5.1.2.4. numdifftools.step_generators.MaxStepGenerator¶
-
class
MaxStepGenerator
(base_step=2.0, step_ratio=2.0, num_steps=15, step_nom=None, offset=0, num_extrap=0, use_exact_steps=False, check_num_steps=True, scale=500)[source]¶ Generates a sequence of steps
- where
- steps = step_nom * base_step * step_ratio ** (-i + offset)
for i = 0, 1, …, num_steps-1.
Parameters: - base_step : float, array-like, default 2.0
Defines the maximum step, if None, the value is set to EPS**(1/scale)
- step_ratio : real scalar, optional, default 2
Ratio between sequential steps generated. Note: Ratio > 1 If None then step_ratio is 2 for n=1 otherwise step_ratio is 1.6
- num_steps : scalar integer, optional, default min_num_steps + num_extrap
defines number of steps generated. It should be larger than min_num_steps = (n + order - 1) / fact where fact is 1, 2 or 4 depending on differentiation method used.
- step_nom : default maximum(log(1+|x|), 1)
Nominal step where x is supplied at runtime through the __call__ method.
- offset : real scalar, optional, default 0
offset to the base step
- num_extrap : scalar integer, default 0
number of points used for extrapolation
- check_num_steps : boolean, default True
If True make sure num_steps is larger than the minimum required steps.
- use_exact_steps : boolean, default True
If true make sure exact steps are generated
- scale : real scalar, default 500
scale used in base step.
-
__init__
(base_step=2.0, step_ratio=2.0, num_steps=15, step_nom=None, offset=0, num_extrap=0, use_exact_steps=False, check_num_steps=True, scale=500)[source]¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__
([base_step, step_ratio, num_steps, …])Initialize self. step_generator_function
(x[, method, n, order])Attributes
base_step
min_num_steps
num_steps
scale
step_nom
step_ratio