sompy module¶
Self Organizing Maps¶
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class
gemseo.third_party.sompy.
SOM
(name, Data, mapsize=None, norm_method='var', initmethod='pca', neigh='Guassian')[source]¶ Bases:
object
name and data, neigh== Bubble or Guassian
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cluster
(method='Kmeans', n_clusters=8)[source]¶ - Parameters
method – Default value = ‘Kmeans’)
n_clusters – Default value = 8)
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find_K_nodes
(data, K=5)[source]¶ - Parameters
data – param K: (Default value = 5)
K – (Default value = 5)
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node_Activation
(data, wt='distance', Target=None)[source]¶ ‘uniform’
- Parameters
data – param wt: (Default value = ‘distance’)
Target – Default value = None)
wt – (Default value = ‘distance’)
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predict
(X_test, K=5, wt='distance')[source]¶ ‘uniform’
- Parameters
X_test – param K: (Default value = 5)
wt – Default value = ‘distance’)
K – (Default value = 5)
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predict_Probability
(data, Target, K=5)[source]¶ - Parameters
data – param Target:
K – Default value = 5)
Target –
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predict_by
(data, Target, K=5, wt='distance')[source]¶ ‘uniform’
- Parameters
data – param Target:
K – Default value = 5)
wt – Default value = ‘distance’)
Target –
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set_algorithm
(initmethod='pca', algtype='batch', neighborhoodmethod='gaussian', alfatype='inv', alfaini=0.5, alfafinal=0.005)[source]¶ initmethod = [‘random’, ‘pca’] algos = [‘seq’,’batch’] all_neigh = [‘gaussian’,’manhatan’,’bubble’,’cut_gaussian’,’epanechicov’ ] alfa_types = [‘linear’,’inv’,’power’]
- Parameters
initmethod – Default value = ‘pca’)
algtype – Default value = ‘batch’)
neighborhoodmethod – Default value = ‘gaussian’)
alfatype – Default value = ‘inv’)
alfaini – Default value = .5)
alfafinal – Default value = .005)
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set_topology
(mapsize=None, mapshape='planar', lattice='rect', mask=None, compname=None)[source]¶ all_mapshapes = [‘planar’,’toroid’,’cylinder’] all_lattices = [‘hexa’,’rect’]
- Parameters
mapsize – Default value = None)
mapshape – Default value = ‘planar’)
lattice – Default value = ‘rect’)
mask – Default value = None)
compname – Default value = None)
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train
(trainlen=None, n_job=1, shared_memory='no', verbose='on')[source]¶ - Parameters
trainlen – Default value = None)
n_job – Default value = 1)
shared_memory – Default value = ‘no’)
verbose – Default value = ‘on’)
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update_codebook_voronoi
(training_data, bmu, H, radius)[source]¶ - Parameters
training_data – param bmu:
H – param radius:
bmu –
radius –
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view_map
(what='codebook', which_dim='all', pack='Yes', text_size=2.8, save='No', save_dir='empty', grid='No', text='Yes', cmap='None', COL_SiZe=6)[source]¶ - Parameters
what – Default value = ‘codebook’)
which_dim – Default value = ‘all’)
pack – Default value = ‘Yes’)
text_size – Default value = 2.8)
save – Default value = ‘No’)
save_dir – Default value = ‘empty’)
grid – Default value = ‘No’)
text – Default value = ‘Yes’)
cmap – Default value = ‘None’)
COL_SiZe – Default value = 6)
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gemseo.third_party.sompy.
batchtrain
(self, njob=1, phase=None, shared_memory='no', verbose='on')[source]¶ - Parameters
njob – Default value = 1)
phase – Default value = None)
shared_memory – Default value = ‘no’)
verbose – Default value = ‘on’)
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gemseo.third_party.sompy.
chunk_based_bmu_find
(self, x, y, y_2)[source]¶ - Parameters
x – param y:
y_2 –
y –
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gemseo.third_party.sompy.
denormalize_by
(data_by, n_vect, n_method='var')[source]¶ - Parameters
data_by – param n_vect:
n_method – Default value = ‘var’)
n_vect –
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gemseo.third_party.sompy.
grid_dist
(self, bmu_ind)[source]¶ som and bmu_ind depending on the lattice “hexa” or “rect” we have different grid distance functions. bmu_ind is a number between 0 and number of nodes-1. depending on the map size bmu_coord will be calculated and then distance matrix in the map will be returned
- Parameters
bmu_ind –
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gemseo.third_party.sompy.
normalize
(data, method='var')[source]¶ - Parameters
data – param method: (Default value = ‘var’)
method – (Default value = ‘var’)
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gemseo.third_party.sompy.
normalize_by
(data_raw, data, method='var')[source]¶ - Parameters
data_raw – param data:
method – Default value = ‘var’)
data –
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gemseo.third_party.sompy.
view_1d
(self, text_size, which_dim='all', what='codebook')[source]¶ - Parameters
text_size – param which_dim: (Default value = ‘all’)
what – Default value = ‘codebook’)
which_dim – (Default value = ‘all’)
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gemseo.third_party.sompy.
view_2d
(self, text_size, which_dim='all', what='codebook')[source]¶ - Parameters
text_size – param which_dim: (Default value = ‘all’)
what – Default value = ‘codebook’)
which_dim – (Default value = ‘all’)
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gemseo.third_party.sompy.
view_2d_Pack
(self, text_size, which_dim='all', what='codebook', save='No', grid='Yes', save_dir='empty', text='Yes', CMAP='None', col_sz=None)[source]¶ - Parameters
text_size – param which_dim: (Default value = ‘all’)
what – Default value = ‘codebook’)
save – Default value = ‘No’)
grid – Default value = ‘Yes’)
save_dir – Default value = ‘empty’)
text – Default value = ‘Yes’)
CMAP – Default value = ‘None’)
col_sz – Default value = None)
which_dim – (Default value = ‘all’)