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src/a/l/algopy-0.5.1/documentation/sphinx/examples/minimization/minhelper.py   algopy(Download)
import numpy
import scipy.optimize
import algopy
import numdifftools
#import pyipopt

src/a/l/algopy-HEAD/documentation/sphinx/examples/minimization/minhelper.py   algopy(Download)
import numpy
import scipy.optimize
import algopy
import numdifftools
#import pyipopt

src/a/l/algopy-0.5.1/documentation/sphinx/examples/taylor_series_of_jacobian.py   algopy(Download)
import numpy
import algopy
from algopy import CGraph, UTPM, Function
 
def eval_g(x, y):

src/a/l/algopy-0.5.1/documentation/sphinx/examples/polarization.py   algopy(Download)
import algopy, numpy
import algopy.exact_interpolation as ei
 
def eval_F(x):
    retval = algopy.zeros(3, dtype=x)

src/a/l/algopy-0.5.1/documentation/sphinx/examples/neg_binom_regression.py   algopy(Download)
import numpy
import scipy.optimize
import algopy
import numdifftools
import pandas

src/a/l/algopy-0.5.1/documentation/sphinx/examples/minimal_surface.py   algopy(Download)
import numpy
import algopy
 
def O_tilde(u):
    """ this is the objective function"""

src/a/l/algopy-0.5.1/documentation/sphinx/examples/matrixexponential.py   algopy(Download)
 
import numpy as np
import algopy
from scipy import optimize, linalg
 

src/a/l/algopy-0.5.1/documentation/sphinx/examples/logistic_regression.py   algopy(Download)
import numpy
import scipy.optimize
import algopy
 
 

src/a/l/algopy-0.5.1/documentation/sphinx/examples/leastsquaresfitting.py   algopy(Download)
import numpy
from scipy import optimize
 
import algopy
 

src/a/l/algopy-0.5.1/documentation/sphinx/examples/householder_qr.py   algopy(Download)
import algopy, numpy
 
def house(x):
    """ computes the Householder vector v and twice its norm beta
 

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