Bokeh Pythonでレーダーチャートを作成する手順は何ですか？

Question

目的：私は解決策にギャップを埋めるのに役立つかもしれませんどのmatplotlibのからthis chart exampleを得た

：後これは私はチャートタイプで有用であることがボケパイソン

内レーダーチャートを作成しますしかし、私はそこに着く方法を見ることができません。任意の助けをいただければ幸いです

from collections import OrderedDict 
from math import log, sqrt 

import numpy as np 
import pandas as pd 
from six.moves import cStringIO as StringIO 

from bokeh.plotting import figure, show, output_file 

antibiotics = """ 
bacteria,      penicillin, streptomycin, neomycin, gram 
Mycobacterium tuberculosis,  800,  5,   2,  negative 
Salmonella schottmuelleri,  10,   0.8,   0.09,  negative 
Proteus vulgaris,    3,   0.1,   0.1,  negative 
Klebsiella pneumoniae,   850,  1.2,   1,  negative 
Brucella abortus,    1,   2,   0.02,  negative 
Pseudomonas aeruginosa,   850,  2,   0.4,  negative 
Escherichia coli,    100,  0.4,   0.1,  negative 
Salmonella (Eberthella) typhosa, 1,   0.4,   0.008, negative 
Aerobacter aerogenes,   870,  1,   1.6,  negative 
Brucella antracis,    0.001,  0.01,   0.007, positive 
Streptococcus fecalis,   1,   1,   0.1,  positive 
Staphylococcus aureus,   0.03,  0.03,   0.001, positive 
Staphylococcus albus,   0.007,  0.1,   0.001, positive 
Streptococcus hemolyticus,  0.001,  14,   10,  positive 
Streptococcus viridans,   0.005,  10,   40,  positive 
Diplococcus pneumoniae,   0.005,  11,   10,  positive 
""" 

drug_color = OrderedDict([ 
    ("Penicillin", "#0d3362"), 
    ("Streptomycin", "#c64737"), 
    ("Neomycin",  "black" ), 
]) 

gram_color = { 
    "positive" : "#aeaeb8", 
    "negative" : "#e69584", 
} 

df = pd.read_csv(StringIO(antibiotics), 
       skiprows=1, 
       skipinitialspace=True, 
       engine='python') 

width = 800 
height = 800 
inner_radius = 90 
outer_radius = 300 - 10 

minr = sqrt(log(.001 * 1E4)) 
maxr = sqrt(log(1000 * 1E4)) 
a = (outer_radius - inner_radius)/(minr - maxr) 
b = inner_radius - a * maxr 

def rad(mic): 
    return a * np.sqrt(np.log(mic * 1E4)) + b 

big_angle = 2.0 * np.pi/(len(df) + 1) 
small_angle = big_angle/7 

p = figure(plot_width=width, plot_height=height, title="", 
    x_axis_type=None, y_axis_type=None, 
    x_range=(-420, 420), y_range=(-420, 420), 
    min_border=0, outline_line_color="black", 
    background_fill_color="#f0e1d2", border_fill_color="#f0e1d2", 
    toolbar_sticky=False) 

p.xgrid.grid_line_color = None 
p.ygrid.grid_line_color = None 

# annular wedges 
angles = np.pi/2 - big_angle/2 - df.index.to_series()*big_angle 
colors = [gram_color[gram] for gram in df.gram] 
p.annular_wedge(
    0, 0, inner_radius, outer_radius, -big_angle+angles, angles, color=colors, 
) 

# small wedges 
p.annular_wedge(0, 0, inner_radius, rad(df.penicillin), 
       -big_angle+angles+5*small_angle, -big_angle+angles+6*small_angle, 
       color=drug_color['Penicillin']) 
p.annular_wedge(0, 0, inner_radius, rad(df.streptomycin), 
       -big_angle+angles+3*small_angle, -big_angle+angles+4*small_angle, 
       color=drug_color['Streptomycin']) 
p.annular_wedge(0, 0, inner_radius, rad(df.neomycin), 
       -big_angle+angles+1*small_angle, -big_angle+angles+2*small_angle, 
       color=drug_color['Neomycin']) 

# circular axes and lables 
labels = np.power(10.0, np.arange(-3, 4)) 
radii = a * np.sqrt(np.log(labels * 1E4)) + b 
p.circle(0, 0, radius=radii, fill_color=None, line_color="white") 
p.text(0, radii[:-1], [str(r) for r in labels[:-1]], 
     text_font_size="8pt", text_align="center", text_baseline="middle") 

# radial axes 
p.annular_wedge(0, 0, inner_radius-10, outer_radius+10, 
       -big_angle+angles, -big_angle+angles, color="black") 

# bacteria labels 
xr = radii[0]*np.cos(np.array(-big_angle/2 + angles)) 
yr = radii[0]*np.sin(np.array(-big_angle/2 + angles)) 
label_angle=np.array(-big_angle/2+angles) 
label_angle[label_angle < -np.pi/2] += np.pi # easier to read labels on the left side 
p.text(xr, yr, df.bacteria, angle=label_angle, 
     text_font_size="9pt", text_align="center", text_baseline="middle") 

# OK, these hand drawn legends are pretty clunky, will be improved in future release 
p.circle([-40, -40], [-370, -390], color=list(gram_color.values()), radius=5) 
p.text([-30, -30], [-370, -390], text=["Gram-" + gr for gr in gram_color.keys()], 
     text_font_size="7pt", text_align="left", text_baseline="middle") 

p.rect([-40, -40, -40], [18, 0, -18], width=30, height=13, 
     color=list(drug_color.values())) 
p.text([-15, -15, -15], [18, 0, -18], text=list(drug_color), 
     text_font_size="9pt", text_align="left", text_baseline="middle") 

output_file("burtin.html", title="burtin.py example") 

show(p) 

：以下

は、私がボケを使ってレーダーチャートに見つけることができる最も近い例です。

Answer 1

ここでは、上記でリンクしたmatplotlibの例に基づいた同様の例を示します。これは、あなたが望むものに非常に近くなるようになります。見栄えを良くするためにすべての書式を修正し、輪郭線を追加する必要があります。

import numpy as np 
from bokeh.plotting import figure, show, output_file 
from bokeh.models import ColumnDataSource, LabelSet 

num_vars = 9 

centre = 0.5 

theta = np.linspace(0, 2*np.pi, num_vars, endpoint=False) 
# rotate theta such that the first axis is at the top 
theta += np.pi/2 

def unit_poly_verts(theta, centre): 
    """Return vertices of polygon for subplot axes. 
    This polygon is circumscribed by a unit circle centered at (0.5, 0.5) 
    """ 
    x0, y0, r = [centre ] * 3 
    verts = [(r*np.cos(t) + x0, r*np.sin(t) + y0) for t in theta] 
    return verts 

def radar_patch(r, theta, centre): 
    """ Returns the x and y coordinates corresponding to the magnitudes of 
    each variable displayed in the radar plot 
    """ 
    # offset from centre of circle 
    offset = 0.01 
    yt = (r*centre + offset) * np.sin(theta) + centre 
    xt = (r*centre + offset) * np.cos(theta) + centre 
    return xt, yt 

verts = unit_poly_verts(theta, centre) 
x = [v[0] for v in verts] 
y = [v[1] for v in verts] 

p = figure(title="Baseline - Radar plot") 
text = ['Sulfate', 'Nitrate', 'EC', 'OC1', 'OC2', 'OC3', 'OP', 'CO', 'O3',''] 
source = ColumnDataSource({'x':x + [centre ],'y':y + [1],'text':text}) 

p.line(x="x", y="y", source=source) 

labels = LabelSet(x="x",y="y",text="text",source=source) 

p.add_layout(labels) 

# example factor: 
f1 = np.array([0.88, 0.01, 0.03, 0.03, 0.00, 0.06, 0.01, 0.00, 0.00]) 
f2 = np.array([0.07, 0.95, 0.04, 0.05, 0.00, 0.02, 0.01, 0.00, 0.00]) 
f3 = np.array([0.01, 0.02, 0.85, 0.19, 0.05, 0.10, 0.00, 0.00, 0.00]) 
f4 = np.array([0.02, 0.01, 0.07, 0.01, 0.21, 0.12, 0.98, 0.00, 0.00]) 
f5 = np.array([0.01, 0.01, 0.02, 0.71, 0.74, 0.70, 0.00, 0.00, 0.00]) 
#xt = np.array(x) 
flist = [f1,f2,f3,f4,f5] 
colors = ['blue','green','red', 'orange','purple'] 
for i in range(len(flist)): 
    xt, yt = radar_patch(flist[i], theta, centre) 
    p.patch(x=xt, y=yt, fill_alpha=0.15, fill_color=colors[i]) 
show(p)