Nov 3, 2021 · Nov 2, 2021 · Nov 2, 2021
diff --git a/control/statesp.py b/control/statesp.py
        # transformed state matrices, at, bt, ct.

        # Start at the second frequency, already have the first.
        for kk, x_kk in enumerate(x_arr[1:len(x_arr)]):
        for kk, x_kk in enumerate(x_arr[1:]):
            result = tb05ad(n, m, p, x_kk, at, bt, ct, job='NH')
            # When job='NH', result = (g_i, hinvb, info)

        Attempts to use Laub's method from Slycot library, with a
        fall-back to python code.
        """
        # Make sure the argument is a 1D array of complex numbers
        x_arr = np.atleast_1d(x).astype(complex, copy=False)

        # return fast on systems with 0 or 1 state
        if not config.defaults['statesp.use_numpy_matrix']:
            if self.nstates == 0:
                return self.D[:, :, np.newaxis] \
                    * np.ones_like(x_arr, dtype=complex)
            if self.nstates == 1:
                with np.errstate(divide='ignore', invalid='ignore'):
                    out = self.C[:, :, np.newaxis] \
                          / (x_arr - self.A[0, 0]) \
                          * self.B[:, :, np.newaxis] \
                          + self.D[:, :, np.newaxis]
                out[np.isnan(out)] = complex(np.inf, np.nan)
                return out

        try:
            out = self.slycot_laub(x)
            out = self.slycot_laub(x_arr)
        except (ImportError, Exception):
            # Fall back because either Slycot unavailable or cannot handle
            # certain cases.

            # Make sure the argument is a 1D array of complex numbers
            x_arr = np.atleast_1d(x).astype(complex, copy=False)

            # Make sure that we are operating on a simple list
            if len(x_arr.shape) > 1:
                raise ValueError("input list must be 1D")
Original file line number	Diff line number	Diff line change
Expand Up		@@ -851,7 +851,7 @@ def slycot_laub(self, x):
		# transformed state matrices, at, bt, ct.

		# Start at the second frequency, already have the first.
		for kk, x_kk in enumerate(x_arr[1:len(x_arr)]):
		for kk, x_kk in enumerate(x_arr[1:]):
		result = tb05ad(n, m, p, x_kk, at, bt, ct, job='NH')
		# When job='NH', result = (g_i, hinvb, info)

Expand DownExpand Up		@@ -885,15 +885,29 @@ def horner(self, x, warn_infinite=True):
		Attempts to use Laub's method from Slycot library, with a
		fall-back to python code.
		"""
		# Make sure the argument is a 1D array of complex numbers
		x_arr = np.atleast_1d(x).astype(complex, copy=False)

		# return fast on systems with 0 or 1 state
		if not config.defaults['statesp.use_numpy_matrix']:
		if self.nstates == 0:
		return self.D[:, :, np.newaxis] \
		* np.ones_like(x_arr, dtype=complex)
		if self.nstates == 1:
		with np.errstate(divide='ignore', invalid='ignore'):
		out = self.C[:, :, np.newaxis] \
		/ (x_arr - self.A[0, 0]) \
		* self.B[:, :, np.newaxis] \
		+ self.D[:, :, np.newaxis]
		out[np.isnan(out)] = complex(np.inf, np.nan)
		return out

		try:
		out = self.slycot_laub(x)
		out = self.slycot_laub(x_arr)
		except (ImportError, Exception):
		# Fall back because either Slycot unavailable or cannot handle
		# certain cases.

		# Make sure the argument is a 1D array of complex numbers
		x_arr = np.atleast_1d(x).astype(complex, copy=False)

		# Make sure that we are operating on a simple list
		if len(x_arr.shape) > 1:
		raise ValueError("input list must be 1D")
Expand Down