def test_from_hsl(self):
c = HSL(10, 0.1, 0.2)
c2 = bcr.RGB.from_hsl(c)
assert c2 is not c
assert c2.a == 1.0
assert c2.r == 56
assert c2.g == 48
assert c2.b == 46
c = HSL(10, 0.1, 0.2, 0.3)
c2 = bcr.RGB.from_hsl(c)
assert c2 is not c
assert c2.a == 0.3
assert c2.r == 56
assert c2.g == 48
assert c2.b == 46
def tree_to_wedge_data(data,
tree,
level=0,
total=None,
subtotal=0,
ancestor_subtotal=None,
threshold=0.0025):
if total is None:
total = float(tree.count)
initial_subtotal = subtotal
final_subtotal = subtotal + tree.count
item_list = tree.key_to_subtree.items()
subtotal_for_color = initial_subtotal if level == 0 else ancestor_subtotal
for key, subtree in sorted(item_list, key=tree_item_count, reverse=True):
if subtree.count / total <= threshold:
break
subtotal_begin = subtotal
subtotal_end = subtotal + subtree.count
if level == 0:
subtotal_for_color = subtotal_begin
elif (subtotal_end - subtotal_begin) / (final_subtotal -
initial_subtotal) >= 0.66:
subtotal_for_color = ancestor_subtotal
else:
subtotal_for_color = fmod(subtotal_for_color + 0.1 * total, total)
data.append({
'inner_radius':
level,
'outer_radius':
level + 1,
'start_angle': (subtotal / total) * 2 * pi,
'end_angle': (subtotal_end / total) * 2 * pi,
'fill_color':
color_for_wedge(level, total, subtotal_for_color),
'name':
key
})
tree_to_wedge_data(data,
subtree,
level=level + 1,
total=total,
subtotal=subtotal,
ancestor_subtotal=subtotal_for_color,
threshold=threshold)
subtotal += subtree.count
ancestor_subtotal = None
if False:
data.append({
'inner_radius': level,
'outer_radius': level + 1,
'start_angle': (subtotal / total) * 2 * pi,
'end_angle': (final_subtotal / total) * 2 * pi,
'fill_color': HSL(0, 1, 1),
'name': '(other)'
})
def color_for_wedge(level, total, subtotal_for_color):
return HSL(
int(256 * 0.99999 * (subtotal_for_color / total)),
1.0, # 1.0 - subtree.count/float(tree.count), # sat [0,1]
0.5, # 0.4+(level*0.2)/6, # light [0=black,1/2=sat,1=white]
1.0) # alpha
def my_colors(self,ii,nn):
return HSL(360*(ii+1)/nn,1,0.4).to_rgb().to_hex()
def string_to_rgb(name):
value = sum(bytearray(name, 'utf-8'))
hue = round(value % 360 / 10) * 10
# print('{}: {}, {}'.format(name, value, hue))
return HSL(hue, 0.75, 0.8)
from bokeh.models.ranges import FactorRange, DataRange1d
from bokeh.plotting import figure
from bokeh.sampledata.commits import data
from bokeh.transform import factor_cmap
from bokeh.colors import HSL
from bokeh.layouts import row, column
from bokeh.themes import built_in_themes
import math
from hexagonal_clusters import hex_y, hex_x, delta_x, delta_y, scale_factor
from nobel_data import nobel
from bokeh.models.tools import BoxZoomTool, PanTool, WheelZoomTool, ResetTool, HoverTool
output_file('nobel.html')
cmap = {
"Chemistry": HSL(0, 0.5, 0.5).to_rgb().to_hex(),
"Medicine": HSL(120, 0.5, 0.5).to_rgb().to_hex(),
"Physics": HSL(180, 0.5, 0.5).to_rgb().to_hex(),
"Peace": HSL(240, 0.5, 0.5).to_rgb().to_hex(),
"Economics": HSL(300, 0.5, 0.5).to_rgb().to_hex(),
"Literature": HSL(60, 0.5, 0.5).to_rgb().to_hex()
}
source = ColumnDataSource(data={
"x": [],
"y": [],
"Category": nobel['Category']
})
aspect_ratio = 2.4
p = figure(title="Nobel Laureates",