When you mouseover an image shown with imshow, you can mouseover the image to inspect its RGB values. The bottom-right corner of the matplotlib window (sharing space with the toolbar), shows the image coordinates and RGB values of the pixel being pointed at:
x = 274.99 y = 235.584 [.241, .213, .203]
However, when I mouseover a quiver plot, it only shows the x and y coords of the pointer, but not the value of the 2D vector being pointed at. Is there a way to get the vector values to show up?
I would be fine with writing a custom mouse event handler, if I only knew how to set that bit of text in the matplotlib window.
Magic commands perform special functions in the IPython shell. Matplotlib Inline command is a magic command that makes the plots generated by matplotlib show into the IPython shell that we are running and not in a separate output window.
Basic text commandsAdd an annotation, with an optional arrow, at an arbitrary location of the Axes . Add a label to the Axes 's x-axis. Add a label to the Axes 's y-axis. Add a title to the Axes .
The only reason %matplotlib inline is used is to render any matplotlib diagrams even if the plt. show() function is not called. However, even if %matplotlib inline is not used, Jupyter will still display the Matplotlib diagram as an object, with something like matplotlib. lines.
Plotly has several advantages over matplotlib. One of the main advantages is that only a few lines of codes are necessary to create aesthetically pleasing, interactive plots. The interactivity also offers a number of advantages over static matplotlib plots: Saves time when initially exploring your dataset.
There were times when the information about the color value was not present by default. In fact I think the current version is based on some code that came up in Stackoverflow on some question about that feature.
I quickly found those two questions:
The idea would be to change the function that is called when the mouse hovers the axes. This function is stored in ax.format_coord
. So a possible solution is to write your custom function to return the desired output based on the input coordinates, e.g. something like
def format_coord(x, y):
try:
z = # get value depending on x,y, e.g. via interpolation on grid
# I can't fill this because the kind of data is unknown here
return "x: {}, y: {}, z: {}".format(x,y,z)
except:
return "x: {}, y: {}".format(x,y)
ax.format_coord = format_coord
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