class_docstr: Class used to calculate the confidence interval.
class_docstr_tok: ["Class","used","to","calculate","the","confidence","interval","."]
docstr: Calculate the probability for given value.
docstr_tok: ["Calculate","the","probability","for","given","value","."]
code: def calc_prob(self, para, val, offset=0.0, restore=False):
      """Calculate the probability for given value."""
      if restore:
          restore_vals(self.org, self.params)
      para.value = val
      save_para = self.params[para.name]
      self.params[para.name] = para
      self.minimizer.prepare_fit(self.params)
      out = self.minimizer.leastsq()
      prob = self.prob_func(self.result, out)
  
      if self.trace:
          x = [i.value for i in out.params.values()]
          self.trace_dict[para.name].append(x + [prob])
      self.params[para.name] = save_para
      return prob - offset
  
file_path: lmfit-py/lmfit/confidence.py
imports: from warnings import warn
  import numpy
  from scipy.optimize import root_scalar
  from scipy.special import erf
  from scipy.stats import f
  from .minimizer import MinimizerException
label_desc: Use image node_id 6 for calling the ConfidenceInterval obj's underlying member method code with example usage: obj.calc_prob(para, val, offset, restore) and returns: unknown