Matplotlib Color Tables

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import matplotlib.pyplot as pl,matplotlib.colors as mcols

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def plot_colortable(colors,title,sort_colors=True,emptycols=0,dpi=72):

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    cell_width,cell_height=212,22

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    swatch_width=48

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    margin,topmargin=12,40

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    if sort_colors is True:

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        by_hsv=sorted(

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            (tuple(mcols.rgb_to_hsv(mcols.to_rgb(color))),name)

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            for name,color in colors.items())

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        names=[name for hsv,name in by_hsv]

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    else:

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        names=list(colors)

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    n=len(names)

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    ncols=4-emptycols; nrows=n//ncols+int(n%ncols>0)

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    width=cell_width*4+2*margin

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    height=cell_height*nrows+margin+topmargin

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    fig,ax=pl.subplots(figsize=(width/dpi,height/dpi),dpi=dpi)

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    fig.subplots_adjust(margin/width,margin/height,

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                        (width-margin)/width,

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                        (height-topmargin)/height)

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    ax.set_xlim(0,cell_width*4)

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    ax.set_ylim(cell_height*(nrows-.5),-cell_height/2.)

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    ax.yaxis.set_visible(False); ax.xaxis.set_visible(False)

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    ax.set_axis_off()

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    ax.set_title(title,fontsize=20,loc='left',pad=10)

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    for i,name in enumerate(names):

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        row=i%nrows; col=i//nrows

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        y=row*cell_height

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        swatch_start_x=cell_width*col

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        swatch_end_x=cell_width*col+swatch_width

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        text_pos_x=cell_width*col+swatch_width+7

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        ax.text(text_pos_x,y,name,fontsize=10,

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                horizontalalignment='left',

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                verticalalignment='center') 

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        ax.hlines(y,swatch_start_x,swatch_end_x,

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                  color=colors[name],linewidth=18)

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    return fig

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col_fig=plot_colortable(mcols.CSS4_COLORS,'CSS Colors')

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col_fig.savefig('css4_colors.png')

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pl.show()

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Plotly Classic Animations

TSSFL Open Discussion Forums

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import plotly.graph_objects as go,numpy as np,pandas as pd

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from plotly.offline import plot

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url='https://raw.githubusercontent.com/plotly/'+\

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    'datasets/master/gapminderDataFiveYear.csv'

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dataset=pd.read_csv(url)

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years=['1952','1962','1967','1972','1977','1982','1987',

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       '1992','1997','2002','2007']

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continents=[]

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for continent in dataset['continent']:

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    if continent not in continents: continents.append(continent)

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fig_dict={"data":[],"layout":{},"frames":[]}

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fig_dict["layout"]["xaxis"]={"range":[30,85],"title":"Life Expectancy"}

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fig_dict["layout"]["yaxis"]={"title":"GDP per Capita","type":"log"}

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fig_dict["layout"]["hovermode"]="closest"

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fig_dict["layout"]["updatemenus"]=[

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    {"buttons":[

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            {"args":[None,{"frame":{"duration":500,"redraw":False},

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                           "fromcurrent":True, 

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                           "transition":{"duration":300,

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                           "easing":"quadratic-in-out"}}],

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             "label":"Play","method":"animate"},

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            {"args":[[None],{"frame":{"duration":0,"redraw":False},

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                             "mode":"immediate",

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                             "transition":{"duration":0}}],

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             "label":"Pause","method":"animate"}],

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     "direction":"left","pad":{"r":10,"t":87},

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     "showactive":False,"type":"buttons",

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     "x":0.1,"xanchor":"right","y":0,"yanchor":"top"}]

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sliders_dict={"active":0,"yanchor":"top","xanchor":"left",

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              "currentvalue":{"font":{"size":20},"prefix":"Year:",

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                              "visible":True,"xanchor":"right"},

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    'transition':{'duration':300,'easing':'cubic-in-out'},

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    'pad':{'b':10,'t':50},'len':.9,'x':.1,'y':0,'steps':[]}

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year=1952

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for continent in continents:

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    dataset_by_year=dataset[dataset["year"]==year]

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    dataset_by_year_and_cont=dataset_by_year[

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        dataset_by_year["continent"]==continent]

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    data_dict={

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        "x":list(dataset_by_year_and_cont["lifeExp"]),

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        "y":list(dataset_by_year_and_cont["gdpPercap"]),

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        "mode":"markers",

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        "text":list(dataset_by_year_and_cont["country"]),

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        "marker":{"sizemode":"area","sizeref":200000,

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                  "size":list(dataset_by_year_and_cont["pop"])},

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        "name":continent}

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    fig_dict["data"].append(data_dict)

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for year in years:

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    frame={"data":[],"name":str(year)}

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    for continent in continents:

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        dataset_by_year=dataset[dataset["year"]==int(year)]

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        dataset_by_year_and_cont=dataset_by_year[

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            dataset_by_year["continent"]==continent]

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        data_dict={

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            "x":list(dataset_by_year_and_cont["lifeExp"]),

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            "y":list(dataset_by_year_and_cont["gdpPercap"]),

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            "mode":"markers",

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            "text":list(dataset_by_year_and_cont["country"]),

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            "marker":{"sizemode":"area","sizeref":200000,

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                      "size":list(dataset_by_year_and_cont["pop"])},

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            'name':continent}

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        frame['data'].append(data_dict) 

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    fig_dict['frames'].append(frame)

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    slider_step={'args':[[year],

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                        {'frame':{'duration':300,'redraw':False},

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                         'mode':'immediate',

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                         'transition':{'duration':300}}],

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                 'label': year,'method':'animate'}

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    sliders_dict['steps'].append(slider_step)

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fig_dict['layout']['sliders']=[sliders_dict]

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fig=go.Figure(fig_dict) ; plot(fig)

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fpath='https://sagecell.sagemath.org/kernel/'

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fpath+=os.getcwd()[14:]+'/files/'

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s1='<iframe src="'

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s2='temp-plot.html" width=600 height=400/></iframe>'

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html(s1+fpath+s2)

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Matplotlib-GIF-3D for Lorenz Systems

TSSFL Open Discussion Forums

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import numpy as np,os

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from scipy import integrate

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from matplotlib import pyplot as pl,animation as an

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from mpl_toolkits.mplot3d import Axes3D

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N_trajectories=20

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def lorentz_deriv(params,t0,sigma=10.,beta=8./3,rho=28.):

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    x,y,z=params

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    return [sigma*(y-x),x*(rho-z)-y,x*y-beta*z]

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np.random.seed(1)

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x0=-15+30*np.random.random((N_trajectories,3))

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t=np.linspace(0,4,1000)

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x_t=np.asarray([integrate.odeint(lorentz_deriv,x0i,t) for x0i in x0])

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fig=pl.figure()

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ax=fig.add_axes([0,0,1,1],projection='3d'); ax.axis('off')

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colors=pl.cm.jet(np.linspace(0,1,N_trajectories))

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lines=sum([ax.plot([],[],[],'-',c=c) for c in colors],[])

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pts=sum([ax.plot([],[],[],'o',c=c) for c in colors],[])

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ax.set_xlim((-25,25)); ax.set_ylim((-35,35)); ax.set_zlim((5,55))

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ax.view_init(30,0)

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def init():

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    for line,pt in zip(lines,pts):

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        line.set_data([],[]); line.set_3d_properties([])

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        pt.set_data([],[]); pt.set_3d_properties([])

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    return lines+pts

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def animate(i):

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    i=(2*i)%x_t.shape[1]

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    for line, pt, xi in zip(lines,pts,x_t):

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        x,y,z=xi[:i].T

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        line.set_data(x,y); line.set_3d_properties(z)

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        pt.set_data(x[-1:],y[-1:]); pt.set_3d_properties(z[-1:])

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    ax.view_init(30,.3*i)

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    fig.canvas.draw()

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    return lines+pts

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anim=an.FuncAnimation(

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    fig,animate,frames=500,interval=30,blit=True,save_count=1500)

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f=r'animation.gif'

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writergif=an.PillowWriter(fps=15)

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anim.save(f,writer=writergif)

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fpath='https://sagecell.sagemath.org/kernel/'

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fpath+=os.getcwd()[14:]+'/files/'

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s1='<figure><embed type="image/gif" src="'

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s2='animation.gif" width=600/></figure>'

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html(s1+fpath+s2)

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