Did I find the right examples for you? yes no      Crawl my project      Python Jobs

# cogent.maths.scipy_optimize.fmin_powell

All Samples(10)  |  Call(5)  |  Derive(0)  |  Import(5)

```from math import ceil, e
from numpy import array, zeros, concatenate, arange, log, sqrt, exp, asarray
from cogent.maths.scipy_optimize import fmin_powell
import cogent.maths.stats.rarefaction as rarefaction

```
```        return ((fitfn(p,n) - y)**2).sum()

p1 = fmin_powell(errfn, params_guess, args=(xvals,yvals), disp=0)
if return_b:
return p1
```

```from math import ceil, e
from numpy import array, zeros, concatenate, arange, log, sqrt, exp, asarray
from cogent.maths.scipy_optimize import fmin_powell
import cogent.maths.stats.rarefaction as rarefaction

```
```        return ((fitfn(p,n) - y)**2).sum()

p1 = fmin_powell(errfn, params_guess, args=(xvals,yvals), disp=0)
if return_b:
return p1
```

```from numpy import array, zeros, concatenate, arange, log, sqrt, exp, asarray
from numpy.random import gamma, shuffle
from cogent.maths.scipy_optimize import fmin_powell
import cogent.maths.stats.rarefaction as rarefaction

```
```        return ((fitfn(p,n) - y)**2).sum()

p1 = fmin_powell(errfn, params_guess, args=(xvals,yvals), disp=0)
if return_b:
return p1
```

```#!/usr/bin/env python

from __future__ import division
import numpy, math, warnings
from cogent.maths.scipy_optimize import fmin_bfgs, fmin_powell, fmin, brent
```
```    def _minimise(self, f, x, **kw):
result = fmin_powell(f, x, linesearch=bound_brent, **kw)
# same length full-results tuple as simplex:
(xopt, fval, directions, iterations, func_calls, warnflag) = result
return (xopt, fval, iterations, func_calls, warnflag)
```

```#!/usr/bin/env python

from __future__ import division
import numpy, math, warnings
from cogent.maths.scipy_optimize import fmin_bfgs, fmin_powell, fmin, brent
```
```    def _minimise(self, f, x, **kw):
result = fmin_powell(f, x, linesearch=bound_brent, **kw)
# same length full-results tuple as simplex:
(xopt, fval, directions, iterations, func_calls, warnflag) = result
return (xopt, fval, iterations, func_calls, warnflag)
```