Matplotlib, adding text with more than one line. Adding text that can follow the curve

Question

I have added text to a plot, coded in each line, and then adjusted it look decent, increase or decrease the width, or change the placement. However, is there a way to have

Answer 1

You can use line separators \n:

 pylab.text(1, 1.5, '$r_1 = 1.0$ AU\n' +\
                    '$r_2 = 1.524$ AU\n' +\
                    '$\\Delta \\nu = 75^{\\circ}$', fontsize = 11, color = 'r')

pylab.text() uses data coordinates by default, but you can use relative positions (0,0) to the lower-left and (1,1) to the upper-right, passing the parameter transform. See this example:

pylab.text(0.6, 0.75, 'using axis coords', transform=ax.transAxes)

The parameters: verticalalignment and horizontalalignment can also help you tremendously. Suppose you want to place a texts at the very corners:

pylab.text(1.,1.,'top-right', transform=ax.transAxes,
           horizontalalignment='right', verticalalignment='top')

pylab.text(0.,0.,'bottom-left', transform=ax.transAxes,
           horizontalalignment='left', verticalalignment='bottom')

To automatically calculate an angle to the text depending on your data you can do the following approach:

• detect the data closest point
• find the a sequence near the closest point and fit a curve using this sequence (the example below uses a fourth order curve)
• calculate the derivative at the point where you want the text placed
• correct the direvative with ax.get_data_ratio() OBS: not needed if ax.axis('scaled') is used, for example

This algorithm can be implemented as follows:

def rtext(line,x,y,s, **kwargs):
    from scipy.optimize import curve_fit
    xdata,ydata = line.get_data()
    dist = np.sqrt((x-xdata)**2 + (y-ydata)**2)
    dmin = dist.min()
    TOL_to_avoid_rotation = 0.3
    if dmin > TOL_to_avoid_rotation:
        r = 0.
    else:
        index = dist.argmin()
        xs = xdata[ [index-2,index-1,index,index+1,index+2] ]
        ys = ydata[ [index-2,index-1,index,index+1,index+2] ]
        def f(x,a0,a1,a2,a3):
            return a0 + a1*x + a2*x**2 + a3*x**3
        popt, pcov = curve_fit(f, xs, ys, p0=(1,1,1,1))
        a0,a1,a2,a3 = popt
        ax = pylab.gca()
        derivative = (a1 + 2*a2*x + 3*a3*x**2)
        derivative /= ax.get_data_ratio()
        r = np.arctan( derivative )
    return pylab.text(x, y, s, rotation=np.rad2deg(r), **kwargs)

The following test example shows how to use it:

ax = pylab.subplot(111)
thetas = np.linspace(0,6*np.pi,1000)
i = np.arange(len(thetas))
xdata = (1. + (3.-1.)*i/len(thetas))*np.cos(thetas)
ydata = (1. + (3.-1.)*i/len(thetas))*np.sin(thetas)
ax.plot(xdata, ydata, color = 'b')
pylab.xlabel('x')
pylab.ylabel('y')
for x, y in zip(xdata,ydata)[::25]:
    rtext(ax.lines[0], x, y,
          '$\\alpha = \\alpha_0$', fontsize = 14, color = 'r',
          horizontalalignment='center', verticalalignment='center')

Changing verticalalignment='bottom'