def main10():
amp = 16385
Tao = 10E-6
Ts = 1E-8
m1 = 297
m2 = 0.297 #0.0515
noi = 0
t, s = Signal(Ts, Tao, amp=amp)
snoise = noise(s, noi)
spz = poleZero(snoise, Tao, Ts)
rn, sn = trapez(spz, m1, m2)
max_ = PHA(sn)
print np.floor(sn[0:100])
print max_
import biggles
p = biggles.FramedPlot()
p.add(biggles.Curve(np.arange(sn.shape[0])[20:70], sn[20:70],
color='blue'))
p.add(biggles.Slope(0, color='green'))
p.show()
def test_example2(self):
p = biggles.FramedPlot()
p.xrange = 0, 100
p.yrange = 0, 100
p.aspect_ratio = 1
x = numpy.arange(0, 100, 5)
yA = numpy.random.normal(40, 10, size=len(x))
yB = x + numpy.random.normal(0, 5, size=len(x))
a = biggles.Points(x, yA, type="circle")
a.label = "a points"
b = biggles.Points(x, yB)
b.label = "b points"
b.style(type="filled circle")
l = biggles.Slope(1, type="dotted")
l.label = "slope"
k = biggles.PlotKey(.1, .9)
k += a
k += b, l
p.add(l, a, b, k)
_write_example(2, p)
def add_curves(ax,
x,
y,
lp,
i,
set_points=True,
lock_levels=True,
intervals=True,
slopes=True,
insets=True):
if set_points and lp.haskey('lock_x'):
ax.add(biggles.LineX(lp['lock_x'][i] * scale))
if lock_levels and lp.haskey('lock_y'):
ax.add(biggles.LineY(lp['lock_y'][i] * scale))
if intervals and lp.haskey('left_x'):
ax.add(biggles.LineX(lp['left_x'][i] * scale, type='dashed'))
if intervals and lp.haskey('right_x'):
ax.add(biggles.LineX(lp['right_x'][i] * scale, type='dashed'))
if slopes:
for d in ['up', 'dn']:
if not lp.haskey('lock_%s_sl' % d): continue
m, x0, y0 = [
lp['lock_%s' % (e)][i]
for e in ['%s_sl' % d, '%s_x' % d, 'y']
]
ax.add(biggles.Slope(m, (x0 * scale, y0 * scale), type='dashed'))
def draw(t, in_, out):
import biggles
p = biggles.FramedPlot()
p.add(biggles.Curve(t, out, color='blue'))
p.add(biggles.Curve(t, in_, color='red'))
p.add(biggles.Slope(0, color='green'))
p.show()
def test_labels(self):
import numpy
from numpy import linspace
key = biggles.PlotKey(0.1, 0.9, halign='left')
plt = biggles.FramedPlot(key=key, aspect_ratio=1)
err = 0.1
x = numpy.arange(10)
y = numpy.arange(10)**2
err = numpy.zeros(x.size) + 2
ydata = y + numpy.random.normal(size=x.size) * err
color = 'red'
pts = biggles.Points(x,
ydata,
color=color,
type='filled diamond',
label='data')
errpts = biggles.SymmetricErrorBarsY(x,
ydata,
err,
color=color,
label='data')
model = biggles.Curve(x, y, label='model')
plt += biggles.Polygon([0, 8, 4], [0, 0, 30],
color='grey20',
label='triangle')
plt += [model, pts, errpts]
plt += biggles.Point(4,
4,
type='filled circle',
color='cyan',
label='other')
# Go from light blue to intense red.
np = 30
xp = linspace(0.5, 4, np)
yp = 20 + 5 * xp.copy()
minColor = [0.6, 0.9, 1.0]
maxColor = [1.0, 0.2, 0.2]
colors = numpy.zeros((np, 3))
colors[:, 0] = numpy.interp(xp, xp,
linspace(minColor[0], maxColor[0], np))
colors[:, 1] = numpy.interp(xp, xp,
linspace(minColor[1], maxColor[1], np))
colors[:, 2] = numpy.interp(xp, xp,
linspace(minColor[2], maxColor[2], np))
plt += biggles.ColoredPoints(
xp,
yp,
colors,
type='cross',
size=1,
label='grad',
)
plt += biggles.LineX(5, color='green', label='lineY')
plt += biggles.LineY(5, color='magenta', type='dashed', label='lineX')
plt += biggles.Slope(-3, (0, 40), color='Hot Pink', label='slope')
plt += biggles.DataBox([5.5, 70], [6.5, 80],
color='Dodger Blue',
label='box')
# label doesn't work, nor does ellipses. fundamental perhaps
#plt += Circle(6.0, 75.0, 1, color='yellow', label='circle')
# not even sure how DataArc works
#plt += DataArc(6.0, 75.0, 1, color='yellow', label='circle')
_write_example('labels', plt)
import biggles import numpy import numpy.random p = biggles.FramedPlot() p.xrange = 0, 100 p.yrange = 0, 100 p.aspect_ratio = 1 x = numpy.arange( 0, 100, 5 ) yA = numpy.random.normal( 40, 10, (len(x),) ) yB = x + numpy.random.normal( 0, 5, (len(x),) ) a = biggles.Points( x, yA, type="circle" ) a.label = "a points" b = biggles.Points( x, yB ) b.label = "b points" b.style( type="filled circle" ) l = biggles.Slope( 1, type="dotted" ) l.label = "slope" k = biggles.PlotKey( .1, .9, [a,b,l] ) p.add( l, a, b, k ) #p.write_img( 400, 400, "example2.png" ) #p.write_eps( "example2.eps" ) p.show()
def plot(
x,
y,
y_rc,
lock_points,
plot_file,
shape=(4, 2),
img_size=None,
scale=1. / 1000,
title=None,
xlabel=None,
ylabel=None,
titles=None,
rows=None,
cols=None,
insets=None,
lock_levels=True,
set_points=False,
intervals=False,
slopes=False,
scale_style='tight',
label_style='row_col',
format=None,
):
nr, nc = y_rc
cl, rl, rcl = False, False, False
if label_style == 'col_only':
cl = True
elif label_style == 'row_col':
rcl = True
if slopes == True:
def get(key, param):
return lock_points.get('lock_%s%s' % (key, param), None)
slopes = []
for d in ['', 'up_', 'dn_']:
m, x0, y0 = [get(d, p) for p in ['slope', 'x', 'y']]
if m is not None:
if y0 is None:
# Use default y-target if separate up/dn aren't there.
y0 = get('', 'y')
slopes.append(zip(m, x0, y0))
pl = util.plotGridder(y_rc,
plot_file,
title=title,
xlabel=xlabel,
ylabel=ylabel,
target_shape=shape,
img_size=img_size,
col_labels=cl,
rowcol_labels=rcl,
format=format)
for r, c, ax in pl:
if r >= nr or c >= nc: continue
i = c + r * nc
if set_points:
ax.add(biggles.LineX(lock_points['lock_x'][i] * scale))
if lock_levels:
ax.add(biggles.LineY(lock_points['lock_y'][i] * scale))
if intervals:
ax.add(
biggles.LineX(lock_points['left_x'][i] * scale, type='dashed'))
ax.add(
biggles.LineX(lock_points['right_x'][i] * scale,
type='dashed'))
if slopes != False:
for s in slopes:
m, x0, y0 = s[i]
ax.add(
biggles.Slope(m, (x0 * scale, y0 * scale), type='dashed'))
if insets is not None:
ax.add(
biggles.PlotLabel(0.,
0.,
insets[i],
halign='left',
valign='bottom'))
if x.shape == y.shape:
ax.add(biggles.Curve(x[i] / 1000., y[i] / 1000.))
else:
ax.add(biggles.Curve(x / 1000., y[i] / 1000.))
if scale_style == 'roll-off':
# Prevent small signals from causing large tick labels
hi, lo = amax(y[i]) / 1000, amin(y[i]) / 1000
if hi - lo < 4:
mid = (hi + lo) / 2
ax.yrange = (mid - 2, mid + 2)
elif scale_style == 'tight':
hi, lo = amax(y[i]) / 1000., amin(y[i]) / 1000.
dx = (hi - lo) * .1
if dx <= 0: # Never set a 0-size yrange.
dx = 0.5
ax.yrange = lo - dx, hi + dx
if x.shape == y.shape:
ax.xrange = x[i][0] / 1000., x[i][-1] / 1000.
else:
ax.xrange = x[0] / 1000., x[-1] / 1000.
pl.cleanup()
return {
'plot_files': pl.plot_files,
}