class SinCos(object):
funcNames = ('sin', 'cos')
filePath = "sc.png"
def __init__(self):
self.X = np.linspace(0, 4 * np.pi, 200)
self.pt = Plotter(1, 2, width=700, height=500, useAgg=True)
self.pt.set_xlabel("X")
self.pt.use_grid()
self.pt.add_annotation(0, "First")
self.pt.add_annotation(199, "Last")
def __call__(self, frequency):
self.pt.set_title("Sin and Cosine: Frequency = {:.2f}x", frequency)
with self.pt as p:
for funcName in self.funcNames:
Y = getattr(np, funcName)(frequency * self.X)
p.set_ylabel("{}(X)".format(funcName))
p(self.X, Y)
with open(self.filePath, "wb") as fh:
self.pt.show(fh=fh)
# Construct a Plotter object for a 700x500 pixel (100 DPI) figure with
# two subplots.
pt = Plotter(1, 2, width=7.0, height=5.0)
# The plots, one in each subplot, will be of a sine and cosine with
# 200 points from 0 to 4*pi.
funcNames = ('sin', 'cos')
X = np.linspace(0, 4 * np.pi, 200)
pt.set_title("Sine and Cosine")
# Each subplot will have an x-axis label of "X" and a grid.
pt.set_xlabel("X")
pt.use_grid()
# Each plot will have an annotation labeled "Last" at its last
# point. Note that we can use negative indices referenced to the last
# element, just as with Python sequences.
pt.add_annotation(-1, "Last")
# Make a subplotting context and work with the two subplots via the
# subplot tool sp. It's actually just a reference to pt, but set up
# for subplotting, with a context for a new subplot each time it's
# called.
with pt as sp:
# Do each plot, sin and then cos.
for k, funcName in enumerate(funcNames):
if k == 0:
# The major ticks are at pi/2 intervals, but only for the
# top subplot to demonstrate that it can be different
pt.set_tickSpacing('x', np.pi / 2)
# Generate the 1-D Numpy array for this plot's y-axis.
Y = getattr(np, funcName)(X)
# The sin plot will have a dashed line instead of the default