| @@ -0,0 +1,10 | |||||
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1 | import numpy | |||
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2 | cimport numpy | |||
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3 | ||||
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4 | def decoder(numpy.ndarray[numpy.float32_t, ndim=2] fft_code, numpy.ndarray[numpy.float32_t, ndim=2] data): | |||
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5 | ||||
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6 | fft_data = numpy.fft.fft(data, axis=1) | |||
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7 | conv = fft_data*fft_code | |||
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8 | data = numpy.fft.ifft(conv, axis=1) | |||
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9 | ||||
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10 | return data No newline at end of file | |||
| @@ -0,0 +1,6 | |||||
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1 | from distutils.core import setup | |||
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2 | from distutils.extension import Extension | |||
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3 | from Cython.Distutils import build_ext | |||
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4 | setup( | |||
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5 | cmdclass = {'build_ext': build_ext}, | |||
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6 | ext_modules = [Extension("cfunctions", ["cfunctions.pyx"])] ) No newline at end of file | |||
| @@ -12,6 +12,11 from jrodata import * | |||||
| 12 | from jrodataIO import * |
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12 | from jrodataIO import * | |
| 13 | from jroplot import * |
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13 | from jroplot import * | |
| 14 |
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14 | |||
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15 | try: | |||
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16 | import cfunctions | |||
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17 | except: | |||
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18 | pass | |||
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19 | ||||
| 15 | class ProcessingUnit: |
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20 | class ProcessingUnit: | |
| 16 |
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21 | |||
| 17 | """ |
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22 | """ | |
| @@ -591,9 +596,9 class Decoder(Operation): | |||||
| 591 |
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596 | |||
| 592 | self.__nChannels, self.__nHeis = shape |
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597 | self.__nChannels, self.__nHeis = shape | |
| 593 |
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598 | |||
| 594 | self.__codeBuffer = numpy.zeros((self.nCode, self.__nHeis)) |
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599 | self.__codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.float) | |
| 595 |
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600 | |||
| 596 |
self.__codeBuffer[:,0:self.nBaud] = self.code |
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601 | self.__codeBuffer[:,0:self.nBaud] = self.code | |
| 597 |
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602 | |||
| 598 | self.fft_code = numpy.conj(numpy.fft.fft(self.__codeBuffer, axis=1)) |
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603 | self.fft_code = numpy.conj(numpy.fft.fft(self.__codeBuffer, axis=1)) | |
| 599 |
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604 | |||
| @@ -623,7 +628,23 class Decoder(Operation): | |||||
| 623 |
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628 | |||
| 624 | return ndatadec, datadec |
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629 | return ndatadec, datadec | |
| 625 |
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630 | |||
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631 | def convolutionInFreqOpt(self, data): | |||
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632 | ||||
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633 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |||
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634 | ||||
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635 | data = cfunctions.decoder(fft_code, data) | |||
| 626 |
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636 | |||
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637 | datadec = data[:,:-self.nBaud+1] | |||
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638 | ndatadec = self.__nHeis - self.nBaud + 1 | |||
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639 | ||||
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640 | if self.__profIndex == self.nCode-1: | |||
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641 | self.__profIndex = 0 | |||
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642 | return ndatadec, datadec | |||
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643 | ||||
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644 | self.__profIndex += 1 | |||
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645 | ||||
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646 | return ndatadec, datadec | |||
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647 | ||||
| 627 | def convolutionInTime(self, data): |
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648 | def convolutionInTime(self, data): | |
| 628 |
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649 | |||
| 629 | self.__nChannels, self.__nHeis = data.shape |
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650 | self.__nChannels, self.__nHeis = data.shape | |
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