Matplotlib: Extended Line Over 2 Control Points

In matplotlib we can draw lines using at least 2 methods: plt.plot plt.plot([1,2],[1,2],color='k',marker='o') Line2D method line = lines.Line2D([0.3,0.6],[0.9,0.3],linestyle='das

Solution 1:

After good lunch I was able to find a way using numpy.

def drawLine2P(x,y,xlims):
    xrange = np.arange(xlims[0],xlims[1],0.1)
    A = np.vstack([x, np.ones(len(x))]).T
    k, b = np.linalg.lstsq(A, y)[0]
    plt.plot(xrange, k*xrange + b, 'k')

Solution 2:

Little late on this, but I just came across this while googling. I was also sick of not being able to do this in matplotlib, so I wrote abline_plot. It includes callbacks to update a 2D line if the axes limits are changed.

Search for the abline_plot examples in the link below.

http://statsmodels.sourceforge.net/devel/examples/generated/example_interactions.html

Documentation:

http://statsmodels.sourceforge.net/devel/generated/statsmodels.graphics.regressionplots.abline_plot.html#statsmodels.graphics.regressionplots.abline_plot

Implementation:

https://github.com/statsmodels/statsmodels/blob/master/statsmodels/graphics/regressionplots.py#L572

Edit: A simpler one that doesn't update

import matplotlib.pyplot as plt
from matplotlib import lines as mpl_lines

defslope_from_points(point1, point2):
    return (point2[1] - point1[1])/(point2[0] - point1[0])

defplot_secant(point1, point2, ax):
    # plot the secant
    slope = slope_from_points(point1, point2)
    intercept = point1[1] - slope*point1[0] 
    # update the points to be on the axes limits
    x = ax.get_xlim()
    y = ax.get_ylim()
    data_y = [x[0]*slope+intercept, x[1]*slope+intercept]
    line = mpl_lines.Line2D(x, data_y, color='red')
    ax.add_line(line)
    return ax.figure()

Solution 3:

Hope this helps

import matplotlib.pyplot as plt
# I am generating 2 random points, u might want to update these
x1,y1,x2,y2 = np.random.uniform(-1,1,4)
# make use of line equation to form function line_eqn(x) that generated y
line_eqn = lambda x : ((y2-y1)/(x2-x1)) * (x - x1) + y1        
# generate range of x values based on your graph
xrange = np.arange(-1.2,1.2,0.2)
# plot the line with generate x ranges and created y ranges
plt.plot(xrange, [ line_eqn(x) for x in xrange], color='k', linestyle='-', linewidth=2)

Solution 4:

Way late, but here's the easiest answer for anyone who stumbles upon this like I did,

As of matplotlib 3.3, you can do this with plt.axline((x1, y1), (x2, y2)).