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miso tf2ss fails without slycot #120
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- changed the title
[-]mimo ss2tf fails without slycot[/-][+]miso ss2tf fails without slycot[/+]on Nov 14, 2016 - changed the title
[-]miso ss2tf fails without slycot[/-][+]miso tf2ss fails without slycot[/+]on Nov 14, 2016 Scipy doesn't seem to like SIMO or MISO, including when denominators are matched. Note the error in that last case: I get the feeling
scipy.signal.ltiis intended for SISO.import sys import numpy import scipy print('sys.version:',sys.version) print('numpy.__version__:',numpy.__version__) print('scipy.__version__:',scipy.__version__) import numpy as np from control.matlab import * import scipy.signal def testit(sys): print('sys is ',sys.outputs,'x',sys.inputs) try: scipy.signal.lti(np.squeeze(sys.num),np.squeeze(sys.den)) print('success!') except ValueError as e: print('gives ValueError',e) # 1x1 testit(tf([1],[1,1])) # 1x1 as list-of-list-of-vectors testit(tf([[[1]]],[[[1,1]]])) # 1x3 testit(tf([[[-235, 1.146e4], [-235, 1.146E4], [-235, 1.146E4, 0]]], [[[1, 48.78, 0], [1, 48.78, 0, 0], [0.008, 1.39, 48.78]]])) # 3x1 testit(tf([[[-235, 1.146e4]], [[-235, 1.146E4]], [[-235, 1.146E4, 0]]], [[[1, 48.78, 0]], [[1, 48.78, 0, 0]], [[0.008, 1.39, 48.78]]])) # 3x1 with matched denominators testit(tf([[[-235, 1.146e4]], [[-235, 1.146E4]], [[-235, 1.146E4, 0]]], [[[1, 48.78, 0]], [[1, 48.78, 0]], [[1, 48.78, 0]]]))
gives
$ python sample.py sys.version: 3.5.2 |Continuum Analytics, Inc.| (default, Jul 2 2016, 17:53:06) [GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] numpy.__version__: 1.11.1 scipy.__version__: 0.18.0 sys is 1 x 1 success! sys is 1 x 1 success! sys is 1 x 3 gives ValueError The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() sys is 3 x 1 gives ValueError The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() sys is 3 x 1 gives ValueError Denominator polynomial must be rank-1 array.- added a commit that references this issue
on Dec 26, 2016
This looks like it is failing to throw the warning to the user about it being miso and not supported without slycot for some reason.
tf = control.tf([[[-235, 1.146e4], [-235, 1.146E4], [-235, 1.146E4, 0]]], [[[1, 48.78, 0], [1, 48.78, 0, 0], [0.008, 1.39, 48.78]]]) tf Out[80]: Input 1 to output 1: -235 s + 1.146e+04 ------------------ s^2 + 48.78 s Input 2 to output 1: -235 s + 1.146e+04 ------------------ s^3 + 48.78 s^2 Input 3 to output 1: -235 s^2 + 1.146e+04 s -------------------------- 0.008 s^2 + 1.39 s + 48.78 In [81]: control.tf2ss(tf) --------------------------------------------------------------------------- ImportError Traceback (most recent call last) /home/jgoppert/anaconda3/lib/python3.5/site-packages/control-dev-py3.5.egg/control/statesp.py in _convertToStateSpace(sys, **kw) 646 try: --> 647 from slycot import td04ad 648 if len(kw): ImportError: No module named 'slycot' During handling of the above exception, another exception occurred: ValueError Traceback (most recent call last) <ipython-input-81-c8ef26438f31> in <module>() 1 ----> 2 control.tf2ss(tf) /home/jgoppert/anaconda3/lib/python3.5/site-packages/control-dev-py3.5.egg/control/statesp.py in tf2ss(*args) 1082 raise TypeError("tf2ss(sys): sys must be a TransferFunction \ 1083 object.") -> 1084 return _convertToStateSpace(sys) 1085 else: 1086 raise ValueError("Needs 1 or 2 arguments; received %i." % len(args)) /home/jgoppert/anaconda3/lib/python3.5/site-packages/control-dev-py3.5.egg/control/statesp.py in _convertToStateSpace(sys, **kw) 671 # I think this will fail if num and den aren't 1-D after 672 # the squeeze --> 673 lti_sys = lti(squeeze(sys.num), squeeze(sys.den)) 674 return StateSpace(lti_sys.A, lti_sys.B, lti_sys.C, lti_sys.D, 675 sys.dt) /home/jgoppert/anaconda3/lib/python3.5/site-packages/scipy/signal/ltisys.py in __init__(self, *system, **kwargs) 759 self._den = None 760 --> 761 self.num, self.den = normalize(*system) 762 763 def __repr__(self): /home/jgoppert/anaconda3/lib/python3.5/site-packages/scipy/signal/filter_design.py in normalize(b, a) 1084 if len(b.shape) == 1: 1085 b = asarray([b], b.dtype.char) -> 1086 while a[0] == 0.0 and len(a) > 1: 1087 a = a[1:] 1088 outb = b * (1.0) / a[0] ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()