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106 lines
2.9 KiB
Python
106 lines
2.9 KiB
Python
import os.path
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import numpy as np
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import itertools
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import Tools
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import scipy.fftpack
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# Those patterns are used for tests and benchmarks.
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# For tests, there is the need to add tests for saturation
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FFTSIZES=[16,32,64,128,256,512,1024,2048,4096]
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SINES=[0.25,0.5,0.9]
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NOISES=[0.1,0.4]
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def randComplex(nb):
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data = np.random.randn(2*nb)
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data = Tools.normalize(data)
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data_comp = data.view(dtype=np.complex128)
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return(data_comp)
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def asReal(a):
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#return(a.view(dtype=np.float64))
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return(a.reshape(np.size(a)).view(dtype=np.float64))
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def randComplex(nb):
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data = np.random.randn(2*nb)
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data = Tools.normalize(data)
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data_comp = data.view(dtype=np.complex128)
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return(data_comp)
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def asReal(a):
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#return(a.view(dtype=np.float64))
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return(a.reshape(np.size(a)).view(dtype=np.float64))
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def noiseSignal(nb):
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return(np.random.randn(nb))
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def sineSignal(freqRatio,nb):
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fc = nb / 2.0
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f = freqRatio*fc
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time = np.arange(0,nb)
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return(np.sin(2 * np.pi * f * time/nb))
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def noisySineSignal(noiseAmp,r,nb):
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return(noiseAmp*noiseSignal(nb) + r*sineSignal(0.25,nb))
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def stepSignal(r,nb):
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n = int(nb/2)
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return(np.concatenate((np.zeros(n), r*np.ones(n))))
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def writeFFTForSignal(config,sig,scaling,i,j,nb,signame):
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fft=scipy.fftpack.fft(sig)
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ifft = np.copy(fft)
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if scaling:
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fft = np.array([x/2**scaling[j] for x in fft])
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config.writeInput(i, asReal(sig),"ComplexInputSamples_%s_%d_" % (signame,nb))
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config.writeInput(i, asReal(fft),"ComplexFFTSamples_%s_%d_" % (signame,nb))
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config.writeInput(i, asReal(fft),"ComplexInputIFFTSamples_%s_%d_" % (signame,nb))
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def writeTests(configs):
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i = 1
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# Write FFT tests for sinusoid
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j = 0
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for nb in FFTSIZES:
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sig = noisySineSignal(0.05,0.7,nb)
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sig = np.array([complex(x) for x in sig])
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for config,scaling in configs:
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writeFFTForSignal(config,sig,scaling,i,j,nb,"Noisy")
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i = i + 1
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j = j + 1
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# Write FFT tests for step
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j = 0
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for nb in FFTSIZES:
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sig = stepSignal(0.9,nb)
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sig = np.array([complex(x) for x in sig])
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for config,scaling in configs:
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writeFFTForSignal(config,sig,scaling,i,j,nb,"Step")
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i = i + 1
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j = j + 1
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data1=np.random.randn(512)
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data1 = Tools.normalize(data1)
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for config,scaling in configs:
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config.writeInput(i, data1,"RealInputSamples" )
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def generatePatterns():
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PATTERNDIR = os.path.join("Patterns","DSP","Transform","Transform")
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PARAMDIR = os.path.join("Parameters","DSP","Transform","Transform")
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configf32=Tools.Config(PATTERNDIR,PARAMDIR,"f32")
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configq31=Tools.Config(PATTERNDIR,PARAMDIR,"q31")
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configq15=Tools.Config(PATTERNDIR,PARAMDIR,"q15")
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scalings = [4,5,6,7,8,9,10,11,12]
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writeTests([(configf32,None)
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,(configq31,scalings)
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,(configq15,scalings)])
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if __name__ == '__main__':
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generatePatterns() |