how to fill region with color

plot_region

asked 2021-01-16 09:11:13 +0200

ortollj
1319 ●17 ●55 ●91

how to fill in gray only the region between the yellow curve the orange curve and the blue dashed line ?

var('x')
PtsL=[[0.13795, 0.37902], [0.33554, 0.92189], [0.84803, 0.2028], [0.80141, 0.37902]]
PtsNamesL=['xy01','xy12','xy02','xyCut']
ellipse0=1/2*sqrt(-x^2 + 1)*sqrt(-sqrt(2) + 2)
ellipse1=x*cos(1/9*pi)/sin(1/9*pi)
ellipse2=sqrt(-4/3*x^2 + 1)
plt=list_plot(PtsL,color='blue',size=30)
for i in range(len(PtsL)) :
    plt+=text(PtsNamesL[i],vector(PtsL[i])*1.05, color='blue')


plt+=line([[0,PtsL[3][1]],PtsL[3]],color='brown',thickness=2,linestyle='dashed')
plt+=line([[PtsL[1][0],0],PtsL[1]],color='blue',thickness=2,linestyle='dashed')
plt+=plot([ellipse0, ellipse1,ellipse2], 0,1, fill={0: [1]}, fillcolor='#ccc')
plt+=plot(ellipse0,color='orange')
plt+=plot(ellipse1,color='yellow')
plt+=plot(ellipse2,color='green')

show(plt,xmin=0,xmax=1,ymin=0,ymax=1)

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answered 2021-01-16 10:51:08 +0200

slelievre
17654 ●22 ●160 ●348 http://carva.org/samue...

updated 2021-01-16 13:52:13 +0200

For the shaded region, use the interval [x01, x12] instead of [0, 1].

Besides, use parametric plots for nicer ellipse arcs than when plotted as function graphs.

Indeed, plotting functions with vertical tangents typically goes wrong near those tangencies.

Here is some amended code.

var('x')
pts = [(0.13795, 0.37902), (0.33554, 0.92189), (0.84803, 0.2028), (0.80141, 0.37902)]
pt_names = ['xy01', 'xy12', 'xy02', 'xyCut']
A0, B0 = 1, (2 - sqrt(2))/4
A2, B2 = 3/4, 1
f0 = sqrt((1 - x^2/A0)*B0)
f1 = x*cot(pi/9)
f2 = sqrt((1 - x^2/A2)*B2)
plt = point2d(pts, color='blue', size=30)
pt_opt = {'color': 'blue', 'horizontal_alignment': 'left', 'vertical_alignment': 'bottom'}
plt += sum(text(name, vector(pt), **pt_opt) for name, pt in zip(pt_names, pts))
plt += line([[0, pts[3][1]], pts[3]], color='brown', thickness=2, linestyle='dashed')
plt += line([[pts[1][0], 0], pts[1]], color='blue', thickness=2, linestyle='dashed')
fill_opt = {'fillcolor': 'lightgrey', 'thickness': 0}
plt += plot([f0, f1], (pts[0][0], pts[1][0]), fill={0: [1]}, **fill_opt)
ell0 = (lambda t: sqrt(A0)*cos(t), lambda t: sqrt(B0)*sin(t))
plt += parametric_plot(ell0, (0, pi/2), color='orange')
plt += plot(f1, color='yellow')
ell2 = (lambda t: sqrt(A2)*cos(t), lambda t: sqrt(B2)*sin(t))
plt += parametric_plot(ell2, (0, pi/2), color='green')
plt.show(xmin=0, xmax=1, ymin=0, ymax=1, aspect_ratio=1, figsize=8)

Shaded region between ellipse and two lines

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thank you @slelievre

ortollj ( 2021-01-16 11:01:19 +0200 )edit

@slelievre But rather than:

A0=1;B0=(sqrt(-sqrt(2) + 2)/2)^2
ell0 = (lambda t: sqrt(A0)*cos(t), lambda t: sqrt(B0)*sin(t))
plt += parametric_plot(ell0, (0, pi/2), color='orange')
plt.show(xmin=0, xmax=1, ymin=0, ymax=1, aspect_ratio=1, figsize=8)

I prefer :

plt+=implicit_plot(ellipse0-y,(x,0,1),(y,0,1),color='orange')
plt.show(xmin=0, xmax=1, ymin=0, ymax=1, aspect_ratio=1, figsize=8)

what do you think ?

ortollj ( 2021-01-16 13:52:18 +0200 )edit

Implicit plots require sampling a whole region to spot the places where some function of x and y is zero, while parametric plots directly give points on a curve and join them.

So I tend to favour parametric plot for efficiency and precision.

Using implicit plot is sometimes convenient. If using it to plot an ellipse, I would take advantage of not having to express $y$ as a function of $x$, and use

implicit_plot(lambda x, y: x^2/A0 + y^2/B0 - 1, (0, 1), (0, 1), color='orange')

x, y = var('x, y')
implicit_plot(x^2/A0 + y^2/B0 - 1, (x, 0, 1), (y, 0, 1), color='orange')

to avoid many square root computations.

slelievre ( 2021-01-16 17:36:24 +0200 )edit

ok @slelievre

ortollj ( 2021-01-16 17:50:08 +0200 )edit

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answered 2021-01-16 16:48:18 +0200

ortollj
1319 ●17 ●55 ●91

updated 2021-01-16 16:51:00 +0200

therefore after the solutions and advices of @slelievre gave me (and above all much more elegant than my initial code, thank you again @slelievre), I prefer the following code (more concise !):

var('x,y')
PtsL = [[0.13795, 0.37902], [0.33554, 0.92189], [0.84803, 0.2028], [0.80141, 0.37902]]
PtsNamesL = ['xy01', 'xy12', 'xy02', 'xyCut']
ellipse0 = 1/2*sqrt(-x^2 + 1)*sqrt(-sqrt(2) + 2)
ellipse1 = x*cos(1/9*pi)/sin(1/9*pi)
ellipse2 = sqrt(-4/3*x^2 + 1)
plt = list_plot(PtsL, color='blue', size=30)
pt_opt = {'color': 'blue', 'horizontal_alignment': 'left', 'vertical_alignment': 'bottom'}
plt += sum(text(name, vector(pt), **pt_opt) for name, pt in zip(PtsNamesL, PtsL))
plt += line([[0, PtsL[3][1]], PtsL[3]], color='brown', thickness=2, linestyle='dashed')
plt += line([[PtsL[1][0], 0], PtsL[1]], color='blue', thickness=2, linestyle='dashed')
plt += plot([ellipse0, ellipse1], (PtsL[0][0], PtsL[1][0]), fill={0: [1]}, fillcolor='#ccc', fillalpha=.3)
plt+=implicit_plot(ellipse0-y,(x,0,1),(y,0,1),color='orange')
plt+=plot(ellipse1,color='yellow')
plt+=implicit_plot(ellipse2-y,(x,0,1),(y,0,1),color='green')
plt.show(xmin=0, xmax=1, ymin=0, ymax=1, aspect_ratio=1, figsize=8)

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The green and orange ellipses can be simply plotted with

plt += arc((0,0), sqrt(A0), sqrt(B0), sector=(0,pi/2), color="orange")
plt += arc((0,0), sqrt(A2), sqrt(B2), sector=(0,pi/2), color="green")

Juanjo ( 2021-01-16 17:11:08 +0200 )edit

Thank you @Juanjo

ortollj ( 2021-01-16 17:48:27 +0200 )edit

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