side-by-side.diff

import numeric_string_parser									   |	from numeric_string_parser import NumericStringParser

SPECS = {												SPECS = {
	'description' : 'Provides functions for statistical analysis',						'description' : 'Provides functions for statistical analysis',
	'functions' : {												'functions' : {
		"gen_math" :{												"gen_math" :{
			'param_order': ['formula', 'xParam'],									'param_order': ['formula', 'xParam'],
			'param': {												'param': {
				'formula': {												'formula': {
					'type': 'text',												'type': 'text',
					'comment': 'Expression to be evaluated',								'comment': 'Expression to be evaluated',
				},													},
				'xParam': {												'xParam': {
					'type': 'field_reference numeric',									'type': 'field_reference numeric',
					'comment': 'x values',											'comment': 'x values',
				}													}
												   >				},
												   >				'entry_result': {
												   >					'result' : 'numeric'
			}													}
		},													},
														
																	
		'basic' : {												'basic' : {
			'param': {												'param': {
				'field': {												'field': {
					'type' : 'field_reference numeric',									'type' : 'field_reference numeric',
					'comment': 'Field to analyze',										'comment': 'Field to analyze',
				}													}
			},													},
			'aggregate_result': {											'aggregate_result': {
				'total': 'numeric',											'total': 'numeric',
				'max' : 'numeric',											'max' : 'numeric',
				'min' : 'numeric',											'min' : 'numeric',
				'average' : 'numeric',											'average' : 'numeric',
				'variance' : 'numeric',											'variance' : 'numeric',
				'standard_deviation' : 'numeric'									'standard_deviation' : 'numeric'
			}													}
		},													},
		"binary_operation" : {											"binary_operation" : {
			'param_order': ['field_1', 'operation', 'field_2'],							'param_order': ['field_1', 'operation', 'field_2'],
			'param': {												'param': {
				'field_1': {												'field_1': {
					'type' : 'field_reference numeric',									'type' : 'field_reference numeric',
					'comment': 'First field',										'comment': 'First field',
				},													},
				'field_2': {												'field_2': {
					'type' : 'field_reference numeric',									'type' : 'field_reference numeric',
					'comment': 'Second field'										'comment': 'Second field'
				},													},
				'operation' : {												'operation' : {
					'type' : 'text',											'type' : 'text',
					'constraints' : {											'constraints' : {
						'choices' : ['+', '-', '/', '*']									'choices' : ['+', '-', '/', '*']
					}													}
				}													}
			},													},
			'entry_result': {											'entry_result': {
				'result' : 'numeric'											'result' : 'numeric'
			}													}
		},													},
		"correlation" : {											"correlation" : {
			'param': {												'param': {
				'field_1': {												'field_1': {
					'type' : 'field_reference numeric',									'type' : 'field_reference numeric',
					'comment': 'First field',										'comment': 'First field',
				},													},
				'field_2': {												'field_2': {
					'type' : 'field_reference numeric',									'type' : 'field_reference numeric',
					'comment': 'Second field'										'comment': 'Second field'
				}													}
			},													},
			'aggregate_result': {											'aggregate_result': {
				'correlation' : 'numeric'										'correlation' : 'numeric'
			}													}
		},													},
		"regression": {												"regression": {
			'param': {												'param': {
				'field_1': {												'field_1': {
					'type': 'field_reference numeric',									'type': 'field_reference numeric',
					'comment': 'First field (X-axis)'									'comment': 'First field (X-axis)'
				},													},
				'field_2': {												'field_2': {
					'type': 'field_reference numeric',									'type': 'field_reference numeric',
					'comment': 'Second field (Y-axis)'									'comment': 'Second field (Y-axis)'
				}													}
			},													},
			'aggregate_result': {											'aggregate_result': {
				'a_value': 'numeric',											'a_value': 'numeric',
				'b_value': 'numeric',											'b_value': 'numeric',
				'equation': 'text'											'equation': 'text'
			}													}
		}													}
	}													}
}													}

def gen_math(working_set, param=False):									def gen_math(working_set, param=False):
	parser = NumericStringParser()										parser = NumericStringParser()
	results = []												results = []
	xList = param['xParam']											xList = param['xParam']
	expression = param['formula']										expression = param['formula']
	for x in range(len(xList)):										for x in range(len(xList)):
		xValue = xList[x]											xValue = xList[x]
		modified_formula = ''											modified_formula = ''
		for i in range (len(expression)):									for i in range (len(expression)):
			if expression[i] != 'x':										if expression[i] != 'x':
				modified_formula += expression[i]									modified_formula += expression[i]
			else:													else:
				modified_formula += xValue					   |					modified_formula += str(xValue)
		r=parser.eval(modified_formula)										r=parser.eval(modified_formula)
		results.append(r)											results.append(r)
	return results										   |		return 	{
												   >			'entry_analysis' : {
												   >				'result' : results
												   >			}
												   >		}
def basic(working_set, param=False):									def basic(working_set, param=False):
	fieldVals = param['field'] 										fieldVals = param['field'] 
	average = 0												average = 0
	total = 0												total = 0
	variance = 0												variance = 0
	maxVal = fieldVals[0]											maxVal = fieldVals[0]
	minVal = fieldVals[0]											minVal = fieldVals[0]

	for r in fieldVals:											for r in fieldVals:
		total += r												total += r
		if r > maxVal:												if r > maxVal:
			maxVal = r												maxVal = r
		elif r < minVal:											elif r < minVal:
			minVal = r												minVal = r
														
	average = total/len(fieldVals)										average = total/len(fieldVals)

	for r in fieldVals:											for r in fieldVals:
		variance += (r - average) ** 2										variance += (r - average) ** 2
	variance /= len(fieldVals) - 1										variance /= len(fieldVals) - 1

	standard_deviation = variance ** (.5)									standard_deviation = variance ** (.5)

	return {												return {
		#'meta' : res_meta,											#'meta' : res_meta,
		'aggregate_analysis': {											'aggregate_analysis': {
				'total': total,												'total': total,
				'max' : maxVal,												'max' : maxVal,
				'min' : minVal,												'min' : minVal,
				'average' : average,											'average' : average,
				'variance' : variance,											'variance' : variance,
				'standard_deviation' : standard_deviation								'standard_deviation' : standard_deviation
		},													},
		'entry_analysis': {}											'entry_analysis': {}
	}													}

def binary_operation(working_set, param=False):								def binary_operation(working_set, param=False):
	field1Vals = param['field_1']										field1Vals = param['field_1']
	field2Vals = param['field_2']										field2Vals = param['field_2']
	op = param['operation']											op = param['operation']
	results = []												results = []
	for i in range(len(field1Vals)):									for i in range(len(field1Vals)):
		v1 = field1Vals[i]											v1 = field1Vals[i]
		v2 = field2Vals[i]											v2 = field2Vals[i]
		r = v1 + v2												r = v1 + v2
		if op == '-':												if op == '-':
			r = v1 - v2												r = v1 - v2
		elif op == '/':												elif op == '/':
			r = v1/v2												r = v1/v2
		elif op == '*':												elif op == '*':
			r = v1*v2												r = v1*v2
		results.append(r)											results.append(r)
	return {												return {
		'entry_analysis' : {											'entry_analysis' : {
			'result' : results											'result' : results
		}													}
	}													}
														
def correlation(working_set, param=False):								def correlation(working_set, param=False):
	field1Vals = param['field_1']										field1Vals = param['field_1']
	field2Vals = param['field_2']										field2Vals = param['field_2']
	sumX = 0												sumX = 0
	sumY = 0												sumY = 0
	sumX2 = 0												sumX2 = 0
	sumY2 = 0												sumY2 = 0
	sumXY = 0												sumXY = 0
	for i in range(len(field1Vals)):									for i in range(len(field1Vals)):
		sumX += field1Vals[i]											sumX += field1Vals[i]
		sumY += field2Vals[i]											sumY += field2Vals[i]
		sumX2 += field1Vals[i]**2										sumX2 += field1Vals[i]**2
		sumY2 += field2Vals[i]**2										sumY2 += field2Vals[i]**2
		sumXY += field1Vals[i] * field2Vals[i]									sumXY += field1Vals[i] * field2Vals[i]

	result = (len(field1Vals)*sumXY - sumX*sumY) / ((len(field1Vals)*sumX2 - sumX**2)**(0.5)		result = (len(field1Vals)*sumXY - sumX*sumY) / ((len(field1Vals)*sumX2 - sumX**2)**(0.5)

	return {												return {
		'aggregate_analysis' : {										'aggregate_analysis' : {
			'correlation': result											'correlation': result
		}													}
	}													}
														
def regression(working_set, param=False):								def regression(working_set, param=False):
	field1Vals = param['field_1']										field1Vals = param['field_1']
	field2Vals = param['field_2']										field2Vals = param['field_2']
	sumX = 0												sumX = 0
	sumY = 0												sumY = 0
	sumX2 = 0												sumX2 = 0
	sumY2 = 0												sumY2 = 0
	sumXY = 0												sumXY = 0
	for i in range(len(field1Vals)):									for i in range(len(field1Vals)):
		sumX += field1Vals[i]											sumX += field1Vals[i]
		sumY += field2Vals[i]											sumY += field2Vals[i]
		sumX2 += field1Vals[i]**2										sumX2 += field1Vals[i]**2
		sumY2 += field2Vals[i]**2										sumY2 += field2Vals[i]**2
		sumXY += field1Vals[i] * field2Vals[i]									sumXY += field1Vals[i] * field2Vals[i]

	a_value = (1.0*sumY*sumX2 - sumX*sumXY)/(len(field1Vals)*sumX2 - sumX**2)				a_value = (1.0*sumY*sumX2 - sumX*sumXY)/(len(field1Vals)*sumX2 - sumX**2)
	b_value = (1.0*len(field1Vals)*sumXY - sumX*sumY)/(len(field1Vals)*sumX2 - sumX**2)			b_value = (1.0*len(field1Vals)*sumXY - sumX*sumY)/(len(field1Vals)*sumX2 - sumX**2)

	return {												return {
		'aggregate_analysis' : {										'aggregate_analysis' : {
			'a_value': a_value,											'a_value': a_value,
			'b_value': b_value,											'b_value': b_value,
			'equation': "y = " + str(a_value) + " + " + str(b_value) + "x"						'equation': "y = " + str(a_value) + " + " + str(b_value) + "x"
		}													}
	}													}