One proviso: The syntax element at the heart of my Question is in the Python language; however, this element appears frequently in the Matplotlib library, which is the only context i have seen it. So whether it's a general Python syntax question or a library-specific one, i am not sure. What i do know is that i could not find anything on point--either in the Python Language Reference or in the Matplotlib docs.
Those who use and/or develop with the excellent Python plotting library, Matplotlib will recognize the syntax pattern below. (
from matplotlib import pyplot as MPL>>> l, = MPL.plot(s, t) # s & t are ordinary NumPy 1D arrays
What is the construction on the left-hand side of this expression? And,
what is the purpose for using it?
I am familiar with Python's assignment unpacking, e.g.,
>>> a, b = [100, 200]
I'm also aware that in Python one-item tuples are sometimes represented as t,
And either could be the answer to the first question above; if so then i don't yet understand the reason why only the first element of the value returned from the call to plot is needed here.
(note: "l" is a lower case "ell"; i am using this letter because ls is the letter most often used here, probably because it is bound to an object that begins with the same letter-see below).
Some additional context:
The call to plot returns a list of line2D instances:
>>> type(l)<class 'matplotlib.lines.Line2D'>
So l is an object of type line2D.
Once bound to the lines2D object, this "variable" is usually seen in Matplotlib code like so:
>>> l.set_color("orange")
This expression changes the color of the line that represents the data values inside the plot window (the "plot line")
Below is one more example; it shows a common scenario for this "variable-comma" construction, which is embedding small toolkit/graphics-backend-independent widgets in a Matplotlib plot window, e.g., to toggle on/off by checkbox, multiple data series appearing in the plot window.
In the code below, a simple Matplotlib plot and a simple widget comprised of two checkboxes one for each data series are created.
l0 and l1 are again bound to calls to plot; both appear a couple of liens later when their get_visible and set_visible methods are called within a custom function passed in when *on_click* is called.
from matplotlib.widgets import CheckButtonsax = plt.subplot(111)
l0, = ax.plot(s, t, visible=False, lw=2)
l1, = ax.plot(t, s1, lw=2)rax = plt.axes( [.05, .4, .1, .15] )
check = CheckButtons(rax, ('raw', 'transformed'), (False, True))def fnx(checkbox_label):if checkbox_label == 'raw': l0.set_visible(not l0.get_visible())elif checkbox_label == 'transformed': l1.set_visible(not l1.get_visible())check.on_clicked(fnx)plt.show()