def analytical_method(container, container_type, norm_type, variable):
analytical_value = GetInitialVariableValue(variable, norm_type)
for item in container:
analytical_value += SpatialMethodTests.__GetNormValue(
variable,
SpatialMethodTests.__GetValue(item, container_type,
variable), norm_type)
return analytical_value
def analytical_method(container, container_type, norm_type, variable):
mean_value = GetInitialVariableValue(variable, norm_type)
variance_value = GetInitialVariableValue(variable, norm_type)
for item in container:
current_value = SpatialMethodTests.__GetNormValue(
variable,
SpatialMethodTests.__GetValue(item, container_type,
variable), norm_type)
mean_value += current_value
variance_value += KratosStats.MethodUtilities.RaiseToPower(
current_value, 2)
n = len(container)
mean_value /= n
variance_value = variance_value / n - KratosStats.MethodUtilities.RaiseToPower(
mean_value, 2)
return mean_value, variance_value
def analytical_method(container, container_type, norm_type, variable):
analytical_value = GetInitialVariableValue(variable, norm_type)
for item in container:
analytical_value += KratosStats.MethodUtilities.RaiseToPower(
SpatialMethodTests.__GetNormValue(
variable,
SpatialMethodTests.__GetValue(item, container_type,
variable), norm_type), 2)
return KratosStats.MethodUtilities.RaiseToPower(
analytical_value * (1.0 / len(container)), 0.5)
def __AnalyticalMethod(norm_type, variable, value_array):
if (norm_type == "none"):
result = GetInitialVariableValue(variable, "none")
for item in value_array:
result += item
else:
result = 0.0
norm_method = KratosStats.MethodUtilities.GetNormMethod(
variable, norm_type)
for item in value_array:
result += norm_method(item)
return result * 2.0
def __AnalyticalMethod(norm_type, variable, value_array):
if (norm_type == "none"):
result = GetInitialVariableValue(variable, "none")
for item in value_array:
result += KratosStats.MethodUtilities.RaiseToPower(item, 2) * 2.0
else:
result = 0.0
norm_method = KratosStats.MethodUtilities.GetNormMethod(
variable, norm_type)
for item in value_array:
result += pow(norm_method(item), 2.0) * 2.0
return KratosStats.MethodUtilities.RaiseToPower(result * (1.0 / max(len(value_array) * 2.0, 1.0)), 0.5)
def __AnalyticalMethod(norm_type, variable, value_array):
if (norm_type == "none"):
result_mean = GetInitialVariableValue(variable, "none")
result_variance = GetInitialVariableValue(variable, "none")
for item in value_array:
result_mean += item * 2.0
result_variance += KratosStats.MethodUtilities.RaiseToPower(
item, 2) * 2.0
else:
result_mean = 0.0
result_variance = 0.0
norm_method = KratosStats.MethodUtilities.GetNormMethod(
variable, norm_type)
for item in value_array:
value = norm_method(item)
result_mean += value * 2.0
result_variance += pow(value, 2) * 2.0
result_mean = result_mean * (1.0 / max(len(value_array) * 2.0, 1.0))
result_variance = result_variance * (
1.0 / max(len(value_array) * 2.0, 1.0)
) - KratosStats.MethodUtilities.RaiseToPower(result_mean, 2)
return result_mean, result_variance
