# How to use the numdifftools.nd_cstep.MinStepGenerator function in numdifftools

## To help you get started, weâ€™ve selected a few numdifftools examples, based on popular ways it is used in public projects.

Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately.

pbrod / numdifftools / numdifftools / nd_cstep.py View on Github
``````method = 'complex'
data = []
for name in ['exp', 'expm1', 'sin', 'cos', 'square']:
# function_names[:-3]:
for order in range(4, 5, 1):
#  order = 1
for n in range(1, 16, 1):
num_steps = n + order - 1 + num_extrap
if method in ['central', 'complex']:
step = 2
if (n > 1 or order >= 4) and method == 'complex':
step = 4
num_steps = (n + order-1) // step + num_extrap

step_ratio = 1.6  # 4**(1./n)
epsilon = MinStepGenerator(num_steps=num_steps,
step_ratio=step_ratio,
offset=0, use_exact_steps=True)
data.append(pd.DataFrame(_example3(x=0.7, fun_name=name,
epsilon=epsilon,
method=method,
scale=None, n=n,
order=order),
index=np.arange(1)))
df = pd.concat(data)
# sprint(df)
print(df.groupby(['n']).mean())
print(np.diff(df.groupby(['n']).mean(), axis=0))
plt.show('hold')``````
pbrod / numdifftools / numdifftools / nd_cstep.py View on Github
``````'''
step_nom : vector   default maximum(log1p(abs(x0)), 1)
Nominal step. (The steps: h_i = step_nom[i] * delta)
step_max : real scalar  (Default 2.0)
Maximum allowed excursion from step_nom as a multiple of it.
step_ratio: real scalar  (Default 2.0)
Ratio used between sequential steps in the estimation of the derivative
step_num : integer  (Default 26)
The minimum step_num for making richardson extrapolation work is
7 + np.ceil(self.n/2.) + self.order + self.richardson_terms
delta : vector default step_max*step_ratio**(-arange(step_num))
Defines the steps sizes used in derivation: h_i = step_nom[i] * delta
'''

class MaxStepGenerator(MinStepGenerator):
'''
Generates a sequence of steps

where
steps = base_step * step_ratio ** (-np.arange(num_steps) + offset)
base_step = step_max * step_nom

Parameters
----------
max_step : float, array-like, optional default 2
Defines the maximum step
step_ratio : real scalar, optional, default 2
Ratio between sequential steps generated.
Note: Ratio > 1
num_steps : scalar integer, optional, default  n + order - 1 + num_extrap
defines number of steps generated. It should be larger than``````
pbrod / numdifftools / numdifftools / nd_cstep.py View on Github
``````def _make_generator(self, step):
if hasattr(step, '__call__'):
return step
if step is None and self.method not in ['complex']:
return MaxStepGenerator(step_ratio=None, num_extrap=7)
return MinStepGenerator(base_step=step, step_ratio=None, num_extrap=0)``````

## numdifftools

Solves automatic numerical differentiation problems in one or more variables.

BSD-3-Clause