python Programming Glossary: scipy.optimize

These spectrum bands used to be judged by eye, how to do it programmatically?

http://stackoverflow.com/questions/10764569/these-spectrum-bands-used-to-be-judged-by-eye-how-to-do-it-programmatically

I hope it is relevant import Image from scipy import from scipy.optimize import leastsq # Load the picture with PIL process if needed..

Fit a gaussian function

http://stackoverflow.com/questions/11507028/fit-a-gaussian-function

fitting arbitrary curves to data. Basically you can use scipy.optimize.curve_fit to fit any function you want to your data. The code.. to this SciPy User mailing list post . import numpy from scipy.optimize import curve_fit import matplotlib.pyplot as plt # Define some..

SciPy instead of GNU Octave

http://stackoverflow.com/questions/12343271/scipy-instead-of-gnu-octave

to use Python for this stuff. import numpy as np import scipy.optimize I usually just need basic calculations x np.linspace 0 10 50.. x ... ynoisy y np.random.normal 0 0.2 size len x popt pcov scipy.optimize.curve_fit func x ynoisy popt array 3.00015527 4.99421236 2.03380468..

ode integration in python versus mathematica results

http://stackoverflow.com/questions/16222302/ode-integration-in-python-versus-mathematica-results

import Axes3D from numpy import linspace from scipy.optimize import brentq me 5.974 10 24 # mass of the earth mm 7.348..

Curve fitting in Scipy with 3d data and parameters

http://stackoverflow.com/questions/17934198/curve-fitting-in-scipy-with-3d-data-and-parameters

import numpy as np import matplotlib.pyplot as plt import scipy.optimize as spopt from textwrap import wrap import collections cl 0.5.. rosenbrock function in 2d and guess the y parameter from scipy.optimize import curve_fit from itertools import imap import numpy as.. optimalparams fitting the colville function in 4d from scipy.optimize import curve_fit import numpy as np # 4 dimensional colville..

Speeding up a closest point on a hyperbolic paraboloid algorithm

http://stackoverflow.com/questions/18858448/speeding-up-a-closest-point-on-a-hyperbolic-paraboloid-algorithm

expression for the closest point to a point p but scipy.optimize can do the job numerically for you import numpy as np from scipy.optimize.. can do the job numerically for you import numpy as np from scipy.optimize import minimize p0 np.array 1.15 0.62 1.01 p1 np.array 1.74..

Solving non-linear equations in python

http://stackoverflow.com/questions/19542801/solving-non-linear-equations-in-python

a b c Non linear Solution You could also solve this using scipy.optimize as @Joe suggested. The most accessible function in scipy.optimize.. as @Joe suggested. The most accessible function in scipy.optimize is scipy.optimize.curve_fit which uses a Levenberg Marquardt.. The most accessible function in scipy.optimize is scipy.optimize.curve_fit which uses a Levenberg Marquardt method by default...

fitting exponential decay with no initial guessing

http://stackoverflow.com/questions/3938042/fitting-exponential-decay-with-no-initial-guessing

numpy as np import scipy as sp import pylab as pl from scipy.optimize.minpack import curve_fit x np.array 50. 110. 170. 230. 290... line to the log of the data. Use a non linear solver e.g. scipy.optimize.curve_fit The first option is by far the fastest and most robust... import matplotlib.pyplot as plt import scipy as sp import scipy.optimize def main # Actual parameters A0 K0 C0 2.5 4.0 2.0 # Generate..

Scipy: bounds for fitting parameter(s) when using optimize.leastsq

http://stackoverflow.com/questions/7409694/scipy-bounds-for-fitting-parameters-when-using-optimize-leastsq

large whenever the parameters exceed the bounds. import scipy.optimize as optimize def residuals p x y if within_bounds p return y..

SciPy LeastSq Goodness of Fit Estimator

http://stackoverflow.com/questions/7588371/scipy-leastsq-goodness-of-fit-estimator

this question If you call leastsq like this import scipy.optimize p cov infodict mesg ier optimize.leastsq residuals a_guess args.. the function evaluated at the output For example import scipy.optimize as optimize import numpy as np import collections import matplotlib.pyplot..

How to solve a pair of nonlinear equations using Python?

http://stackoverflow.com/questions/8739227/how-to-solve-a-pair-of-nonlinear-equations-using-python

fsolve http docs.scipy.org doc scipy reference generated scipy.optimize.fsolve.html#scipy.optimize.fsolve from scipy.optimize import.. doc scipy reference generated scipy.optimize.fsolve.html#scipy.optimize.fsolve from scipy.optimize import fsolve import math def equations.. scipy.optimize.fsolve.html#scipy.optimize.fsolve from scipy.optimize import fsolve import math def equations p x y p return x y 2..

scipy.optimize.leastsq with bound constraints

http://stackoverflow.com/questions/9878558/scipy-optimize-leastsq-with-bound-constraints

with bound constraints I am looking for an optimisation.. from __future__ import division import numpy as np from scipy.optimize import leastsq __date__ 2012 03 26 mar def leastsq_bounds func.. leastsq http docs.scipy.org doc scipy reference generated scipy.optimize.leastsq.html Notes The bounds may not be met if boundsweight..