def test_update(self):
try:
OrderedDict().update([('a', 1), ('b', 2)], None) # too many args
assert False
except TypeError:
pass
else:
assert False
pairs = [('a', 1), ('b', 2), ('c', 3), ('d', 4), ('e', 5)]
od = OrderedDict()
od.update(dict(pairs))
self.assertEqual(sorted(od.items()), pairs) # dict input
od = OrderedDict()
od.update(**dict(pairs))
self.assertEqual(sorted(od.items()), pairs) # kwds input
od = OrderedDict()
od.update(pairs)
self.assertEqual(list(od.items()), pairs) # pairs input
od = OrderedDict()
od.update([('a', 1), ('b', 2), ('c', 9), ('d', 4)], c=3, e=5)
self.assertEqual(list(od.items()), pairs) # mixed input
# Make sure that direct calls to update do not clear previous contents
# add that updates items are not moved to the end
d = OrderedDict([('a', 1), ('b', 2), ('c', 3), ('d', 44), ('e', 55)])
d.update([('e', 5), ('f', 6)], g=7, d=4)
self.assertEqual(list(d.items()),
[('a', 1), ('b', 2), ('c', 3), ('d', 4), ('e', 5), ('f', 6), ('g', 7)])
def test_copying(self):
# Check that ordered dicts are copyable, deepcopyable, picklable,
# and have a repr/eval round-trip
pairs = [('c', 1), ('b', 2), ('a', 3), ('d', 4), ('e', 5), ('f', 6)]
od = OrderedDict(pairs)
update_test = OrderedDict()
update_test.update(od)
for i, dup in enumerate([
od.copy(),
copy.copy(od),
copy.deepcopy(od),
pickle.loads(pickle.dumps(od, 0)),
pickle.loads(pickle.dumps(od, 1)),
pickle.loads(pickle.dumps(od, 2)),
pickle.loads(pickle.dumps(od, -1)),
eval(repr(od)),
update_test,
OrderedDict(od),
]):
self.assertTrue(dup is not od)
self.assertEquals(dup, od)
self.assertEquals(list(dup.items()), list(od.items()))
self.assertEquals(len(dup), len(od))
self.assertEquals(type(dup), type(od))
class LightcurveFunc(object):
'''Wrap function for the lightcurve analysis function registry
This wrapper is to be used for fucntions that operate on individual
lightcurves.
Functions in the registry of analysis function for lightcurves need
some metadata for make sure that they can be called correctly, when
:class:`atlas.YSOVAR_atlas` autogenerated columns in the table.
This class warps a function and provides some metadata.
This metadata includes:
- The number of bands the function requires as input.
- Does the function require the uncertainty of the mags?
- Does the function require the time of the observations?
- What is the name of the function, so that it can be found?
- Some short description of the function.
- Default names for the columns that are autogenerated.
Use the following command to read the full docstring of the function
that is wrapped in this object::
help(my_object.func)
.. note::
This class is usually not called directly.
Use :func:`YSOVAR.registry.register`.
'''
''' hold default keyword arguments for this function'''
kwargs = {}
def __init__(self, func, n_bands, error, time, name = '',
default_colnames = [], default_colunits=[None], default_coldescriptions=None, other_cols = dict(), description = '', kwargs = {}):
'''Wrap function for the lightcurve analysis function registry
Parameters
----------
func : function or callable object
This function will be called.
n_bands : int
Number of spectral bands required by this function.
error : bool
If ``True`` the uncertainties in each lightcurve band will be passed
to the function.
time : bool
If ``True`` the observations times will be passed as first argument.
name : string
Set the name used to identify the function in the registry.
Default is the name of the function.
description : string
One line description of the function.
Default is the first line of the docstring of the function.
default_colnames : list of strings
Prefix used for naming auto-generated data columns in a :class:`YSOVAR_atlas`.
All generated columns are of type ``np.float``; this is just a
convenience, since most column are float columns. It is equally
possible to define each column with its datatype explicitly in
``other_col``.
The length of the list should equal the number of values returned by the
function. If neither this keyword nor ``other_col``is set,
it defaults to the name of the function. However, if the function
returns more than on output value then this keyword is required.
default_colunits : list of strings or None's
Default unit for auto-generated data columns. If not set, the unit
will be ``None``.
default_coldescriptions : list of strings or None
Default column description for auto-generated columns. Note that
this will often be different from ``description``, e.g. when a
function call generates more than one output value.
Nevertheless, if this keyword is not set, the first column will
have ``description`` and all further columns not receive a
descriptive text.
other_cols : Ordered dictionary
This dictionary fullfills the same role as ``default_colname``, but
if allows to specify ``{colname: dtype}`` pairs.
If both ``default_colname`` and ``other_col`` are present, then
the first values are assigned to the columns named in
``default_colname``.
kwargs : dictionary
This supplied keyword arguments that will be passed to ``func`` each
time it is called, unless the keyword of the same name is passed
when calling. Essentially, this provides a mechnism to
easily freeze a keyword argument.
'''
self.func = func
self.n_bands = n_bands
self.error = error
self.time = time
if name == '':
self.name = func.__name__
else:
self.name = name
if '_' in name:
raise ValueError('{0} contains an "_". This does not work for autogeneration of columns. Use name = name to speficy an alternative name.'.format(name))
if default_colnames == [] and other_cols == OrderedDict():
self.default_colnames = OrderedDict([[func.__name__, float]])
else:
self.default_colnames = OrderedDict(
zip(default_colnames, [float]*len(default_colnames)))
self.default_colnames.update(other_cols)
if description == '':
# Find first non-empty line in description
descr = func.__doc__.split('\n')
# Just to safeguard for empty docstrings
try:
self.description = descr.pop(0).strip()
while self.description == '':
self.description = descr.pop(0).strip()
except IndexError:
pass
else:
self.description = description
self.default_colunits = default_colunits
self.default_coldescriptions = [self.description] if (default_coldescriptions is None) else default_coldescriptions
self.kwargs = kwargs
def __call__(self, *args, **kwargs):
pass_args = self.kwargs.copy()
pass_args.update(kwargs)
return self.func(*args, **pass_args)
def __str__(self):
return '{0:10s} - {1}'.format(self.name, self.description)
