def initparser(cls, parser, env):
def observable(path):
#
# Future spectra location
#
try:
return env.future['spectra'][path]
except KeyError:
pass
# To be deprecated spectra location
nspath, name = path.split('/')
try:
return env.ns(nspath).observables[name]
except KeyError:
raise PartNotFoundError("observable", path)
parser.add_argument('plot', default=[],
metavar=('DATA',),
action=append_typed(observable))
parser.add_argument('-J', '--no-joints', action='store_false', dest='joints', help='disable joints')
parser.add_argument('--subgraph', action='store_true', help='enable subgraphs')
parser.add_argument('-s', '--splines', help='splines option [dot]')
parser.add_argument('-o', '--output', nargs='+', default=[], dest='outputs', help='output dot/pdf/png file')
parser.add_argument('-O', '--stdout', action='store_true', help='output to stdout')
parser.add_argument('-E', '--stderr', action='store_true', help='output to stderr')
parser.add_argument('-n', '--namespace', '--ns', default=cls.undefined, nargs='?', help='use <namespace> to read parameters', metavar='namespace')
parser.add_argument('--option', nargs=2, action='append', dest='options', default=[], help='AGraph kwargs key value pair')
parser.add_argument_group(title='filters', description='Options to filter nodes')
parser.add_argument('-i', '--include-only', '--include', nargs='+', help='Pattersn to be included (exclusive)')
def initparser(cls, parser, env):
parser.add_argument('--reldelta',
type=float,
default=1.0 / (65536 * 16))
parser.add_argument(
'-a',
'--add',
nargs=3,
default=[],
metavar=('NAME', 'PREDICTION', 'PAR'),
action=append_typed(str, env.parts.prediction, str),
help='add prediction NAME for derivative of PREDICTION wrt PAR')
def initparser(cls, parser, env):
def observable(path):
nspath, name = path.split('/')
try:
return env.ns(nspath).observables[name]
except KeyError:
raise PartNotFoundError("observable", path)
parser.add_argument('-p',
'--plot',
default=[],
metavar=('DATA', ),
action=append_typed(observable))
def initparser(cls, parser, env):
parser.add_argument('name')
parser.add_argument(
'-a',
'--add',
nargs=2,
default=[],
metavar=('NAME', 'DIAGONAL'),
action=append_typed(
str, qualified(env.parts.prediction, env.parts.data)),
help='add statistical covariance matrix NAME from DIAGONAL')
parser.add_argument('-f',
'--fix',
default=[],
action=append_typed(env.parts.covmat, lazy=True),
help='fix covariance matrix NAME')
parser.add_argument('-p',
'--print',
default=[],
metavar='NAME',
action=append_typed(env.parts.covmat, lazy=True),
help='print covariance matrix NAME')
def initparser(cls, parser, env):
parser.add_argument(
'-a',
'--add',
nargs=2,
default=[],
metavar=('NAME', 'PREDICTION'),
action=append_typed(str, env.parts.prediction),
help='set data NAME to Asimov from prediction PREDICTION')
parser.add_argument('-p',
'--print',
action='append',
default=[],
metavar='NAME',
type=env.parts.data,
help='print data NAME')
def initparser(cls, parser, env):
def observable(path):
#
# Future spectra location
#
try:
return env.future[path]
except KeyError:
import IPython
IPython.embed()
pass
# To be deprecated spectra location
try:
return env.ns('').getobservable(path)
except KeyError:
raise PartNotFoundError("observable", path)
def yamlload(s):
ret = yaml.load(s, Loader=yaml.Loader)
return ret
parser.add_argument('plot',
nargs='+',
metavar='DATA',
default=[],
action=append_typed(observable))
parser.add_argument(
'--plot-kwargs',
type=yamlload,
help=
'All additional plotting options go here. They are applied for all plots'
)
parser.add_argument('-l',
'--log',
action='store_true',
help='use log scale')
parse_filters = parser.add_mutually_exclusive_group()
parse_filters.add_argument('--filter',
'-f',
choices=filters.keys(),
help='filter the matrix')
def initparser(cls, parser, env):
def observable(path):
#
# Future spectra location
#
try:
return env.future['spectra'][path]
except KeyError:
pass
# To be deprecated spectra location
try:
return env.ns('').getobservable(path)
except KeyError:
raise PartNotFoundError("observable", path)
def yamlload(s):
ret = yaml.load(s, Loader=yaml.Loader)
return ret
what = parser.add_mutually_exclusive_group()
what.add_argument(
'-dp',
'--difference-plot',
'--diff',
default=[],
nargs=2,
action=append_typed(observable, observable),
help='Subtract two obs, they MUST have the same binning')
what.add_argument('--ratio',
default=[],
nargs=2,
action=append_typed(observable, observable),
help="Plot ratio of 2 observables")
what.add_argument('--offset-ratio',
'--oratio',
default=[],
nargs=2,
action=append_typed(observable, observable),
help="Plot ratio of 2 observables -1")
what.add_argument('-p',
'--plot',
default=[],
metavar=('DATA', ),
action=append_typed(observable))
parser.add_argument('--vs',
metavar='X points',
type=observable,
help='Points over X axis to plot vs')
parser.add_argument('--plot-type',
choices=[
'histo', 'bin_center', 'bar', 'hist',
'errorbar', 'plot', 'ravelplot'
],
metavar='PLOT_TYPE',
help='Select plot type')
parser.add_argument('--scale',
action='store_true',
help='scale histogram by bin width')
parser.add_argument(
'-l',
'--legend',
action='append',
default=[],
metavar=('Legend', ),
help=
'Add legend to the plot, note that number of legends must match the number of plots'
)
parser.add_argument(
'--plot-kwargs',
type=yamlload,
help=
'All additional plotting options go here. They are applied for all plots'
)
def initparser(cls, parser, env):
#
# Make variable parser
#
import argparse
varparser = AppendSubparser(prefix_chars='+', prog='--var')
varparser.add_argument('parname', help='variable name')
varparser.add_argument('+L',
'++log',
action='store_true',
help='use logarithmic scale')
# varparser.add_argument( '++split', default=1, type=int, help='split the range into <N> subranges. To be used with --split key', metavar='N' )
# varparser.add_argument( '+v', '++value', help='saved value to use for center' )
group = varparser.add_mutually_exclusive_group(required=True)
group.add_argument('+l',
'++limits',
nargs=2,
type=float,
help='variable limits')
group.add_argument('+e',
'++err',
type=float,
help='error to set limits (+/-e)')
group = varparser.add_mutually_exclusive_group(required=True)
group.add_argument('+s', '++step', type=float, help='variable step')
group.add_argument('+n',
'++npoints',
type=int,
help='number of points')
#
# Make main parser
#
parser.add_argument('minimizer',
default=[],
metavar=('MINIMIZER'),
action=append_typed(env.parts.minimizer))
parser.add_argument('--pars',
nargs='+',
required=True,
help='All parameters track')
# parser.add_argument( '--file', default='main', help='select target file' )
# parser.add_argument( '--hdf', help='save hdf output' )
parser.add_argument(
'-v',
'--var',
nargs='+',
action=varparser,
help='variables specification, use +h/++help for syntax',
dest='variables')
parser.add_argument('-f',
'--folder',
default='scanXd',
help='folder to store the data')
parser.add_argument('-V',
'--verbose',
action='count',
default=0,
help='verbose')
parser.add_argument('-s',
'--scan',
action='store_true',
help='do scan')
group = parser.add_mutually_exclusive_group()
group.add_argument('-m',
'--minimize',
action='store_true',
help='minimize on each step')
group.add_argument('--dummy',
action='store_true',
help='run script without actual calculation')
group.add_argument(
'--dummyfalse',
action='store_true',
help='run script without actual calculation, with failure status')
parser.add_argument('--start-from',
choices=['default', 'bestfit'],
default='default',
help='the very starting point')