Merge c268c7c into a4b4c43

control/bdalg.py

@@ -62,7 +62,7 @@
 
 
 def series(sys1, *sysn):
-    """Return the series connection (... \* sys3 \*) sys2 \* sys1
+    """Return the series connection (... \\* sys3 \\*) sys2 \\* sys1
 
     Parameters
     ----------

control/freqplot.py

@@ -110,7 +110,7 @@ def bode_plot(syslist, omega=None,
         config.defaults['freqplot.number_of_samples'].
     margins : bool
         If True, plot gain and phase margin.
-    \*args, \**kwargs:
+    \\*args, \\*\\*kwargs:
         Additional options to matplotlib (color, linestyle, etc)
 
     Returns
@@ -139,7 +139,7 @@ def bode_plot(syslist, omega=None,
 
     2. If a discrete time model is given, the frequency response is plotted
     along the upper branch of the unit circle, using the mapping z = exp(j
-    \omega dt) where omega ranges from 0 to pi/dt and dt is the discrete
+    \\omega dt) where omega ranges from 0 to pi/dt and dt is the discrete
     timebase.  If not timebase is specified (dt = True), dt is set to 1.
 
     Examples
@@ -450,7 +450,7 @@ def nyquist_plot(syslist, omega=None, Plot=True, color=None,
         Used to specify the color of the plot
     labelFreq : int
         Label every nth frequency on the plot
-    \*args, \**kwargs:
+    \\*args, \\*\\*kwargs:
         Additional options to matplotlib (color, linestyle, etc)
 
     Returns

control/grid.py

@@ -175,7 +175,7 @@ def zgrid(zetas=None, wns=None):
         an_x = xret[an_i]
         an_y = yret[an_i]
         num = '{:1.1f}'.format(a)
-        ax.annotate("$\\frac{"+num+"\pi}{T}$", xy=(an_x, an_y), xytext=(an_x, an_y), size=9)
+        ax.annotate(r"$\frac{"+num+r"\pi}{T}$", xy=(an_x, an_y), xytext=(an_x, an_y), size=9)
 
     _final_setup(ax)
     return ax, fig

control/iosys.py

@@ -1244,7 +1244,7 @@ def _parse_signal(self, spec, signame='input', dictname=None):
 
         if isinstance(spec, str):
             # If we got a dotted string, break up into pieces
-            namelist = re.split('\.', spec)
+            namelist = re.split(r'\.', spec)
 
             # For now, only allow signal level of system name
             # TODO: expand to allow nested signal names

control/matlab/wrappers.py

@@ -130,7 +130,7 @@ def dcgain(*args):
     -------
     gain: ndarray
         The gain of each output versus each input:
-        :math:`y = gain \cdot u`
+        :math:`y = gain \\cdot u`
 
     Notes
     -----
@@ -140,7 +140,7 @@ def dcgain(*args):
     All systems are first converted to state space form. The function then
     computes:
 
-    .. math:: gain = - C \cdot A^{-1} \cdot B + D
+    .. math:: gain = - C \\cdot A^{-1} \\cdot B + D
     '''
     #Convert the parameters to state space form
     if len(args) == 4:

control/statefbk.py

@@ -270,7 +270,7 @@ def lqr(*args, **keywords):
     The lqr() function computes the optimal state feedback controller
     that minimizes the quadratic cost
 
-    .. math:: J = \int_0^\infty (x' Q x + u' R u + 2 x' N u) dt
+    .. math:: J = \\int_0^\\infty (x' Q x + u' R u + 2 x' N u) dt
 
     The function can be called with either 3, 4, or 5 arguments:
 

control/tests/xferfcn_test.py

@@ -449,7 +449,7 @@ def test_evalfr_mimo(self):
         np.testing.assert_array_almost_equal(sys(2.j), resp)
 
     def test_freqresp_siso(self):
-        """Evaluate the magnitude and phase of a SISO system at 
+        """Evaluate the magnitude and phase of a SISO system at
         multiple frequencies."""
 
         sys = TransferFunction([1., 3., 5], [1., 6., 2., -1])
@@ -467,7 +467,7 @@ def test_freqresp_siso(self):
 
     @unittest.skipIf(not slycot_check(), "slycot not installed")
     def test_freqresp_mimo(self):
-        """Evaluate the magnitude and phase of a MIMO system at 
+        """Evaluate the magnitude and phase of a MIMO system at
         multiple frequencies."""
 
         num = [[[1., 2.], [0., 3.], [2., -1.]],
@@ -496,7 +496,7 @@ def test_freqresp_mimo(self):
         np.testing.assert_array_equal(omega, true_omega)
 
     # Tests for TransferFunction.pole and TransferFunction.zero.
-    
+
     @unittest.skipIf(not slycot_check(), "slycot not installed")
     def test_pole_mimo(self):
         """Test for correct MIMO poles."""
@@ -510,11 +510,11 @@ def test_pole_mimo(self):
 
     @unittest.skipIf(not slycot_check(), "slycot not installed")
     def test_double_cancelling_poles_siso(self):
-        
+
         H = TransferFunction([1, 1], [1, 2, 1])
         p = H.pole()
         np.testing.assert_array_almost_equal(p, [-1, -1])
-    
+
     # Tests for TransferFunction.feedback
     def test_feedback_siso(self):
         """Test for correct SISO transfer function feedback."""
@@ -756,6 +756,28 @@ def test_size_mismatch(self):
         self.assertRaises(NotImplementedError,
                           TransferFunction.feedback, sys2, sys1)
 
+    def test_latex_repr(self):
+        """ Test latex printout for TransferFunction """
+        Hc = TransferFunction([1e-5, 2e5, 3e-4],
+                              [1.2e34, 2.3e-4, 2.3e-45])
+        Hd = TransferFunction([1e-5, 2e5, 3e-4],
+                              [1.2e34, 2.3e-4, 2.3e-45],
+                              .1)
+        # TODO: make the multiplication sign configurable
+        expmul = r'\times'
+        for var, H, suffix in zip(['s', 'z'],
+                                  [Hc, Hd],
+                                  ['', r'\quad dt = 0.1']):
+            ref = (r'$$\frac{'
+                   r'1 ' + expmul + ' 10^{-5} ' + var + '^2 '
+                   r'+ 2 ' + expmul + ' 10^{5} ' + var + ' + 0.0003'
+                   r'}{'
+                   r'1.2 ' + expmul + ' 10^{34} ' + var + '^2 '
+                   r'+ 0.00023 ' + var + ' '
+                   r'+ 2.3 ' + expmul + ' 10^{-45}'
+                   r'}' + suffix + '$$')
+            self.assertEqual(H._repr_latex_(), ref)
+
 
 def suite():
     return unittest.TestLoader().loadTestsFromTestCase(TestXferFcn)

control/xferfcn.py

@@ -62,6 +62,7 @@
 from copy import deepcopy
 from warnings import warn
 from itertools import chain
+from re import sub
 from .lti import LTI, timebaseEqual, timebase, isdtime
 
 __all__ = ['TransferFunction', 'tf', 'ss2tf', 'tfdata']
@@ -302,6 +303,9 @@ def _repr_latex_(self, var=None):
                 numstr = _tf_polynomial_to_string(self.num[i][j], var=var)
                 denstr = _tf_polynomial_to_string(self.den[i][j], var=var)
 
+                numstr = _tf_string_to_latex(numstr, var=var)
+                denstr = _tf_string_to_latex(denstr, var=var)
+
                 out += [r"\frac{", numstr, "}{", denstr, "}"]
 
                 if mimo and j < self.outputs - 1:
@@ -315,7 +319,7 @@ def _repr_latex_(self, var=None):
 
         # See if this is a discrete time system with specific sampling time
         if not (self.dt is None) and type(self.dt) != bool and self.dt > 0:
-            out += ["\quad dt = ", str(self.dt)]
+            out += [r"\quad dt = ", str(self.dt)]
 
         out.append("$$")
 
@@ -1098,6 +1102,18 @@ def _tf_polynomial_to_string(coeffs, var='s'):
     return thestr
 
 
+def _tf_string_to_latex(thestr, var='s'):
+    """ make sure to superscript all digits in a polynomial string
+        and convert float coefficients in scientific notation
+        to prettier LaTeX representation """
+    # TODO: make the multiplication sign configurable
+    expmul = r' \\times'
+    thestr = sub(var + r'\^(\d{2,})', var + r'^{\1}', thestr)
+    thestr = sub(r'[eE]\+0*(\d+)', expmul + r' 10^{\1}', thestr)
+    thestr = sub(r'[eE]\-0*(\d+)', expmul + r' 10^{-\1}', thestr)
+    return thestr
+
+
 def _add_siso(num1, den1, num2, den2):
     """Return num/den = num1/den1 + num2/den2.