IA / AI 2022-10-19

# 5.py Basic Statistics
class BasicStatistics:
    @staticmethod
    def sumOfAll(pCol):
        sum=0
        # iterable walk from 0 to length of pCol-1
        for idx in range(len(pCol)):
            currentValue = pCol[idx]
            sum += currentValue
        # for
        return sum
    # def sumOfAll

    @staticmethod
    def sum (pCol):
        sum = 0
        for n in pCol:
            sum += n
        # for
        return sum
    # def sum

    @staticmethod
    def average(pCol):
        try:
            return BasicStatistics.sum(pCol)/len(pCol)
        except Exception as e:
            return "Empty collection. Average not Computable."
    # def average

    @staticmethod
    def minValue(pCol):
        try:
            return min(pCol)
        except:
            return "Empty collection. Min not computable."
    # def minValue

    @staticmethod
    def maxValue(pCol):
        try:
            return max(pCol)
        except:
            return "Empty colletion. Max not computable."
    # def maxValue

    @staticmethod
    def variance(pCol):
        sumOfSquaredDistances = 0
        mean = BasicStatistics.average(pCol)
        bOKMean = type(mean)!=str
        if (bOKMean):
            for n in pCol:
                dist = n-mean
                distSquared = dist**2
                sumOfSquaredDistances += distSquared
            # for
        # if
        try:
            return sumOfSquaredDistances / len(pCol)
        except Exception as e:
            strMsg = f"Exception: {str(e)}\n"
            strMsg += f"Variance not computable.\n"
            return strMsg
        # try-except
    # def variance

    @staticmethod
    def standardDeviation(pCol):
        v = BasicStatistics.variance(pCol)
        bOKVariance = type(v)!=str
        if (bOKVariance):
            import math
            return math.sqrt(v)
            #return v**(1/2)
        # if
    # def standardDeviation
# class BasicStatistics

someNumbers = [10, 20, 30]
theSum = BasicStatistics.sum(someNumbers)
theAverage = BasicStatistics.average(someNumbers)
theMin = BasicStatistics.minValue(someNumbers)
theMax = BasicStatistics.maxValue(someNumbers)
theVariance = BasicStatistics.variance(someNumbers)
theStandardDevPop = BasicStatistics.standardDeviation(someNumbers)

strMsg = f"Some stats about these numbers {someNumbers}\n"
strMsg+=f"Sum: {theSum}\n"
strMsg+=f"Average: {theAverage}\n"
strMsg+=f"Min: {theMin}\n"
strMsg+=f"Max: {theMax}\n"
strMsg+=f"Variance: {theVariance}\n"
strMsg+=f"Standard Deviation: {theStandardDevPop}\n"
print(strMsg)