def createDictionary(self):
fileName = QtGui.QFileDialog.getSaveFileName(self , 'Save dictionary to a file' , expanduser('~')+'/dictionary' , 'Matlab file (*.mat);;Python pickle (*.p);;Comma sep. values (*.csv);;Excel file (*.xlsx)')
if len(fileName) == 0:
return
self.displayInformation('Saving dictionary...' , flag='new')
fileName = str(fileName)
self.setDictionaryConfig()
self.setAlgorithmConfig()
config = generateFinalConfig(self.dictionaryConfig , self.dataMatrixes[self.filePath][1] , self.dataMatrixes[self.filePath][2])
time = np.arange(0,self.dataMatrixes[self.filePath][1]['numberOfSamples'])
dictionary = generateDictionary(time , config)
if fileName[-4:] == '.mat':
dic = {col_name : dictionary[col_name].values for col_name in dictionary.columns.values}
savemat(fileName , dic)
elif fileName[-2:] == '.p':
dictionary.to_pickle(fileName)
elif fileName[-4:] == '.csv':
dictionary.to_csv(fileName)
elif fileName[-5:] == '.xlsx':
dictionary.to_excel(fileName, sheet_name='dictionary')
self.displayInformation('Dictionary saved.' , flag='new')
def initializeVariables(self , dataMatrixes , dictionaryConfig): self.input = dataMatrixes self.output = [] self.files2run = self.input.keys() self.numberOfFiles = len(self.input) maximumLength = 0 for f in self.files2run: if self.input[f][1]['numberOfSamples'] > maximumLength: maximumLength = self.input[f][1]['numberOfSamples'] self.timeVector = np.arange(0,maximumLength) self.dictionaryConfig = dictionaryConfig self.dictionary = generateDictionary(self.timeVector , retranslateDictionaryConfig(self.dictionaryConfig))
def initializeVariables(self, dataMatrixes, dictionaryConfig):
self.input = dataMatrixes
self.output = []
self.files2run = self.input.keys()
self.numberOfFiles = len(self.input)
maximumLength = 0
for f in self.files2run:
if self.input[f][1]['numberOfSamples'] > maximumLength:
maximumLength = self.input[f][1]['numberOfSamples']
self.timeVector = np.arange(0, maximumLength)
self.dictionaryConfig = dictionaryConfig
self.dictionary = generateDictionary(
self.timeVector,
retranslateDictionaryConfig(self.dictionaryConfig))
config['flags'] = flags config['algorithm'] = 'smp' config['minS'] = 32 config['maxS'] = numberOfSamples config['density'] = 0.01 config['maxNumberOfIterations'] = 4 config['minEnergyExplained'] = 0.99 config['samplingFrequency'] = samplingFrequency config['minNFFT'] = 256 # 2*samplingFrequency # optional config for t-f map drawing # config['mapFreqRange'] = [0.0 , samplingFrequency/2] # config['mapStructFreqs'] = [0.0 , samplingFrequency/2] # config['mapStructSigmas'] = [0.0 , 4.0] dictionary = generateDictionary(time , config) book = calculateMP(dictionary , signal , config) # print book # plot resulting functions plt.figure() plt.subplot(4,1,1) plt.plot(time,signal,'k') plt.plot(time,sum(book['reconstruction']).real , 'r') plt.subplot(4,1,2) plt.plot(time,book['reconstruction'][0].real , 'r') plt.subplot(4,1,3) plt.plot(time,book['reconstruction'][1].real , 'r')
flags['useRectA'] = 0
flags['useGradientOptimization'] = 1
flags['displayInfo'] = 0
config = {}
config['flags'] = flags
config['algorithm'] = 'smp'
config['minS'] = 32
config['maxS'] = numberOfSamples
config['density'] = 0.01
config['maxNumberOfIterations'] = 4
config['minEnergyExplained'] = 0.99
config['samplingFrequency'] = samplingFrequency
config['minNFFT'] = 2 * samplingFrequency
dictionary = generateDictionary(time, config)
book = calculateMP(dictionary, signal, config)
flags = {}
flags['useAsymA'] = 1
flags['useRectA'] = 0
flags['useGradientOptimization'] = 1
flags['displayInfo'] = 0
config['flags'] = flags
advancedDictionary = generateDictionary(time, config)
advancedBook = calculateMP(advancedDictionary, advancedSignal, config)
flags = {}
flags['useAsymA'] = 1
flags['useRectA'] = 1
config['flags'] = flags
config['algorithm'] = 'smp'
config['minS'] = 32
config['maxS'] = numberOfSamples
config['density'] = 0.01
config['maxNumberOfIterations'] = 4
config['minEnergyExplained'] = 0.99
config['samplingFrequency'] = samplingFrequency
config['minNFFT'] = 256 # 2*samplingFrequency
# optional config for t-f map drawing
# config['mapFreqRange'] = [0.0 , samplingFrequency/2]
# config['mapStructFreqs'] = [0.0 , samplingFrequency/2]
# config['mapStructSigmas'] = [0.0 , 4.0]
dictionary = generateDictionary(time, config)
book = calculateMP(dictionary, signal, config)
# print book
# plot resulting functions
plt.figure()
plt.subplot(4, 1, 1)
plt.plot(time, signal, 'k')
plt.plot(time, sum(book['reconstruction']).real, 'r')
plt.subplot(4, 1, 2)
plt.plot(time, book['reconstruction'][0].real, 'r')
plt.subplot(4, 1, 3)
plt.plot(time, book['reconstruction'][1].real, 'r')
flags["useRectA"] = 0
flags["useGradientOptimization"] = 1
flags["displayInfo"] = 0
config = {}
config["flags"] = flags
config["algorithm"] = "smp"
config["minS"] = 32
config["maxS"] = numberOfSamples
config["density"] = 0.01
config["maxNumberOfIterations"] = 4
config["minEnergyExplained"] = 0.99
config["samplingFrequency"] = samplingFrequency
config["minNFFT"] = 2 * samplingFrequency
dictionary = generateDictionary(time, config)
book = calculateMP(dictionary, signal, config)
flags = {}
flags["useAsymA"] = 1
flags["useRectA"] = 0
flags["useGradientOptimization"] = 1
flags["displayInfo"] = 0
config["flags"] = flags
advancedDictionary = generateDictionary(time, config)
advancedBook = calculateMP(advancedDictionary, advancedSignal, config)
flags = {}
flags["useAsymA"] = 1
flags["useRectA"] = 1
