def newPopulation(x0, a, b, npop):
nx = len(x0)
nf = 0
ninf = 0
pop = []
n = 0
ntries = 0
x = x0
while ((n < npop) & ((ntries + 1) < 3 * npop)):
vctr = x[:]
try:
nf = nf + 1
y = f.eval(x)
ny = len(y)
for i in range(ny):
vctr.append(y[i])
pop.append(vctr)
n = n + 1
except Exception as e:
ninf = ninf + 1
#print(e)
r = []
for i in range(nx):
r.append(random.uniform(0, 1))
x = sum(mult(r, res(b, a)), a)
#print("n: " + str(n) + " ninf: " + str(ninf) + " x: " + str(x))
return [pop, nx, ny, nf, ninf]
def mc_stack_n_data_sum(wrps, merge_mc_key_func=None, use_all_data_lumi=False):
"""
Stacks MC histos and merges data, input needs to be sorted and grouped.
The output are tuples of MC stacks and data histograms.
ATTENTION: This crashes, if the proper histograms are not present!
:param wrps: Iterables of HistoWrapper (grouped)
:param merge_mc_key_func: key function for python sorted(...), default
tries to sort after stack position
:yields: (StackWrapper, HistoWrapper)
"""
if not merge_mc_key_func:
merge_mc_key_func = lambda w: settings.get_stack_position(w.sample)
for grp in wrps:
# split stream
data, mc = split_data_mc(grp)
# sum up data
data_sum = None
try:
data_sum = op.sum(data)
except op.TooFewWrpsError:
print "WARNING generators.mc_stack_n_data_sum(..): "\
"No data histos present! I will yield only mc."
if use_all_data_lumi:
data_lumi = settings.data_lumi_sum_wrp()
else:
data_lumi = op.lumi(data_sum)
# merge mc samples (merge also normalizes to lumi = 1.)
mc_sorted = sorted(mc, key=merge_mc_key_func)
mc_groupd = group(mc_sorted, merge_mc_key_func)
mc_merged = (op.merge(g) for g in mc_groupd)
mc_colord = apply_histo_fillcolor(mc_merged)
# stack mc
mc_norm = gen_prod(
itertools.izip(mc_colord, itertools.repeat(data_lumi)))
mc_stck = None
try:
mc_stck = op.stack(mc_norm)
except op.TooFewWrpsError:
print "WARNING generators.mc_stack_n_data_sum(..): " \
"No mc histos present! I will yield only data"
if mc_stck and data_sum:
yield mc_stck, data_sum
elif mc_stck:
yield (mc_stck, )
elif data_sum:
yield (data_sum, )
else:
raise op.TooFewWrpsError("Neither data nor mc histos present!")
def mc_stack_n_data_sum(wrps, merge_mc_key_func=None, use_all_data_lumi=False):
"""
Stacks MC histos and merges data, input needs to be sorted and grouped.
The output are tuples of MC stacks and data histograms.
ATTENTION: This crashes, if the proper histograms are not present!
:param wrps: Iterables of HistoWrapper (grouped)
:param merge_mc_key_func: key function for python sorted(...), default
tries to sort after stack position
:yields: (StackWrapper, HistoWrapper)
"""
if not merge_mc_key_func:
merge_mc_key_func = lambda w: settings.get_stack_position(w.sample)
for grp in wrps:
# split stream
data, mc = split_data_mc(grp)
# sum up data
data_sum = None
try:
data_sum = op.sum(data)
except op.TooFewWrpsError:
print "WARNING generators.mc_stack_n_data_sum(..): "\
"No data histos present! I will yield only mc."
if use_all_data_lumi:
data_lumi = settings.data_lumi_sum_wrp()
else:
data_lumi = op.lumi(data_sum)
# merge mc samples (merge also normalizes to lumi = 1.)
mc_sorted = sorted(mc, key=merge_mc_key_func)
mc_groupd = group(mc_sorted, merge_mc_key_func)
mc_merged = (op.merge(g) for g in mc_groupd)
mc_colord = apply_histo_fillcolor(mc_merged)
# stack mc
mc_norm = gen_prod(itertools.izip(mc_colord, itertools.repeat(data_lumi)))
mc_stck = None
try:
mc_stck = op.stack(mc_norm)
except op.TooFewWrpsError:
print "WARNING generators.mc_stack_n_data_sum(..): " \
"No mc histos present! I will yield only data"
if mc_stck and data_sum:
yield mc_stck, data_sum
elif mc_stck:
yield (mc_stck, )
elif data_sum:
yield (data_sum, )
else:
raise op.TooFewWrpsError("Neither data nor mc histos present!")
def plantPopulation(x0, a, b, ngen, npop, nrmax, output):
plPop = NewPopulation.newPopulation(x0, a, b, npop)
phi = plPop[0]
nx = plPop[1]
ny = plPop[2]
nf = plPop[3]
ninf = plPop[4]
#print(plPop)
pop = PlantSort.plantSort(phi, nx, ny)
#print(pop)
gen = 0
x = []
y = []
while gen < ngen:
N = PlantFitness.computeFitness(pop, nx, ny, npop)
N = N[0]
phi = []
for i in range(npop):
phi.append(pop[i])
# print(N[p])
nr = ceil(nrmax * (1 - N[i]) * random.random())
if nr < 1:
nr = 1
for j in range(nr):
dx = []
for n in range(nx):
dx.append(random.random() * nx)
dx = mult(res(dx, 0.5), (2 * (1 - N[i])))
x = []
for k in range(nx):
x.append(pop[i][k])
x = sum(x, dx)
#print("x:"); print(x);
# reset boundaries
x = resetBoundaries(x, a, True, b)
#print("xa:"); print(x);
x = resetBoundaries(x, b, False, b)
#print("xb:"); print(x);
nf = 0
try:
nf = nf + 1
y = f.eval(x)
for k in range(len(y)):
x.append(y[k])
phi.append(x)
except Exception as e:
ninf = ninf + 1
pop = PlantSort.plantSort(phi, nx, ny)
gen = gen + 1
x = []
y = []
#print(pop);
#stop = input("prompt: ")
for c in range(len(pop)):
tX = []
tY = []
for i in range(nx):
tX.append(pop[c][i])
for j in range(len(pop[0]) - nx):
tY.append(pop[c][j + (nx)])
x.append(tX)
y.append(tY)
return [x, y, nf, ninf]
while True:
array1 = []
print("Enter 10 positive or negative integers into a list: ")
elms = 0
while elms != 10:
try:
array1.append(int(input()))
elms += 1
except ValueError:
print("INCORRECT INPUT, TRY AGAIN")
print("Your array is:")
print(array1)
print("The sum of the elements in the array is " + str(sum(array1)))
print("The largest element of the array is " + str(getLargestNum(array1)))
print("The smallest element of the array is " +
str(getSmallestNum(array1)))
print("The even elements of the array are " + str(getEvenNums(array1)))
print("The odd elements of the array are " + str(getOddNums(array1)))
print("The positive elements of the array are " +
str(printPositiveNums(array1)))
print("All of the elements converted to positive: " +
str(convertPositiveNums(array1)))
factor = int(input("Enter a factor to multiply elements of the array: "))
print("The elements multipled by the inputed factor are: " +
str(multiplyList(array1, factor)))
#print(vectorMultiply(testArray,testArray2))
def mc_stack_n_data_sum(wrps, merge_mc_key_func=None, use_all_data_lumi=True):
"""
Stacks MC histos and merges data, input needs to be sorted and grouped.
Yields tuples of an MC stack, signal histograms, and a data histogram, if
all kinds of data are present. Raises an exception if no histograms are
given at all.
:param wrps: Iterables of HistoWrapper (grouped)
:param merge_mc_key_func: key function for python sorted(...), default
tries to sort after stack position
:yields: WrapperWrapper of wrappers for plotting
"""
if not merge_mc_key_func:
merge_mc_key_func = analysis.get_stack_position
for grp in wrps:
# split stream
dat, bkg, sig = split_data_bkg_sig(grp)
# data
dat_sum = None
try:
dat_sum = op.sum(dat)
except op.TooFewWrpsError:
monitor.message('generators.mc_stack_n_data_sum',
'DEBUG No data histograms present!')
if dat_sum and not use_all_data_lumi:
data_lumi = op.lumi(dat_sum)
else:
data_lumi = analysis.data_lumi_sum_wrp()
# background (op.merge normalizes to lumi = 1.)
bkg = sorted(bkg, key=merge_mc_key_func)
is_2d = bkg and 'TH2' in bkg[0].type
bkg = group(bkg, merge_mc_key_func)
bkg = (op.merge(g) for g in bkg)
bkg = apply_fillcolor(bkg)
if settings.stack_line_color:
bkg = apply_linecolor(bkg, settings.stack_line_color)
if data_lumi.float != 1.:
bkg = gen_prod(itertools.izip(bkg, itertools.repeat(data_lumi)))
try:
if is_2d:
bkg_stk = gen_squash_sys_acc(bkg, op.sum)
else:
bkg_stk = gen_squash_sys_acc(bkg, op.stack)
except op.TooFewWrpsError:
bkg_stk = None
monitor.message('generators.mc_stack_n_data_sum',
'DEBUG No background histograms present!')
# signal
sig = sorted(sig, key=merge_mc_key_func)
sig = group(sig, merge_mc_key_func)
sig = list(op.merge(g) for g in sig)
if any(s.sys_info for s in sig):
sig = sorted(sig, key=lambda s: s.sample)
sig = group(sig, lambda s: s.sample)
sig = (gen_squash_sys(s) for s in sig)
sig = apply_linecolor(sig)
sig = apply_linewidth(sig)
sig = list(sig)
if not sig:
monitor.message('generators.mc_stack_n_data_sum',
'DEBUG No signal histograms present!')
# return in order for plotting: bkg, signals, data
res = [bkg_stk] + sig + [dat_sum]
res = list(r for r in res if r)
if res:
yield wrappers.WrapperWrapper(res, name=grp.name)
else:
raise op.TooFewWrpsError('No histograms present!')