https://github.com/lmfit/lmfit-py
Tip revision: 2720249ffd37a7cd94e3b25d442db336fc0bac4e authored by Matt Newville on 07 July 2016, 16:46:18 UTC
Merge pull request #343 from lmfit/prep0.9.4
Merge pull request #343 from lmfit/prep0.9.4
Tip revision: 2720249
printfuncs.py
# -*- coding: utf-8 -*-
"""
Created on Fri Apr 20 19:24:21 2012
@author: Tillsten
Changes:
- 13-Feb-2013 M Newville
complemented "report_errors" and "report_ci" with
"error_report" and "ci_report" (respectively) which
return the text of the report. Thus report_errors()
is simply:
def report_errors(params, modelpars=None, show_correl=True):
print error_report(params, modelpars=modelpars,
show_correl=show_correl)
and similar for report_ci() / ci_report()
"""
from __future__ import print_function
from .parameter import Parameters
import re
def alphanumeric_sort(s, _nsre=re.compile('([0-9]+)')):
return [int(text) if text.isdigit() else text.lower()
for text in re.split(_nsre, s)]
def getfloat_attr(obj, attr, fmt='%.3f'):
"format an attribute of an object for printing"
val = getattr(obj, attr, None)
if val is None:
return 'unknown'
if isinstance(val, int):
return '%d' % val
if isinstance(val, float):
return fmt % val
else:
return repr(val)
def gformat(val, length=11):
"""format a number with '%g'-like format, except that
the return will be length ``length`` (default=12)
and have at least length-6 significant digits
"""
length = max(length, 7)
fmt = '{0: .%ig}' % (length-6)
if isinstance(val, int):
out = ('{0: .%ig}' % (length-2)).format(val)
if len(out) > length:
out = fmt.format(val)
else:
out = fmt.format(val)
if len(out) < length:
if 'e' in out:
ie = out.find('e')
if '.' not in out[:ie]:
out = out[:ie] + '.' + out[ie:]
out = out.replace('e', '0'*(length-len(out))+'e')
else:
fmt = '{0: .%ig}' % (length-1)
out = fmt.format(val)[:length]
if len(out) < length:
pad = '0' if '.' in out else ' '
out += pad*(length-len(out))
return out
CORREL_HEAD = '[[Correlations]] (unreported correlations are < % .3f)'
def fit_report(inpars, modelpars=None, show_correl=True, min_correl=0.1,
sort_pars=False):
"""return text of a report for fitted params best-fit values,
uncertainties and correlations
arguments
----------
inpars Parameters from fit or Minizer object returned from a fit.
modelpars Optional Known Model Parameters [None]
show_correl whether to show list of sorted correlations [True]
min_correl smallest correlation absolute value to show [0.1]
sort_pars If True, then fit_report will show parameter names
sorted in alphanumerical order. If False, then the
parameters will be listed in the order they were added to
the Parameters dictionary. If sort_pars is callable, then
this (one argument) function is used to extract a
comparison key from each list element.
"""
if isinstance(inpars, Parameters):
result, params = None, inpars
if hasattr(inpars, 'params'):
result = inpars
params = inpars.params
if sort_pars:
if callable(sort_pars):
key = sort_pars
else:
key = alphanumeric_sort
parnames = sorted(params, key=key)
else:
# dict.keys() returns a KeysView in py3, and they're indexed further
# down
parnames = list(params.keys())
buff = []
add = buff.append
if result is not None:
add("[[Fit Statistics]]")
add(" # function evals = %s" % getfloat_attr(result, 'nfev'))
add(" # data points = %s" % getfloat_attr(result, 'ndata'))
add(" # variables = %s" % getfloat_attr(result, 'nvarys'))
add(" chi-square = %s" % getfloat_attr(result, 'chisqr'))
add(" reduced chi-square = %s" % getfloat_attr(result, 'redchi'))
add(" Akaike info crit = %s" % getfloat_attr(result, 'aic'))
add(" Bayesian info crit = %s" % getfloat_attr(result, 'bic'))
namelen = max([len(n) for n in parnames])
add("[[Variables]]")
for name in parnames:
par = params[name]
space = ' '*(namelen+1-len(name))
nout = "%s:%s" % (name, space)
inval = '(init= ?)'
if par.init_value is not None:
inval = '(init=% .7g)' % par.init_value
if modelpars is not None and name in modelpars:
inval = '%s, model_value =% .7g' % (inval, modelpars[name].value)
try:
sval = gformat(par.value)
except (TypeError, ValueError):
sval = 'Non Numeric Value?'
if par.stderr is not None:
serr = gformat(par.stderr, length=9)
try:
spercent = '({0:.2%})'.format(abs(par.stderr/par.value))
except ZeroDivisionError:
spercent = ''
sval = '%s +/-%s %s' % (sval, serr, spercent)
if par.vary:
add(" %s %s %s" % (nout, sval, inval))
elif par.expr is not None:
add(" %s %s == '%s'" % (nout, sval, par.expr))
else:
add(" %s % .7g (fixed)" % (nout, par.value))
if show_correl:
add(CORREL_HEAD % min_correl)
correls = {}
for i, name in enumerate(parnames):
par = params[name]
if not par.vary:
continue
if hasattr(par, 'correl') and par.correl is not None:
for name2 in parnames[i+1:]:
if (name != name2 and name2 in par.correl and
abs(par.correl[name2]) > min_correl):
correls["%s, %s" % (name, name2)] = par.correl[name2]
sort_correl = sorted(correls.items(), key=lambda it: abs(it[1]))
sort_correl.reverse()
for name, val in sort_correl:
lspace = max(1, 25 - len(name))
add(' C(%s)%s = % .3f ' % (name, (' '*30)[:lspace], val))
return '\n'.join(buff)
def report_errors(params, **kws):
"""print a report for fitted params: see error_report()"""
print(fit_report(params, **kws))
def report_fit(params, **kws):
"""print a report for fitted params: see error_report()"""
print(fit_report(params, **kws))
def ci_report(ci, with_offset=True, ndigits=5):
"""return text of a report for confidence intervals
Parameters
----------
with_offset : bool (default `True`)
whether to subtract best value from all other values.
ndigits : int (default 5)
number of significant digits to show
Returns
-------
text of formatted report on confidence intervals.
"""
maxlen = max([len(i) for i in ci])
buff = []
add = buff.append
def convp(x):
if abs(x[0]) < 1.e-2:
return "_BEST_"
return "%.2f%%" % (x[0]*100)
title_shown = False
fmt_best = fmt_diff = "{0:.%if}" % ndigits
if with_offset:
fmt_diff = "{0:+.%if}" % ndigits
for name, row in ci.items():
if not title_shown:
add("".join([''.rjust(maxlen+1)]+[i.rjust(ndigits+5)
for i in map(convp, row)]))
title_shown = True
thisrow = [" %s:" % name.ljust(maxlen)]
offset = 0.0
if with_offset:
for cval, val in row:
if abs(cval) < 1.e-2:
offset = val
for cval, val in row:
if cval < 1.e-2:
sval = fmt_best.format(val)
else:
sval = fmt_diff.format(val-offset)
thisrow.append(sval.rjust(ndigits+5))
add("".join(thisrow))
return '\n'.join(buff)
def report_ci(ci):
"""print a report for confidence intervals"""
print(ci_report(ci))