fixed Fourier, plotting styles

pyboat/__init__.py

@@ -3,7 +3,7 @@
 import sys,os
 import argparse
 
-__version__ = '0.8.1.3'
+__version__ = '0.8.1.5'
 
 # the object oriented API
 from .api import WAnalyzer

pyboat/core.py

@@ -440,7 +440,7 @@ def smooth(x, window_len=11, window="flat", data=None):
     if window_len < 3:
         raise ValueError("window must not be shorter than 3")
 
-    if window_len % 2 is 0:
+    if window_len % 2 == 0:
         raise ValueError("window_len should be odd")
 
     if not window in ["flat", "extern"]:
@@ -596,7 +596,7 @@ def normalize_with_envelope(dsignal, window_size, dt):
     ----------
 
     dsignal : ndarray, the (detrended) signal
-    window_size : int, the window size in time units
+    window_size : int, the window size in sampling time units
     dt : float, the sampling interval 
     """
 

pyboat/plotting.py

@@ -14,29 +14,33 @@ TREND_COLOR = rgb_2mpl(165, 105, 189)  # orchidy
 ENVELOPE_COLOR = 'orange'
 
 DETREND_COLOR = 'black'
-FOURIER_COLOR = 'slategray'
+FOURIER_COLOR = 'cadetblue'
 RIDGE_COLOR = "crimson"
 
 COI_COLOR = '0.6' # light gray
 
 # average power histogram
-HIST_COLOR = 'lightslategray'
+HIST_COLOR = 'cadetblue'
 
 # the readouts
 PERIOD_COLOR = 'cornflowerblue'
 PHASE_COLOR = 'crimson'
 AMPLITUDE_COLOR = 'k'
-POWER_COLOR = 'gray'
-POWERKDE_COLOR = rgba_2mpl(10,10,10,180)
+POWER_COLOR = 'cadetblue'
+POWERKDE_COLOR = rgba_2mpl(10,10,10,160)
 
 # the colormap for the wavelet spectra
 CMAP = "YlGnBu_r"
 # CMAP = 'cividis'
 # CMAP = 'magma'
 
+# --- max size of signal to plot also the sample points
+Nmax = 250
+
 # --- define line widths ---
 TREND_LW = 1.5
 SIGNAL_LW = 1.5
+MARKER_SIZE = 4
 
 # --- standard sizes ---
 label_size = 18
@@ -47,6 +51,19 @@ tick_label_size = 16
 # match dimensions of spectrum and signal plots
 x_size = 6.5
 
+
+# signal plot style, markers only for short signals
+def get_marker_lw(signal):
+
+    if len(signal) <= Nmax:
+        m = 'o'
+        lw = 1.2
+    else:
+        m = ''
+        lw = SIGNAL_LW        
+    return m, lw
+
+
 # --- Signal and Trend -----------------------------------------------
 
 
@@ -69,14 +86,17 @@ def mk_signal_ax(time_unit="a.u.", fig=None):
     return ax
 
 
-def draw_signal(ax, time_vector, signal):
-        
-    ax.plot(time_vector, signal, lw=SIGNAL_LW,
-            color=SIG_COLOR, alpha=0.8, label="signal")
+def draw_signal(ax, time_vector, signal, label = "signal"):
+
+    m, lw = get_marker_lw(signal)
+    
+    ax.plot(time_vector, signal, lw=lw, marker = m, ms = MARKER_SIZE,
+            color=SIG_COLOR, alpha=0.8, label=label)
 
 
-def draw_trend(ax, time_vector, trend):
-    ax.plot(time_vector, trend, color=TREND_COLOR, alpha=0.8, lw=TREND_LW, label="trend")
+def draw_trend(ax, time_vector, trend, label = 'trend'):
+    ax.plot(time_vector, trend, color=TREND_COLOR,
+            alpha=0.8, lw=TREND_LW, label=label)
 
 def draw_envelope(ax, time_vector, envelope):
     ax.plot(time_vector, envelope, color=ENVELOPE_COLOR,
@@ -85,9 +105,11 @@ def draw_envelope(ax, time_vector, envelope):
 
 def draw_detrended(ax, time_vector, detrended):
 
+    m, lw = get_marker_lw(detrended)
+    
     ax2 = ax.twinx()
-    ax2.plot(time_vector, detrended, "-",
-             color=DETREND_COLOR, lw=1.5, alpha=0.6, label = 'detrended')
+    ax2.plot(time_vector, detrended, "-", marker = m, ms = MARKER_SIZE,
+             color=DETREND_COLOR, lw=lw, alpha=0.6, label = 'detrended')
 
     ax2.set_ylabel("detrended", fontsize=label_size)
     ax2.ticklabel_format(style="sci", axis="y", scilimits=(0, 0))
@@ -223,7 +245,11 @@ def plot_signal_modulus(axs, time_vector, signal, modulus, periods, p_max=None):
 
     # Plot Signal above spectrum
 
-    sig_ax.plot(time_vector, signal, color="black", lw=1.5, alpha=0.7)
+    m, lw = get_marker_lw(signal)
+    
+    sig_ax.plot(time_vector, signal, color="black",
+                lw=lw, alpha=0.65, marker = m, ms = MARKER_SIZE)
+    
     # sig_ax.plot(time_vector, signal, ".", color="black", ms=2.0, alpha=0.5)
     sig_ax.ticklabel_format(style="sci", axis="y", scilimits=(0, 0))
     sig_ax.tick_params(axis="both", labelsize=tick_label_size)
@@ -380,12 +406,13 @@ def plot_readout(ridge_data, time_unit="a.u.", draw_coi = False, fig=None):
     ax3.tick_params(axis="both", labelsize=tick_label_size)
 
     # powers
-    ax4.plot(ridge_t.loc[i_left:i_right], powers.loc[i_left:i_right], "k-", lw=2.5, alpha=0.5,
+    ax4.plot(ridge_t.loc[i_left:i_right], powers.loc[i_left:i_right],
+             lw=2.5, alpha=0.8, color = POWER_COLOR,
              ls = lstyle, marker = mstyle, ms = 1.5)
 
     # inside COI
-    ax4.plot(ridge_t.loc[:i_left], powers.loc[:i_left], '--',color='gray', alpha=0.6, ms = 2.5)
-    ax4.plot(ridge_t.loc[i_right:], powers.loc[i_right:], '--', color='gray', alpha=0.6, ms = 2.5)
+    ax4.plot(ridge_t.loc[:i_left], powers.loc[:i_left], '--',color=POWER_COLOR, alpha=0.6, ms = 2.5)
+    ax4.plot(ridge_t.loc[i_right:], powers.loc[i_right:], '--', color=POWER_COLOR, alpha=0.6, ms = 2.5)
     
     ax4.set_ylim((0, 1.1 * powers.max()))
     ax4.set_ylabel("Power (wnp)", fontsize=label_size)
@@ -478,7 +505,6 @@ def plot_power_distribution(powers, kde = True, fig = None):
             dens(support),
             color = POWERKDE_COLOR,
             lw = 2.,
-            alpha = 0.8,
             label = 'KDE'
         )
 

pyboat/ui/analysis.py

@@ -64,7 +64,8 @@ class FourierAnalyzer(QWidget):
         # plot it
         ax = pl.mk_Fourier_ax(self.fCanvas.fig, self.time_unit, self.show_T)
         pl.Fourier_spec(ax, self.fft_freqs, self.fpower, self.show_T)
-
+        self.fCanvas.fig.subplots_adjust(left = 0.15)
+        # self.fCanvas.fig.tight_layout()
         
         main_layout = QGridLayout()
         main_layout.addWidget(self.fCanvas,0,0,9,1)

pyboat/ui/data_viewer.py

@@ -960,7 +960,7 @@ class DataViewer(QWidget):
 
         if self.cb_use_envelope2.isChecked():
             L = self.get_L(self.L_edit)
-            signal = pyboat.normalize_with_envelope(signal, self.L, self.dt)
+            signal = pyboat.normalize_with_envelope(signal, L, self.dt)
 
         # periods or frequencies?
         if self.cb_FourierT.isChecked():

pyboat/ui/synth_gen.py

@@ -608,7 +608,7 @@ class SynthSignalGen(QWidget):
                 print("L ValueError", text)
             pass
 
-        # transform to sampling intervals
+        # still in sampling interval units
         self.L = int(L)
 
         if self.debug:
@@ -1076,7 +1076,7 @@ class SynthSignalGen(QWidget):
             return
 
         elif self.cb_use_envelope2.isChecked():
-            signal = pyboat.normalize_with_envelope(signal, self.L)
+            signal = pyboat.normalize_with_envelope(signal, self.L, self.dt)
 
         # periods or frequencies?
         if self.cb_FourierT.isChecked():

scripting_template.py

@@ -19,7 +19,7 @@ time_unit = 's'
 
 eps = 0.5 # noise intensity
 alpha = 0.4 # AR1 parameter
-Nt = 500 # number of samples
+Nt = 400 # number of samples
 
 signal1 = ssg.create_noisy_chirp(T1 = 30 / dt, T2 = 50 / dt, Nt = Nt, eps = eps, alpha = alpha)
 
@@ -37,7 +37,7 @@ detr_signal = signal - trend
 # plot the signal/trend
 tvec = np.arange(len(signal)) * dt
 ax = pl.mk_signal_ax(time_unit = 's')
-pl.draw_signal(ax, tvec, signal)
+pl.draw_signal(ax, tvec, signal, label = '2 chirps')
 # pl.draw_detrended(ax, tvec, signal)
 pl.draw_trend(ax, tvec, trend)
 ppl.legend(ncol = 2)
@@ -49,7 +49,7 @@ modulus, wlet = pyboat.compute_spectrum(signal, dt, periods)
 # plot spectrum and ridge
 ax_sig, ax_spec = pl.mk_signal_modulus_ax(time_unit)
 pl.plot_signal_modulus((ax_sig, ax_spec), tvec, signal, modulus, periods)
-
+ppl.tight_layout()
 
 # --- compute spectrum on the detrended signal ---
 modulus, wlet = pyboat.compute_spectrum(detr_signal, dt, periods)
@@ -57,16 +57,19 @@ modulus, wlet = pyboat.compute_spectrum(detr_signal, dt, periods)
 # get maximum ridge
 ridge_ys = pyboat.get_maxRidge_ys(modulus)
 
-# evaluate along the ridge
+# evaluate along the ridge, ridge_results is a pandas DataFrame
 ridge_results = pyboat.eval_ridge(ridge_ys, wlet, signal, periods, tvec)
 
 
 # plot spectrum and ridge
 ax_sig2, ax_spec2 = pl.mk_signal_modulus_ax(time_unit)
 
-pl.plot_signal_modulus((ax_sig2, ax_spec2), tvec, signal, modulus, periods)
+pl.plot_signal_modulus((ax_sig2, ax_spec2), tvec, detr_signal, modulus, periods)
 pl.draw_Wavelet_ridge(ax_spec2, ridge_results)
 ppl.tight_layout()
+ppl.savefig('detr_signal_spec.png')
+
 
 # plot readout
 pl.plot_readout(ridge_results)
+ppl.savefig('detr_signal_readout.png')

scripting_templateOOP.py

@@ -16,7 +16,7 @@ time_unit = 's'
 
 eps = 0.5 # noise intensity
 alpha = 0.4 # AR1 parameter
-Nt = 500 # number of samples
+Nt = 400 # number of samples
 
 signal1 = ssg.create_noisy_chirp(T1 = 30 / dt, T2 = 50 / dt, Nt = Nt, eps = eps, alpha = alpha)
 
@@ -43,6 +43,10 @@ wAn.compute_spectrum(signal)
 
 wAn.get_maxRidge(power_thresh = 5)
 wAn.draw_Ridge()
+ppl.savefig('detr_signal_spec.png')
+
 wAn.plot_readout(draw_coi = True)
-rd = wAn.ridge_data
+ppl.savefig('detr_signal_readout.png')
+
+rd = wAn.ridge_data # this is a pandas DataFrame holding the ridge results