Visualization Notes: 12/20/19

Friday, December 20, 2019

HTML Table Structure

xxxxxxxxxx
 
%%html
  <table style='width:600px; background-color:slategray; color:white; 
                text-shadow:2px 2px 2px whitesmoke; 
                font-size:90%; padding-left:20px;'>
<tr><th>Crayola Fluorescent Colors</th><th>Hex</th></tr>
<tr><td style='background-color:#FF355E;'>=>Radical Red</td>
<td style='color:#FF355E;'><center>&#35;FF355E</center></td></tr>
<tr><td style='background-color:#FD5B78;'>=>Wild Watermelon</td>
<td style='color:#FD5B78;'><center>&#35;FD5B78</center></td></tr>
<tr><td style='background-color:#FF6037;'>=>Outrageous Orange</td>
<td style='color:#FF6037;'><center>&#35;FF6037</center></td></tr>
<tr><td style='background-color:#FF9966;'>=>Atomic Tangerine</td>
<td style='color:#FF9966;'><center>&#35;FF9966</center></td></tr>
<tr><td style='background-color:#FF9933;'>=>Neon Carrot</td>
<td style='color:#FF9933;'><center>&#35;FF9933</center></td></tr>
<tr><td style='background-color:#FFCC33;'>=>Sunglow</td>
<td style='color:#FFCC33;'><center>&#35;FFCC33</center></td></tr>    
<tr><td style='background-color:#FFFF66;'>=>Laser Lemon</td>
<td style='color:#FFFF66;'><center>&#35;FFFF66</center></td></tr>
<tr><td style='background-color:#CCFF00;'>=>Electric Lime</td>
<td style='color:#CCFF00;'><center>&#35;CCFF00</center></td></tr>
<tr><td style='background-color:#66FF66;'>=>Screamin&#39; Green</td>
<td style='color:#66FF66;'><center>&#35;66FF66</center></td></tr>
<tr><td style='background-color:#AAF0D1;'>=>Magic Mint</td>
<td style='color:#AAF0D1;'><center>&#35;AAF0D1</center></td></tr>
<tr><td style='background-color:#50BFE6;'>=>Blizzard Blue</td>
<td style='color:#50BFE6;'><center>&#35;50BFE6</center></td></tr>
<tr><td style='background-color:#FF6EFF;'>=>Shocking Pink</td>
<td style='color:#FF6EFF;'><center>&#35;FF6EFF</center></td></tr>
<tr><td style='background-color:#EE34D2;'>=>Razzle Dazzle Rose</td>
<td style='color:#EE34D2;'><center>&#35;EE34D2</center></td></tr>
<tr><td style='background-color:#FF00CC;'>=>Hot Magenta</td>
<td style='color:#FF00CC;'><center>&#35;FF00CC</center></td></tr>
  </table>

Matrix Manipulations

xxxxxxxxxx
 
a1=r([[2.9,3.,2.5,2.6,3.2],
      [3.8,2.7,4.,2.4],
      [2.8,3.4,3.7,2.2,2.]])
a2=r.factor([5*[1]+4*[2]+5*[3]])
A=r.matrix([a1,a2],nrow=14,ncol=2); r.t(A)

DataFrame Manipulations

xxxxxxxxxx
 
import pandas
fp='https://raw.githubusercontent.com/'+\
   'OlgaBelitskaya/data/main/external_json/'
se=pandas.read_json(fp+'h7rb-945c.json')
fl=['dbn','ell_programs','language_classes',
    'finalgrades','total_students',
    'graduation_rate','attendance_rate',
    'college_career_rate','pct_stu_safe',
    'pct_stu_enough_variety','latitude',
    'longitude','council_district','city']
se=se[fl]
sesum=se.isna().sum()[se.isna().sum()!=0]
print(sesum.to_frame()); print('\n')
se=se.dropna(); se.head().loc[:2].T

Fun Symbol Plotting

xxxxxxxxxx
 
v=[(1/cos(-pi/2+pi*i/100),tan(-pi/2+pi*i/100)) 
   for i in [1,3,..,99]+[101,103,..,199]]
L=[(a/(a^2+b^2),b/(a^2+b^2)) for a,b in v]
def col(i): return colormaps.cool(2*i)[:3]
p=sum([text(chr(i+160),L[i],fontsize=20,rgbcolor=col(i))
       for i in [0..99]])
p.show(figsize=(5,4),gridlines=True)

Surface Textures 2

xxxxxxxxxx
 
@interact
def _(a=[2,4,6,8],b=[4,8,12,16],
      cm=['cool','jet','bwr','hsv']):
    var('u,phi'); curve=(u^3,cos(a*u),u^2)
    def cf(u,phi): return sin(phi+b*u)^2
    p=revolution_plot3d(curve,(u,0,1),(phi,0,2*pi),
                        parallel_axis='z',plot_points=120,
                        color=(cf,colormaps[cm]))
    p.show(frame=False)

Moving Average

xxxxxxxxxx
 
import pandas,warnings
warnings.simplefilter('ignore')
fp='https://olgabelitskaya.github.io/c_bank.csv'
df=pandas.read_csv(fp)['silver'].values
silver=finance.TimeSeries(df)
silver_mav=stats.moving_average(silver,5)
silver=list(enumerate(silver))
silver_mav=list(enumerate(silver_mav))
t='The moving_average() usage for silver prices'
sp1=scatter_plot(
    silver,edgecolor='#3636ff',facecolor='none',markersize=5)
sp2=scatter_plot(
    silver_mav,edgecolor='#36ff36',facecolor='none',markersize=5)
(sp1+sp2).show(title=t,figsize=6,gridlines=True)

Vertex & Edge Labels

xxxxxxxxxx
 
import warnings; warnings.simplefilter('ignore')
@interact
def _(N=[2,3,4]):
    bd=digraphs.ButterflyGraph(N)
    nvl=[u+'$\\to$'+str(v) for u,v in bd.vertices()]
    bd.relabel(dict(zip(bd.vertices(),nvl)))
    [bd.set_edge_label(u,v,v) 
     for u,v,l in bd.edges()]
    bd.show(figsize=6,vertex_size=3,
            layout='circular',color_by_label=True)

HTML Zoom Effect

xxxxxxxxxx
 
%%html
<style>
@import 'https://fonts.googleapis.com/css?family=Monoton';
#svg0001 {background:silver; width:400px; height:300px;}
circle {fill:#3636ff; stroke-width:5; 
        stroke:#fff; transition:transform .8s;}
circle:hover {-ms-transform:scale(1.5); 
              -webkit-transform:scale(1.5); 
              transform:scale(1.5);}
</style>
<h3 style='color:#3636ff; font-family:Monoton; 
          font-size:250%; text-shadow:4px 4px 4px silver;'>
Zoom &nbsp; on &nbsp; Hover</h3>
<svg id='svg0001'><g transform='translate(200,150)'>
<circle cx='0' cy='0' r='70'></circle></g></svg>

DataFrame Aggregations

xxxxxxxxxx
 
print(r.eval("""
fp<-'https://olgabelitskaya.github.io/huge_cities.tsv'
hc<-data.frame(read.csv(fp,header=T,sep='\t'))
aggregate(hc['growth'],list(hc$country),mean)"""))

DataFrame Plotting

xxxxxxxxxx
 
import pandas,seaborn,pylab
pylab.style.use('ggplot')
user='https://raw.githubusercontent.com/OlgaBelitskaya/'
path1='machine_learning_engineer_nd009/'
path2='master/Machine_Learning_Engineer_ND_P3/'
data=pandas.read_csv(user+path1+path2+'customers.csv')
data.drop(['Region','Channel'],axis=1,inplace=True)
data.plot.area(stacked=False,figsize=(6.5,5)) 
pylab.title('Data Values by Product Categories')
pylab.grid(); pylab.show()

Conditional Functions

xxxxxxxxxx
 
@interact
def _(N=[1,2,3]):
    def rho(phi):
        if N==1: 
            return sqrt(2*cos(2*phi)) \
            if 2*cos(2*phi)>=0 else 0
        if N==2: 
            return 4*cos(2*phi-pi/4)^2
        if N==3: 
            return 6*cos(2*phi) \
            if 6*cos(2*phi)>=3 else 0
    var('phi')
    p=polar_plot(rho,(phi,0,2*pi),
                 fill=True,fillcolor='#3636ff')
    p.show(figsize=(5,5),gridlines=True)

Differentiation Rules

xxxxxxxxxx
 
var('x'); s=['-','--','-.',':']
c=[colormaps.cool(30*i)[:3] for i in [1..8]]
f=[sin(-x),cos(-x),tan(-x),exp(-x)]
df=[el.diff() for el in f]
p=plot(f+df,(x,-1,1),
       linestyle=s,thickness=3,color=c,
       gridlines=True,legend_label='automatic')
p.set_legend_options(
    back_color='silver',bbox_to_anchor=(1.,.75))
p.show(figsize=(6,5))

Interactive Kautz Digraphs

xxxxxxxxxx
 
@interact
def _(layout=['spring','circular'],n=[3,4,5]):
    dg=digraphs.Kautz(n,2)
    dg.show(vertex_color='silver',vertex_size=300,
            layout=layout,edge_style='-.',
            color_by_label=True,figsize=(5,5))

Surface Textures

xxxxxxxxxx
 
@interact
def _(axis=['x','y','z'],
      cm=['bwr','jet','cool','hsv']):
    var('u,phi'); curve=(1+u^2/8,1-u^3/128,u)
    def cf(u,phi): return cos(2*phi+u)^2
    p=revolution_plot3d(
        curve,(u,-4,8),(phi,0,2*pi),
        parallel_axis=axis,color=(cf,colormaps[cm]))
    p.show(frame=False)

TSV Reading

xxxxxxxxxx
 
print(r.eval("""
fp<-'https://olgabelitskaya.github.io/huge_cities.tsv'
hc<-data.frame(read.csv(fp,header=T,sep='\t'))
jpn_chn<-hc$country=='Japan'|hc$country=='China'
t(hc[which(jpn_chn),2:9])"""))

3D Spherical Elevation

xxxxxxxxxx
 
var('r,phi,theta')
SE=SphericalElevation('elevation',['radius','azimuth'])
sum([plot3d(pi/i,(r,0,1),(theta,0,2*pi),transformation=SE,
            frame=False,opacity=.1*i,
            color=colormaps.cool(35*(i-2))[:3])
     for i in [3..9]]).show()

3D Polygon Drawing

xxxxxxxxxx
 
@interact
def _(N=[20,40,60],CM=['hsv','prism','jet']):
    def f(i): return (ln(i)*cos(i),ln(i)*sin(i))
    def c(i,cmap): return colormaps[cmap](i/(1.*N))[:3]
    p=sum([polygon([f(i),(0,f(i)[1]),(f(i)[0],0)],
                   color=c(i,CM),alpha=.5).plot3d(z=-.1*i) 
           for i in [1..N]])
    p.show(frame=False)

Bernoulli RBM

xxxxxxxxxx
 
import numpy as np
from sklearn import datasets,model_selection,\
linear_model,pipeline,neural_network,metrics
digits=datasets.load_digits()
X,y=digits.data,digits.target
X_train,X_test,y_train,y_test=\
model_selection.train_test_split(
    X,y,test_size=.2,random_state=1)
X_train_scaled=\
(X_train-np.min(X_train,0))/(np.max(X_train,0)+.1^4)
X_test_scaled=\
(X_test-np.min(X_test,0))/(np.max(X_test,0)+.1^4)
logistic=linear_model.LogisticRegression(
    max_iter=50,solver='liblinear',multi_class='ovr')
logistic.C=2000.
brbm=neural_network.BernoulliRBM(
    random_state=0,verbose=False)
brbm.learning_rate,brbm.n_iter,brbm.n_components=.05,50,96
nn_clf=pipeline.Pipeline(steps=[('brbm',brbm),
                                ('logistic',logistic)])
nn_clf.fit(X_train_scaled,y_train)
print('Logistic regression using BRBM features:\n%s\n'%\
     (metrics.classification_report(
          y_test,nn_clf.predict(X_test_scaled))))

Interactive Exploration of Elliptic Curves

xxxxxxxxxx
 
@interact
def _(k1=[3,4,5],k2=[2..8]):
    v=EllipticCurve('%s%sa'%(k1,k2)).lseries(); n=120
    i=sqrt(-1)
    v=v.values_along_line(1-10*i,1+10*i,n)
    v=[(v[i][1].real(),v[i][1].imag()) for i in range(n)]
    col=[[random() for i in range(3)] for j in range(n)]
    l=sum([line([v[i],v[i+1]],color='silver',
                marker=r'$\Re \Im$',markersize=16,
                markerfacecolor='w',markeredgecolor=col[i])
           for i in range(n-1)])
    l.show(figsize=(6,5))

3D Graphics Objects

xxxxxxxxxx
 
@interact
def _(season=['winter','spring','summer','autumn']):
    var('x,y,z'); x0,y0,z0,s=.4,.15,.15,.1
    f=4*x^2+4*y^2-(z-1.3)^2; g=cos(49*x+16*y)*sin(50*z)
    hat=implicit_plot3d(f,(x,-1,1),(y,-1,1),(z,.3,1.3),\
        color=(g.function(x,y,z),colormaps[season]))
    head=sphere(size=5*s,color='pink')
    eyes=sum([sphere((x0,i*y0,z0),size=s,color=(1,1,1))+\
              sphere((x0+.06,i*y0,z0+.02),size=s/2,
                     color=(0,0,0)) for i in [-1,1]])
    nose=sphere((x0+.1,0,-z0+.05),size=s,color='pink')
    mouth=sphere((x0-.1,0,-2*z0),size=s,color='red')
    (hat+head+eyes+nose+mouth).show(frame=False)