Example #1
0
 def get_init_parameters(self, name):
     parameters = DataFrame(
         columns=['initial', 'pmin', 'pmax', 'vary', 'name'])
     if self.up:
         parameters.loc[name + '_A'] = (
             1 / self.meanstress, 0, 100 / self.meanstress, 1, name)
     else:
         parameters.loc[name + '_A'] = (
             -1 / self.meanstress, -100 / self.meanstress, 0, 1, name)
     parameters.loc[name + '_a'] = (10, 0.01, 5000, 1, name)
     return parameters
Example #2
0
 def get_init_parameters(self, name):
     parameters = DataFrame(
         columns=['initial', 'pmin', 'pmax', 'vary', 'name'])
     a_init = 1
     b_init = 0.1
     c_init = 1 / np.exp(-2 * a_init) / self.meanstress
     parameters.loc[name + '_a'] = (a_init, 0, 100, 1, name)
     parameters.loc[name + '_b'] = (b_init, 0, 10, 1, name)
     if self.up:
         parameters.loc[name + '_c'] = (c_init, 0, c_init * 100, 1, name)
     else:
         parameters.loc[name + '_c'] = (-c_init, -c_init * 100, 0, 1, name)
     return parameters
Example #3
0
 def get_init_parameters(self, name):
     parameters = DataFrame(
         columns=['initial', 'pmin', 'pmax', 'vary', 'name'])
     if self.up:
         parameters.loc[name + '_A'] = (1 / self.meanstress, 0,
                                        100 / self.meanstress, 1, name)
     else:
         parameters.loc[name + '_A'] = (-1 / self.meanstress,
                                        -100 / self.meanstress, 0, 1, name)
     # if n is too small, the length of the response function is close to zero
     parameters.loc[name + '_n'] = (1, 0.1, 10, 1, name)
     parameters.loc[name + '_a'] = (10, 0.01, 5000, 1, name)
     return parameters