Feb 11, 2021 · Feb 11, 2021
diff --git a/control/iosys.py b/control/iosys.py

        # Evaluate the function on the argument
        out = sys._out(0, np.array((0,)), np.asarray(u))
        _, out = _process_time_response(sys,[], out,[], squeeze=squeeze)
        _, out = _process_time_response(sys,None, out,None, squeeze=squeeze)
        return out

    def _update_params(self, params, warning=False):

 # Utility function to parse a signal parameter
 def _parse_signal_parameter(value, name, kwargs, end=False):
    # Check kwargs for a variant of the parameter name
    if value is None and name in kwargs:
        value = list(kwargs.pop(name))
        value = kwargs.pop(name)

    if end and kwargs:
        raise TypeError("unknown parameters %s" % kwargs)
    return value
diff --git a/control/timeresp.py b/control/timeresp.py

    Parameters
    ----------
    sys : LTI or InputOutputSystem
        System that generated the data (used to check if SISO/MIMO).

    T : 1D array
        Time values of the output
        Time values of the output.  Ignored if None.

    yout : ndarray
        Response of the system.  This can either be a 1D array indexed by time

    xout : array, optional
        Individual response of each x variable (if return_x is True). For a
        SISO system (or if a single input is specified),This should be a 2D
        SISO system (or if a single input is specified),this should be a 2D
        array indexed by the state index and time (for single input systems)
        or a 3D array indexed by state, input, and time.
        or a 3D array indexed by state, input, and time. Ignored if None.

    transpose : bool, optional
        If True, transpose all input and output arrays (for backward
        raise ValueError("unknown squeeze value")

    # Figure out whether and how to squeeze the state data
    if issiso and len(xout.shape) > 2:
    if issiso andxout is not None andlen(xout.shape) > 2:
        xout = xout[:, 0, :]            # remove input

    # See if we need to transpose the data back into MATLAB form

        # For signals, put the last index (time) into the first slot
        yout = np.transpose(yout, np.roll(range(yout.ndim), 1))
        xout = np.transpose(xout, np.roll(range(xout.ndim), 1))
        if xout is not None:
            xout = np.transpose(xout, np.roll(range(xout.ndim), 1))

    # Return time, output, and (optionally) state
    return (tout, yout, xout) if return_x else (tout, yout)
Original file line number	Diff line number	Diff line change
Expand Up		@@ -855,7 +855,7 @@ def __call__(sys, u, params=None, squeeze=None):

		# Evaluate the function on the argument
		out = sys._out(0, np.array((0,)), np.asarray(u))
		_, out = _process_time_response(sys,[], out,[], squeeze=squeeze)
		_, out = _process_time_response(sys,None, out,None, squeeze=squeeze)
		return out

		def _update_params(self, params, warning=False):
Expand DownExpand Up		@@ -1867,8 +1867,10 @@ def linearize(sys, xeq, ueq=[], t=0, params={}, **kw):

		# Utility function to parse a signal parameter
		def _parse_signal_parameter(value, name, kwargs, end=False):
		# Check kwargs for a variant of the parameter name
		if value is None and name in kwargs:
		value = list(kwargs.pop(name))
		value = kwargs.pop(name)

		if end and kwargs:
		raise TypeError("unknown parameters %s" % kwargs)
		return value
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -467,8 +467,11 @@ def _process_time_response(

		Parameters
		----------
		sys : LTI or InputOutputSystem
		System that generated the data (used to check if SISO/MIMO).

		T : 1D array
		Time values of the output
		Time values of the output. Ignored if None.

		yout : ndarray
		Response of the system. This can either be a 1D array indexed by time
Expand All		@@ -478,9 +481,9 @@ def _process_time_response(

		xout : array, optional
		Individual response of each x variable (if return_x is True). For a
		SISO system (or if a single input is specified),This should be a 2D
		SISO system (or if a single input is specified),this should be a 2D
		array indexed by the state index and time (for single input systems)
		or a 3D array indexed by state, input, and time.
		or a 3D array indexed by state, input, and time. Ignored if None.

		transpose : bool, optional
		If True, transpose all input and output arrays (for backward
Expand DownExpand Up		@@ -545,7 +548,7 @@ def _process_time_response(
		raise ValueError("unknown squeeze value")

		# Figure out whether and how to squeeze the state data
		if issiso and len(xout.shape) > 2:
		if issiso andxout is not None andlen(xout.shape) > 2:
		xout = xout[:, 0, :] # remove input

		# See if we need to transpose the data back into MATLAB form
Expand All		@@ -555,7 +558,8 @@ def _process_time_response(

		# For signals, put the last index (time) into the first slot
		yout = np.transpose(yout, np.roll(range(yout.ndim), 1))
		xout = np.transpose(xout, np.roll(range(xout.ndim), 1))
		if xout is not None:
		xout = np.transpose(xout, np.roll(range(xout.ndim), 1))

		# Return time, output, and (optionally) state
		return (tout, yout, xout) if return_x else (tout, yout)
Expand Down