[FIXED] Plotting data of unequal size or x-vector in an intensity plot

Issue

Suppose you have the following data:

x1_Length = 100
x1 = np.linspace(10,100,num=x1_Length)
y1 = np.linspace(0, 1.3, num=x1_Length)

x2_Length = 200
x2 = np.linspace(50, 200, num=x2_Length)
y2 = np.exp(np.linspace(0, 1, num=x2_Length))

If you wanted to plot this, it would be straightforward:

fig, ax = plt.subplots()
ax.plot(x1,y1, ".g")
ax.plot(x2,y2, "--r")

Which gives an expected result, EVEN THOUGH THE ARRAYS THAT WERE PLOTTED ARE OF DIFFERENT LENGTHS AND DO NOT SHARE THE x-data.

NOW, suppose you wanted to plot this same data in an intensity plot. This causes some problems:

1. it is my understanding that an intensity plot (for example imshow) plots 2D arrays and as such have no direct concept of an x-axis scale or y-axis scale. Data is presented based on its index in the array. Here, this would be a problem because the first elements of the two arrays DO NOT correspond to the same x-value.

2. all the rows/columns need to be of the same length in a 2D array. This is the minor of the two problems, as i could always figure out the longest dataset and pad all shorter ones with, for example, NaNs, like so:

dataset = [x1_data, x2_data]
max_Length = np.max([array[0,:].shape[0] for array in dataset ])
data_array = np.nan * np.ones((2*len(dataset), max_Length))
for i, spectrum_array2D in enumerate(dataset):
    length = spectrum_array2D[0,:].shape[0]
    firstRowOfInsertion = 2*i
    data_array[[firstRowOfInsertion, firstRowOfInsertion+1], :length] = spectrum_array2D

I don't see any technological limitation why one should not be able to plot several arrays of different data into an intensity plot much like plt.plot()can. Ideally, what I need is to tell the intensity plot that it can expect, in this example, 2 horizontal slices of data, and then supply the x-data (plotted againt the x-axis), the y-data (plotted against the colorbar) for each index of the slice into which this plot should go. Do you know of a way to achieve this, or any package capable of this?

EDIT: Ultimately, I want a plot that can look like this, which was adopted from @wtw suggestion below (the data in this plot is random, I need it to be my y1 and y2 arrays):

Solution

Following discussions, I think what is wanted is a line plotted with x points and colour values, possibly with a different y value each time.

A slight modification on the answer here (just to pass plotting variables through): Color line by third variable - Python

import matplotlib.cm as cm
import matplotlib.pyplot as plt
import numpy as np

def plot_colourline(x,y,c, **xargs):
    c = cm.viridis((c-np.min(c))/(np.max(c)-np.min(c)))
    ax = plt.gca()
    for i in np.arange(len(x)-1):
        ax.plot([x[i],x[i+1]], [y[i],y[i+1]], c=c[i], **xargs)
    return

# First data set
x1 = np.arange(0, 10, 1)
y1 = np.zeros(len(x1))  # use 0 as the y value for all points
c1 = np.random.uniform(size=len(x1))

# Second dataset, different number of points, x values and y value
x2 = np.arange(8, 12, 0.1)
y2 = np.ones(len(x2))  # Use 1 as the y value for all points
c2 = np.random.uniform(size=len(x2))

fig, ax = plt.subplots(1)
plot_colourline(x1, y1, c1, linewidth=5)
plot_colourline(x2, y2, c2, linewidth=5, alpha=0.5)

Answered By - wtw