.OPERATORS_SENSOR_SPECIFIC_BANDMATH.get(function).get('sensors').get(storage_type).get('function')
return self.OPERATORS_SENSOR_SPECIFIC_BANDMATH.get(function).get('functions').get(function_id)
