Generating a heat map using 3D data in matplotlib

Question

I have a function returnValuesAtTime that returns three lists-x_vals,y_vals and swe_vals. All three lists are of the same length and each element in swe_vals corresponds to a x-value from x_vals and a y-value from y_vals. I wish to generate a heatmap with a legend that uses the (x,y) coordinates and the swe_vals as the intensity.

I wrote the following code:

def plotValuesAtTimeMap(t):
    x_vals,y_vals,swe_vals=returnValuesAtTime(t)
    x_points=len(x_vals)
    y_points=len(y_vals)
    xx=np.linspace(x_vals[0],x_vals[-1],x_points)
    yy=np.linspace(y_vals[0],y_vals[-1],y_points)
    fig,ax=plt.subplots()
    im=ax.pcolormesh(xx,yy,z)
    fig.colorbar(im)
    ax.axis('tight')
    plt.show()

Once the three lists are obtained using returnValuesAtTime(t), I take the lengths of x_vals and y_vals. I then use these to generate the spacing for x and y-directions, with the limits being the first and last elements of x_vals and y_vals. I then try to generate the colormesh. But this gives me an empty colormesh with no values.

What might be going wrong? Will using a 3D numpy array instead of the three lists solve the problem?

The first 10 elements of each of the lists are:

x_vals[0:10]

[439936.86573189893,
 439936.86573189893,
 439936.86573189893,
 439936.86573189893,
 439936.86573189893,
 439936.86573189893,
 439936.86573189893,
 439936.86573189893,
 439936.86573189893,
 439936.86573189893]

y_vals[0:10]

[4514018.2797159087,
 4513898.2797159087,
 4513778.2797159087,
 4513658.2797159087,
 4513538.2797159087,
 4513418.2797159087,
 4513298.2797159087,
 4513178.2797159087,
 4513058.2797159087,
 4512938.2797159087]

swe_vals[0:10]

[2.7520323,
 2.7456229,
 2.7456021,
 2.745455,
 2.7478349,
 2.7445269,
 2.7484877,
 2.7524617,
 2.75491,
 2.7509627]

Edit:

I have added a scatter plot showing the (x,y) grid range below:

The x and y values are in lists, each 6804 in length. Each (x,y) point has a corresponding z-value in a separate list, which is also 6804 in length. To clarify what I hope to achieve, I want to generate a heatmap like plot with the magnitude of z-axis represented by the color of each grid on the plot. Something like what's shown below:

In the example plot, all z-values are the same. So the color is same across the entire grid space.

Edited with new resultant plot (based on member CT Zhu's suggestions):

Answer 1

It looks like if reshape x, y, z to square matrix, you can do a contourf plot:

In [7]:X
Out[7]:
array([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])

In [8]:Y
Out[8]:
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [2, 2, 2, 2, 2, 2, 2, 2, 2, 2],
       [3, 3, 3, 3, 3, 3, 3, 3, 3, 3],
       [4, 4, 4, 4, 4, 4, 4, 4, 4, 4],
       [5, 5, 5, 5, 5, 5, 5, 5, 5, 5],
       [6, 6, 6, 6, 6, 6, 6, 6, 6, 6],
       [7, 7, 7, 7, 7, 7, 7, 7, 7, 7],
       [8, 8, 8, 8, 8, 8, 8, 8, 8, 8],
       [9, 9, 9, 9, 9, 9, 9, 9, 9, 9]])

plt.contourf(X,Y,np.random.random((10,10))) #reshape Z too!
plt.colorbar()