Mercurial > repos > rnateam > rnacommender
comparison data.py @ 4:a609d6dc8047 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/rna_commander/tools/rna_tools/rna_commender commit 7ad344d108076116e702e1c1e91cea73d8fcadc4
| author | rnateam |
|---|---|
| date | Thu, 28 Jul 2016 05:55:25 -0400 |
| parents | 8918de535391 |
| children |
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| 3:ecf125a1ad73 | 4:a609d6dc8047 |
|---|---|
| 1 """Dataset handler.""" | 1 """Dataset handler.""" |
| 2 | 2 |
| 3 import numpy as np | 3 import numpy as np |
| 4 | 4 |
| 5 import pandas as pd | 5 import pandas as pd |
| 6 | |
| 7 from theano import config | |
| 8 | 6 |
| 9 __author__ = "Gianluca Corrado" | 7 __author__ = "Gianluca Corrado" |
| 10 __copyright__ = "Copyright 2016, Gianluca Corrado" | 8 __copyright__ = "Copyright 2016, Gianluca Corrado" |
| 11 __license__ = "MIT" | 9 __license__ = "MIT" |
| 12 __maintainer__ = "Gianluca Corrado" | 10 __maintainer__ = "Gianluca Corrado" |
| 28 Protein features | 26 Protein features |
| 29 | 27 |
| 30 fr : str | 28 fr : str |
| 31 The name of the HDF5 file containing features for the RNAs. | 29 The name of the HDF5 file containing features for the RNAs. |
| 32 """ | 30 """ |
| 33 self.Fp = fp.astype(config.floatX) | 31 self.Fp = fp.astype('float32') |
| 34 | 32 |
| 35 store = pd.io.pytables.HDFStore(fr) | 33 store = pd.io.pytables.HDFStore(fr) |
| 36 self.Fr = store.features.astype(config.floatX) | 34 self.Fr = store.features.astype('float32') |
| 37 store.close() | 35 store.close() |
| 38 | 36 |
| 39 def load(self): | 37 def load(self): |
| 40 """Load dataset in memory.""" | 38 """Load dataset in memory.""" |
| 41 raise NotImplementedError() | 39 raise NotImplementedError() |
| 72 | 70 |
| 73 """ | 71 """ |
| 74 protein_input_dim = self.Fp.shape[0] | 72 protein_input_dim = self.Fp.shape[0] |
| 75 rna_input_dim = self.Fr.shape[0] | 73 rna_input_dim = self.Fr.shape[0] |
| 76 num_examples = self.Fp.shape[1] * self.Fr.shape[1] | 74 num_examples = self.Fp.shape[1] * self.Fr.shape[1] |
| 77 p = np.zeros((num_examples, protein_input_dim)).astype(config.floatX) | 75 p = np.zeros((num_examples, protein_input_dim)).astype('float32') |
| 78 p_names = [] | 76 p_names = [] |
| 79 r = np.zeros((num_examples, rna_input_dim)).astype(config.floatX) | 77 r = np.zeros((num_examples, rna_input_dim)).astype('float32') |
| 80 r_names = [] | 78 r_names = [] |
| 81 index = 0 | 79 index = 0 |
| 82 for protein in self.Fp.columns: | 80 for protein in self.Fp.columns: |
| 83 for rna in self.Fr.columns: | 81 for rna in self.Fr.columns: |
| 84 p[index] = self.Fp[protein] | 82 p[index] = self.Fp[protein] |