Algo1.py

"""
The implemention of Algorithm1
"""

import os
import numpy as np
import math
class Algo1(object):
    def __init__(self):
        print("use Algo1")

    # read and combine the csv file in `data_path`
    def _get_original_data(self, data_path):
        original_data = np.genfromtxt(data_path, delimiter=',')
        print("get original data")
        return original_data

    # convert the data to the (theta,r)-->(x,y)
    def _get_processed_data(self, original_data):
        processed_data = []
        for data in original_data:
            theta = data[0]
            r = data[1]
            processed_data.append([r * math.cos(theta), r * math.sin(theta)])
        print("get processed data")
        return processed_data

    # return the ultimate data
    def get_data(self, data_path):
        return self._get_processed_data(self._get_original_data(data_path))

    # for Algo1, calculate the distance is compute the Euclidean distance
    def calculate_distance(self, pointA, pointB):
        res = float(0)
        for i in range(len(pointA)):
            diff = pointA[i] - pointB[i]
            res += diff ** 2
        return math.sqrt(res)

    # calculate the mean and variance of the points in Euclidean space
    def calculate_mean_point(self, points):
        x_sum = float(0)
        y_sum = float(0)
        x_mean = float(0)
        y_mean = float(0)
        N = len(points)

        for point in points:
            x_sum += point[0]
            y_sum += point[1]
        x_mean = x_sum / N
        y_mean = y_sum / N

        mean_point = [x_mean, y_mean]

        var_sum = float(0)
        variance = float(0)
        for point in points:
            var_sum += (self.calculate_distance(point, mean_point)) ** 2
        variance = var_sum / (N - 1)

        return mean_point, variance