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