remove most uses of matplotlib.pyplot.tight_layout; use figure(layout…

…="constrained") instead

cla module still needs to be updated

pyyeti/cb.py

@@ -179,8 +179,8 @@ def cbtf(m, b, k, a, freq, bset, save=None):
 
         >>> a = T @ tf.a
         >>> d = T @ tf.d
-        >>> fig = plt.figure('Example')
-        >>> fig.clf()
+        >>> fig = plt.figure('Example', clear=True,
+        ...                  layout='constrained')
         >>> ax = plt.subplot(211)
         >>> lines = ax.plot(outfreq, np.abs(tf.frc).T, label='Force')
         >>> lines += ax.plot(outfreq, np.abs(a).T)
@@ -199,7 +199,6 @@ def cbtf(m, b, k, a, freq, bset, save=None):
         ...               loc='best')
         >>> _ = ax.set_title('Phase')
         >>> _ = ax.set_xlabel('Freq (Hz)')
-        >>> plt.tight_layout()
     """
     freq = np.atleast_1d(freq).ravel()
     Omega = 2 * math.pi * freq

pyyeti/dsp.py

@@ -143,7 +143,8 @@ def resample(data, p, q, *, axis=-1, beta=14, pts=10, t=None, getfir=False):
         >>> n = len(data)
         >>> x = np.arange(n)
         >>> upx = np.arange(n*p)/p
-        >>> _ = plt.figure('Example', figsize=(10, 8), clear=True)
+        >>> _ = plt.figure('Example', figsize=(10, 8), clear=True,
+        ...                layout='constrained')
         >>> _ = plt.subplot(211)
         >>> _ = plt.plot(x, data, 'o-', label='Original')
         >>> res = {}
@@ -172,7 +173,6 @@ def resample(data, p, q, *, axis=-1, beta=14, pts=10, t=None, getfir=False):
         >>> _ = plt.legend(loc='best')
         >>> _ = plt.title('FFT Mag.')
         >>> _ = plt.xlabel('Frequency - fraction of original sample rate')
-        >>> _ = plt.tight_layout()
         >>> np.allclose(up2, upx)
         True
         >>> np.allclose(res[5][::p], data)  # original data still here
@@ -190,7 +190,8 @@ def resample(data, p, q, *, axis=-1, beta=14, pts=10, t=None, getfir=False):
         >>> data = rng.normal(size=n)
         >>> x = np.arange(n)
         >>> dndata, dnx = dsp.resample(data, p, q, t=x)
-        >>> fig = plt.figure('Example 2', clear=True)
+        >>> fig = plt.figure('Example 2', clear=True,
+        ...                  layout='constrained')
         >>> _ = plt.subplot(211)
         >>> _ = plt.plot(x, data, 'o-', label='Original', alpha=0.3)
         >>> _ = plt.plot(dnx, dndata, label='Resample', lw=2)
@@ -214,7 +215,6 @@ def resample(data, p, q, *, axis=-1, beta=14, pts=10, t=None, getfir=False):
         >>> xlbl = 'Frequency - fraction of original sample rate'
         >>> _ = plt.xlabel(xlbl)
         >>> _ = plt.xlim(-0.01, 0.13)
-        >>> _ = plt.tight_layout()
     """
     data = np.atleast_1d(data)
     ln = data.shape[axis]
@@ -761,7 +761,8 @@ def despike(
         >>> import matplotlib.pyplot as plt
         >>> np.set_printoptions(linewidth=65)
         >>> x = [100, 2, 3, -4, 25, -6, 6, 3, -2, 4, -2, -100]
-        >>> _ = plt.figure('Example', figsize=(8, 11), clear=True)
+        >>> _ = plt.figure('Example', figsize=(8, 11), clear=True,
+        ...                layout='constrained')
         >>> for i in range(5):
         ...     s = dsp.despike(x, n=9, sigma=2, maxiter=1,
         ...                     threshold_sigma=0.1,
@@ -772,7 +773,6 @@ def despike(
         ...     _ = plt.plot(s.lolim, 'k--')
         ...     _ = plt.title(f'Iteration {i+1}')
         ...     x = s.x
-        >>> plt.tight_layout()
         >>> s.x
         array([ 2,  3,  6,  3, -2,  4, -2])
 
@@ -2085,7 +2085,8 @@ def windowends(sig, portion=0.01, ends="front", axis=-1):
         :context: close-figs
 
         >>> import matplotlib.pyplot as plt
-        >>> _ = plt.figure('Example', figsize=[8, 3], clear=True)
+        >>> _ = plt.figure('Example', figsize=[8, 3], clear=True,
+        ...                layout='constrained')
         >>> sig = np.ones(100)
         >>> wesig = dsp.windowends(sig, 5, ends='both')
         >>> _ = plt.plot(sig, label='Original')
@@ -2253,7 +2254,7 @@ def waterfall(
         ...                          slicefunc=dsp.windowends,
         ...                          sliceargs=[.02],
         ...                          slicekwargs=dict(ends='front'))
-        >>> _ = plt.figure('Example', clear=True)
+        >>> _ = plt.figure('Example', clear=True, layout='constrained')
         >>> cs = plt.contour(t, f, mp, 40, cmap=cm.plasma_r)
         >>> # This doesn't work in matplotlib 3.5.0:
         >>> #   cbar = plt.colorbar()
@@ -2264,7 +2265,7 @@ def waterfall(
         ...            vmin=cs.cvalues.min(), vmax=cs.cvalues.max()
         ...        )
         >>> sm = plt.cm.ScalarMappable(norm=norm, cmap=cs.cmap)
-        >>> cb = plt.colorbar(sm)  # , ticks=cs.levels)
+        >>> cb = plt.colorbar(sm, ax=plt.gca())  # , ticks=cs.levels)
         >>> #
         >>> _ = plt.xlabel('Time (s)')
         >>> _ = plt.ylabel('Frequency (Hz)')
@@ -2276,7 +2277,8 @@ def waterfall(
 
         Also show results on a 3D surface plot:
 
-        >>> fig = plt.figure("Example 2", clear=True)
+        >>> fig = plt.figure("Example 2", clear=True,
+        ...                  layout='constrained')
         >>> ax = fig.add_subplot(projection="3d")
         >>> x, y = np.meshgrid(t, f)
         >>> surf = ax.plot_surface(x, y, mp, rstride=1, cstride=1,
@@ -2510,7 +2512,8 @@ def calcenv(
         >>> from pyyeti import dsp
         >>> x = np.arange(1.0, 31.0, 1.0)
         >>> y = np.cos(x)
-        >>> fig = plt.figure('Example', figsize=[10, 8], clear=True)
+        >>> fig = plt.figure('Example', figsize=[10, 8], clear=True,
+        ...                  layout='constrained')
         >>>
         >>> ax = plt.subplot(411)
         >>> env = dsp.calcenv(x, y, base=None, makeplot='add')
@@ -2536,7 +2539,6 @@ def calcenv(
         >>> env = dsp.calcenv(x, y, method='min', makeplot='add')
         >>> _ = plt.title('method="min"')
         >>> ax.legend().set_visible(False)
-        >>> fig.subplots_adjust(right=0.7)
     """
     x, y = np.atleast_1d(x, y)
     if np.any(np.diff(x) <= 0):
@@ -2647,7 +2649,7 @@ def fdscale(y, sr, scale, axis=-1):
         ...                   [9., 1.0],
         ...                   [100., 1.0]])
         >>> sig_scaled = dsp.fdscale(sig, 1/t[1], scale)
-        >>> _ = plt.figure('Example', clear=True)
+        >>> _ = plt.figure('Example', clear=True, layout='constrained')
         >>> _ = plt.subplot(211)
         >>> _ = plt.plot(f, sig)
         >>> _ = plt.title('Sine Sweep vs Frequency')
@@ -2661,7 +2663,6 @@ def fdscale(y, sr, scale, axis=-1):
         >>> _ = plt.xlabel('Frequency (Hz)')
         >>> _ = plt.xlim([f[0], f[-1]])
         >>> _ = plt.grid(True)
-        >>> _ = plt.tight_layout()
     """
     y = np.atleast_1d(y)
     n = y.shape[axis]
@@ -2837,24 +2838,20 @@ def fftfilt(
 
         >>> sr = 1/h
         >>> nyq = sr/2
-        >>> _ = plt.figure('Example', clear=True)
-        >>> _ = plt.figure('Example 2', clear=True)
+        >>> _ = plt.figure('Ex1', clear=True, layout='constrained')
+        >>> _ = plt.figure('Ex2', clear=True, layout='constrained')
         >>> for j, (w, pz, yj) in enumerate(((7, None, y1),
         ...                                 ([7, 18], None, y2),
         ...                                 ([18, 45], None, y3),
         ...                                 (45, False, y4))):
-        ...     _ = plt.figure('Example')
+        ...     _ = plt.figure('Ex1')
         ...     _ = plt.subplot(4, 1, j+1)
         ...     yf = dsp.fftfilt(y, w, pass_zero=pz, nyq=nyq,
         ...                      makeplot='add')[0]
         ...     _ = plt.xlim(0, 75)
-        ...     _ = plt.figure('Example 2')
+        ...     _ = plt.figure('Ex2')
         ...     _ = plt.subplot(4, 1, j+1)
         ...     _ = plt.plot(t, yj, t, yf)
-        >>> _ = plt.figure('Example')
-        >>> _ = plt.tight_layout()
-        >>> _ = plt.figure('Example 2')
-        >>> _ = plt.tight_layout()
     """
     # main routine:
     sig, w = np.atleast_1d(sig, w)
@@ -3057,7 +3054,7 @@ def fftcoef(
         >>> x = rng.normal(size=n)
         >>> t = np.arange(n)
         >>> mag, phase, frq = dsp.fftcoef(x, 1.0)
-        >>> _ = plt.figure('Example', clear=True)
+        >>> _ = plt.figure('Example', clear=True, layout='constrained')
         >>> _ = plt.subplot(211)
         >>> _ = plt.plot(frq, mag)
         >>> _ = plt.ylabel('Magnitude')
@@ -3082,7 +3079,8 @@ def fftcoef(
         >>> for k, (a, b, f) in enumerate(zip(A, B, frq)):
         ...     x3 = x3 + a*np.cos(k*w*t2) + b*np.sin(k*w*t2)
         >>>
-        >>> _ = plt.figure('Example 2', clear=True)
+        >>> _ = plt.figure('Example 2', clear=True,
+        ...                layout='constrained')
         >>> _ = plt.plot(t, x, 'o', label='Original')
         >>> _ = plt.plot(t2, x2, label='FFT fit w/ Mag & Phase')
         >>> _ = plt.plot(t2, x3, '--', label='FFT fit w/ A & B')
@@ -3245,7 +3243,7 @@ def fftmap(
         ...            vmin=cs.cvalues.min(), vmax=cs.cvalues.max()
         ...        )
         >>> sm = plt.cm.ScalarMappable(norm=norm, cmap=cs.cmap)
-        >>> cb = plt.colorbar(sm)  # , ticks=cs.levels)
+        >>> cb = plt.colorbar(sm, ax=plt.gca())  # , ticks=cs.levels)
         >>> #
         >>> _ = plt.xlabel('Time (s)')
         >>> _ = plt.ylabel('Frequency (Hz)')
@@ -3443,7 +3441,8 @@ def transmissibility(
         >>> tr = dsp.transmissibility(
         ...           in_acce, out_acce, sr, getmap=True)
         >>>
-        >>> fig = plt.figure('Example', figsize=(8, 11), clear=True)
+        >>> fig = plt.figure('Example', figsize=(8, 11), clear=True,
+        ...                  layout='tight')
         >>>
         >>> # use GridSpec to make a nice layout with colorbars:
         >>> gs = gridspec.GridSpec(5, 2, width_ratios=[30, 1])
@@ -3527,8 +3526,6 @@ def transmissibility(
         >>> cb = plt.colorbar(sm, cax=ax)  # , ticks=c.levels)
         >>>
         >>> _ = ax.set_title("TR Phase (deg)")
-        >>>
-        >>> fig.tight_layout()
 
     As an aside and for fun, compare the actual root-mean-square
     response to the Miles' equation estimate. Miles' should be a

pyyeti/era.py

@@ -1116,7 +1116,9 @@ def _plot_era(self):
 
         # plot each input in its own window
         for j in range(self.n_inputs):
-            fig = plt.figure(f"{self.figure_label}, input {j}", clear=True)
+            fig = plt.figure(
+                f"{self.figure_label}, input {j}", clear=True, layout="constrained"
+            )
 
             if self.FFT:
                 ax1 = fig.add_subplot(211)
@@ -1192,7 +1194,6 @@ def _plot_era(self):
                 ax2.set_ylabel("Magnitude")
                 ax2.set_title("Magnitude of Frequency Responses of Data")
 
-            fig.tight_layout()
             fig.canvas.draw()
         plt.show()
 
@@ -1580,7 +1581,8 @@ def NExT(
         >>> t_irf = t[1 : lag_stop + 1]
         >>> irf = era.NExT(sol.a, sr, lag_stop=lag_stop)
         >>>
-        >>> fig = plt.figure("corr comp", clear=True, figsize=(6.4, 6.4))
+        >>> fig = plt.figure("corr comp", clear=True, figsize=(6.4, 6.4),
+        ...                  layout='constrained')
         >>> ax = fig.subplots(4, 1)
         >>>
         >>> _ = ax[0].plot(t, sol.a.T)
@@ -1595,7 +1597,6 @@ def NExT(
         ...     _ = ax[ref + 1].set_title(f"IRFs with reference channel {ref}")
         ...     _ = ax[ref + 1].set_ylabel("X-corr IRFs")
         >>> _ = ax[3].set_xlabel("Time (s)")
-        >>> fig.tight_layout()
 
     .. plot::
         :context: close-figs

pyyeti/fdepsd.py

@@ -470,8 +470,8 @@ def fftroll(sig, sr, ppc, frq):
         ...     spec, ppc=10, fstart=20, fstop=50, df=1 / TF,
         ...     winends=dict(portion=10), gettime=True)
         >>>
-        >>> fig = plt.figure('Example', figsize=[9, 6])
-        >>> fig.clf()
+        >>> fig = plt.figure('Example', figsize=[9, 6], clear=True,
+        ...                  layout='constrained')
         >>> _ = plt.subplot(211)
         >>> _ = plt.plot(t, sig)
         >>> _ = plt.title(r'Input Signal - Specification Level = '
@@ -507,16 +507,14 @@ def fftroll(sig, sr, ppc, frq):
         >>> _ = plt.legend(loc='upper left',
         ...                bbox_to_anchor=(1.02, 1.),
         ...                borderaxespad=0.)
-        >>> plt.tight_layout()
-        >>> fig.subplots_adjust(right=0.78)
 
     .. plot::
         :context: close-figs
 
         Compare to theoretical bin counts @ 30 Hz:
 
-        >>> _ = plt.figure('Example 2')
-        >>> plt.clf()
+        >>> _ = plt.figure('Example 2', clear=True,
+        ...                layout='constrained')
         >>> Frq = freq[np.searchsorted(freq, 30)]
         >>> _ = plt.semilogy(fde.binamps.loc[Frq]**2,
         ...                  fde.count.loc[Frq],

pyyeti/frclim.py

@@ -119,7 +119,8 @@ def calcAM(S, freq):
         >>> zeta_ff = C_ff[1, 1] / 2 / omega_ff[1]
         >>>
         >>> freq = np.geomspace(0.5, 100.0, 500)
-        >>> fig = plt.figure("apparent mass", clear=True)
+        >>> fig = plt.figure("apparent mass", clear=True,
+        ...                  layout='constrained')
         >>> ax = fig.subplots(1, 1)
         >>>
         >>> fx_frqs = []
@@ -180,8 +181,6 @@ def calcAM(S, freq):
         ...         "\n (free-free)"
         ...     )
         >>> _ = ax.text(frq_ff[1], 2.0, label, va="bottom", ha="left")
-        >>>
-        >>> fig.tight_layout()
     """
 
     lf = len(freq)
@@ -688,8 +687,7 @@ def ntfl(Source, Load, As, freq):
         5. Plot comparisons:
 
         >>> import matplotlib.pyplot as plt
-        >>> _ = plt.figure('Example')
-        >>> plt.clf()
+        >>> _ = plt.figure('Example', clear=True, layout='constrained')
         >>> _ = plt.subplot(211)
         >>> _ = plt.semilogy(freq, abs(A_coupled),
         ...                  label='Coupled')
@@ -706,15 +704,14 @@ def ntfl(Source, Load, As, freq):
         >>> _ = plt.title('Interface Force')
         >>> _ = plt.xlabel('Frequency (Hz)')
         >>> _ = plt.legend(loc='best')
-        >>> plt.tight_layout()
 
     .. plot::
         :context: close-figs
 
         6. Plot apparent masses:
 
-        >>> _ = plt.figure('Example 2')
-        >>> plt.clf()
+        >>> _ = plt.figure('Example 2', clear=True,
+        ...                layout='constrained')
         >>> _ = plt.semilogy(freq, abs(r.TAM[0, :, 0]),
         ...                  label='Total App. Mass')
         >>> _ = plt.semilogy(freq, abs(r.SAM[0, :, 0]),
@@ -731,8 +728,8 @@ def ntfl(Source, Load, As, freq):
         7. Plot accelerations and
         8. Plot force limit factor:
 
-        >>> _ = plt.figure('Example 3')
-        >>> plt.clf()
+        >>> _ = plt.figure('Example 3', clear=True,
+        ...                layout='constrained')
         >>> _ = plt.subplot(211)
         >>> _ = plt.semilogy(freq, abs(As).T,
         ...                  label='Free-Acce')
@@ -746,7 +743,6 @@ def ntfl(Source, Load, As, freq):
         >>> _ = plt.title('NT Response Ratio: '
         ...               'R = Coupled Acce / Free-Acce')
         >>> _ = plt.xlabel('Frequency (Hz)')
-        >>> plt.tight_layout()
     """
     # Calculate apparent masses:
     if isinstance(Source, (list, tuple)):

pyyeti/nastran/bulk.py

@@ -3921,7 +3921,6 @@ def _plot_rspline(
 
     ytools.axis_equal_3d(ax)
     ax.legend(loc="upper left", bbox_to_anchor=(1.0, 1.0))
-    ax.get_figure().tight_layout()
 
 
 def wtrspline_rings(

pyyeti/ode/_utilities.py

@@ -116,7 +116,7 @@ def get_su_coef(m, b, k, h, rbmodes=None, rfmodes=None):
     else:
         wo2 = k / m
         C = (b / m) / 2
-    w2 = wo2 - C ** 2
+    w2 = wo2 - C**2
 
     if rbmodes is None:
         pvrb = (wo2 < 0.005).astype(int)
@@ -1064,8 +1064,8 @@ def solvepsd(fs, forcepsd, t_frc, freq, drmlist, rbduf=1.0, elduf=1.0, **kwargs)
         Plot the four accelerations PSDs:
 
         >>> import matplotlib.pyplot as plt
-        >>> fig = plt.figure('Example', figsize=[8, 8])
-        >>> fig.clf()
+        >>> fig = plt.figure('Example', figsize=[8, 8], clear=True,
+        ...                  layout='constrained')
         >>> labels = ['Rigid-body', 'Underdamped',
         ...           'Critically Damped', 'Overdamped']
         >>> for j, name in zip(range(4), labels):
@@ -1074,7 +1074,6 @@ def solvepsd(fs, forcepsd, t_frc, freq, drmlist, rbduf=1.0, elduf=1.0, **kwargs)
         ...     _ = plt.title(name)
         ...     _ = plt.ylabel(r'Accel PSD ($g^2$/Hz)')
         ...     _ = plt.xlabel('Frequency (Hz)')
-        >>> fig.tight_layout()
     """
     ndrms = len(drmlist)
     forcepsd, t_frc = np.atleast_2d(forcepsd, t_frc)