Mar 20, 2021 · Mar 17, 2021 · Mar 17, 2021 · Mar 17, 2021 · Mar 17, 2021 · Mar 18, 2021
diff --git a/control/matlab/timeresp.py b/control/matlab/timeresp.py
                        transpose=True, return_x=return_x)
    return (out[1], out[0], out[2]) if return_x else (out[1], out[0])

 def stepinfo(sys, T=None, SettlingTimeThreshold=0.02,

 def stepinfo(sysdata, T=None, yfinal=None, SettlingTimeThreshold=0.02,
             RiseTimeLimits=(0.1, 0.9)):
 '''
 """
    Step response characteristics (Rise time, Settling Time, Peak and others).

    Parameters
    ----------
 sys: StateSpace, or TransferFunction
        LTI system tosimulate

    T: array-like ornumber, optional
 sysdata: StateSpace or TransferFunction or array_like
 The system data. EitherLTI system tosimilate (StateSpace,
        TransferFunction), or a time series of step response data.
    T : array_like orfloat, optional
        Time vector, or simulation time duration if a number (time vector is
        autocomputed if not given)

    SettlingTimeThreshold: float value, optional
        autocomputed if not given).
        Required, if sysdata is a time series of response data.
    yfinal : scalar or array_like, optional
        Steady-state response. If not given, sysdata.dcgain() is used for
        systems to simulate and the last value of the the response data is
        used for a given time series of response data. Scalar for SISO,
        (noutputs, ninputs) array_like for MIMO systems.
    SettlingTimeThreshold : float, optional
        Defines the error to compute settling time (default = 0.02)

    RiseTimeLimits: tuple (lower_threshold, upper_theshold)
    RiseTimeLimits : tuple (lower_threshold, upper_theshold)
        Defines the lower and upper threshold for RiseTime computation

    Returns
    -------
    S: a dictionary containing:
        RiseTime: Time from 10% to 90% of the steady-state value.
        SettlingTime: Time to enter inside a default error of 2%
        SettlingMin: Minimum value after RiseTime
        SettlingMax: Maximum value after RiseTime
        Overshoot: Percentage of the Peak relative to steady value
        Undershoot: Percentage of undershoot
        Peak: Absolute peak value
        PeakTime: time of the Peak
        SteadyStateValue: Steady-state value
    S : dict or list of list of dict
        If `sysdata` corresponds to a SISO system, S is a dictionary
        containing:

        RiseTime:
            Time from 10% to 90% of the steady-state value.
        SettlingTime:
            Time to enter inside a default error of 2%
        SettlingMin:
            Minimum value after RiseTime
        SettlingMax:
            Maximum value after RiseTime
        Overshoot:
            Percentage of the Peak relative to steady value
        Undershoot:
            Percentage of undershoot
        Peak:
            Absolute peak value
        PeakTime:
            time of the Peak
        SteadyStateValue:
            Steady-state value

        If `sysdata` corresponds to a MIMO system, `S` is a 2D list of dicts.
        To get the step response characteristics from the j-th input to the
        i-th output, access ``S[i][j]``


    See Also
    Examples
    --------
    >>> S = stepinfo(sys, T)
 '''
 """
    from ..timeresp import step_info

    # Call step_info with MATLAB defaults
    S = step_info(sys, T, None, SettlingTimeThreshold, RiseTimeLimits)
    S = step_info(sysdata, T=T, T_num=None, yfinal=yfinal,
                  SettlingTimeThreshold=SettlingTimeThreshold,
                  RiseTimeLimits=RiseTimeLimits)

    return S

diff --git a/control/tests/sisotool_test.py b/control/tests/sisotool_test.py

        # Check the step response before moving the point
        step_response_original = np.array(
            [0.    , 0.021, 0.124, 0.3146, 0.5653, 0.8385, 1.0969, 1.3095,
             1.4549, 1.5231])
            [0.    , 0.0216, 0.1271, 0.3215, 0.5762, 0.8522, 1.1114, 1.3221,
             1.4633, 1.5254])
        assert_array_almost_equal(
            ax_step.lines[0].get_data()[1][:10], step_response_original, 4)


        # Check if the step response has changed
        step_response_moved = np.array(
            [0.    , 0.023, 0.1554, 0.4401, 0.8646, 1.3722, 1.875, 2.2709,
 2.4633, 2.3827])
            [0.    , 0.0237, 0.1596, 0.4511, 0.884, 1.3985, 1.9031, 2.2922,
 2.4676, 2.3606])
        assert_array_almost_equal(
            ax_step.lines[0].get_data()[1][:10], step_response_moved, 4)

        # but 2 input, 1 output should
        with pytest.raises(ControlMIMONotImplemented):
            sisotool(sys221)
Original file line number	Diff line number	Diff line change
Expand Up		@@ -64,38 +64,59 @@ def step(sys, T=None, X0=0., input=0, output=None, return_x=False):
		transpose=True, return_x=return_x)
		return (out[1], out[0], out[2]) if return_x else (out[1], out[0])

		def stepinfo(sys, T=None, SettlingTimeThreshold=0.02,

		def stepinfo(sysdata, T=None, yfinal=None, SettlingTimeThreshold=0.02,
		RiseTimeLimits=(0.1, 0.9)):
		'''
		"""
		Step response characteristics (Rise time, Settling Time, Peak and others).

		Parameters
		----------
		sys: StateSpace, or TransferFunction
		LTI system tosimulate

		T: array-like ornumber, optional
		sysdata: StateSpace or TransferFunction or array_like
		The system data. EitherLTI system tosimilate (StateSpace,
		TransferFunction), or a time series of step response data.
		T : array_like orfloat, optional
		Time vector, or simulation time duration if a number (time vector is
		autocomputed if not given)

		SettlingTimeThreshold: float value, optional
		autocomputed if not given).
		Required, if sysdata is a time series of response data.
		yfinal : scalar or array_like, optional
		Steady-state response. If not given, sysdata.dcgain() is used for
		systems to simulate and the last value of the the response data is
		used for a given time series of response data. Scalar for SISO,
		(noutputs, ninputs) array_like for MIMO systems.
		SettlingTimeThreshold : float, optional
		Defines the error to compute settling time (default = 0.02)

		RiseTimeLimits: tuple (lower_threshold, upper_theshold)
		RiseTimeLimits : tuple (lower_threshold, upper_theshold)
		Defines the lower and upper threshold for RiseTime computation

		Returns
		-------
		S: a dictionary containing:
		RiseTime: Time from 10% to 90% of the steady-state value.
		SettlingTime: Time to enter inside a default error of 2%
		SettlingMin: Minimum value after RiseTime
		SettlingMax: Maximum value after RiseTime
		Overshoot: Percentage of the Peak relative to steady value
		Undershoot: Percentage of undershoot
		Peak: Absolute peak value
		PeakTime: time of the Peak
		SteadyStateValue: Steady-state value
		S : dict or list of list of dict
		If `sysdata` corresponds to a SISO system, S is a dictionary
		containing:

		RiseTime:
		Time from 10% to 90% of the steady-state value.
		SettlingTime:
		Time to enter inside a default error of 2%
		SettlingMin:
		Minimum value after RiseTime
		SettlingMax:
		Maximum value after RiseTime
		Overshoot:
		Percentage of the Peak relative to steady value
		Undershoot:
		Percentage of undershoot
		Peak:
		Absolute peak value
		PeakTime:
		time of the Peak
		SteadyStateValue:
		Steady-state value

		If `sysdata` corresponds to a MIMO system, `S` is a 2D list of dicts.
		To get the step response characteristics from the j-th input to the
		i-th output, access ``S[i][j]``


		See Also
Expand All		@@ -105,11 +126,13 @@ def stepinfo(sys, T=None, SettlingTimeThreshold=0.02,
		Examples
		--------
		>>> S = stepinfo(sys, T)
		'''
		"""
		from ..timeresp import step_info

		# Call step_info with MATLAB defaults
		S = step_info(sys, T, None, SettlingTimeThreshold, RiseTimeLimits)
		S = step_info(sysdata, T=T, T_num=None, yfinal=yfinal,
		SettlingTimeThreshold=SettlingTimeThreshold,
		RiseTimeLimits=RiseTimeLimits)

		return S

Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -68,8 +68,8 @@ def test_sisotool(self, sys):

		# Check the step response before moving the point
		step_response_original = np.array(
		[0. , 0.021, 0.124, 0.3146, 0.5653, 0.8385, 1.0969, 1.3095,
		1.4549, 1.5231])
		[0. , 0.0216, 0.1271, 0.3215, 0.5762, 0.8522, 1.1114, 1.3221,
		1.4633, 1.5254])
		assert_array_almost_equal(
		ax_step.lines[0].get_data()[1][:10], step_response_original, 4)

Expand DownExpand Up		@@ -113,8 +113,8 @@ def test_sisotool(self, sys):

		# Check if the step response has changed
		step_response_moved = np.array(
		[0. , 0.023, 0.1554, 0.4401, 0.8646, 1.3722, 1.875, 2.2709,
		2.4633, 2.3827])
		[0. , 0.0237, 0.1596, 0.4511, 0.884, 1.3985, 1.9031, 2.2922,
		2.4676, 2.3606])
		assert_array_almost_equal(
		ax_step.lines[0].get_data()[1][:10], step_response_moved, 4)

Expand DownExpand Up		@@ -157,7 +157,3 @@ def test_sisotool_mimo(self, sys222, sys221):
		# but 2 input, 1 output should
		with pytest.raises(ControlMIMONotImplemented):
		sisotool(sys221)