stats265
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STATS265 (Stats 1)의 모든 분포를 희망하는 PIP 패키지 - 곧 Ualberta
현재:
항상 위험에 처한 경우 항상 그렇듯이 가상 환경에서 먼저 시도해 볼 수 있습니다.
테스트는 UnitTest 라이브러리 https://docs.python.org/3/library/unittest.html을 사용하여 수행되었습니다
* Calling a distribution
* from stats265 import Bernoulli
* g = Bernolli(p = 0.7)
* from stats265 import Gaussian
* g = Gaussian(mean, stdev)
* from stats265 import Binomial
* g = Binomial(p = 0.7, n = 20)
* from stats265 import Poisson
* g = Poisson(mean)
* Methods of distributions (varies for obvious reasons)
* read_data_file(file_name)
reads the data in said file into our object, and now we can play around with the data
* calculate_mean()
calculates and returns the mean
* calculate_stdev()
calculates and returns the standard deviation of the distribution
* plot_histogram()
plots a histogram of the data
* pdf(x)
returns probability density function for a value x
* plot_histogram_pdf()
Plots histogram of data and pdf
* Distribution_1 + Distribution_2 (__add__)
Add a two distributions
same type only for now
* print(Distribution) (__repr__)
Allows for representation on a print call
설치:
종속성 :