python-control | Python Control Systems Library is a Python module
kandi X-RAY | python-control Summary
kandi X-RAY | python-control Summary
The Python Control Systems Library is a Python module that implements basic operations for analysis and design of feedback control systems.
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Top functions reviewed by kandi - BETA
- Construct an input output response
- Return True if sys isctime
- Determine the size of a system component
- Return whether this time is actime
- Solve the linear objective function
- Compute the basis matrix for a flag
- Evaluate the derivative of a function
- R Generate a linear solution to a point
- R Compute the solution of an equation
- Plot a phase plot
- Return the first occurrence of a condition
- Create a StateFK with the given parameters
- Create a StateSystem object from an LTI system
- Create an estimator for a given system
- Simulate a step response
- R Compute transfer function
- R Solve an objective problem
- Construct a StateSpace from an LTI system
- Generate a Gangof4 plot
- Generate a plot of a function
- Generate sisotool plot
- Compute the equation of the equation
- Use legacy defaults
- Convert a tf to a StateSpace object
- Generate the constraint function
- Calculate the cost function
- Return the frequency response of the system
python-control Key Features
python-control Examples and Code Snippets
y, f_lin = linearize(f, x)
y_dot = f_lin(x_dot)
y, y_dot = jvp(f, (x,), (x_dot,))
jvp : (a -> b) -> (UnrestrictedUse a, T a) -o (UnrestrictedUse b, T b)
def split_half(lst: List[Any]) -> Tuple[List[Any], List[Any]]:
assert not len(lst)
def jit(f):
def f_jitted(*args):
avals_in = [raise_to_shaped(get_aval(x)) for x in args]
jaxpr, consts, out_tree = make_jaxpr(f, *avals_in)
outs = bind(xla_call_p, *consts, *args, jaxpr=jaxpr, num_consts=len(consts))
return tree_unf
:id: nVkhbIFAOGZk
from jax import custom_jvp
import jax.numpy as jnp
# f :: a -> b
@custom_jvp
def f(x):
return jnp.sin(x)
# f_jvp :: (a, T a) -> (b, T b)
def f_jvp(primals, tangents):
x, = primals
t, = tangents
return f(x), jnp.cos(
def function(func=None,
input_signature=None,
autograph=True,
jit_compile=None,
reduce_retracing=False,
experimental_implements=None,
experimental_autograph_options=None,
def defun(func=None,
input_signature=None,
autograph=True,
experimental_autograph_options=None,
reduce_retracing=False):
"""Compiles a Python function into a callable TensorFlow graph.
`defun` (short for "
#!/usr/bin/env python
import sqlite3
import sys
from pygments.lexers.sql import SqlLexer
from prompt_toolkit import PromptSession
from prompt_toolkit.completion import WordCompleter
from prompt_toolkit.lexers import PygmentsLexer
from prompt_toolki
student_data = {}
with open("test.txt", 'r') as f:
data = f.readlines()
for line in data:
line_list = line.strip().split()
student_data[line_list[0] + ' ' + line_list[1]] = int(line_list[2])
print("Students with gr
Nesterenkov P. 4
Ivanov O. 4
Dmitriev N. 2
Petrov I. 3
...
file = open("grades.txt", 'r')
lines = file.readlines()
for line in lines:
if line == '' or line == '\n' or line.__len__() < 5:
continue
return concat_order(str1[1:], str2[1:])
return new_str
def concat_order(str1, str2, new_str):
if len(str1) == 0:
return new_str
new_str += str1[0] + str2[0]
return concat_order(str1[1:]
Community Discussions
Trending Discussions on python-control
QUESTION
The following code does not work:
...ANSWER
Answered 2021-May-30 at 03:49No, for the reasons you mention, there's currently no way to use jnp.unique
on a non-static value.
In similar cases, JAX sometimes adds extra parameters that can be used to specify a static size for the output (for example, the size
parameter in jax.numpy.nonzero
) but nothing like that is currently implemented for jnp.unique
. If that is something you'd like, it would be worth filing a feature request.
QUESTION
I have some code like this here that describes an expression in SymPy
(https://www.sympy.org/en/index.html):
ANSWER
Answered 2020-May-21 at 23:58Poly
has an all_coeffs
method that can be applied to the identified numerator and denominator of a rational expression, e.g.
QUESTION
I am using Eclipse (NSight Release 8.0) with PyDev (4.5.5) as my Python editor and I just started using Anaconda 3.6, since I need some GPU capabilities of it (Numba).
I am trying to import a Python module named "Control", a PyPi package. I installed it using conda skeleton, as described in here. When I try to import it using IDLE3 (which is configured for Anaconda), everything works fine, but when I try it inside Eclipse, I get the following error message:
import control ModuleNotFoundError: No module named 'control'
I tried many solution that I've found, for example, here and here, but none of them work.
How can I make Eclipse recognize the installed packages?
...ANSWER
Answered 2017-Sep-22 at 18:01The solution is, instead of using conda skeleton, use
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install python-control
You can use python-control like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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