SciPy stands for Scientific Python. Scipy is a Scientific library for python is an open source, The Scipy library functions depends on Numpy. It is under best on BSD license. SciPy was created by NumPy’s created by Travis Olliphant.
SciPy Sub Packages
- Scipy.io
- scipy.special
- scipy.linalg
- scipy.interpolate
- scipy.optimize
- scipt.stats
- scipt.integrate
- scipyt.fftpack
- scipy.signal
- scipy.ndimage
Scipy.io
The SciPy.io package supports a web range of functions to work with a different format of files. sio means is Scipy input output.
These are some formats are following :-
- Matlab
- IDL
- Matrix Market
- Wave
- Arff
- Netcdf
Example of Scipy.io
import numpy as np from scipy import io as sio array = np.ones((5, 5)) why.savemat('what.mat', {'ar': array}) data = why.loadmat(‘what.mat', struct_as_record=True) data['ar']
Output
array([[ 1.,1., 1., 1., 1.], [ 1., 1., 1., 1., 1.], [ 1.,1., 1., 1., 1.], [ 1.,1., 1., 1., 1.], [ 1., 1., 1., 1., 1.]])
scipy.special
This package contains numerous functions of mathematical. SciPy special function includes Cubic Root, Exponential, Permutation and Combinations, Gamma, Bessel, hypergeometric, Kelvin, beta, parabolic cylinder etc.
Cubic Root Function
Cubic Root function defines the cube root of values.
Syntax
scipy.special.cbrt(x)
Example of Cubic Root Function
from scipy.special import cbrt #Find cubic root of 8 & 125 using cbrt() function cb = cbrt([8, 125]) #print value of cb print(cb)
Output:
([2., 5.])
Exponential Function
Example of Exponential Function
from scipy.special import exp10 #define exp10 function and pass value in its exp = exp10([1,10]) print(exp)
Output
[1.e+01 1.e+10]
Permutations & Combinations
Permutations
Syntax
scipy.special.perm(x,y)
Example of Permutation
from scipy.special import perm #find permutation of 5, 3 using perm (N, k) function per = perm(5, 3, exact = True) print(per)
Output: 60
Combinations
Syntax
scipy.special.comb(x,y)
Example of Combination
from scipy.special import comb #find combinations of 5, 3 values using comb(N, k) com = comb(5, 3, exact = False, repetition=True) print(com)
Output: 10
Scipy Stats
The scipy.stats contains a large number of statistics, probability distributions functions is knows as Scipy stats.
Syntax
scipy.stats.lognorm.method_name(data,loc,size,moments,scale)
Scipy ndimage
scipy.ndimage is a submodule of SciPy. ndimage means “n” dimensional image. SciPy Image Processing provides Geometrics transformation, image filter , display image, image segmentation, classification and features extraction.
Example of Scipy ndimage
from scipy import misc from matplotlib import pyplot as plt import numpy as np #get face image of panda from misc package panda = misc.face() #plot or show image of face plt.imshow( apple ) plt.show()
Scipy optimize
Scipy Optimize provides a useful algorithm for minimization of curve fitting, multidimensional or scalar and root fitting is knows as Scipy Optimize.
Example of Scipy Optimize
%matplotlib inline import matplotlib.pyplot as plt from scipy import optimize import numpy as np def function(d): return a*4 + 10 * np.sin(d) plt.plot(a, function(a)) plt.show() #use BFGS algorithm for optimization optimize.fmin_bfgs(function, 0)
Scipy fftpack
- It is stands for Fast Fourier Transformation.
- FFT is apply to a multidimensional array.
- The Frequency defines the number of signal or wavelength in particular time period.
Example of Scipy fffpack
%matplotlib inline from matplotlib import pyplot as plt import numpy as np #Frequency in terms of Hertz fre = 15 #Sample rate fre_samp = 55 t = np.linspace(0, 2, 2 * fre_samp, endpoint = False ) a = np.sin(fre * 2 * np.pi * t) figure, axis = plt.subplots() axis.plot(t, a) axis.set_xlabel ('Time (s)') axis.set_ylabel ('Signal amplitude') plt.show()
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