def main(opts, args):
sys.stdout.write('dhad.gen.subset ... ')
sys.stdout.flush()
parsed = parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
mode = modes[0]
modekey, sign = get_modekey_sign(mode)
input_label = label.split('/')[0]
children = label.split('/')[1]
infile = get_rootfile(datatype, mode, input_label)
outfile = get_rootfile(datatype, mode, label, opt='Create')
if opts.test:
outfile += '.test'
sys.stdout.write('Input rootfile: %s \n' % infile)
sys.stdout.write('Output rootfile: %s \n' % outfile)
pt = add_rootfile(infile)
nselected, ntotal = copy_events(pt, outfile, sign, children, opts.test)
sys.stdout.write(' selected %s out of %s.\n' % (nselected, ntotal))
sys.stdout.flush()
def main(opts, args):
tools.set_root_style(stat=1, grid=0)
parsed = parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
figpath = os.path.join(attr.figpath, label, 'trkmtm')
for mode in modes:
modekey = tools.get_modekey(mode)
sname = attr.modes[modekey]['sname'].lower()
if sname == 'kpipi0':
draw_momenta_kpipi0(datatype, mode, label, test=opts.test)
elif sname == 'k3pi':
draw_momenta_k3pi(datatype, mode, label, test=opts.test)
elif sname == 'kpipi':
draw_momenta_kpipi(datatype, mode, label, test=opts.test)
elif sname == 'kpipipi0':
draw_momenta_kpipipi0(datatype, mode, label, test=opts.test)
elif sname == 'kspipi0':
draw_momenta_kspipi0(datatype, mode, label, test=opts.test)
elif sname == 'ks3pi':
draw_momenta_ks3pi(datatype, mode, label, test=opts.test)
elif sname == 'kkpi':
draw_momenta_kkpi(figpath, datatype, mode, label, test=opts.test)
else:
raise NameError(sname)
def main(opts, args):
sys.stdout.write('dhad.gen.subset ... ')
sys.stdout.flush()
parsed = parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
mode = modes[0]
modekey, sign = get_modekey_sign(mode)
input_label = label.split('/')[0]
children = label.split('/')[1]
infile = get_rootfile(datatype, mode, input_label)
outfile = get_rootfile(datatype, mode, label, opt='Create')
if opts.test:
outfile += '.test'
sys.stdout.write('Input rootfile: %s \n' % infile)
sys.stdout.write('Output rootfile: %s \n' % outfile)
pt = add_rootfile(infile)
nselected, ntotal = copy_events(pt, outfile, sign, children, opts.test)
sys.stdout.write(' selected %s out of %s.\n' % (nselected, ntotal))
sys.stdout.flush()
def main(opts, args):
tools.set_root_style(stat=1, grid=0)
parsed = parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
figpath = os.path.join(attr.figpath, label, 'trkmtm')
for mode in modes:
modekey = tools.get_modekey(mode)
sname = attr.modes[modekey]['sname'].lower()
if sname == 'kpipi0':
draw_momenta_kpipi0(datatype, mode, label, test=opts.test)
elif sname == 'k3pi':
draw_momenta_k3pi(datatype, mode, label, test=opts.test)
elif sname == 'kpipi':
draw_momenta_kpipi(datatype, mode, label, test=opts.test)
elif sname == 'kpipipi0':
draw_momenta_kpipipi0(datatype, mode, label, test=opts.test)
elif sname == 'kspipi0':
draw_momenta_kspipi0(datatype, mode, label, test=opts.test)
elif sname == 'ks3pi':
draw_momenta_ks3pi(datatype, mode, label, test=opts.test)
elif sname == 'kkpi':
draw_momenta_kkpi(figpath, datatype, mode, label, test=opts.test)
else:
raise NameError(sname)
def main(opts, args):
parsed = parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
for mode in modes:
if opts.set and opts.set == 'interact':
if tag == 'single' or tag == 'double':
single_tag_mode(datatype, mode, label, opts.test)
else:
raise ValueError(tag)
else:
submit_batch_job(datatype, tag, mode, label, opts)
def main(opts, args):
parsed = parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
for mode in modes:
if opts.set and opts.set == 'interact':
if tag == 'single' or tag == 'double':
single_tag_mode(datatype, mode, label, opts.test)
else:
raise ValueError(tag)
else:
submit_batch_job(datatype, tag, mode, label, opts)
def main():
alpha, num_iterations, animate = tools.parse_args()
data = pd.read_csv("data.csv")
X = np.array(data['km'], dtype='float64')
y = np.array(data['price'], dtype='float64')
X_norm, mu, sigma = feature_normalize(X)
theta = np.array([0, 0], dtype='float64')
theta, J_history, weight_list = fit(X_norm, y, theta, alpha,
num_iterations)
if animate == True:
v.visualize_animate(weight_list, X_norm, X, y, num_iterations)
else:
v.visualize_cost(J_history)
v.visualize_regression(theta, X_norm, X, y)
tools.save_theta(theta, mu, sigma)
def main():
# parse a set of parameters
args = parse_args()
# parameters
image_height, image_width = args.input_shape[0], args.input_shape[1]
# create directory tree
dir_dict = {}
dir_dict = {'root' : ['logs', 'data'],\
'data' : ['h5'],\
'logs' : ['nn_logs'] }
dir_create(args.dir, dir_dict)
# Load and split data set
train_lines, validation_lines = data_load(args)
# Build a model
model = model_build(args)
# Train and save the model
history = model_train(args, model, train_lines, validation_lines)
def main(opts, args):
if args[0] == 'crossfeeds':
import crossfeeds
crossfeeds.entry(opts, args[1:])
return
if args[0] == 'events':
import events
events.main(opts, args[1:])
return
if args[0] == 'backgrounds':
import backgrounds
backgrounds.main(opts, args[1:])
return
if args[0] == 'var':
import var
var.main(opts, args[1:])
return
parsed = parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
for mode in modes:
if opts.set and opts.set == 'interact':
if tag == 'single':
single_tag_mode(datatype, mode, label, opts.test)
elif tag == 'double':
double_tag_mode(datatype, mode, label, opts.test)
else:
raise ValueError(tag)
else:
submit_batch_job(datatype, tag, mode, label, opts)
"rbf": True
} # easy check to validate -k option
# -- parse command line and convert to convenience variables -----------------------------------------------
flags = { # define possible flags and the default: map key, type, default value
"-a": ("pr_ave", str_flag, "binary"),
"-N": ("normalise", bool_flag, True),
"-f": ("classfirst", bool_flag, False),
"-k": ("kernel_type", str_flag, "linear"),
"-l": ("learn_curve", bool_flag,
True), # generate learning curve unless -l given
"-s": ("rstate", int_flag, 100),
"-t": ("tsize", int_flag, 30)
}
opts = {} # map where option values or defaults come back
pparms = parse_args(flags, opts, "training-file [testing-file]")
if pparms == None or len(pparms) < 1:
printf("missing filename on command line\n")
sys.exit(1)
kernel_type = opts["kernel_type"]
if not kernel_type in valid_ktypes:
printf("[FAIL] %s is not a valid kernel type for -k parameter\n",
kernel_type)
printf("\tvalid types are: linear, polynomial, or RBF\n")
os.exit(1)
filen = pparms[0] # raw data file manditory first parameter
pr_ave = opts["pr_ave"]
gen_lc = opts["learn_curve"]
def main(opts, args):
if args[0] == 'backgrounds':
import backgrounds
backgrounds.main(opts, args[1:])
return
if args[0] == 'brs':
import brs
brs.main(opts, args[1:])
return
if args[0] == 'compare':
import compare
compare.main(opts, args[1:])
return
if args[0] == 'cbx':
import cbx
cbx.main(opts, args[1:])
return
if args[0] == 'crossfeeds':
import crossfeeds
crossfeeds.main(opts, args[1:])
return
if args[0] == 'evt':
import evt
evt.main(opts, args[1:])
return
if args[0] == 'fun':
import fun
fun.main(opts, args[1:])
return
if args[0] == 'kkmass':
import kkmass
kkmass.main(opts, args[1:])
return
if args[0] == 'kpimass':
import kpimass
kpimass.main(opts, args[1:])
return
if args[0] == 'trim':
import trim
trim.main(opts, args[1:])
return
if args[0] == 'trkmtm':
import trkmtm
trkmtm.main(opts, args[1:])
return
if args[0] == 'trkmtm1':
import trkmtm1
trkmtm1.main(opts, args[1:])
return
if args[0] == 'trkmtm2':
import trkmtm2
trkmtm2.main(opts, args[1:])
return
if args[0] == 'var':
import var
var.main(opts, args[1:])
return
figname = '_'.join(args).replace('/', '_')
parsed = parse_args(args)
dt_type = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
sqrt = False
if opts.set and opts.set == 'sqrt':
sqrt = True
linr = False
if opts.set and opts.set == 'linr':
linr = True
org = UserFile()
org.append(attr.fig_web_header)
for mode in modes:
if mode == 'double_all_d0s' or mode == 'double_all_dps':
modekey = mode
else:
modekey = get_modekey(mode)
if sqrt:
sqrt_fig_mode(tag, dt_type, modekey, label)
sys.stdout.write('Creating %s ...' % mode)
sys.stdout.flush()
msg = create_fig_mode(tag, dt_type, modekey, label)
sys.stdout.write(' OK.\n')
org.append(msg)
org.append(attr.fig_web_footer)
figlabel = label.split('/')[0]
figname = figname.replace(figlabel, '')
figname = figname.replace('__', '_')
orgname = figname + '.org'
orgname = orgname.replace('_.org', '.org')
orgpath = os.path.join(attr.figpath, figlabel)
orgfile = tools.check_and_join(orgpath, orgname)
verbose = opts.verbose
if opts.test:
verbose = 1
org.output(orgfile, verbose=verbose)
orglink = '[[./fig/%s/%s][figure]]' % (figlabel, orgname)
sys.stdout.write('\n%s\n\n' % orglink)
if opts.test:
return
tools.org_export_as_html(orgfile)
def main(opts, args):
if args[0] == 'backgrounds':
import backgrounds
backgrounds.main(opts, args[1:])
return
if args[0] == 'brs':
import brs
brs.main(opts, args[1:])
return
if args[0] == 'compare':
import compare
compare.main(opts, args[1:])
return
if args[0] == 'cbx':
import cbx
cbx.main(opts, args[1:])
return
if args[0] == 'crossfeeds':
import crossfeeds
crossfeeds.main(opts, args[1:])
return
if args[0] == 'evt':
import evt
evt.main(opts, args[1:])
return
if args[0] == 'fun':
import fun
fun.main(opts, args[1:])
return
if args[0] == 'kkmass':
import kkmass
kkmass.main(opts, args[1:])
return
if args[0] == 'kpimass':
import kpimass
kpimass.main(opts, args[1:])
return
if args[0] == 'trim':
import trim
trim.main(opts, args[1:])
return
if args[0] == 'trkmtm':
import trkmtm
trkmtm.main(opts, args[1:])
return
if args[0] == 'trkmtm1':
import trkmtm1
trkmtm1.main(opts, args[1:])
return
if args[0] == 'trkmtm2':
import trkmtm2
trkmtm2.main(opts, args[1:])
return
if args[0] == 'var':
import var
var.main(opts, args[1:])
return
figname = '_'.join(args).replace('/', '_')
parsed = parse_args(args)
dt_type = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
sqrt = False
if opts.set and opts.set == 'sqrt':
sqrt = True
linr = False
if opts.set and opts.set == 'linr':
linr = True
org = UserFile()
org.append(attr.fig_web_header)
for mode in modes:
if mode == 'double_all_d0s' or mode == 'double_all_dps' :
modekey = mode
else:
modekey = get_modekey(mode)
if sqrt:
sqrt_fig_mode(tag, dt_type, modekey, label)
sys.stdout.write('Creating %s ...' % mode)
sys.stdout.flush()
msg = create_fig_mode(tag, dt_type, modekey, label)
sys.stdout.write(' OK.\n')
org.append(msg)
org.append(attr.fig_web_footer)
figlabel = label.split('/')[0]
figname = figname.replace(figlabel, '')
figname = figname.replace('__', '_')
orgname = figname+'.org'
orgname = orgname.replace('_.org', '.org')
orgpath = os.path.join(attr.figpath, figlabel)
orgfile = tools.check_and_join(orgpath, orgname)
verbose = opts.verbose
if opts.test:
verbose = 1
org.output(orgfile, verbose=verbose)
orglink = '[[./fig/%s/%s][figure]]' %(figlabel, orgname)
sys.stdout.write('\n%s\n\n' % orglink)
if opts.test:
return
tools.org_export_as_html(orgfile)
pass
def test_all(self):
pass
if __name__ == "__main__":
args = sys.argv[1:]
if len(args) == 0:
print "Running unittests."
unittest.main()
[input_args, output_args] = tools.parse_args(
args, [["-in", "-i", "-input", "--input"], ["-out", "-o", "-output", "--output"]]
)
input = input_fname = None
output = output_fname = None
if len(input_args) == 0:
print "error: no input files understood."
quit()
while len(output_args) < len(input_args):
output_args.append("")
for k, ofname in enumerate(output_args):
if ofname in ["", None]:
ifname = input_args[k]
self.plot_scatter(lat, lon)
lat, lon = self.coor_vgt.get_row_by_name(pt)[['LATITUDE',
'LONGITUDE']].values.T
self.plot_scatter(lat, lon)
def show(self):
plt.gca().axis('equal')
## Set colorscale identical for all imshow
vmin, vmax = self.imshow_clim
for im in self.imshow:
im.set_clim(vmin=vmin, vmax=vmax)
#self.fig.colorbar(im, ax=self.ax)
self.fig.colorbar(im, ax=self.ax)
plt.show()
if __name__ == '__main__':
kwargs = tools.parse_args()
m = Main()
#m.plot_grid(**kwargs) # input args: f1=<path>:f2=<path>
m.extract_land_mask(**kwargs) # input args: f1=<path>
#m.plot_extract_coor(**kwargs) # input args: csvcoorfile, f1, f2
#m.show()
print ''
sys.stdout.write("done.\n")
return tex_lines
if __name__ == "__main__":
args = sys.argv[1:]
[input_args, output_args ] = tools.parse_args(args, [['-in','-i','-input','--input'], ['-out','-o','-output','--output'] ] )
input = input_fname = None
output = output_fname = None
if len(input_args) == 0:
print "error: no input files understood."
quit()
while len(output_args) < len(input_args):
output_args.append('')
for k,ofname in enumerate(output_args):
if ofname in [ '', None ]:
ifname = input_args[k]
(name, in_ext) = os.path.splitext(ifname)
def main(opts, args):
if args[0] == 'crossfeeds':
import crossfeeds
crossfeeds.main(opts, args[1:])
return
if args[0] == 'backgrounds':
import backgrounds
backgrounds.main(opts, args[1:])
return
if args[0] == 'sidebands':
import sidebands
sidebands.main(opts, args[1:])
return
if args[0] == 'kkmass':
import kkmass
kkmass.main(opts, args[1:])
return
if args[0] == 'kkmass2':
import kkmass2
kkmass2.main(opts, args[1:])
return
if args[0] == 'kpimass':
import kpimass
kpimass.main(opts, args[1:])
return
ROOT.gROOT.SetBatch(1)
ROOT.gROOT.SetStyle("Plain")
parsed = parse_args(args)
dt_type = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
if modes == ['double_all_d0s']:
mode = modes[0]
if opts.set and opts.set == 'interact':
double_all_d0s(dt_type, mode, label, test=opts.test)
else:
pyline = 'import fit; fit.%s("%s", "%s", "%s", test=%s)' % (
mode, dt_type, mode, label, opts.test)
bash_file_name = 'fit-mbc.sh'
bash_file = create_bash_file_pyline(opts, label, dt_type, pyline,
bash_file_name)
logfile = tools.set_file('txt',
dt_type,
mode,
tag,
prefix='dir_' + label,
extbase=attr.logpath)
qjobname = 'fitd0s'
tools.qsub_jobs(logfile, qjobname, bash_file, opts.test)
return
if modes == ['double_all_dps']:
mode = modes[0]
if opts.set and opts.set == 'interact':
double_all_dps(dt_type, mode, label, test=opts.test)
else:
pyline = 'import fit; fit.%s("%s", "%s", "%s", test=%s)' % (
mode, dt_type, mode, label, opts.test)
bash_file_name = 'fit-mbc.sh'
bash_file = create_bash_file_pyline(opts, label, dt_type, pyline,
bash_file_name)
logfile = tools.set_file('txt',
dt_type,
mode,
tag,
prefix='dir_' + label,
extbase=attr.logpath)
qjobname = 'fitdps'
tools.qsub_jobs(logfile, qjobname, bash_file, opts.test)
return
for mode in modes:
if opts.set and opts.set == 'interact':
if tag == 'single':
single_tag_mode(dt_type,
mode,
label,
interact=True,
test=opts.test)
elif tag == 'double':
double_tag_mode(dt_type,
mode,
label,
interact=True,
test=opts.test)
else:
raise ValueError(tag)
continue
else:
submit_batch_job(dt_type, tag, mode, label, opts)
def main(opts, args):
if args[0] == 'crossfeeds':
import crossfeeds
crossfeeds.main(opts, args[1:])
return
if args[0] == 'backgrounds':
import backgrounds
backgrounds.main(opts, args[1:])
return
if args[0] == 'sidebands':
import sidebands
sidebands.main(opts, args[1:])
return
if args[0] == 'kkmass':
import kkmass
kkmass.main(opts, args[1:])
return
if args[0] == 'kkmass2':
import kkmass2
kkmass2.main(opts, args[1:])
return
if args[0] == 'kpimass':
import kpimass
kpimass.main(opts, args[1:])
return
ROOT.gROOT.SetBatch(1)
ROOT.gROOT.SetStyle("Plain")
parsed = parse_args(args)
dt_type = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
if modes == ['double_all_d0s']:
mode = modes[0]
if opts.set and opts.set == 'interact':
double_all_d0s(dt_type, mode, label, test=opts.test)
else:
pyline = 'import fit; fit.%s("%s", "%s", "%s", test=%s)'% (
mode, dt_type, mode, label, opts.test)
bash_file_name = 'fit-mbc.sh'
bash_file = create_bash_file_pyline(opts, label, dt_type, pyline,
bash_file_name)
logfile = tools.set_file('txt', dt_type, mode, tag,
prefix='dir_'+label, extbase=attr.logpath)
qjobname = 'fitd0s'
tools.qsub_jobs(logfile, qjobname, bash_file, opts.test)
return
if modes == ['double_all_dps']:
mode = modes[0]
if opts.set and opts.set == 'interact':
double_all_dps(dt_type, mode, label, test=opts.test)
else:
pyline = 'import fit; fit.%s("%s", "%s", "%s", test=%s)'% (
mode, dt_type, mode, label, opts.test)
bash_file_name = 'fit-mbc.sh'
bash_file = create_bash_file_pyline(opts, label, dt_type, pyline,
bash_file_name)
logfile = tools.set_file('txt', dt_type, mode, tag,
prefix='dir_'+label, extbase=attr.logpath)
qjobname = 'fitdps'
tools.qsub_jobs(logfile, qjobname, bash_file, opts.test)
return
for mode in modes:
if opts.set and opts.set == 'interact':
if tag == 'single':
single_tag_mode(dt_type, mode, label, interact=True,
test=opts.test)
elif tag == 'double':
double_tag_mode(dt_type, mode, label, interact=True,
test=opts.test)
else:
raise ValueError(tag)
continue
else:
submit_batch_job(dt_type, tag, mode, label, opts)
