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src/c/o/cogent-1.5.3/cogent/maths/stats/alpha_diversity.py   cogent(Download)
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

src/p/y/pycogent-HEAD/cogent/maths/stats/alpha_diversity.py   pycogent(Download)
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

src/q/i/qiime-1.8.0/qiime/pycogent_backports/alpha_diversity.py   qiime(Download)
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

src/c/o/cogent-1.5.3/cogent/maths/scipy_optimisers.py   cogent(Download)
#!/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)

src/p/y/pycogent-HEAD/cogent/maths/scipy_optimisers.py   pycogent(Download)
#!/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)