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,
symboltype="filled circle",
symbolsize=1.5,
color="red"))
p[0, 0].add(biggles.SymmetricErrorBarsX(y, x, yerr1, color="red"))
p[0, 0].add(biggles.SymmetricErrorBarsX(y, x, yerr2, color="red"))
p[0, 0].x.range = 0.7, 1.7
p[0, 0].y.range = -0.5, len(names) - 0.5
p[0, 0].y.draw_ticks = 0
p[0, 0].y.draw_ticklabels = 0
p[0, 0].frame.ticklabels_style["fontsize"] = 3.5
p = biggles.FramedPlot() xf = Numeric.arange(9460-5, 9460+5, 0.025) yf = map(lambda xi: u1func(318.5185, 3.78739, 0.40577*nbish2nb, 0.053, 0.01864, 0., 0.0267, 0.2, 0., 0.0792, xi), xf) p.add(biggles.Curve(xf, yf)) x = []; y = []; dy = []; dx = []; lab = [] for s in u1runs: x.append(ggdata[s][0]*2000. + u1shifts[s][0]) y.append(ggdata[s][1]) dy.append(ggdata[s][2]) dx.append(u1shifts[s][1]) lab.append(s) p.add(biggles.Points(x, y, symboltype="filled circle", symbolsize=1)) p.add(biggles.SymmetricErrorBarsX(x, y, dx)) p.add(biggles.SymmetricErrorBarsY(x, y, dy)) # x = []; y = []; dy = []; dx = []; lab = [] # for s in u1runs: # x.append(bbindata[s][0]*2000. + u1shifts[s][0]) # y.append(bbindata[s][1]) # dy.append(bbindata[s][2]) # dx.append(u1shifts[s][1]) # lab.append(s) # p.add(biggles.Points(x, y, symboltype="filled circle", symbolsize=1, color="blue")) # p.add(biggles.SymmetricErrorBarsX(x, y, dx, color="blue")) # p.add(biggles.SymmetricErrorBarsY(x, y, dy, color="blue")) x = []; y = []; dy = []; dx = []; lab = [] for s in u1runs:
u3outee = [
-3.26950954112, -3.81874447879, -2.69523715354, -2.74889362332,
-2.66285796831, -2.70059556893, -2.90842427327
]
u3outee_err = [
0.154412757067, 0.119568862537, 0.155137761393, 0.160767851983,
0.104925973842, 0.130096282742, 0.145423604825
]
ggrange = Numeric.array(range(0, -len(names1), -1)) + 0.2
ineerange = Numeric.array(range(0, -len(names1), -1))
outeerange = Numeric.array(range(0, -len(names1), -1)) - 0.2
p = biggles.FramedPlot()
tmp1 = biggles.Points(u1gg, ggrange, size=1.5, type="filled circle")
p.add(tmp1)
p.add(biggles.SymmetricErrorBarsX(u1gg, ggrange, u1gg_err))
tmp2 = biggles.Points(u1inee, ineerange, size=2, type="triangle")
p.add(tmp2)
p.add(biggles.SymmetricErrorBarsX(u1inee, ineerange, u1inee_err))
tmp3 = biggles.Points(u1outee,
outeerange,
size=2,
type="filled inverted triangle")
p.add(tmp3)
p.add(biggles.SymmetricErrorBarsX(u1outee, outeerange, u1outee_err))
tmp1.label = r"$\gamma\gamma$ luminosity"
tmp2.label = r"inner $e^+e^-$"
tmp3.label = r"outer $e^+e^-$"
p.add(biggles.PlotKey(0.6, 0.7, [tmp1, tmp2, tmp3]))
p.yrange = -len(names1), 1
p.y.ticks = ineerange
12.767438367915,
57.6641809947519,
]
p = biggles.FramedPlot()
p.add(biggles.Points(area1s, chi21s, symboltype="filled circle", symbolsize=1))
p.add(
biggles.SymmetricErrorBarsY(area1s,
chi21s,
chi21s_err,
symboltype="filled circle",
symbolsize=1))
p.add(
biggles.SymmetricErrorBarsX(area1s,
chi21s,
area1s_err,
symboltype="filled circle",
symbolsize=1))
for a, c, j in zip(area1s, chi21s, jit1s):
a += 0.0005
c += 0.002
if j == 0.01:
p.add(
biggles.DataLabel(a,
c,
"0.01 MeV RMS jitter",
texthalign="left",
textvalign="top"))
else:
p.add(
biggles.DataLabel(a,
def bscatter(xin, yin, show=True, plt=None, **keywords):
"""
Name:
bscatter
Purpose:
A wrapper to perform a quick scatter plot with biggles. For anything
more complex, it is better to use the object oriented interface.
Calling Sequence:
bscatter(x, y,
xerr=None,
yerr=None,
xrange=None,
yrange=None,
type='filled circle',
color=None,
xlabel=None,
ylabel=None,
label=None,
title=None,
file=None,
xsize=None,
ysize=None,
aspect_ratio=None,
show=True,
plt=None)
Return value is the used biggles plot object.
For overplotting, send an existing biggles plot object in the plt= keyword
"""
import biggles
if plt is None:
plt = biggles.FramedPlot()
xlog = keywords.get('xlog', False)
ylog = keywords.get('ylog', False)
else:
xlog = plt.xlog
ylog = plt.ylog
pdict = {}
# plot symbol or line type
type = keywords.get('type', 'filled circle')
xerr = keywords.get('xerr', None)
yerr = keywords.get('yerr', None)
x = xin
y = yin
xrng = keywords.get('xrange', None)
yrng = keywords.get('yrange', None)
# For log, Don't plot points less than zero
w = None
if xlog and ylog:
xrng = get_log_plot_range(x, err=xerr, input_range=xrng)
yrng = get_log_plot_range(y, err=yerr, input_range=yrng)
w, = numpy.where((x > xrng[0]) & (y > yrng[0]))
elif xlog:
xrng = get_log_plot_range(x, err=xerr, input_range=xrng)
w, = numpy.where(x > xrng[0])
elif ylog:
yrng = get_log_plot_range(y, err=yerr, input_range=yrng)
w, = numpy.where(y > yrng[0])
if w is not None:
if w.size == 0:
raise ValueError("no points > 0 for log plot")
x = x[w]
y = y[w]
pkeywords = {}
if 'color' in keywords:
pkeywords['color'] = keywords['color']
if 'width' in keywords:
pkeywords['width'] = keywords['width']
if type in [
"solid", "dotted", "dotdashed", "shortdashed", "longdashed",
"dotdotdashed", "dotdotdotdashed"
]:
if 'width' in keywords:
pkeywords['width'] = keywords['width']
p = biggles.Curve(x, y, type=type, **pkeywords)
else:
size = keywords.get('size', 1)
p = biggles.Points(x, y, type=type, size=size, **pkeywords)
label = keywords.get('label', None)
if label is not None:
p.label = label
plt.add(p)
pdict['p'] = p
# note for log error bars, we start with original points since
# the bars may extend above zero even for negative points
if yerr is not None:
if ylog:
pdict['p_yerr'] = add_log_error_bars(plt, 'y', xin, yin, yerr,
yrng, **pkeywords)
#p_yerr = add_log_error_bars(plt, 'y', xin, yin, yerr, yrng, **pkeywords)
else:
p_yerr = biggles.SymmetricErrorBarsY(x, y, yerr, **pkeywords)
plt.add(p_yerr)
pdict['p_yerr'] = p_yerr
if xerr is not None:
if xlog:
pdict['p_xerr'] = add_log_error_bars(plt, 'y', xin, yin, xerr,
xrng, **pkeywords)
#p_xerr = add_log_error_bars(plt, 'y', xin, yin, xerr, xrng, **pkeywords)
else:
p_xerr = biggles.SymmetricErrorBarsX(x, y, xerr, **pkeywords)
plt.add(p_xerr)
pdict['p_xerr'] = p_xerr
plt.xlog = xlog
plt.ylog = ylog
if xrng is not None:
plt.xrange = xrng
if yrng is not None:
plt.yrange = yrng
if 'xlabel' in keywords:
plt.xlabel = keywords['xlabel']
if 'ylabel' in keywords:
plt.ylabel = keywords['ylabel']
if 'title' in keywords:
plt.title = keywords['title']
if 'aspect_ratio' in keywords:
plt.aspect_ratio = keywords['aspect_ratio']
if 'file' in keywords:
fname = keywords['file']
if fname.find('.eps') != -1 or fname.find('.ps') != -1:
plt.write_eps(fname)
else:
xsize = keywords.get('xsize', 512)
ysize = keywords.get('ysize', 512)
plt.write_image(xsize, ysize, fname)
else:
if show:
plt.show()
pdict['plt'] = plt
if 'dict' in keywords:
if keywords['dict']:
return pdict
return plt
def bscatter(xin, yin, show=True, plt=None, **keywords):
"""
Name:
bscatter
Purpose:
A wrapper to perform a quick scatter plot with biggles. For anything
more complex, it is better to use the object oriented interface.
Calling Sequence:
bscatter(x, y,
xerr=None,
yerr=None,
xrange=None,
yrange=None,
type='filled circle',
color=None,
xlabel=None,
ylabel=None,
label=None,
title=None,
file=None,
xsize=None,
ysize=None,
aspect_ratio=None,
show=True,
plt=None)
Return value is the used biggles plot object.
For overplotting, send an existing biggles plot object in the plt= keyword
"""
import biggles
if plt is None:
plt = biggles.FramedPlot()
xlog = keywords.get("xlog", False)
ylog = keywords.get("ylog", False)
else:
xlog = plt.xlog
ylog = plt.ylog
pdict = {}
# plot symbol or line type
type = keywords.get("type", "filled circle")
xerr = keywords.get("xerr", None)
yerr = keywords.get("yerr", None)
x = xin
y = yin
xrng = keywords.get("xrange", None)
yrng = keywords.get("yrange", None)
# For log, Don't plot points less than zero
w = None
if xlog and ylog:
xrng = get_log_plot_range(x, err=xerr, input_range=xrng)
yrng = get_log_plot_range(y, err=yerr, input_range=yrng)
(w, ) = np.where((x > xrng[0]) & (y > yrng[0]))
elif xlog:
xrng = get_log_plot_range(x, err=xerr, input_range=xrng)
(w, ) = np.where(x > xrng[0])
elif ylog:
yrng = get_log_plot_range(y, err=yerr, input_range=yrng)
(w, ) = np.where(y > yrng[0])
if w is not None:
if w.size == 0:
raise ValueError("no points > 0 for log plot")
x = x[w]
y = y[w]
pkeywords = {}
if "color" in keywords:
pkeywords["color"] = keywords["color"]
if "width" in keywords:
pkeywords["width"] = keywords["width"]
if type in [
"solid",
"dotted",
"dotdashed",
"shortdashed",
"longdashed",
"dotdotdashed",
"dotdotdotdashed",
]:
if "width" in keywords:
pkeywords["width"] = keywords["width"]
p = biggles.Curve(x, y, type=type, **pkeywords)
else:
size = keywords.get("size", 1)
p = biggles.Points(x, y, type=type, size=size, **pkeywords)
label = keywords.get("label", None)
if label is not None:
p.label = label
plt.add(p)
pdict["p"] = p
# note for log error bars, we start with original points since
# the bars may extend above zero even for negative points
if yerr is not None:
if ylog:
pdict["p_yerr"] = add_log_error_bars(plt, "y", xin, yin, yerr,
yrng, **pkeywords)
else:
p_yerr = biggles.SymmetricErrorBarsY(x, y, yerr, **pkeywords)
plt.add(p_yerr)
pdict["p_yerr"] = p_yerr
if xerr is not None:
if xlog:
pdict["p_xerr"] = add_log_error_bars(plt, "y", xin, yin, xerr,
xrng, **pkeywords)
else:
p_xerr = biggles.SymmetricErrorBarsX(x, y, xerr, **pkeywords)
plt.add(p_xerr)
pdict["p_xerr"] = p_xerr
plt.xlog = xlog
plt.ylog = ylog
if xrng is not None:
plt.xrange = xrng
if yrng is not None:
plt.yrange = yrng
if "xlabel" in keywords:
plt.xlabel = keywords["xlabel"]
if "ylabel" in keywords:
plt.ylabel = keywords["ylabel"]
if "title" in keywords:
plt.title = keywords["title"]
if "aspect_ratio" in keywords:
plt.aspect_ratio = keywords["aspect_ratio"]
if "file" in keywords:
fname = keywords["file"]
if fname.find(".eps") != -1 or fname.find(".ps") != -1:
plt.write_eps(fname)
else:
xsize = keywords.get("xsize", 512)
ysize = keywords.get("ysize", 512)
plt.write_img(xsize, ysize, fname)
else:
if show:
plt.show()
pdict["plt"] = plt
if "dict" in keywords:
if keywords["dict"]:
return pdict
return plt
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]
hads_sigs = []
for r, c, e in zip(testsample, hads, hads_err):
hads_sigs.append((c - hads_center) / e)
hads_hist = hist.h1(50, -5, 5).fill(hads_sigs).rootn()
def gauss(x, a, m, s):
return a * math.exp(-(x - m)**2 / 2. / s**2) / math.sqrt(
2. * math.pi) / s
chipoints = hads_hist.frame + (hads_hist.frame[1] -
hads_hist.frame[0]) / 2.
def chi2(a, m, s):
c = 0.
for i, x in zip(range(len(hads_hist.frame)), chipoints):
if hads_hist.errs[i] > 0:
c += (hads_hist.vals[i] -
gauss(x, a, m, s))**2 / hads_hist.errs[i]**2
return c
# def hist_look(a, m, s):
# p = hads_hist.plot()
# values = []
# for x in chipoints:
# values.append(gauss(x, a, m, s))
# p.add(biggles.Curve(chipoints, values))
# p.show()
# hist_look(len(testsample)/5., 0, 1)
m = Minuit(chi2, start=[len(testsample) / 5., 0, 1])
m.migrad()
hist_chi2, hist_params, hist_errors = m.fval, m.values, m.errors
ndf = len(filter(lambda x: x > 0, hads_hist.errs))
values = []
for x in chipoints:
values.append(gauss(x, *hist_params))
hist_info = [["$\chi^2/ndf$", hist_chi2, "/", ndf], \
["RMS", hist_params[2], "$\pm$", hist_errors[2]]]
p = biggles.Table(2, 1)
p[0, 0] = biggles.FramedPlot()
p[0, 0].add(
biggles.Points(Numeric.array(hads) / hads_center,
range(len(testsample)),
type="filled circle"))
p[0, 0].add(
biggles.SymmetricErrorBarsX(
Numeric.array(hads) / hads_center, range(len(testsample)),
Numeric.array(hads_err) / hads_center))
p[0, 0].y1.draw_ticklabels = 0
p[0, 0].x1.label = "$\propto$ hadronic cross-section"
p[0, 0].add(biggles.LineX(1.))
p[0, 0].add(biggles.LineY(41.5, type="dashed"))
l, r = 0.8, 1.2
p[0, 0].xrange = l, r
p[0, 0].add(biggles.DataLabel(l + 0.15 * (r - l), 41.5 - 7, "db16"))
p[0, 0].add(biggles.DataLabel(l + 0.15 * (r - l), 41.5 + 7, "db17"))
p[0, 1] = hads_hist.plot()
p[0, 1].add(biggles.Curve(chipoints, values))
hist.addinfobox(p[0, 1],
hist_info,
width=0.8,
colwidth=[0.2, 0.09, 0.23],
corner=1,
numformat="%.2g")
p[0, 1].x1.label = "sigmas away from weighted mean"
p[0, 1].yrange = 0, 17
p.aspect_ratio = 8.5 / 11. * 4
p.show()
p.write_eps(filename)