![]() ![]() Plt.imshow(zi, vmin=-0. # Set up a regular grid of interpolation points ![]() so the Max colour only appears in one of the images and does not correspond to my Z max value in each single image. I want that my Z max value to be always the same in colour in the interpolation colour. The problem is the scale changes all the time as the Z max value always corresponds to the highest colour. I am trying to build the same plot for several timeframes, lets say one for min 1 the other for min 2 and a third for min 3. Directly use tricontour or tricontourf which will perform a triangulation internally. Then plot the interpolated data with the usual contour. via LinearTriInterpolator or using external functionality e.g. ![]() This can be done with on-board means, e.g. I have the X, Y coordinates and the Z values. The two options are: Interpolate the data to a regular grid first. import numpy as np import pandas as pd from matplotlib.mlab import griddata from mpltoolkits.basemap import Basemap, interp import matplotlib as mpl import. Here is the sample data if you want to experiment: x1 = One other factor is the desired smoothness of the interpolator. The choice of a specific interpolation routine depends on the data: whether it is one-dimensional, is given on a structured grid, or is unstructured. What I get in the end is only the scatter with the lines on my screen and I want to put those lines into the scatter plot where I can see the points that do not have the line. There are several general facilities available in SciPy for interpolation and smoothing for data in 1, 2, and higher dimensions. I tried using plt.fill_between but it seems I can't use it with scatter or I don't know how to use it properly. ![]() Whereas plotly.express has two functions scatter and line, go.Scatter can be used both for plotting points (makers) or lines, depending on the value of mode. What I want to do is combine the following two plots: fig, ax = plt.subplots()Īx.scatter(x1, y1, color='blue', label='Series 1')Īx.scatter(x2, y2, color='green', label='Series 2')Ī second plot that uses the x1,x2,y1,y2 data but has been filtered to create a line between two points that have same y1=y2 and their x1 > x2. This plot shows that the points in this numerical array are an approximation to the actual function as they dont have the functions value at all possible. Scatter and line plots with go.Scatter If Plotly Express does not provide a good starting point, it is possible to use the more generic go.Scatter class from aphobjects. I am having difficulties plotting data when using a for loop. ![]()
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