Add a label= to each of your plot() calls, and then call legend(loc=”upper left”). Consider this sample (tested with Python 3.8.0): import numpy as np import matplotlib.pyplot as plt x = np.linspace(0, 20, 1000) y1 = np.sin(x) y2 = np.cos(x) plt.plot(x, y1, “-b”, label=”sine”) plt.plot(x, y2, “-r”, label=”cosine”) plt.legend(loc=”upper left”) plt.ylim(-1.5, 2.0) plt.show() Slightly modified … Read more
The solution is borrowed from the comment by CrazyArm, found here: Matplotlib, legend with multiple different markers with one label. Apparently you can make a list of handles and assign only one label and it magically combines the two handles/artists. import matplotlib.patches as mpatches import matplotlib.pyplot as plt import numpy as np x = np.linspace(0,1,11) … Read more
You can use traceorder key for legend: Determines the order at which the legend items are displayed. If “normal”, the items are displayed top-to-bottom in the same order as the input data. If “reversed”, the items are displayed in the opposite order as “normal”. If “grouped”, the items are displayed in groups (when a trace … Read more
The problem is that when you plot dynamically, matplotlib determines the borders automatically to fit all your objects. When you save a file, things are not being done automatically, so you need to specify the size of your figure, and then the bounding box of your axes object. Here is how to correct your code: … Read more
I do not like storing the handle values, it becomes a mess when I have a lot of graphs in my figures. Therefore i found another solution. t = 0 : 0.01 : 2 * pi; s = sin(t); c = cos(t); m = -sin(t); hold on; plot(t, s, ‘r’, ‘HandleVisibility’,’off’); % Plotting and telling … Read more
You can specify linestyle=”None” as a keyword argument in the plot command: import matplotlib.pyplot as pyplot Fig, ax = pyplot.subplots() for i, (mark, color) in enumerate(zip( [‘s’, ‘o’, ‘D’, ‘v’], [‘r’, ‘g’, ‘b’, ‘purple’])): ax.plot(i+1, i+1, color=color, marker=mark, markerfacecolor=”None”, markeredgecolor=color, linestyle=”None”, label=`i`) ax.set_xlim(0,5) ax.set_ylim(0,5) ax.legend(numpoints=1) pyplot.show() Since you’re only plotting single points, you can’t see … Read more
There’s a section in the matplotlib documentation on that exact subject. Here’s code for your specific example: import itertools from matplotlib import pyplot colors = [‘b’, ‘r’, ‘g’, ‘c’] cc = itertools.cycle(colors) plot_lines = [] for p in parameters: d1 = algo1(p) d2 = algo2(p) d3 = algo3(p) pyplot.hold(True) c = next(cc) l1, = pyplot.plot(d1, … Read more