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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,141 +1,141 @@ | ||
| import numpy as np | ||
| import scipy.stats as stats | ||
| import matplotlib.pyplot as plt | ||
|
|
||
|
|
||
| # noinspection PyTypeChecker | ||
| class DataToolkit: | ||
| def __init__(self, data): | ||
| self._data = np.array(data) | ||
| self._sorted_data = np.sort(self._data) | ||
| self._n = len(self._data) | ||
| self._mean = self._variance = self._std = None | ||
| self._moments = [] | ||
| self._q1 = self._q3 = None | ||
|
|
||
| def get_moment(self, k): | ||
| if len(self._moments) < k: | ||
| self._moments += [None] * (k - len(self._moments)) | ||
| if self._moments[k-1] is None: | ||
| self._moments[k-1] = np.sum((self._data - self.mean) ** k) / self._n | ||
| return self._moments[k-1] | ||
|
|
||
| def get_mp(self, p): | ||
| _np = self._n * p | ||
| int_np = int(_np) | ||
| if not int(_np % 1): | ||
| return self._sorted_data[int_np] | ||
| return 0.5 * (self._sorted_data[int_np-1] + self._sorted_data[int_np]) | ||
|
|
||
| @property | ||
| def min(self): | ||
| return self._sorted_data[0] | ||
|
|
||
| @property | ||
| def max(self): | ||
| return self._sorted_data[-1] | ||
|
|
||
| @property | ||
| def mean(self): | ||
| if self._mean is None: | ||
| self._mean = self._data.mean() | ||
| return self._mean | ||
|
|
||
| @property | ||
| def variance(self): | ||
| if self._variance is None: | ||
| self._variance = np.sum((self._data - self.mean) ** 2) / (self._n - 1) | ||
| return self._variance | ||
|
|
||
| @property | ||
| def std(self): | ||
| if self._std is None: | ||
| self._std = (np.sum((self._data - self.mean) ** 2) / (self._n - 1)) ** 0.5 | ||
| return self._std | ||
|
|
||
| @property | ||
| def g1(self): | ||
| n, moment3 = self._n, self.get_moment(3) | ||
| return n ** 2 * moment3 / ((n - 1) * (n - 2) * self.std ** 3) | ||
|
|
||
| @property | ||
| def g2(self): | ||
| n, moment4 = self._n, self.get_moment(4) | ||
| return n**2*(n+1)*moment4 / ((n-1)*(n-2)*(n-3)*self.std**4) - 3*(n-1)**2/((n-2)*(n-3)) | ||
|
|
||
| @property | ||
| def med(self): | ||
| n, hn = self._n, int(self._n*0.5) | ||
| if n & 1: | ||
| return self._sorted_data[hn-1] | ||
| return 0.5 * (self._sorted_data[hn-1] + self._sorted_data[hn]) | ||
|
|
||
| @property | ||
| def q1(self): | ||
| if self._q1 is None: | ||
| self._q1 = self.get_mp(0.25) | ||
| return self._q1 | ||
|
|
||
| @property | ||
| def q3(self): | ||
| if self._q3 is None: | ||
| self._q3 = self.get_mp(0.75) | ||
| return self._q3 | ||
|
|
||
| @property | ||
| def r(self): | ||
| return self._sorted_data[-1] - self._sorted_data[0] | ||
|
|
||
| @property | ||
| def r1(self): | ||
| return self.q3 - self.q1 | ||
|
|
||
| @property | ||
| def trimean(self): | ||
| return 0.25 * (self.q1 + self.q3) + 0.5 * self.med | ||
|
|
||
| @property | ||
| def loval(self): | ||
| return self.q1 - 1.5 * self.r1 | ||
|
|
||
| @property | ||
| def hival(self): | ||
| return self.q3 + 1.5 * self.r1 | ||
|
|
||
| def draw_histogram(self, bin_size=10): | ||
| bins = np.arange(self._sorted_data[0]-self.r1, self._sorted_data[-1]+self.r1, bin_size) | ||
| plt.hist(self._data, bins=bins, alpha=0.5) | ||
| plt.title("Histogram (bin_size: {})".format(bin_size)) | ||
| plt.show() | ||
|
|
||
| def qq_plot(self): | ||
| stats.probplot(self._data, dist="norm", plot=plt) | ||
| plt.show() | ||
|
|
||
| def box_plot(self): | ||
| plt.figure() | ||
| plt.boxplot(self._data, vert=False, showmeans=True) | ||
| plt.show() | ||
|
|
||
| if __name__ == '__main__': | ||
| toolkit = DataToolkit([ | ||
| 53, 70.2, 84.3, 55.3, 78.5, 63.5, 71.4, 53.4, 82.5, 67.3, 69.5, 73, 55.7, 85.8, 95.4, 51.1, 74.4, | ||
| 54.1, 77.8, 52.4, 69.1, 53.5, 64.3, 82.7, 55.7, 70.5, 87.5, 50.7, 72.3, 59.5 | ||
| ]) | ||
| print("mean : ", toolkit.mean) | ||
| print("variance : ", toolkit.variance) | ||
| print("g1 : ", toolkit.g1) | ||
| print("g2 : ", toolkit.g2) | ||
| print("med : ", toolkit.med) | ||
| print("r : ", toolkit.r) | ||
| print("q3 : ", toolkit.q3) | ||
| print("q1 : ", toolkit.q1) | ||
| print("r1 : ", toolkit.r1) | ||
| print("trimean : ", toolkit.trimean) | ||
| print("hival : ", toolkit.hival) | ||
| print("loval : ", toolkit.loval) | ||
| print("min : ", toolkit.min) | ||
| print("max : ", toolkit.max) | ||
| toolkit.draw_histogram() | ||
| toolkit.qq_plot() | ||
| toolkit.box_plot() | ||
| import numpy as np | ||
| import scipy.stats as stats | ||
| import matplotlib.pyplot as plt | ||
|
|
||
|
|
||
| # noinspection PyTypeChecker | ||
| class DataToolkit: | ||
| def __init__(self, data): | ||
| self._data = np.asarray(data) | ||
| self._sorted_data = np.sort(self._data) | ||
| self._n = len(self._data) | ||
| self._mean = self._variance = self._std = None | ||
| self._moments = [] | ||
| self._q1 = self._q3 = None | ||
|
|
||
| def get_moment(self, k): | ||
| if len(self._moments) < k: | ||
| self._moments += [None] * (k - len(self._moments)) | ||
| if self._moments[k-1] is None: | ||
| self._moments[k-1] = np.sum((self._data - self.mean) ** k) / self._n | ||
| return self._moments[k-1] | ||
|
|
||
| def get_mp(self, p): | ||
| _np = self._n * p | ||
| int_np = int(_np) | ||
| if not int(_np % 1): | ||
| return self._sorted_data[int_np] | ||
| return 0.5 * (self._sorted_data[int_np-1] + self._sorted_data[int_np]) | ||
|
|
||
| @property | ||
| def min(self): | ||
| return self._sorted_data[0] | ||
|
|
||
| @property | ||
| def max(self): | ||
| return self._sorted_data[-1] | ||
|
|
||
| @property | ||
| def mean(self): | ||
| if self._mean is None: | ||
| self._mean = self._data.mean() | ||
| return self._mean | ||
|
|
||
| @property | ||
| def variance(self): | ||
| if self._variance is None: | ||
| self._variance = np.sum((self._data - self.mean) ** 2) / (self._n - 1) | ||
| return self._variance | ||
|
|
||
| @property | ||
| def std(self): | ||
| if self._std is None: | ||
| self._std = (np.sum((self._data - self.mean) ** 2) / (self._n - 1)) ** 0.5 | ||
| return self._std | ||
|
|
||
| @property | ||
| def g1(self): | ||
| n, moment3 = self._n, self.get_moment(3) | ||
| return n ** 2 * moment3 / ((n - 1) * (n - 2) * self.std ** 3) | ||
|
|
||
| @property | ||
| def g2(self): | ||
| n, moment4 = self._n, self.get_moment(4) | ||
| return n**2*(n+1)*moment4 / ((n-1)*(n-2)*(n-3)*self.std**4) - 3*(n-1)**2/((n-2)*(n-3)) | ||
|
|
||
| @property | ||
| def med(self): | ||
| n, hn = self._n, int(self._n*0.5) | ||
| if n & 1: | ||
| return self._sorted_data[hn-1] | ||
| return 0.5 * (self._sorted_data[hn-1] + self._sorted_data[hn]) | ||
|
|
||
| @property | ||
| def q1(self): | ||
| if self._q1 is None: | ||
| self._q1 = self.get_mp(0.25) | ||
| return self._q1 | ||
|
|
||
| @property | ||
| def q3(self): | ||
| if self._q3 is None: | ||
| self._q3 = self.get_mp(0.75) | ||
| return self._q3 | ||
|
|
||
| @property | ||
| def r(self): | ||
| return self._sorted_data[-1] - self._sorted_data[0] | ||
|
|
||
| @property | ||
| def r1(self): | ||
| return self.q3 - self.q1 | ||
|
|
||
| @property | ||
| def trimean(self): | ||
| return 0.25 * (self.q1 + self.q3) + 0.5 * self.med | ||
|
|
||
| @property | ||
| def loval(self): | ||
| return self.q1 - 1.5 * self.r1 | ||
|
|
||
| @property | ||
| def hival(self): | ||
| return self.q3 + 1.5 * self.r1 | ||
|
|
||
| def draw_histogram(self, bin_size=10): | ||
| bins = np.arange(self._sorted_data[0]-self.r1, self._sorted_data[-1]+self.r1, bin_size) | ||
| plt.hist(self._data, bins=bins, alpha=0.5) | ||
| plt.title("Histogram (bin_size: {})".format(bin_size)) | ||
| plt.show() | ||
|
|
||
| def qq_plot(self): | ||
| stats.probplot(self._data, dist="norm", plot=plt) | ||
| plt.show() | ||
|
|
||
| def box_plot(self): | ||
| plt.figure() | ||
| plt.boxplot(self._data, vert=False, showmeans=True) | ||
| plt.show() | ||
|
|
||
| if __name__ == '__main__': | ||
| toolkit = DataToolkit([ | ||
| 53, 70.2, 84.3, 55.3, 78.5, 63.5, 71.4, 53.4, 82.5, 67.3, 69.5, 73, 55.7, 85.8, 95.4, 51.1, 74.4, | ||
| 54.1, 77.8, 52.4, 69.1, 53.5, 64.3, 82.7, 55.7, 70.5, 87.5, 50.7, 72.3, 59.5 | ||
| ]) | ||
| print("mean : ", toolkit.mean) | ||
| print("variance : ", toolkit.variance) | ||
| print("g1 : ", toolkit.g1) | ||
| print("g2 : ", toolkit.g2) | ||
| print("med : ", toolkit.med) | ||
| print("r : ", toolkit.r) | ||
| print("q3 : ", toolkit.q3) | ||
| print("q1 : ", toolkit.q1) | ||
| print("r1 : ", toolkit.r1) | ||
| print("trimean : ", toolkit.trimean) | ||
| print("hival : ", toolkit.hival) | ||
| print("loval : ", toolkit.loval) | ||
| print("min : ", toolkit.min) | ||
| print("max : ", toolkit.max) | ||
| toolkit.draw_histogram() | ||
| toolkit.qq_plot() | ||
| toolkit.box_plot() |
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