t_eval is not respected for system with 0 states

It seems that t_eval is ignored when simulating a system with nstates=0.

The bug seems to be located at:

Lines 1767 to 1777 in 3b5f199

    
           if nstates == 0: 
        
               # No states => map input to output 
        
               u = U[0] if len(U.shape) == 1 else U[:, 0] 
        
               y = np.zeros((np.shape(sys._out(T[0], X0, u))[0], len(T))) 
        
               for i in range(len(T)): 
        
                   u = U[i] if len(U.shape) == 1 else U[:, i] 
        
                   y[:, i] = sys._out(T[i], [], u) 
        
               return TimeResponseData( 
        
                   T, y, None, U, issiso=sys.issiso(), 
        
                   output_labels=sys.output_index, input_labels=sys.input_index, 
        
                   transpose=transpose, return_x=return_x, squeeze=squeeze)

Instead, the following lines are expected to be used, I think:

python-control/control/iosys.py

Lines 1798 to 1825 in 3b5f199

    
           def ufun(t): 
        
               # Find the value of the index using linear interpolation 
        
               # Use clip to allow for extrapolation if t is out of range 
        
               idx = np.clip(np.searchsorted(T, t, side='left'), 1, len(T)-1) 
        
               dt = (t - T[idx-1]) / (T[idx] - T[idx-1]) 
        
               return U[..., idx-1] * (1. - dt) + U[..., idx] * dt 
        
           # Check to make sure this is not a static function 
        
           if nstates == 0:            # No states => map input to output 
        
               # Make sure the user gave a time vector for evaluation (or 'T') 
        
               if t_eval is None: 
        
                   # User overrode t_eval with None, but didn't give us the times... 
        
                   warn("t_eval set to None, but no dynamics; using T instead") 
        
                   t_eval = T 
        
               # Allocate space for the inputs and outputs 
        
               u = np.zeros((ninputs, len(t_eval))) 
        
               y = np.zeros((noutputs, len(t_eval))) 
        
               # Compute the input and output at each point in time 
        
               for i, t in enumerate(t_eval): 
        
                   u[:, i] = ufun(t) 
        
                   y[:, i] = sys._out(t, [], u[:, i]) 
        
               return TimeResponseData( 
        
                   t_eval, y, None, u, issiso=sys.issiso(), 
        
                   output_labels=sys.output_index, input_labels=sys.input_index, 
        
                   transpose=transpose, return_x=return_x, squeeze=squeeze)

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	if nstates == 0:
	# No states => map input to output
	u = U[0] if len(U.shape) == 1 else U[:, 0]
	y = np.zeros((np.shape(sys._out(T[0], X0, u))[0], len(T)))
	for i in range(len(T)):
	u = U[i] if len(U.shape) == 1 else U[:, i]
	y[:, i] = sys._out(T[i], [], u)
	return TimeResponseData(
	T, y, None, U, issiso=sys.issiso(),
	output_labels=sys.output_index, input_labels=sys.input_index,
	transpose=transpose, return_x=return_x, squeeze=squeeze)

	def ufun(t):
	# Find the value of the index using linear interpolation
	# Use clip to allow for extrapolation if t is out of range
	idx = np.clip(np.searchsorted(T, t, side='left'), 1, len(T)-1)
	dt = (t - T[idx-1]) / (T[idx] - T[idx-1])
	return U[..., idx-1] * (1. - dt) + U[..., idx] * dt

	# Check to make sure this is not a static function
	if nstates == 0: # No states => map input to output
	# Make sure the user gave a time vector for evaluation (or 'T')
	if t_eval is None:
	# User overrode t_eval with None, but didn't give us the times...
	warn("t_eval set to None, but no dynamics; using T instead")
	t_eval = T

	# Allocate space for the inputs and outputs
	u = np.zeros((ninputs, len(t_eval)))
	y = np.zeros((noutputs, len(t_eval)))

	# Compute the input and output at each point in time
	for i, t in enumerate(t_eval):
	u[:, i] = ufun(t)
	y[:, i] = sys._out(t, [], u[:, i])

	return TimeResponseData(
	t_eval, y, None, u, issiso=sys.issiso(),
	output_labels=sys.output_index, input_labels=sys.input_index,
	transpose=transpose, return_x=return_x, squeeze=squeeze)

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