from scipy import cluster import scipy help(cluster) scipy.info(cluster) scipy.source(cluster)
def main(): print(sp.info(cs_diff)) print('-' * 60) print(sp.source(cs_diff))
import numpy as np import scipy as sp from scipy import stats data = np.genfromtxt('iris.data', delimiter=',', dtype='f8,f8,f8,f8,S15',names=['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'type_string']) sizeofdata, (minval,maxval), mean, variance, skew, kurtosis = stats.describe(data['petal_width']) #provides further info of what the stats above are returning sp.info(stats.describe) #returns max and other data stats on petal_length stats.describe(data['petal_length']) # returns (150, (1.0, 6.9000000000000004), 3.7586666666666693, 3.1131794183445156, -0.2717119501716454, -1.395359302139705) #median is not provided can be found using sp.median sp.median(data['petal_length'])
import scipy as sp import numpy as np from scipy import stats # help help(open) sp.info("mean") sp.info(sp.mean) data = np.genfromtxt( 'iris.data', delimiter=',', dtype='f8,f8,f8,f8,S15', names=['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'type_string'] ) sizeofdata, (minval,maxval), mean, variance, skew, kurtosis = stats.describe(data['petal_width']) sp.median(data['petal_length'])
import scipy as sp from scipy import integrate from scipy import cluster from scipy import fftpack # help(integrate) sp.info(fftpack) #To get info about any sub-package sp.source(cluster) #To get the source code of any subpackage
import numpy as np import scipy as sp import matplotlib as mpl import matplotlib.pyplot as plt from scipy import linalg, optimize print sp.info(optimize.fmin)