Merge pull request #22 from tensionhead/21-batch-processing-of-indivi…

…dual-fourier-distributions 21 batch processing of individual fourier distributions
tensionhead · Jun 5, 2023 · 2df4a8e · 2df4a8e
2 parents 0cf7997 + d8defd5
commit 2df4a8e
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Showing 3 changed files with 27 additions and 10 deletions.
diff --git a/pyboat/__init__.py b/pyboat/__init__.py
@@ -4,7 +4,7 @@
 import os
 import argparse
 
-__version__ = "0.9.11"
+__version__ = "0.9.12"
 
 # the object oriented API
 from .api import WAnalyzer

diff --git a/pyboat/plotting.py b/pyboat/plotting.py
@@ -333,8 +333,8 @@ def plot_signal_modulus(axs, time_vector, signal, modulus, periods, p_max=None):
     )
     cb.set_ticks(cb_ticks)
     cb.ax.set_xticklabels(cb_ticks, fontsize=tick_label_size)
-    # cb.set_label('$|\mathcal{W}_{\Psi}(t,T)|^2$',rotation = '0',labelpad = 5,fontsize = 15)
-    cb.set_label("Wavelet Power", rotation="0", labelpad=-12, fontsize=0.9 * label_size)
+    # cb.set_label('$|\mathcal{W}_{\Psi}(t,T)|^2$', rotation = "horizontal",labelpad = 5,fontsize = 15)
+    cb.set_label("Wavelet Power", rotation="horizontal", labelpad=-12, fontsize=0.9 * label_size)
 
 
 def plot_modulus(mod_ax, time_vector, modulus, periods, p_max=None):
@@ -364,8 +364,8 @@ def plot_modulus(mod_ax, time_vector, modulus, periods, p_max=None):
     )
     cb.set_ticks(cb_ticks)
     cb.ax.set_xticklabels(cb_ticks, fontsize=tick_label_size)
-    # cb.set_label('$|\mathcal{W}_{\Psi}(t,T)|^2$',rotation = '0',labelpad = 5,fontsize = 15)
-    cb.set_label("Wavelet Power", rotation="0", labelpad=-12, fontsize=0.9 * label_size)
+    # cb.set_label('$|\mathcal{W}_{\Psi}(t,T)|^2$',rotation = 'horizontal',labelpad = 5,fontsize = 15)
+    cb.set_label("Wavelet Power", rotation="horizontal", labelpad=-12, fontsize=0.9 * label_size)
 
 
 def draw_Wavelet_ridge(ax, ridge_data, marker_size=1.5):

diff --git a/pyboat/ui/batch_process.py b/pyboat/ui/batch_process.py
@@ -85,9 +85,9 @@ def initUI(self, wlet_pars):
         self.cb_plot_global_spec = QCheckBox("Global Wavelet Spectrum")
         self.cb_plot_global_spec.setStatusTip("Ensemble averaged Wavelet spectrum")
 
-        self.cb_plot_Fourier_dis = QCheckBox("Global Fourier Estimate")
+        self.cb_plot_Fourier_dis = QCheckBox("Ensemble Fourier Estimate")
         self.cb_plot_Fourier_dis.setStatusTip(
-            "Ensemble median and quartiles of the time averaged Wavelet spectra"
+            "Plots median and quartiles of the ensemble Fourier power spectral distribution"
         )
 
         self.cb_power_hist = QCheckBox("Ridge Power Histogram")
@@ -169,7 +169,7 @@ def initUI(self, wlet_pars):
 
         self.cb_readout = QCheckBox("Ridge Readouts")
         self.cb_readout.setStatusTip(
-            "Saves one analysis result per signal to disc as csv"
+            "Saves one ridge analysis result per signal to disc as csv"
         )
 
         self.cb_readout_plots = QCheckBox("Ridge Readout Plots")
@@ -183,6 +183,11 @@ def initUI(self, wlet_pars):
             "Saves period, amplitude, power and phase summary statistics to csv files"
         )
 
+        self.cb_Fourier_est = QCheckBox("Fourier Estimates")
+        self.cb_Fourier_est.setStatusTip(
+            "Saves individual Fourier power spectral estimates"
+        )
+
         self.cb_save_Fourier_dis = QCheckBox("Global Fourier Estimate")
         self.cb_save_Fourier_dis.setStatusTip(
             "Saves median and quartiles of the ensemble Fourier power spectral distribution"
@@ -199,8 +204,9 @@ def initUI(self, wlet_pars):
         lo.addWidget(self.cb_filtered_sigs, 0, 0)
         lo.addWidget(self.cb_readout, 1, 0)
         lo.addWidget(self.cb_sorted_powers, 2, 0)
-        lo.addWidget(self.cb_save_ensemble_dynamics, 3, 0)
+        lo.addWidget(self.cb_Fourier_est, 3, 0)
         lo.addWidget(self.cb_save_Fourier_dis, 4, 0)
+        lo.addWidget(self.cb_save_ensemble_dynamics, 5, 0)
 
         export_data.setLayout(lo)
 
@@ -377,6 +383,16 @@ def run_batch(self):
 
         # --- Fourier Distribution Outputs ---
 
+        if self.cb_Fourier_est.isChecked():
+
+            fname = os.path.join(OutPath, f"{dataset_name}_fourier-estimates.csv")
+            if self.debug:
+                print(f"Saving fourier estimate to {fname}")
+
+            df_fouriers.to_csv(
+                fname, sep=",", float_format=float_format, index=True
+            )
+
         if self.cb_plot_Fourier_dis.isChecked():
 
             self.fdw = FourierDistributionWindow(
@@ -537,6 +553,7 @@ def do_the_loop(self, norm_vec):
         # ensemble averaged wavelet spectrum
         global_modulus = np.zeros((len(periods), len(norm_vec)))
 
+        # TODO: parallelize
         for i, signal_id in enumerate(self.parentDV.df):
 
             # log to terminal
@@ -816,7 +833,7 @@ def __init__(self, modulus, time_unit, dataset_name="", parent=None):
 
     def initUI(self, dataset_name):
 
-        self.setWindowTitle(f"Global Wavelet Spectrum - {dataset_name}")
+        self.setWindowTitle(f"Ensemble Wavelet Spectrum - {dataset_name}")
         self.setGeometry(410, 360, 700, 500)
 
         Canvas = mkGenericCanvas()