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Commit 5acb956

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FranzForstmayrFranzForstmayr
authored
DEP: lsim2 deprecated in favor of lsim (scipy#15929)
likewise for step2 & impulse2
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‎doc/source/conf.py

Copy file name to clipboardExpand all lines: doc/source/conf.py
+3Lines changed: 3 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -316,6 +316,9 @@
316316
plot_pre_code = """
317317
import warnings
318318
for key in (
319+
'lsim2 is deprecated', # Deprecation of scipy.signal.lsim2
320+
'impulse2 is deprecated', # Deprecation of scipy.signal.impulse2
321+
'step2 is deprecated', # Deprecation of scipy.signal.step2
319322
'scipy.misc' # scipy.misc deprecated in v1.10.0; use scipy.datasets
320323
):
321324
warnings.filterwarnings(action='ignore', message='.*' + key + '.*')

‎scipy/signal/_ltisys.py

Copy file name to clipboardExpand all lines: scipy/signal/_ltisys.py
+64-16Lines changed: 64 additions & 16 deletions
Original file line numberDiff line numberDiff line change
@@ -34,6 +34,7 @@
3434

3535
import numpy
3636
import numpy as np
37+
from numpy.testing import suppress_warnings
3738
from numpy import (real, atleast_1d, atleast_2d, squeeze, asarray, zeros,
3839
dot, transpose, ones, zeros_like, linspace, nan_to_num)
3940
import copy
@@ -1769,6 +1770,10 @@ def lsim2(system, U=None, T=None, X0=None, **kwargs):
17691770
Simulate output of a continuous-time linear system, by using
17701771
the ODE solver `scipy.integrate.odeint`.
17711772
1773+
.. deprecated:: 1.11.0
1774+
Function `lsim2` is deprecated in favor of the faster `lsim` function.
1775+
`lsim2` will be removed in SciPy 1.13.
1776+
17721777
Parameters
17731778
----------
17741779
system : an instance of the `lti` class or a tuple describing the system.
@@ -1812,11 +1817,16 @@ def lsim2(system, U=None, T=None, X0=None, **kwargs):
18121817
18131818
Notes
18141819
-----
1815-
This function uses `scipy.integrate.odeint` to solve the
1816-
system's differential equations. Additional keyword arguments
1817-
given to `lsim2` are passed on to `odeint`. See the documentation
1820+
This function uses `scipy.integrate.odeint` to solve the system's
1821+
differential equations. Additional keyword arguments given to `lsim2`
1822+
are passed on to `scipy.integrate.odeint`. See the documentation
18181823
for `scipy.integrate.odeint` for the full list of arguments.
18191824
1825+
As `lsim2` is now deprecated, users are advised to switch to the faster
1826+
and more accurate `lsim` function. Keyword arguments for
1827+
`scipy.integrate.odeint` are not supported in `lsim`, but not needed in
1828+
general.
1829+
18201830
If (num, den) is passed in for ``system``, coefficients for both the
18211831
numerator and denominator should be specified in descending exponent
18221832
order (e.g. ``s^2 + 3s + 5`` would be represented as ``[1, 3, 5]``).
@@ -1885,6 +1895,10 @@ def lsim2(system, U=None, T=None, X0=None, **kwargs):
18851895
>>> plt.show()
18861896
18871897
"""
1898+
warnings.warn("lsim2 is deprecated and will be removed from scipy 1.13. "
1899+
"Use the feature-equivalent lsim function.",
1900+
DeprecationWarning, stacklevel=2)
1901+
18881902
if isinstance(system, lti):
18891903
sys = system._as_ss()
18901904
elif isinstance(system, dlti):
@@ -1929,7 +1943,7 @@ def lsim2(system, U=None, T=None, X0=None, **kwargs):
19291943

19301944
def fprime(x, t, sys, ufunc):
19311945
"""The vector field of the linear system."""
1932-
return dot(sys.A, x) + squeeze(dot(sys.B, nan_to_num(ufunc([t]))))
1946+
return dot(sys.A, x) + squeeze(dot(sys.B, nan_to_num(ufunc(t))))
19331947
xout = integrate.odeint(fprime, X0, T, args=(sys, ufunc), **kwargs)
19341948
yout = dot(sys.C, transpose(xout)) + dot(sys.D, transpose(U))
19351949
else:
@@ -2103,10 +2117,8 @@ def lsim(system, U, T, X0=None, interp=True):
21032117
return T, squeeze(yout), squeeze(xout)
21042118

21052119
dt = T[1] - T[0]
2106-
if not np.allclose((T[1:] - T[:-1]) / dt, 1.0):
2107-
warnings.warn("Non-uniform timesteps are deprecated. Results may be "
2108-
"slow and/or inaccurate.", DeprecationWarning)
2109-
return lsim2(system, U, T, X0)
2120+
if not np.allclose(np.diff(T), dt):
2121+
raise ValueError("Time steps are not equally spaced.")
21102122

21112123
if no_input:
21122124
# Zero input: just use matrix exponential
@@ -2279,6 +2291,10 @@ def impulse2(system, X0=None, T=None, N=None, **kwargs):
22792291
"""
22802292
Impulse response of a single-input, continuous-time linear system.
22812293
2294+
.. deprecated:: 1.11.0
2295+
Function `impulse2` is deprecated in favor of the faster `impulse`
2296+
function. `impulse2` will be removed in SciPy 1.13.
2297+
22822298
Parameters
22832299
----------
22842300
system : an instance of the LTI class or a tuple of array_like
@@ -2322,6 +2338,11 @@ def impulse2(system, X0=None, T=None, N=None, **kwargs):
23222338
The solution is generated by calling `scipy.signal.lsim2`, which uses
23232339
the differential equation solver `scipy.integrate.odeint`.
23242340
2341+
As `impulse2` is now deprecated, users are advised to switch to the faster
2342+
and more accurate `impulse` function. Keyword arguments for
2343+
`scipy.integrate.odeint` are not supported in `impulse`, but not needed in
2344+
general.
2345+
23252346
If (num, den) is passed in for ``system``, coefficients for both the
23262347
numerator and denominator should be specified in descending exponent
23272348
order (e.g. ``s^2 + 3s + 5`` would be represented as ``[1, 3, 5]``).
@@ -2334,12 +2355,18 @@ def impulse2(system, X0=None, T=None, N=None, **kwargs):
23342355
root: ``x''(t) + 2*x'(t) + x(t) = u(t)``
23352356
23362357
>>> from scipy import signal
2358+
23372359
>>> system = ([1.0], [1.0, 2.0, 1.0])
2360+
23382361
>>> t, y = signal.impulse2(system)
23392362
>>> import matplotlib.pyplot as plt
23402363
>>> plt.plot(t, y)
23412364
23422365
"""
2366+
warnings.warn("impulse2 is deprecated and will be removed from "
2367+
"scipy 1.13. Use the feature-equivalent impulse function.",
2368+
DeprecationWarning, stacklevel=2)
2369+
23432370
if isinstance(system, lti):
23442371
sys = system._as_ss()
23452372
elif isinstance(system, dlti):
@@ -2361,7 +2388,12 @@ def impulse2(system, X0=None, T=None, N=None, **kwargs):
23612388
# Move the impulse in the input to the initial conditions, and then
23622389
# solve using lsim2().
23632390
ic = B + X0
2364-
Tr, Yr, Xr = lsim2(sys, T=T, X0=ic, **kwargs)
2391+
with suppress_warnings() as sup:
2392+
sup.filter(DeprecationWarning,
2393+
"lsim2 is deprecated and will be removed from scipy 1.13. "
2394+
"Use the feature-equivalent lsim function.")
2395+
2396+
Tr, Yr, Xr = lsim2(sys, T=T, X0=ic, **kwargs)
23652397
return Tr, Yr
23662398

23672399

@@ -2394,9 +2426,6 @@ def step(system, X0=None, T=None, N=None):
23942426
yout : 1D ndarray
23952427
Step response of system.
23962428
2397-
See Also
2398-
--------
2399-
scipy.signal.step2
24002429
24012430
Notes
24022431
-----
@@ -2442,6 +2471,10 @@ def step2(system, X0=None, T=None, N=None, **kwargs):
24422471
it uses the function `scipy.signal.lsim2` to compute the step
24432472
response.
24442473
2474+
.. deprecated:: 1.11.0
2475+
Function `step2` is deprecated in favor of the faster `step` function.
2476+
`step2` will be removed in SciPy 1.13.
2477+
24452478
Parameters
24462479
----------
24472480
system : an instance of the LTI class or a tuple of array_like
@@ -2479,6 +2512,11 @@ def step2(system, X0=None, T=None, N=None, **kwargs):
24792512
24802513
Notes
24812514
-----
2515+
As `step2` is now deprecated, users are advised to switch to the faster
2516+
and more accurate `step` function. Keyword arguments for
2517+
`scipy.integrate.odeint` are not supported in `step`, but not needed in
2518+
general.
2519+
24822520
If (num, den) is passed in for ``system``, coefficients for both the
24832521
numerator and denominator should be specified in descending exponent
24842522
order (e.g. ``s^2 + 3s + 5`` would be represented as ``[1, 3, 5]``).
@@ -2489,15 +2527,21 @@ def step2(system, X0=None, T=None, N=None, **kwargs):
24892527
--------
24902528
>>> from scipy import signal
24912529
>>> import matplotlib.pyplot as plt
2530+
24922531
>>> lti = signal.lti([1.0], [1.0, 1.0])
24932532
>>> t, y = signal.step2(lti)
2533+
24942534
>>> plt.plot(t, y)
24952535
>>> plt.xlabel('Time [s]')
24962536
>>> plt.ylabel('Amplitude')
24972537
>>> plt.title('Step response for 1. Order Lowpass')
24982538
>>> plt.grid()
24992539
25002540
"""
2541+
warnings.warn("step2 is deprecated and will be removed from scipy 1.13. "
2542+
"Use the feature-equivalent step function.",
2543+
DeprecationWarning, stacklevel=2)
2544+
25012545
if isinstance(system, lti):
25022546
sys = system._as_ss()
25032547
elif isinstance(system, dlti):
@@ -2512,7 +2556,12 @@ def step2(system, X0=None, T=None, N=None, **kwargs):
25122556
else:
25132557
T = asarray(T)
25142558
U = ones(T.shape, sys.A.dtype)
2515-
vals = lsim2(sys, U, T, X0=X0, **kwargs)
2559+
2560+
with suppress_warnings() as sup:
2561+
sup.filter(DeprecationWarning,
2562+
"lsim2 is deprecated and will be removed from scipy 1.13. "
2563+
"Use the feature-equivalent lsim function.")
2564+
vals = lsim2(sys, U, T, X0=X0, **kwargs)
25162565
return vals[0], vals[1]
25172566

25182567

@@ -3358,10 +3407,9 @@ def place_poles(A, B, poles, method="YT", rtol=1e-3, maxiter=30):
33583407
# don't annoy him
33593408
err_msg = (
33603409
"Convergence was not reached after maxiter iterations.\n"
3361-
"You asked for a relative tolerance of %f we got %f" %
3362-
(rtol, cur_rtol)
3410+
f"You asked for a tolerance of {rtol}, we got {cur_rtol}."
33633411
)
3364-
warnings.warn(err_msg)
3412+
warnings.warn(err_msg, stacklevel=2)
33653413

33663414
# reconstruct transfer_matrix to match complex conjugate pairs,
33673415
# ie transfer_matrix_j/transfer_matrix_j+1 are

‎scipy/signal/tests/test_cont2discrete.py

Copy file name to clipboardExpand all lines: scipy/signal/tests/test_cont2discrete.py
+7-11Lines changed: 7 additions & 11 deletions
Original file line numberDiff line numberDiff line change
@@ -5,8 +5,8 @@
55

66
import pytest
77
from scipy.signal import cont2discrete as c2d
8-
from scipy.signal import dlsim, ss2tf, ss2zpk, lsim2, lti
9-
from scipy.signal import tf2ss, impulse2, dimpulse, step2, dstep
8+
from scipy.signal import dlsim, ss2tf, ss2zpk, lsim, lti
9+
from scipy.signal import tf2ss, impulse, dimpulse, step, dstep
1010

1111
# Author: Jeffrey Armstrong <jeff@approximatrix.com>
1212
# March 29, 2011
@@ -294,9 +294,8 @@ def u(t):
294294
dt = t[1] - t[0]
295295
u1 = u(t)
296296

297-
# Use lsim2 to compute the solution to the continuous system.
298-
t, yout, xout = lsim2((a, b, c, d), T=t, U=u1, X0=x0,
299-
rtol=1e-9, atol=1e-11)
297+
# Use lsim to compute the solution to the continuous system.
298+
t, yout, xout = lsim((a, b, c, d), T=t, U=u1, X0=x0)
300299

301300
# Convert the continuous system to a discrete approximation.
302301
dsys = c2d((a, b, c, d), dt, method='bilinear')
@@ -390,15 +389,12 @@ class TestC2dInvariants:
390389
(tf2ss(0.1, [1, 1, 2, 1]), 0.5, 10),
391390
]
392391

393-
# Some options for lsim2 and derived routines
394-
tolerances = {'rtol': 1e-9, 'atol': 1e-11}
395-
396392
# Check that systems discretized with the impulse-invariant
397393
# method really hold the invariant
398394
@pytest.mark.parametrize("sys,sample_time,samples_number", cases)
399395
def test_impulse_invariant(self, sys, sample_time, samples_number):
400396
time = np.arange(samples_number) * sample_time
401-
_, yout_cont = impulse2(sys, T=time, **self.tolerances)
397+
_, yout_cont = impulse(sys, T=time)
402398
_, yout_disc = dimpulse(c2d(sys, sample_time, method='impulse'),
403399
n=len(time))
404400
assert_allclose(sample_time * yout_cont.ravel(), yout_disc[0].ravel())
@@ -407,14 +403,14 @@ def test_impulse_invariant(self, sys, sample_time, samples_number):
407403
@pytest.mark.parametrize("sys,sample_time,samples_number", cases)
408404
def test_step_invariant(self, sys, sample_time, samples_number):
409405
time = np.arange(samples_number) * sample_time
410-
_, yout_cont = step2(sys, T=time, **self.tolerances)
406+
_, yout_cont = step(sys, T=time)
411407
_, yout_disc = dstep(c2d(sys, sample_time, method='zoh'), n=len(time))
412408
assert_allclose(yout_cont.ravel(), yout_disc[0].ravel())
413409

414410
# Linear invariant should hold for FOH discretized systems
415411
@pytest.mark.parametrize("sys,sample_time,samples_number", cases)
416412
def test_linear_invariant(self, sys, sample_time, samples_number):
417413
time = np.arange(samples_number) * sample_time
418-
_, yout_cont, _ = lsim2(sys, T=time, U=time, **self.tolerances)
414+
_, yout_cont, _ = lsim(sys, T=time, U=time)
419415
_, yout_disc, _ = dlsim(c2d(sys, sample_time, method='foh'), u=time)
420416
assert_allclose(yout_cont.ravel(), yout_disc.ravel())

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