bundles / scipy latest / scipy / odr / _odrpack / ODR
class
scipy.odr._odrpack:ODR
source: /scipy/odr/_odrpack.py :661
Signature
class ODR ( data , model , beta0 = None , delta0 = None , ifixb = None , ifixx = None , job = None , iprint = None , errfile = None , rptfile = None , ndigit = None , taufac = None , sstol = None , partol = None , maxit = None , stpb = None , stpd = None , sclb = None , scld = None , work = None , iwork = None , overwrite = False ) Members
Summary
The ODR class gathers all information and coordinates the running of the main fitting routine.
Extended Summary
Members of instances of the ODR class have the same names as the arguments to the initialization routine.
Parameters
data: Data class instanceinstance of the Data class
model: Model class instanceinstance of the Model class
Attributes
data: DataThe data for this fit
model: ModelThe model used in fit
output: OutputAn instance if the Output class containing all of the returned data from an invocation of ODR.run() or ODR.restart()
Other Parameters
beta0: array_like of rank-1a rank-1 sequence of initial parameter values. Optional if model provides an "estimate" function to estimate these values.
delta0: array_like of floats of rank-1, optionala (double-precision) float array to hold the initial values of the errors in the input variables. Must be same shape as data.x
ifixb: array_like of ints of rank-1, optionalsequence of integers with the same length as beta0 that determines which parameters are held fixed. A value of 0 fixes the parameter, a value > 0 makes the parameter free.
ifixx: array_like of ints with same shape as data.x, optionalan array of integers with the same shape as data.x that determines which input observations are treated as fixed. One can use a sequence of length m (the dimensionality of the input observations) to fix some dimensions for all observations. A value of 0 fixes the observation, a value > 0 makes it free.
job: int, optionalan integer telling ODRPACK what tasks to perform. See p. 31 of the ODRPACK User's Guide if you absolutely must set the value here. Use the method set_job post-initialization for a more readable interface.
iprint: int, optionalan integer telling ODRPACK what to print. See pp. 33-34 of the ODRPACK User's Guide if you absolutely must set the value here. Use the method set_iprint post-initialization for a more readable interface.
errfile: str, optionalstring with the filename to print ODRPACK errors to. If the file already exists, an error will be thrown. The
overwriteargument can be used to prevent this. Do Not Open This File Yourself!rptfile: str, optionalstring with the filename to print ODRPACK summaries to. If the file already exists, an error will be thrown. The
overwriteargument can be used to prevent this. Do Not Open This File Yourself!ndigit: int, optionalinteger specifying the number of reliable digits in the computation of the function.
taufac: float, optionalfloat specifying the initial trust region. The default value is 1. The initial trust region is equal to taufac times the length of the first computed Gauss-Newton step. taufac must be less than 1.
sstol: float, optionalfloat specifying the tolerance for convergence based on the relative change in the sum-of-squares. The default value is eps**(1/2) where eps is the smallest value such that 1 + eps > 1 for double precision computation on the machine. sstol must be less than 1.
partol: float, optionalfloat specifying the tolerance for convergence based on the relative change in the estimated parameters. The default value is eps**(2/3) for explicit models and
eps**(1/3)for implicit models. partol must be less than 1.maxit: int, optionalinteger specifying the maximum number of iterations to perform. For first runs, maxit is the total number of iterations performed and defaults to 50. For restarts, maxit is the number of additional iterations to perform and defaults to 10.
stpb: array_like, optionalsequence (
len(stpb) == len(beta0)) of relative step sizes to compute finite difference derivatives wrt the parameters.stpd: optionalarray (
stpd.shape == data.x.shapeorstpd.shape == (m,)) of relative step sizes to compute finite difference derivatives wrt the input variable errors. If stpd is a rank-1 array with length m (the dimensionality of the input variable), then the values are broadcast to all observations.sclb: array_like, optionalsequence (
len(stpb) == len(beta0)) of scaling factors for the parameters. The purpose of these scaling factors are to scale all of the parameters to around unity. Normally appropriate scaling factors are computed if this argument is not specified. Specify them yourself if the automatic procedure goes awry.scld: array_like, optionalarray (scld.shape == data.x.shape or scld.shape == (m,)) of scaling factors for the errors in the input variables. Again, these factors are automatically computed if you do not provide them. If scld.shape == (m,), then the scaling factors are broadcast to all observations.
work: ndarray, optionalarray to hold the double-valued working data for ODRPACK. When restarting, takes the value of self.output.work.
iwork: ndarray, optionalarray to hold the integer-valued working data for ODRPACK. When restarting, takes the value of self.output.iwork.
overwrite: bool, optionalIf it is True, output files defined by
errfileandrptfileare overwritten. The default is False.
Aliases
-
scipy.odr.ODR