Adding diagional line y=x with an offset

Question

I am trying to add the y=x line along with an offset from the y=x line a better way than the code I shared. For example, with Y=X, i want two additional diagonal lines +0.5 and -0.5 from the Y=X but the code I show is a bit harder to understand. Any help with this would be appreciated.

    x=np.linspace(0,5,101) 
    y=np.random.normal(x)    # add some noise

    plt.plot(x,y,'r.') # x vs y
    plt.plot(x,x,'k-') # identity line

    plt.plot(x+0.25,x-0.25,'b-') # identity line
    plt.plot(x-0.25,x+0.25,'b-') # identity line

    plt.xlim(0,5)
    plt.ylim(0,5)
    plt.show()

Make a function that computes `y=mx+b`. The offset would be equivalent to changing `b`. — pylang, Apr 10 '18 at 15:35
Yes, that can be done but is there something along the lines of this: https://stackoverflow.com/questions/25497402/adding-y-x-to-a-matplotlib-scatter-plot-if-i-havent-kept-track-of-all-the-data — Charanjit Pabla, Apr 10 '18 at 15:40
Is it possible to simply use ax.get_xlim() and ax.get_ylim() as done with the example shown in the link but adding an offset like I want. — Charanjit Pabla, Apr 10 '18 at 15:51
It is not clear why you would need the limits. See the updated post. — pylang, Apr 10 '18 at 15:59
If you are trying to automate the subplot dimensions, you can use `get_...lim`, but you will need to specify process for handling outliers. `np.random` can generate outliers that will skew your plots. — pylang, Apr 10 '18 at 16:34

pylang · Answer 1 · 2018-04-10T16:30:35.017

It seems you wish to implement a function that plots linear lines for a given offset.

import numpy as np
import matplotlib.pyplot as plt


np.random.seed(123)
%matplotlib inline

# Functions
def linear(x, m=1, b=0):
    """Return y values for a line."""
    return x*m + b


def plot_offsets(x, func=linear, thres=0.25, ax=None):
    """Plot lines seperated by the given offset."""
    if ax is None:
        ax = plt.gca()
    half = thres/2.
    ax.plot(x+half, func(x, b=-half), "b-")        # lower
    ax.plot(x-half, func(x, b=half), "b-")         # upper
    return ax


# Data
x_lin = np.linspace(0, 5, 101) 
y_data = np.random.normal(x_lin)                   # add some noise


# Plot
fig, ax = plt.subplots(figsize=(8, 6))
ax.plot(x_lin, y_data, "r.")                       # x vs y
ax.plot(x_lin, linear(x_lin), "k-")                # identity line
plot_offsets(x_lin, thres=0.5, ax=ax)
ax.set_xlim(0, 5)
ax.set_ylim(0, 5)
plt.show()

Two functions were added to your code to abstract plotting linear lines and linear "offsets" (given a threshold). Most of the remaining additions (np.random.seed, _, ax = plt.subplots) are included for reproducible code.

Output

Adding diagional line y=x with an offset

1 Answers1