Python PCA.compute示例

示例#1

    for struct in structures:
        print struct.label
        kernelpot.acquire(struct, 1., label=struct.label)
        print kernelpot.IX.shape
    np.savetxt('out.kernelpot.ix.txt', kernelpot.IX)
    ofs = open('out.kernelpot.labels.txt', 'w')
    for idx, label in enumerate(kernelpot.labels):
        ofs.write('%3d %s\n' % (idx, label))
    ofs.close()
else:
    IX = np.loadtxt('out.kernelpot.ix.txt')
    kernelpot.importAcquire(IX, 1.)

# KERNEL PCA
pca = PCA()
pca.compute(kernelpot.IX, normalize_mean=norm_mean, normalize_std=norm_std)
#pca = IPCA()
#pca.compute(IX, normalize_mean=False, normalize_std=False)

# =============================
# CHECK COMPONENT NORMALIZATION
# =============================

ones_vec = np.zeros(567)
ones_vec.fill(1.)
np.savetxt('out.pca.unnorm.txt', pca.unnormBlock(ones_vec))

# =================
# INDEX CUTOFF SCAN
# =================

示例#2

文件： config_pca.py 项目： wenwenqingqing/soapxx

# FILL KERNEL
generate = False
if generate:
    for struct in structures:
        print struct.label    
        kernelpot.acquire(struct, 1., label=struct.label)
        print kernelpot.IX.shape
    np.savetxt('out.kernelpot.ix.txt', kernelpot.IX)
else:
    IX = np.loadtxt('out.kernelpot.ix.txt')
    kernelpot.importAcquire(IX, 1.)

# KERNEL PCA
pca = PCA()
pca.compute(IX, normalize_mean=False, normalize_std=False)
#pca = IPCA()
#pca.compute(IX, normalize_mean=False, normalize_std=False)


# =============================
# CHECK COMPONENT NORMALIZATION
# =============================

ones_vec = np.zeros(567)
ones_vec.fill(1.)
np.savetxt('out.pca.unnorm.txt', pca.unnormBlock(ones_vec))

# =================
# INDEX CUTOFF SCAN
# =================

示例#3

文件： 0_compute_pca.py 项目： capoe/soapxx

    for struct in structures:
        print struct.label    
        kernelpot.acquire(struct, 1., label=struct.label)
        print kernelpot.IX.shape
    np.savetxt('out.kernelpot.ix.txt', kernelpot.IX)
    ofs = open('out.kernelpot.labels.txt', 'w')
    for idx,label in enumerate(kernelpot.labels):
        ofs.write('%3d %s\n' % (idx,label))
    ofs.close()
else:
    IX = np.loadtxt('out.kernelpot.ix.txt')
    kernelpot.importAcquire(IX, 1.)

# KERNEL PCA
pca = PCA()
pca.compute(kernelpot.IX, normalize_mean=norm_mean, normalize_std=norm_std)
#pca = IPCA()
#pca.compute(IX, normalize_mean=False, normalize_std=False)


# =============================
# CHECK COMPONENT NORMALIZATION
# =============================

ones_vec = np.zeros(567)
ones_vec.fill(1.)
np.savetxt('out.pca.unnorm.txt', pca.unnormBlock(ones_vec))

# =================
# INDEX CUTOFF SCAN
# =================