I am displaying a jpg image (I rotate this by 90 degrees, if this is relevant) and of course the axes display the pixel coordinates. I would like to convert the axis so that instead of displaying the pixel number, it will display my unit of choice - be it radians, degrees, or in my case an astronomical coordinate. I know the conversion from pixel to (eg) degree. Here is a snippet of what my code looks like currently:
import matplotlib.pyplot as plt import Image import matplotlib thumb = Image.open(self.image) thumb = thumb.rotate(90) dpi = plt.rcParams['figure.dpi'] figsize = thumb.size/dpi, thumb.size/dpi fig = plt.figure(figsize=figsize) plt.imshow(thumb, origin='lower',aspect='equal') plt.show()
...so following on from this, can I take each value that matplotlib would print on the axis, and change/replace it with a string to output instead? I would want to do this for a specific coordinate format - eg, rather than an angle of 10.44 (degrees), I would like it to read 10 26' 24'' (ie, degrees, arcmins, arcsecs)
Finally on this theme, I'd want control over the tick frequency, on the plot. Matplotlib might print the axis value every 50 pixels, but I'd really want it every (for example) degree.
It sounds like I would like to define some kind of array with the pixel values and their converted values (degrees etc) that I want to be displayed, having control over the sampling frequency over the range xmin/xmax range.
Are there any matplotlib experts on Stack Overflow? If so, thanks very much in advance for your help! To make this a more learning experience, I'd really appreciate being prodded in the direction of tutorials etc on this kind of matplotlib problem. I've found myself getting very confused with axes, axis, figures, artists etc!
It looks like you're dealing with the
matplotlib.pyplot interface, which means that you'll be able to bypass most of the dealing with artists, axes, and the like. You can control the values and labels of the tick marks by using the
matplotlib.pyplot.xticks command, as follows:
tick_locs = [list of locations where you want your tick marks placed] tick_lbls = [list of corresponding labels for each of the tick marks] plt.xticks(tick_locs, tick_lbls)
For your particular example, you'll have to compute what the tick marks are relative to the units (i.e. pixels) of your original plot (since you're using
imshow) - you said you know how to do this, though.
I haven't dealt with images much, but you may be able to use a different plotting method (e.g.
pcolor) that allows you to supply
y information. That may give you a few more options for specifying the units of your image.
For tutorials, you would do well to look through the matplotlib gallery - find something you like, and read the code that produced it. One of the guys in our office recently bought a book on Python visualization - that may be worthwhile looking at.
The way that I generally think of all the various pieces is as follows:
Figureis a container for all the
Axesis the space where what you draw (i.e. your plot) actually shows up
Axisis the actual
pyplotmodule in production plots.