5.1.2.3. numdifftools.step_generators.MinStepGenerator
- class MinStepGenerator(base_step=None, step_ratio=None, num_steps=None, step_nom=None, offset=0, num_extrap=0, use_exact_steps=True, check_num_steps=True, scale=None)[source]
Generates a sequence of steps
- where
steps = step_nom * base_step * step_ratio ** (i + offset)
for i = num_steps-1,… 1, 0.
- Parameters:
base_step (float, array-like, optional) – Defines the minimum 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(exp(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, optional) – scale used in base step. If not None it will override the default computed with the default_scale function.
- __init__(base_step=None, step_ratio=None, num_steps=None, step_nom=None, offset=0, num_extrap=0, use_exact_steps=True, check_num_steps=True, scale=None)[source]
Methods
__init__([base_step, step_ratio, num_steps, ...])step_generator_function(x[, method, n, order])Step generator function
Attributes
Base step defines the minimum or maximum step when offset==0.
Minimum number of steps required given the differentiation method and order.
Defines number of steps generated
Scale used in base step.
Nominal step
Ratio between sequential steps generated