numpy.random.standard_gamma() in Python
Last Updated :
18 Aug, 2020
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With the help of numpy.random.standard_gamma() method, we can get the random samples from standard gamma distribution and return the random samples by using this method.
Syntax : numpy.random.standard_gamma(shape, size=None)
Return : Return the random samples as numpy array.
Example #1 :
In this example we can see that by using numpy.random.standard_gamma() method, we are able to get the random samples from standard gamma distribution and return the random samples.
# import numpy
import numpy as np
import matplotlib.pyplot as plt
# Using standard_gamma() method
gfg = np.random.standard_gamma(3.47, 5000)
plt.hist(gfg, bins = 50, density = True)
plt.show()
# import numpyimport numpy as npimport matplotlib.pyplot as plt# Using standard_gamma() methodgfg = np.random.standard_gamma(3.47, 5000)plt.hist(gfg, bins = 50, density = True)plt.show()Output :
Example #2 :
# import numpy
import numpy as np
import matplotlib.pyplot as plt
# Using standard_gamma() method
gfg = np.random.standard_gamma(3.47, 5000)
gfg1 = np.random.power(gfg, 5000)
plt.hist(gfg1, bins = 50, density = True)
plt.show()
# import numpyimport numpy as npimport matplotlib.pyplot as plt# Using standard_gamma() methodgfg = np.random.standard_gamma(3.47, 5000)gfg1 = np.random.power(gfg, 5000)plt.hist(gfg1, bins = 50, density = True)plt.show()Output :
