def plot3(w):
# For the final graph we wish to override the default tick
# intervals, so do not use w.plenv
w.pladv(0)
# Use standard viewport, and define X range from 0 to 360
# degrees, Y range from -1.2 to 1.2.
w.plvsta()
w.plwind(0.0, 360.0, -1.2, 1.2)
# Draw a box with ticks spaced 60 degrees apart in X, and 0.2 in Y.
w.plcol0(1)
w.plbox("bcnst", 60.0, 2, "bcnstv", 0.2, 2)
# Superimpose a dashed line grid, with 1.5 mm marks and spaces.
w.plstyl([1500], [1500])
w.plcol0(2)
w.plbox("g", 30.0, 0, "g", 0.2, 0)
w.plstyl([], [])
w.plcol0(3)
w.pllab("Angle (degrees)", "sine", "#frPLplot Example 1 - Sine function")
x = 3.6 * arange(101)
y = sin((pi / 180.) * x)
w.plcol0(4)
w.plline(x, y)
w.plflush()
def plotHistogram(self):
def plfbox(x0, y0):
x = numpy.array([x0, x0, x0 + 1.0, x0 + 1.0])
y = numpy.array([0.0, y0, y0, 0.0])
plplot.plfill(x, y)
plplot.plcol0(1)
plplot.pllsty(1)
plplot.plline(x, y)
self.plot.clearWidget();
y0 = numpy.array([5, 15, 12, 24, 28, 30, 20, 8, 12, 3])
pos = numpy.array([0.0, 0.25, 0.5, 0.75, 1.0])
red = numpy.array([0.0, 0.25, 0.5, 1.0, 1.0])
green = numpy.array([1.0, 0.5, 0.5, 0.5, 1.0])
blue = numpy.array([1.0, 1.0, 0.5, 0.25, 0.0])
plplot.pladv(0)
plplot.plvsta()
plplot.plcol0(2)
plplot.plwind(1980.0, 1990.0, 0.0, 35.0)
plplot.plbox("bc", 1.0, 0, "bcnv", 10.0, 0)
plplot.plcol0(2)
plplot.pllab("Year", "Widget Sales (millions)", "#frPLplot Example 12")
plplot.plscmap1l(1,pos,red,green,blue)
for i in range(10):
plplot.plcol1(i/9.0)
plplot.plpsty(0)
plfbox((1980. + i), y0[i])
string = "%.0f" % (y0[i])
plplot.plptex((1980. + i + .5), (y0[i] + 1.), 1.0, 0.0, .5, string)
string = "%d" % (1980 + i)
plplot.plmtex("b", 1.0, ((i + 1) * .1 - .05), 0.5, string)
self.update()
def main(w):
nsteps = 1000
# If db is used the plot is much more smooth. However, because of the
# async X behaviour, one does not have a real-time scripcharter.
# w.plsetopt("db", "")
# w.plsetopt("np", "")
# User sets up plot completely except for window and data
# Eventually settings in place when strip chart is created will be
# remembered so that multiple strip charts can be used simultaneously.
#
# Specify some reasonable defaults for ymin and ymax
# The plot will grow automatically if needed (but not shrink)
ymin = -0.1
ymax = 0.1
# Specify initial tmin and tmax -- this determines length of window.
# Also specify maximum jump in t
# This can accomodate adaptive timesteps
tmin = 0.
tmax = 10.
tjump = 0.3 # percentage of plot to jump
# Axes options same as w.plbox.
# Only automatic tick generation and label placement allowed
# Eventually I ll make this fancier
colbox = 1
collab = 3
styline = [2, 3, 4, 5]
colline = [2, 3, 4, 5]
legline = ["sum", "sin", "sin*noi", "sin+noi"]
xlab = 0.
ylab = 0.25 # legend position
autoy = 1 # autoscale y
acc = 1 # don t scrip, accumulate
w.pladv(0)
w.plvsta()
# Register our error variables with PLplot
# From here on, we're handling all errors here
#w.plsError(&pl_errcode, errmsg)
id1 = w.plstripc("bcnst", "bcnstv", tmin, tmax, tjump, ymin, ymax, xlab,
ylab, autoy, acc, colbox, collab, colline, styline,
legline, "t", "", "Strip chart demo")
# Let plplot handle errors from here on
#w.plsError(NULL, NULL)
autoy = 0 # autoscale y
acc = 1 # accumulate
# This is to represent a loop over time
# Let's try a random walk process
y1 = y2 = y3 = y4 = 0.0
dt = 0.1
for n in range(nsteps):
sleep(0.01)
t = n * dt
noise = w.plrandd() - 0.5
y1 = y1 + noise
y2 = sin(t * pi / 18.)
y3 = y2 * noise
y4 = y2 + noise / 3.
# There is no need for all pens to have the same number of
# points or beeing equally time spaced.
if n % 2:
w.plstripa(id1, 0, t, y1)
if n % 3:
w.plstripa(id1, 1, t, y2)
if n % 4:
w.plstripa(id1, 2, t, y3)
if n % 5:
w.plstripa(id1, 3, t, y4)
# Destroy strip chart and it's memory
w.plstripd(id1)
