def draw_SOM (self,srch_str, dist_neu_searchq, neuron_labels,map_path):
TOOLS = "pan,wheel_zoom,box_zoom,hover,resize"
plot = figure(title=srch_str,title_text_font_size='20pt',tools=TOOLS,plot_width=1000,plot_height=1000)
nid = sorted(dist_neu_searchq)
dist = [dist_neu_searchq[n] for n in nid]
norm_dist = [round((x-min(dist))*255/(max(dist)-min(dist))) for x in dist] # Light is might
node_pos = utilities.generate_positions(self._map_dimensions)
xx = [sub[0]for sub in node_pos]
yy = [sub[1]for sub in node_pos]
colours=["#%02x%02x%02x" % (g,0,g) for g in norm_dist]
source = ColumnDataSource(
data=dict(
x=xx,
y=yy,
nid=nid,
colors=colours,
labels = neuron_labels
)
)
plot.circle(xx,yy,source=source,size=50,fill_color=colours,fill_alpha=0.7,line_color=None)
plot.text(xx, yy, text=norm_dist, alpha=0.5, text_font_size="15pt",text_baseline="middle", text_align="center")
hover = plot.select(dict(type=HoverTool))
hover.tooltips = [
("index", "@nid"),
("labels", "@labels")
]
output_file(map_path)
show(plot)
def __init__(self, map_dimensions=[15,15], weight_dimensions=200):
self._map_dimensions = map_dimensions
self._weight_dimensions = weight_dimensions
self._neurons = []
self._neu_index= {}
self._glomat = {}
# Initializing neurons with random weights:
logger.info('Beginning init of neurons in map')
for idx, position in enumerate(utilities.generate_positions(map_dimensions)):
random_wt=[random.random()*10 for i in range(weight_dimensions)]
self._neurons.append(Neuron(id=idx, position=position, weights=random_wt))
self._neu_index.update({idx:self._neurons[-1]})
logger.info('Map neurons initialized')
def __init__(self, map_dimensions=[15, 15], weight_dimensions=200):
self._map_dimensions = map_dimensions
self._weight_dimensions = weight_dimensions
self._neurons = []
self._neu_index = {}
self._glomat = {}
# Initializing neurons with random weights:
logger.info('Beginning init of neurons in map')
for idx, position in enumerate(
utilities.generate_positions(map_dimensions)):
random_wt = [
random.random() * 10 for i in range(weight_dimensions)
]
self._neurons.append(
Neuron(id=idx, position=position, weights=random_wt))
self._neu_index.update({idx: self._neurons[-1]})
logger.info('Map neurons initialized')
def draw_SOM(self, srch_str, dist_neu_searchq, neuron_labels, map_path):
TOOLS = "pan,wheel_zoom,box_zoom,hover,resize"
plot = figure(title=srch_str,
title_text_font_size='20pt',
tools=TOOLS,
plot_width=1000,
plot_height=1000)
nid = sorted(dist_neu_searchq)
dist = [dist_neu_searchq[n] for n in nid]
norm_dist = [
round((x - min(dist)) * 255 / (max(dist) - min(dist)))
for x in dist
] # Light is might
node_pos = utilities.generate_positions(self._map_dimensions)
xx = [sub[0] for sub in node_pos]
yy = [sub[1] for sub in node_pos]
colours = ["#%02x%02x%02x" % (g, 0, g) for g in norm_dist]
source = ColumnDataSource(data=dict(
x=xx, y=yy, nid=nid, colors=colours, labels=neuron_labels))
plot.circle(xx,
yy,
source=source,
size=50,
fill_color=colours,
fill_alpha=0.7,
line_color=None)
plot.text(xx,
yy,
text=norm_dist,
alpha=0.5,
text_font_size="15pt",
text_baseline="middle",
text_align="center")
hover = plot.select(dict(type=HoverTool))
hover.tooltips = [("index", "@nid"), ("labels", "@labels")]
output_file(map_path)
show(plot)
