pySoundToolbox.py
def func(t):
        """
        Array response function.

        @param t time, which needs to be a float or a numpy array with times
        @return a numpy array with the elongation of the wave at times t.
            A row represents one microphone within the array.
        """
        if type(t) != np.ndarray:
            t = np.array([t])

        data = np.matrix(np.empty((antennaNum, t.shape[0]), dtype=np.complex))
        for i in range(t.shape[0]):
            sourceData = np.matrix([[sourceSignals[k](t[i])] for k in range(sourcesNum)], dtype=np.complex256)
            noise = 0
            if noiseStd != 0:
                noise = np.matrix(np.random.normal(size=antennaNum, scale=noiseStd), dtype=np.complex256).transpose()\
                    + 1j * np.matrix(np.random.normal(size=antennaNum, scale=noiseStd), dtype=np.complex256).transpose()
            data[:, i] = steeringMat * sourceData + noise

        return data

        Array response function.

        @param t time, which needs to be a float or a numpy array with times
        @return a numpy array with the elongation of the wave at times t.
            A row represents one microphone within the array.
        
Array response function.
@param t time, which needs to be a float or a numpy array with times
@return a numpy array with the elongation of the wave at times t.
A row represents one microphone within the array.
Array response function . @param t time which needs to be a float or a numpy array with times @return a numpy array with the elongation of the wave at times t . A row represents one microphone within the array .
def func(t):
        if type(t) != np.ndarray:
            t = np.array([t])
        data = np.matrix(np.empty((antennaNum, t.shape[0]), dtype=np.complex))
        for i in range(t.shape[0]):
            sourceData = np.matrix([[sourceSignals[k](t[i])] for k in range(sourcesNum)], dtype=np.complex256)
            noise = 0
            if noiseStd != 0:
                noise = np.matrix(np.random.normal(size=antennaNum, scale=noiseStd), dtype=np.complex256).transpose()\
                    + 1j * np.matrix(np.random.normal(size=antennaNum, scale=noiseStd), dtype=np.complex256).transpose()
            data[:, i] = steeringMat * sourceData + noise
        return data
def func ( t ) : if type ( t ) != np . ndarray : t = np . array ( [ t ] ) data = np . matrix ( np . empty ( ( antennaNum , t . shape [ 0 ] ) , dtype = np . complex ) ) for i in range ( t . shape [ 0 ] ) : sourceData = np . matrix ( [ [ sourceSignals [ k ] ( t [ i ] ) ] for k in range ( sourcesNum ) ] , dtype = np . complex256 ) noise = 0 if noiseStd != 0 : noise = np . matrix ( np . random . normal ( size = antennaNum , scale = noiseStd ) , dtype = np . complex256 ) . transpose ( ) + 1j * np . matrix ( np . random . normal ( size = antennaNum , scale = noiseStd ) , dtype = np . complex256 ) . transpose ( ) data [ : , i ] = steeringMat * sourceData + noise return data
Array response function.
Array response function .
"""
        Array response function.

        @param t time, which needs to be a float or a numpy array with times
        @return a numpy array with the elongation of the wave at times t.
            A row represents one microphone within the array.
        """
t