comparison model.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
comparison
equal deleted inserted replaced
3:ecf125a1ad73 4:a609d6dc8047
3 3
4 import sys 4 import sys
5 5
6 import numpy as np 6 import numpy as np
7 7
8 from theano import config, function, shared 8 from theano import function, shared
9 import theano.tensor as T 9 import theano.tensor as T
10 10
11 __author__ = "Gianluca Corrado" 11 __author__ = "Gianluca Corrado"
12 __copyright__ = "Copyright 2016, Gianluca Corrado" 12 __copyright__ = "Copyright 2016, Gianluca Corrado"
13 __license__ = "MIT" 13 __license__ = "MIT"
59 59
60 self.learning_rate = learning_rate 60 self.learning_rate = learning_rate
61 self.lambda_reg = lambda_reg 61 self.lambda_reg = lambda_reg
62 np.random.seed(seed) 62 np.random.seed(seed)
63 # explictit features for proteins 63 # explictit features for proteins
64 fp = T.matrix("Fp", dtype=config.floatX) 64 fp = T.matrix("Fp", dtype='float32')
65 # explictit features for RNAs 65 # explictit features for RNAs
66 fr = T.matrix("Fr", dtype=config.floatX) 66 fr = T.matrix("Fr", dtype='float32')
67 # Correct label 67 # Correct label
68 y = T.vector("y") 68 y = T.vector("y")
69 69
70 # projection matrix for proteins 70 # projection matrix for proteins
71 self.Ap = shared(((.5 - np.random.rand(kp, sp)) * 71 self.Ap = shared(((.5 - np.random.rand(kp, sp)) *
72 irange).astype(config.floatX), name="Ap") 72 irange).astype('float32'), name="Ap")
73 self.bp = shared(((.5 - np.random.rand(kp)) * 73 self.bp = shared(((.5 - np.random.rand(kp)) *
74 irange).astype(config.floatX), name="bp") 74 irange).astype('float32'), name="bp")
75 # projection matrix for RNAs 75 # projection matrix for RNAs
76 self.Ar = shared(((.5 - np.random.rand(kr, sr)) * 76 self.Ar = shared(((.5 - np.random.rand(kr, sr)) *
77 irange).astype(config.floatX), name="Ar") 77 irange).astype('float32'), name="Ar")
78 self.br = shared(((.5 - np.random.rand(kr)) * 78 self.br = shared(((.5 - np.random.rand(kr)) *
79 irange).astype(config.floatX), name="br") 79 irange).astype('float32'), name="br")
80 # generalization matrix 80 # generalization matrix
81 self.B = shared(((.5 - np.random.rand(kp, kr)) * 81 self.B = shared(((.5 - np.random.rand(kp, kr)) *
82 irange).astype(config.floatX), name="B") 82 irange).astype('float32'), name="B")
83 83
84 # Latent space for proteins 84 # Latent space for proteins
85 p = T.nnet.sigmoid(T.dot(fp, self.Ap.T) + self.bp) 85 p = T.nnet.sigmoid(T.dot(fp, self.Ap.T) + self.bp)
86 # Latent space for RNAs 86 # Latent space for RNAs
87 r = T.nnet.sigmoid(T.dot(fr, self.Ar.T) + self.br) 87 r = T.nnet.sigmoid(T.dot(fr, self.Ar.T) + self.br)