Added batching of spectra for TrueMatch when using AdvancedWITec

ramancom/WITecCOM.py

@@ -205,6 +205,7 @@ class WITecCOM(RamanBase):
         self.advSpec = AdvancedWITecSpectra()
         if 'Autofocus' not in [param.name for param in self.ramanParameters]:
             self.ramanParameters.append(RamanSettingParam('Autofocus', 'checkBox', default=False))
+            self.ramanParameters.append(RamanSettingParam('Spectra Batch Size', 'int', default=1000, minVal=1, maxVal=1e6))
     
     def getBrightness(self):
         assert self.connected
@@ -381,6 +382,7 @@ class WITecCOM(RamanBase):
     
     def initateSilentSpectrumAcquisition(self, ramanSettings):
         self.advSpec.setDatasetPath(ramanSettings['path'])
+        self.advSpec.setSpectraBatchSize(ramanSettings['Spectra Batch Size'])
         
         self.doAutoFocus = ramanSettings['Autofocus']
         

ramancom/advancedWITec.py

@@ -32,9 +32,13 @@ class AdvancedWITecSpectra(object):
         self.tmpspecpath = None
         self.curSpecIndex = None
         self.excitWavel = None
+        self.spectraBatchSize = None
     
     def setDatasetPath(self, path):
         self.dsetpath = path
+    
+    def setSpectraBatchSize(self, batchSize):
+        self.spectraBatchSize = batchSize
         
     def createTmpSpecFolder(self):
         assert self.dsetpath is not None
@@ -152,39 +156,52 @@ class AdvancedWITecSpectra(object):
         return allSpectra
     
     def createTrueMatchTxt(self, allSpectra, wavelength):
-        wavenumbers = allSpectra[:, 0]
-        spectra = allSpectra[:, 1:]
-        specSize = allSpectra.shape[0]
-        del allSpectra
-        outName = os.path.join(self.dsetpath, 'SpectraForTrueMatch.txt')
-        if os.path.exists(outName):
-            os.remove(outName)
-            
-        with open(outName, 'w') as fp:
+        def writeHeader(fp):
             fp.write('[WITEC_TRUEMATCH_ASCII_HEADER]\n\r')
             fp.write('Version = 2.0\n\r\n\r')
+        
+        def writeWavenumbers(fp, wavenumbers):
             fp.write('[XData]\n\r')
             for line in wavenumbers:
                 fp.write(str(line) + '\n\r')
-            
-            for specIndex in range(spectra.shape[1]):
-                fp.write('\n\r')
-                fp.write('[SpectrumHeader]\n\r')
-                fp.write(f'Title = Spectrum {specIndex} \n\r')
-                fp.write(f'ExcitationWavelength = {wavelength}\n\r')
-                fp.write(f'SpectrumSize = {specSize}\n\r')
-                fp.write('XDataKind = 1/cm\n\r\n\r')
-                fp.write('[SampleMetaData]\n\r')
-#                fp.write(f'double Integration_Time = )
-                fp.write(f'int Spectrum_Number = {specIndex}\n\r\n\r')
-                fp.write('[SpectrumData]\n\r')
                 
-                spec = spectra[:, specIndex]
-                for line in spec:
+        def writeSpectrum(fp, intensities):
+            fp.write('\n\r')
+            fp.write('[SpectrumHeader]\n\r')
+            fp.write(f'Title = Spectrum {specIndex} \n\r')
+            fp.write(f'ExcitationWavelength = {wavelength}\n\r')
+            fp.write(f'SpectrumSize = {specSize}\n\r')
+            fp.write('XDataKind = 1/cm\n\r\n\r')
+            fp.write('[SampleMetaData]\n\r')
+            fp.write(f'int Spectrum_Number = {specIndex}\n\r\n\r')
+            fp.write('[SpectrumData]\n\r')
+            for line in intensities:
                     fp.write(str(line) + '\n\r')
-    
-                
+            
+        wavenumbers = allSpectra[:, 0]
+        spectra = allSpectra[:, 1:]
+        specSize = allSpectra.shape[0]
+        del allSpectra
+        numSpectra = spectra.shape[1]
+        numBatches = np.ceil(numSpectra/self.spectraBatchSize)
+        
+        for batchIndex in range(numBatches):
+            outName = os.path.join(self.dsetpath, f'SpectraForTrueMatch {batchIndex}.txt')
+            if os.path.exists(outName):
+                os.remove(outName)
+            
+            if batchIndex < numBatches-1:
+                specIndicesInBatch = np.arange(batchIndex*self.spectraBatchSize, (batchIndex+1)*self.spectraBatchSize)
+            else:
+                specIndicesInBatch = np.arange(batchIndex*self.spectraBatchSize, numSpectra)
+            
+            with open(outName, 'w') as fp:
+                writeHeader(fp)
+                writeWavenumbers(fp, wavenumbers)
                 
+                for specIndex in specIndicesInBatch:
+                    spec = spectra[:, specIndex]
+                    writeSpectrum(fp, spec)
             
     def isNumber(self, string):
         isNumber = False