| @@ -406,12 +406,10 class HDF5Reader(ProcessingUnit): | |||
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406 | 406 | blocksPerFile = self.blocksPerFile |
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407 | 407 | |
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408 | 408 | #Depending on what mode the data was stored |
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409 |
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410 | # strds = 'channel' | |
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411 | # nDatas = nDim2 | |
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412 | # newShapes = (blocksPerFile,nDim1,nDim0) | |
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409 | if mode == 0: #Divided in channels | |
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410 | arrayData = dataset.value.astype(numpy.float)[0][blockList] | |
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413 | 411 | if mode == 1: #Divided in parameter |
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414 |
strds = ' |
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412 | strds = 'table' | |
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415 | 413 | nDatas = nDim1 |
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416 | 414 | newShapes = (blocksPerFile,nDim2,nDim0) |
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417 | 415 | elif mode==2: #Concatenated in a table |
| @@ -428,7 +426,7 class HDF5Reader(ProcessingUnit): | |||
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428 | 426 | return arrayData |
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429 | 427 | |
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430 | 428 | #------- One dimension --------------- |
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431 |
if nDims == |
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429 | if nDims == 0: | |
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432 | 430 | arrayData = dataset.value.astype(numpy.float)[0][blockList] |
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433 | 431 | |
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434 | 432 | #------- Two dimensions ----------- |
| @@ -476,6 +474,8 class HDF5Reader(ProcessingUnit): | |||
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476 | 474 | setattr(self.dataOut,listDataname[j],listData[j][blockIndex]) |
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477 | 475 | elif nShapes > 1: |
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478 | 476 | setattr(self.dataOut,listDataname[j],listData[j][blockIndex,:]) |
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477 | elif mode==0: | |
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478 | setattr(self.dataOut,listDataname[j],listData[j][blockIndex]) | |
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479 | 479 | #Mode Meteors |
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480 | 480 | elif mode ==2: |
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481 | 481 | selectedData = self.__selectDataMode2(listData[j], blockIndex) |
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