def dothatplot(whatphi):
p = biggles.FramedArray(2, 1)
x, y = makeplot(phi=whatphi, show="chi")
x = list(x)
y = list(y)
x.append(0.)
y.append(240.4)
p[0, 0].add(biggles.Points(x, y, symboltype="filled circle"))
p[0, 0].add(biggles.LineY(240.4))
p[0, 0].add(biggles.LineY(240.4 + 1.))
x, y = makeplot(phi=whatphi, show="area")
x = list(x)
y = list(y)
x.append(0.)
y.append(324.13)
p[1, 0].add(biggles.Points(x, y, symboltype="filled circle"))
# p[1,0].add(biggles.LineY(324.13))
# p[1,0].add(biggles.LineY(324.13*0.99))
p.xrange = 0., 3.
p.ylabel = r"Area (MeV nb) $\chi^2$"
p.xlabel = r"$y_{ggg} / y_{qq} = sqrt(f B_{ggg} / B_{qq}$)"
p[0, 0].yrange = 230., 330.
p[1, 0].yrange = 310., 339.999
p.title = r"Fit results with $\phi_g$ = " + str(whatphi) + r"$\degree$"
p.write_eps("interference_nowwithphi_" + str(whatphi) + ".eps")
p.show()
def addtogroupsplot(p, csfunc, offset, color, kind):
combinemap = {}
combinemap[0] = []
combinemap[1] = []
combinemap[2] = []
combinemap[3] = []
combinemap[4] = []
combinemap[5] = []
combinemap[6] = []
combinemap[7] = []
combinemap[8] = []
combinemap[9] = []
for r in testsample:
combinemap[0].append(csfunc(r))
combinemap[groupify(r)].append(csfunc(r))
groups = range(1, 10)
hadgroup = [0] * 9
hadgroup_err = [0] * 9
for g in groups:
hadgroup[g - 1], hadgroup_err[g - 1] = jt.wmean(combinemap[g])
center_of_groups = jt.wmean(combinemap[0])[0]
tmp = biggles.Points(Numeric.array(groups) + offset,
Numeric.array(hadgroup) / center_of_groups,
type=kind,
color=color)
p.add(tmp)
p.add(
biggles.SymmetricErrorBarsY(Numeric.array(groups) + offset,
Numeric.array(hadgroup) / center_of_groups,
Numeric.array(hadgroup_err) /
center_of_groups,
color=color))
p.add(biggles.LineY(1., type="longdashed"))
return tmp
def plotInfo(info):
"""
biggles FramedArray with only information labels
"""
stat = biggles.FramedPlot()
#stat.title = 'grouping info'
## turn off drawing of all axis related objects
## note: if all is turned off plotting doesnt work, so make one white
stat.x.draw_ticks = 0
stat.y.draw_ticks = 0
stat.x.draw_ticklabels = 0
stat.y.draw_ticklabels = 0
stat.y.draw_spine = 0
stat.x.spine_style['color'] = 'white'
## have to make it a plot - add a white line
stat.add(biggles.LineY(0.01, type='dot', color='white'))
## add info lines one by one (from bottom and up!)
info = string.split(info, '\n')
for l in range(len(info)):
yPos = 0.95 - 0.04 * l
stat.add( biggles.PlotLabel( .05, yPos, info[l], halign='left', \
size=1, face='courier' ) )
return stat
def plotKey(data, name, key):
## plot the cluster rmsd dist.
plot = biggles.FramedPlot()
plot.add(biggles.PlotLabel(0.5, 0.90, name, size=4))
## customize plot appearence
#plot.x1.label = 'cluster'
plot.y2.label = 'size'
plot.y1.label = key
plot.x2.draw_ticks = 0
plot.y2.draw_ticks = 0
## Plot
plot.add(
biggles.ErrorBarsY(clst_range, data[key][1], data[key][2], width=1))
plot.add(biggles.Points(clst_range, data[key][0], type='cross', size=1))
plot.add(biggles.LineY(0.25, type='dot'))
## add label with info about 'good' solutions
good = []
for clst in clst_range:
if data[key][0][clst - 1] > 0.25:
good += [clst]
plot.add(biggles.PlotLabel(0.5, 0.80, str(good), size=1))
return plot
def plotLines(nr, style='dot', col='black', ref=None):
"""
Greate a plot grid
-> list of biggles objects
"""
l = []
for i in range(1, nr + 1):
l += [biggles.LineY(i, type=style, color=col)]
l += [biggles.LineX(i, type=style, color=col)]
if ref:
l += [biggles.LineY(ref[0], color='grey')]
l += [biggles.LineX(ref[1], color='grey')]
return l
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 plot_voltages(fs, vecs):
import biggles
all_values = np.concatenate( vecs )
hi = all_values.max()
lo = all_values.min()
plot = biggles.Table(len(vecs), 1)
plot.cellpadding = 0
plot.cellspacing = 0
for i,vec in enumerate(vecs):
p = biggles.Plot()
p.add( biggles.Curve(wv.t(fs, vec), vec) )
p.yrange = (lo, hi)
plot[i,0] = p
p.add( biggles.LineX(0) )
p.add( biggles.Label(0, (hi+lo)/2, "%.2f mV" % (hi-lo), halign='left') )
p.add( biggles.LineY(lo) )
p.add( biggles.Label((len(vec)/fs/2), lo, "%.1f ms" % (1000*len(vec)/fs), valign='bottom') )
return plot
def use_cross_section(csfunc, filename):
hads = []
hads_err = []
for r in testsample:
c, e = csfunc(r)
hads.append(c)
hads_err.append(e)
hads_center = jt.wmean(zip(hads, hads_err))[0]
p = biggles.FramedPlot()
p.add(
biggles.Points(range(len(testsample)),
Numeric.array(hads) / hads_center,
type="filled circle"))
p.add(
biggles.SymmetricErrorBarsY(range(len(testsample)),
Numeric.array(hads) / hads_center,
Numeric.array(hads_err) / hads_center))
p.x1.draw_ticklabels = 0
p.x1.label = "Runs by index"
p.y1.label = "Normalized hadronic cross-section"
p.add(biggles.LineY(1.))
p.add(biggles.LineX(41.5, type="dashed"))
l, r = 0.8, 1.2
p.yrange = l, r + 0.001
p.add(biggles.DataLabel(41.5 - 10, l + 0.15 * (r - l), "db16"))
p.add(biggles.DataLabel(41.5 + 10, l + 0.15 * (r - l), "db17"))
p.aspect_ratio = 8.5 / 11.
p.show()
p.write_eps(filename)
def plot(complex_lst):
## plot the cluster rmsd dist.
plot = biggles.FramedPlot()
inset = biggles.FramedPlot()
## plot title
plot.title = '/'.join(string.split(absfile(options['o']), '/')[-5:-1])
## customize plot appearence
plot.x1.label = 'cluster'
plot.y2.label = 'size'
plot.y1.label = 'rmsd'
plot.x2.draw_ticks = 0
plot.y2.draw_ticks = 0
inset.frame.draw_ticks = 0
inset.x1.draw_ticklabels = 0
inset.y1.draw_ticklabels = 0
inset.y2.draw_ticklabels = 1
inset.y2.draw_ticks = 1
inset.y2.ticks_style['color'] = 'red'
## get cluter and rmsd lists
clst_list = []
rms_list = []
for compl in complex_lst:
clst_list += [compl.info['hex_clst']]
rms_list += [compl.info['rms']]
## get average, max, min and size of cluster
data = []
clst_range = range(1, max(clst_list) + 1)
for clst in clst_range:
rms = compress(equal(clst_list, clst), rms_list)
data += [[average(rms), max(rms), min(rms), len(rms)]]
data = transpose(data)
## Inset
inset.add(biggles.Curve(clst_range, data[3], color='red'))
## Plot
plot.add(biggles.ErrorBarsY(clst_range, data[1], data[2]))
plot.add(biggles.Points(clst_range, data[0], type='cross', size=1))
plot.add(biggles.Inset((0.0, 0.0), (1.0, 1.0), inset))
plot.add(biggles.LineY(10, type='dot'))
## add label with info about 'good' solutions (average rmsd < 10A)
good = []
for clst in clst_range:
if data[0][clst - 1] < 10:
good += [clst]
plot.add(biggles.PlotLabel(0.5, 0.98, 'Solutions with rmsd < 10A', size=1))
plot.add(biggles.PlotLabel(0.5, 0.95, str(good), size=1))
## plot and save
plot.show()
plot.write_eps(string.split(options['o'], '.')[0] + '.eps')
def plotthree(h,
title,
filename=None,
ghigh=0.966 * nbha["high"],
ghoff=nbha["hoff"],
glow=0.966 * nbha["low"],
gloff=nbha["loff"]):
# hups = h["high"] - h["hoff"]*ptoc_high
# lups = h["low"] - h["loff"]*ptoc_low
# frac = hups/lups * 1.*ngam["low"]/ngam["high"]
# hups = h["high"]/float(ngam["high"]) - h["hoff"]/float(ngam["hoff"])
# lups = h["low"]/float(ngam["low"]) - h["loff"]/float(ngam["loff"])
# frac = hups/lups
hups = h["high"] / float(ghigh) - h["hoff"] / float(ghoff)
lups = h["low"] / float(glow) - h["loff"] / float(gloff)
frac = hups / lups
wm = jt.wmean(zip(frac.values, frac.errors))[0]
sigmas = []
for i in range(frac.bins):
if frac.errors[i] > 0.:
sigmas.append((frac.values[i] - wm) / frac.errors[i])
else:
sigmas.append(0.)
p = biggles.FramedArray(3, 1)
addtoplot(p[0, 0], hups)
p[0, 0].yrange = 0., max(hups.values) * 1.1
addtoplot(p[1, 0], frac)
p[1, 0].add(biggles.LineY(wm))
p[1, 0].yrange = 0.701, 1.299
p[2, 0].add(biggles.Points(frac.bin_centers(), sigmas))
p[2, 0].add(biggles.LineY(0.))
p[2, 0].yrange = -4., 4.
p.xlabel = title
p.show()
if filename != None: p.write_eps(filename)
def test_example5():
x = numpy.arange(0, 3 * numpy.pi, numpy.pi / 10)
y = numpy.sin(x)
a = biggles.FramedArray(2, 2, title='title')
a.aspect_ratio = 0.75
a.xlabel = "x label"
a.ylabel = "y label"
a.uniform_limits = 1
a.cellspacing = 1.
a += biggles.LineY(0, type='dot')
a += [biggles.LineY(-1, type='dashed'), biggles.LineY(1, type='dashed')]
a[0, 0].add(biggles.Curve(x, .25 * y))
a[0, 1].add(biggles.Curve(x, .50 * y))
a[1, 0].add(biggles.Curve(x, .75 * y))
a[1, 1].add(biggles.Curve(x, y))
_write_example(5, a)
def test_example11(self):
p = biggles.FramedPlot()
p.title = "title"
p.xlabel = r"$x$"
p.ylabel = r"$\Theta$"
p.ylog = 1
p.xlog = 1
p.add(biggles.LineX(0.5))
p.add(biggles.LineY(0.5))
_write_example(11, p)
def plotfrac(histhigh, histlow, histhoff, histloff, p):
global numbha_high, numbha_low, numbha_hoff, numbha_loff
histhigh.rootn()
histlow.rootn()
histhoff.rootn()
histloff.rootn()
upshigh = histhigh / float(numbha_high) - histhoff / float(numbha_hoff)
upslow = histlow / float(numbha_low) - histloff / float(numbha_loff)
frac = upshigh / upslow
x, y, dy = frac.bin_centers(), frac.values, frac.errors
ave = jt.wmean(zip(y, dy))[0]
print ave
p.add(biggles.Points(x, y, symboltype="filled circle", symbolsize=0.8))
p.add(biggles.SymmetricErrorBarsY(x, y, dy))
p.add(biggles.LineY(ave))
return p
def plotsig(histhigh, histlow, histhoff, histloff, p):
global numbha_high, numbha_low, numbha_hoff, numbha_loff
histhigh.rootn()
histlow.rootn()
histhoff.rootn()
histloff.rootn()
upshigh = histhigh / float(numbha_high) - histhoff / float(numbha_hoff)
upslow = histlow / float(numbha_low) - histloff / float(numbha_loff)
frac = upshigh / upslow
x, y, dy = frac.bin_centers(), frac.values, frac.errors
ave = jt.wmean(zip(y, dy))[0]
sig = [-1000.] * len(y)
for i in range(len(y)):
try:
sig[i] = (y[i] - ave) / dy[i]
except ZeroDivisionError:
sig[i] = -1000.
p.add(biggles.Points(x, sig, symboltype="filled circle", symbolsize=0.8))
p.add(biggles.LineY(0))
p.yrange = -5, 5
return p
#!/usr/bin/env python import sys sys.path.insert(1, '..') import biggles import math, numpy x = numpy.arange(0, 3 * math.pi, math.pi / 10) y = numpy.sin(x) a = biggles.FramedArray(2, 2, title='title') a.aspect_ratio = 0.75 a.xlabel = "x label" a.ylabel = "y label" a.uniform_limits = 1 a.cellspacing = 1. a.add(biggles.LineY(0, type='dot')) a[0, 0].add(biggles.Curve(x, .25 * y)) a[0, 1].add(biggles.Curve(x, .50 * y)) a[1, 0].add(biggles.Curve(x, .75 * y)) a[1, 1].add(biggles.Curve(x, y)) #a.write_img( 400, 400, "example5.png" ) #a.write_eps( "example5.eps" ) a.show()
yerr2 = []
for i, n in enumerate(names):
if n == "CLEO-III '05":
x.append(i)
y.append(gwhich[n][0])
yerr1.append(gwhich[n][1])
yerr2.append(sqrt(gwhich[n][1]**2 + gwhich[n][2]**2))
return x, y, yerr1, yerr2
p = biggles.Table(1, 3)
p[0, 0] = biggles.FramedPlot()
p[0, 0].add(biggles.LineX(1.216, linetype="longdashed", linecolor="black"))
p[0, 0].add(biggles.LineX(1.216 + 0.027, linetype="dotted", linecolor="black"))
p[0, 0].add(biggles.LineX(1.216 - 0.027, linetype="dotted", linecolor="black"))
p[0, 0].add(biggles.LineY(0.5))
p[0, 0].add(
biggles.PlotLabel(0.1,
0.95,
r"$\Upsilon(1S)$",
texthalign="left",
textvalign="top",
fontsize=5.))
x, y, yerr1, yerr2 = fillemup(g1)
p[0, 0].add(biggles.Points(y, x, symboltype="filled circle", symbolsize=1.5))
p[0, 0].add(biggles.SymmetricErrorBarsX(y, x, yerr1))
p[0, 0].add(biggles.SymmetricErrorBarsX(y, x, yerr2))
x, y, yerr1, yerr2 = fillemup_mine(g1)
p[0, 0].add(
biggles.Points(y,
x,
#!/usr/bin/env python
import biggles
p = biggles.FramedPlot()
p.title = "title"
p.xlabel = r"$x$"
p.ylabel = r"$\Theta$"
p.ylog = 1
p.xlog = 1
p.add(biggles.LineX(0.5))
p.add(biggles.LineY(0.5))
p.write("example11.png", dpi=55)
p.write("example11.eps")
p.write("example11.pdf")
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,
}
def plot(yvecarr,
xvecarr=None,
color="black",
title="",
xsize=600,
ysize=300,
xrange=None,
yrange=None,
psfile=None):
"""
Use biggles to plot the spectrum in the 'yvecarr' array. 'yvecarr' may be
a 1-dimensional or a 2-dimensional array containing a single spectrum
or a set of spectra, respectively
"""
# Set the plotting screen to the demanded size
biggles.configure('screen', 'width', xsize)
biggles.configure('screen', 'height', ysize)
# Prepare the frame object and give it a title
frame = biggles.FramedPlot()
frame.aspect_ratio = 0.5
frame.title = title
# Make sure yvecarr is defined and make sense of it
if yvecarr is None:
return
else:
try:
nyvec, nypixels = numpy.shape(yvecarr)
except ValueError:
# Apparently, yvecarr is a one-dimensional array
nyvec = 1
nypixels = len(yvecarr)
yvecarr = numpy.array([yvecarr])
# If no xvecarr is defined, fill the x-axis array with increasing
# integers
if xvecarr is None:
xvecarr = numpy.zeros((nyvec, nypixels), dtype=numpy.float64)
nxpixels = nypixels
for i in range(nyvec):
xvecarr[i, :] = numpy.arange(nypixels)
else:
# If not, it is either a 1- or 2-dimensional array (similar to yvecarr)
try:
nxvec, nxpixels = numpy.shape(xvecarr)
except ValueError:
nxvec = 1
nxpixels = len(xvecarr)
xvecarr = numpy.array([xvecarr])
# Make sure that x and y arrays have identical length.
if (nxpixels != nypixels):
print 'Unequal length of x- and y-data'
return
# Set the plotting x-range if this was specified
if xrange:
frame.xrange = xrange
else:
frame.xrange = (xvecarr.min(), xvecarr.max())
# And similar for the y-range
if yrange:
frame.yrange = yrange
# else :
# frame.yrange = (yvecarr.min(), yvecarr.max())
# Now, start the loop over the spectra (or spectrum)
for i in range(nyvec):
# Select the x- and y-vectors
try:
xvec = xvecarr[i]
except IndexError:
xvec = range(0, len(yvec))
yvec = yvecarr[i]
# And plot these in the 'frame' object
frame.add(biggles.Curve(xvec, yvec, color=color))
# Also add a line indicating the zero-level
frame.add(biggles.LineY(0, color='blue'))
# And display this plot on screen
frame.show()
# Save to encapsulated postscript
# CURRENTLY NOT IMPLEMENTED. FOR LARGE PLOTS THIS MAY RESULT IN HEAVY DISK I/O
if psfile is not None:
frame.write_img(xsize, ysize, psfile)
# Return the object to the caller, in case it would like to do more with it...
return frame
#!/usr/bin/env python
import biggles
import math
import numpy
x = numpy.arange(0, 3 * math.pi, math.pi / 10)
y = numpy.sin(x)
a = biggles.FramedArray(2, 2, title='title')
a.aspect_ratio = 0.75
a.xlabel = "x label"
a.ylabel = "y label"
a.uniform_limits = 1
a.cellspacing = 1.
a += biggles.LineY(0, type='dot')
a += [biggles.LineY(-1, type='dashed'), biggles.LineY(1, type='dashed')]
a[0, 0].add(biggles.Curve(x, .25 * y))
a[0, 1].add(biggles.Curve(x, .50 * y))
a[1, 0].add(biggles.Curve(x, .75 * y))
a[1, 1].add(biggles.Curve(x, y))
a.write("example5.png", dpi=55)
a.write("example5.eps")
a.write("example5.pdf")
a.show()
float(n4)))
block5.append(float(b5) / float(n5))
block5err.append(
math.sqrt((float(b5) / float(n5)) * (1. - float(b5) / float(n5)) /
float(n5)))
block6.append(float(b6) / float(n6))
block6err.append(
math.sqrt((float(b6) / float(n6)) * (1. - float(b6) / float(n6)) /
float(n6)))
p1 = biggles.FramedArray(2, 1)
p1[0,
0].add(biggles.Points(rnum, eff, symboltype="filled circle",
symbolsize=0.2))
p1[0, 0].add(biggles.SymmetricErrorBarsY(rnum, eff, efferr))
p1[0, 0].add(biggles.LineY(1., linetype="dotted"))
p1[0, 0].yrange = (0.987, 1.005)
p1[0, 0].xrange = (min(rnum) - 100, max(rnum) + 100)
p1[1,
0].add(biggles.Points(rnum, eff, symboltype="filled circle",
symbolsize=0.2))
p1[1, 0].add(biggles.SymmetricErrorBarsY(rnum, eff, efferr))
p1[1, 0].add(biggles.LineY(1., linetype="dotted"))
p1[1, 0].yrange = (0.8, 1.1)
p1[1, 0].xrange = (min(rnum) - 100, max(rnum) + 100)
p1.xlabel = "Run number"
p1.ylabel = "BarrelBhabha trigger efficiency"
p1[1, 0].add(biggles.PlotLabel(0.25, 0.25, "same outliers as last time"))
p1.show()
p1.write_eps("plottrig3_p1.eps")
print map(lambda (r, e): r, filter(lambda (r, e): e < 0.99, zip(rnum, eff)))
def makep1(p1x, p1y, p1z, run):
return sqrt(p1x**2 + p1y**2 + p1z**2) / runsummary[run].energy
print "zero", time.asctime(time.localtime(time.time()))
histhigh_p1peak.ntuple(high, makep1, hadron_peak_noconv)
print "one", time.asctime(time.localtime(time.time()))
histhoff_p1peak.ntuple(hoff, makep1, hadron_peak_noconv)
print "two", time.asctime(time.localtime(time.time()))
plotdiff(
histhigh_p1peak, histlow_p1peak, histhoff_p1peak, histloff_p1peak,
"Biggest track momentum (/ebeam) with charged energy > 0.98 ECOM and tracks > 4"
)
savefig("rootstab6_plotbb_p1peak_noconv.eps")
import biggles
h = (histhigh_p1peak / float(numbha_high) -
histhoff_p1peak / float(numbha_hoff))
x, y, dy = h.bin_centers(), h.values, h.errors
p = biggles.FramedPlot()
p.add(biggles.Points(x, y, symboltype="filled circle", symbolsize=0.8))
p.add(biggles.SymmetricErrorBarsY(x, y, dy))
p.add(biggles.LineY(0))
p.add(biggles.LineX(0.8, linetype="dashed"))
p.x1.label = "p1 with charged energy > 0.98 ECOM and tracks > 4"
p.aspect_ratio = 1
p.y1.range = -3e-5, 7e-5
p.show()
p.write_eps("rootstab6_plotbb_p1peak_noconv.eps")
and not (75-2 < i < 82+2 and 58-2 < j < 62+2):
num += allnumer[i,j]
den += alldenom[i,j]
thetanumer[i] += num
thetadenom[i] += den
# thetanumer = Numeric.sum(Numeric.transpose(allnumer))
# thetadenom = Numeric.sum(Numeric.transpose(alldenom))
p = (hist.h1(100, 0., 1., vals=thetanumer)/hist.h1(100, 0., 1., vals=thetadenom)).plot(False, points=True, errorbars=True)
p.add(biggles.LineX(0.05, linetype="longdashed"))
p.add(biggles.LineX(0.19, linetype="longdashed"))
p.add(biggles.LineX(0.36, linetype="longdashed"))
p.add(biggles.LineX(0.52, linetype="longdashed"))
p.add(biggles.LineX(0.64, linetype="longdashed"))
p.add(biggles.LineX(0.75, linetype="longdashed"))
p.add(biggles.LineX(0.81, linetype="longdashed"))
p.add(biggles.LineY(1., linetype="solid"))
p.xrange = (0.0, 0.9)
p.yrange = (0.98, 1.002)
p.xlabel = r"|cos$\theta$| of tracks with tile divisions"
p.ylabel = r"$\epsilon$ with blocks A, B, C, removed"
p.show()
p.write_eps("plottrig2_4.eps")
# gamgams grow more slowly than bhabhas
# q = hist.h1(100, 0., 1., vals=thetadenom).plot()
# x = Numeric.arange(0., 0.99, 0.01)
# y = Numeric.arange(0., 0.99, 0.01)
# for i in range(len(y)):
# y[i] = (1. + math.pow(x[i], 2)) / math.sqrt(1. - math.pow(x[i], 2)) * \
# hist.h1(100, 0., 1., vals=thetadenom).int()
# q.add(biggles.Curve(x,y))
sigshist.underflow))) + r" runs total",
angle=90,
halign="left"))
sigsplot.show()
sigsplot.write_eps("plottrig_3.eps")
newplot = biggles.FramedArray(5, 1)
num = hist.h1(100, 0, 1)
den = hist.h1(100, 0, 1)
num.vals = 0. + Numeric.array(run[121928].numer)
den.vals = 0. + Numeric.array(run[121928].denom)
newplot[0, 0].add((num / den).points(True,
symboltype="filled circle",
symbolsize=1))
newplot[0, 0].add((num / den).errorbars(True))
newplot[0, 0].add(biggles.LineY(1, linetype="dotted"))
newplot[0, 0].add(biggles.LineX(0.45, linetype="longdashed"))
newplot[0, 0].add(biggles.LineX(0.70, linetype="longdashed"))
newplot[0, 0].add(biggles.PlotLabel(0.1, 0.85, "121928"))
newplot[0, 0].add(biggles.PlotLabel(0.675, 0.2, "accepted region"))
num = hist.h1(100, 0, 1)
den = hist.h1(100, 0, 1)
num.vals = 0. + Numeric.array(run[121929].numer)
den.vals = 0. + Numeric.array(run[121929].denom)
newplot[1, 0].add((num / den).points(True,
symboltype="filled circle",
symbolsize=1))
newplot[1, 0].add((num / den).errorbars(True))
newplot[1, 0].add(biggles.LineY(1, linetype="dotted"))
newplot[1, 0].add(biggles.LineX(0.45, linetype="longdashed"))
newplot[1, 0].add(biggles.LineX(0.70, linetype="longdashed"))
pull[0, 0], u1data["mar13"], mymar13,
lambda w: u1func(myarea, myrfeb, myback, myfullgam, myyint, myphi,
mybtautau, mytauyint, mytauphi, mytwophofrac, w))
adddata_pull(
pull[0, 0], u1data["apr08"], myapr08,
lambda w: u1func(myarea, myrapr2, myback, myfullgam, myyint, myphi,
mybtautau, mytauyint, mytauphi, mytwophofrac, w))
adddata_pull(
pull[0, 0], u1data["apr09"], myapr09,
lambda w: u1func(myarea, myrapr2, myback, myfullgam, myyint, myphi,
mybtautau, mytauyint, mytauphi, mytwophofrac, w))
adddata_pull(
pull[0, 0], u1data["apr10"], myapr10,
lambda w: u1func(myarea, myrapr2, myback, myfullgam, myyint, myphi,
mybtautau, mytauyint, mytauphi, mytwophofrac, w))
pull[0, 0].add(biggles.LineY(0.))
pull[0, 0].x.range = 9.42, 9.51
pull[0, 0].x.ticks = [9.42, 9.45, 9.48, 9.51]
pull[0, 0].x.draw_ticklabels = 0
pull[0, 0].x.subticks = Numeric.arange(9.42, 9.51 + 0.01, 0.01)
pull[0, 0].y.range = -4., 4.
pull[0, 0].y.ticks = [-3., 0., 3.]
pull[0, 0].y.subticks = [-4., -3., -2., -1., 0., 1., 2., 3., 4.]
pull[0, 0].y2.draw_ticklabels = 0
myarea, myrmsbeam, myback, mymay29, myjun11, myjun12, myjul10, myjul24, myaug07, myfullgam, myyint, myphi, mybtautau, mytauyint, mytauphi, mytwophofrac, myu1area = fitrecord[
2].values
thefunc = lambda w: u2func(myarea, myrmsbeam, myback, myfullgam, myyint, myphi,
mybtautau, mytauyint, mytauphi, mytwophofrac,
myu1area, w)
thefunc_bkgnd = lambda w: u2func_bkgndonly(
p_reference = []
p_histogram = []
p_popLines = []
spectrum = colorSpectrum(len(e_key), 'FF0000', '00FF00')
for i in range(len(e_key)):
## plot data points
p_energy += [ biggles.Points( l_fnc, e_val[i], color=spectrum[i],\
size=1, type='filled circle') ]
## frame label
p_label += [biggles.PlotLabel(.50, .90, e_key[i], size=6)]
## average energy line
p_average += [biggles.LineY(average(e_val[i]), type='shortdashed')]
## reference complex energy line
p_reference += [biggles.LineY(bind_ref[str(e_key[i])])]
## histogram inset
inset = biggles.FramedPlot()
inset.frame.draw_spine = 0
inset.x2.draw_ticks = 0
inset.x1.draw_ticks = 0
inset.x1.draw_ticklabels = 0
inset.y1.draw_ticklabels = 0
inset.y1.draw_subticks = 0
inset.y2.draw_ticks = 0
dens = Biskit.hist.density(e_val[i], 25)
inset.add(
import biggles, Numeric
x = [9.460 - 0.020, 9.460, 10.023 - 0.020, 10.023, 10.355 - 0.020, 10.355]
y = [0.9990, 0.9921, 1.0002, 0.9969, 0.9983, 0.9928]
dy = [0.0025, 0.0020, 0.0017, 0.0037, 0.0029, 0.0023]
p = biggles.Table(2, 1)
p[0, 0] = biggles.FramedPlot()
p[0, 0].add(biggles.Points(x, y, symboltype="filled circle"))
p[0, 0].add(biggles.SymmetricErrorBarsY(x, y, dy))
p[0, 0].add(biggles.LineY(1.))
p[0, 0].x1.range = 9.3, 10.5
p[0, 0].y1.range = 0.985, 1.0035
p[0, 0].x1.label = "Center of mass energy (GeV)"
p[0, 0].y1.label = "BB lumi / GG lumi"
p[1, 0] = biggles.FramedPlot()
p[1,0].add(biggles.Curve([9.3, 9.4, 9.4, 9.5, 9.5, 10, 10, 10.1, 10.1, 10.3, 10.3, 10.4, 10.4, 10.5],\
Numeric.array([0, 0, 350.3*0.025/8.993, 350.3*0.025/8.993, 0, 0, 142.32*0.020/7.945, 142.32*0.020/7.945, 0, 0, 96.14*0.024/7.361, 96.14*0.024/7.361, 0, 0])*18/350.3))
p[1, 0].x1.range = 9.3, 10.5
p[1, 0].x1.label = "Center of mass energy (GeV)"
p[1, 0].y1.label = r"Size of $\Upsilon \to e^+e^-$ correction"
p[1, 0].y1.range = 0., 0.06
p.show()
p.write_eps("lumiratio.eps")
]
y = y / sqrt(2.)
ye1 = ye1 / sqrt(2.)
ye2 = ye2 / sqrt(2.)
tell_me_about_it(9460.3)
y = y / (9460.3 / 2.) * 1.e6
ye1 = ye1 / (9460.3 / 2.) * 1.e6
ye2 = ye2 / (9460.3 / 2.) * 1.e6
p[0, 0] = biggles.FramedPlot()
p[0, 0].add(biggles.Points(x, y, symboltype="filled circle", symbolsize=1.5))
p[0, 0].add(biggles.ErrorBarsY(x, y - ye1, y + ye2))
p[0, 0].add(
biggles.LineY(3.78739 / sqrt(2.) / (9460.3 / 2.) * 1.e6,
linetype="dashed"))
p[0, 0].x.ticks = x
p[0, 0].x.ticklabels = names
p[0, 0].x2.draw_ticklabels = 0
p[0, 0].x.draw_subticks = 0
p[0, 0].aspect_ratio = 0.3
p[0, 0].yrange = 400., 700.
p[0, 0].y1.label = r"$\Upsilon(1S)$ $\sigma_E/E$ $\times$ 10$^{6}$ in MeV"
p[0, 0].show()
x = range(6)
y = Numeric.array([
4.28629322679, 4.01314654533, 4.25415201809, 3.91987316377, 3.7696777093,
4.23821651803
])
ye1 = Numeric.array([
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)
def __init__(self,
matrix,
mesh=0,
palette="plasma",
legend=0,
step=1,
vmin=None,
vmax=None):
"""
@param matrix: the 2-D array to plot
@type matrix: array
@param mesh: create a plot with a dotted mesh
@type mesh: 1|0
@param palette: color palette name see L{Biskit.ColorSpectrum}
@type palette: str
@param legend: create a legend (scale) showing the walues of the
different colors in the plot.
@type legend: 1|0
@param step: reduce matrix -- take only each step position in x and y
@type step: int
@param vmin: override minimal value, all values below will revert
to default color
@return: biggles plot object, view with biggles.FramedPlot.show() or
save with biggles.FramedPlot.write_eps(file_name).
@rtype: biggles.FramedPlot
"""
if not biggles:
raise ImportError, 'biggles module could not be imported.'
FramedPlot.__init__(self)
if step != 1:
matrix = self.__thinarray(matrix, step)
if vmin is None:
vmin = N0.amin(matrix)
if vmax is None:
vmax = N0.amax(matrix)
self.palette = ColorSpectrum(palette, vmin=vmin, vmax=vmax)
self.matrix = self.palette.color_array(matrix, resetLimits=0)
s = N0.shape(self.matrix)
for i in range(s[0]):
for j in range(s[1]):
col = self.matrix[i, j]
x1 = (j, j + 1)
y1 = (i, i)
y2 = (i + 1, i + 1)
cell = biggles.FillBetween(x1, y1, x1, y2, color=col)
self.add(cell)
if mesh:
for i in range(s[0] + 1):
self.add(biggles.LineY(i, linetype='dotted'))
for i in range(s[1] + 1):
self.add(biggles.LineX(i, linetype='dotted'))
if legend:
legend = self.__make_legend()
self.add(legend)
self.add(biggles.PlotBox((-0.17, -0.1), (1.25, 1.1)))
self.aspect_ratio = 1.0
