def __init__(self, inputs, *args, **kwargs):
# create a new converter from an operator
if len(args) == 3:
self.extra_op, self.oldname, self.newname = args
else:
self.extra_op, self.oldname, self.newname = None, None, None
self.converters = [lambda x: x] * len(inputs)
outputs = copy.deepcopy(inputs)
for i in xrange(0, len(inputs)):
if 'Properties/UnitofMeasure' in inputs[i]:
unit, converter = self.find_conversion(inputs[i])
# make a closure with the converter
def make_converter():
_converter = converter
if callable(_converter):
return _converter([inputs[i]])
else:
return lambda x: np.dstack((x[0][:, 0], _converter *
(x[0][:, 1])))
self.converters[i] = make_converter()
outputs[i]['Properties/UnitofMeasure'] = unit
Operator.__init__(self, inputs, outputs)
def __init__(self, inputs):
outputs = [{} for x in xrange(0, len(inputs))]
for i, stream in enumerate(inputs):
for k, v in stream.iteritems():
if not k.startswith('Metadata/'):
outputs[i][k] = v
Operator.__init__(self, inputs, outputs)
def __init__(self, inputs, *args, **kwargs):
# create a new converter from an operator
if len(args) == 3:
self.extra_op, self.oldname, self.newname = args
else:
self.extra_op, self.oldname, self.newname = None, None, None
self.converters = [lambda x: x] * len(inputs)
outputs = copy.deepcopy(inputs)
for i in xrange(0, len(inputs)):
if "Properties/UnitofMeasure" in inputs[i]:
unit, converter = self.find_conversion(inputs[i])
# make a closure with the converter
def make_converter():
_converter = converter
if callable(_converter):
return _converter([inputs[i]])
else:
return lambda x: np.dstack((x[0][:, 0], _converter * (x[0][:, 1])))
self.converters[i] = make_converter()
outputs[i]["Properties/UnitofMeasure"] = unit
Operator.__init__(self, inputs, outputs)
def __init__(self, inputs, cols="1", operator=None):
self.cols = make_colspec(cols)
self.ops = map(lambda x: operator([x]), inputs)
self.name = "catcol(%s, %s)" % (",".join(map(str, self.cols)), str(self.ops[0]))
# print self.cols, self.ops
Operator.__init__(self, inputs, operators.OP_N_TO_N)
def __init__(self, inputs):
outputs = [{} for x in xrange(0, len(inputs))]
for i, stream in enumerate(inputs):
for k, v in stream.iteritems():
if not k.startswith("Metadata/"):
outputs[i][k] = v
Operator.__init__(self, inputs, outputs)
def __init__(self, inputs, cols="1", operator=None):
self.cols = make_colspec(cols)
self.ops = map(lambda x: operator([x]), inputs)
self.name = 'catcol(%s, %s)' % (','.join(map(
str, self.cols)), str(self.ops[0]))
# print self.cols, self.ops
Operator.__init__(self, inputs, operators.OP_N_TO_N)
def __init__(self, inputs, tag, newname):
self.name = "rename(%s, %s)" % (tag, newname)
output = copy.deepcopy(inputs)
for s in output:
if tag in s:
s[newname] = s[tag]
del s[tag]
Operator.__init__(self, inputs, output)
def __init__(self, inputs, tag, newname):
self.name = 'rename(%s, %s)' % (tag, newname)
output = copy.deepcopy(inputs)
for s in output:
if tag in s:
s[newname] = s[tag]
del s[tag]
Operator.__init__(self, inputs, output)
def __init__(self, inputs, tag, newname, remove=True):
self.name = 'rename(%s, %s)' % (tag, newname)
output = copy.deepcopy(inputs)
for s in output:
if tag in s:
s[newname] = s[tag]
if remove:
del s[tag]
Operator.__init__(self, inputs, output)
def __init__(self, inputs):
# don't change uuids
Operator.__init__(self, inputs, inputs)
def __init__(self, inputs, key, value):
# don't change uuids
outputs = copy.deepcopy(inputs)
for o in outputs:
o[key] = value
Operator.__init__(self, inputs, outputs)
def __init__(self, inputs):
# don't change uuids
Operator.__init__(self, inputs, inputs)
def __init__(self, inputs, key, value):
# don't change uuids
outputs = copy.deepcopy(inputs)
for o in outputs:
o[key] = value
Operator.__init__(self, inputs, outputs)
def __init__(self, inputs, *vals, **kwargs):
tag = kwargs.get('tag', 'uuid')
keys = map(lambda x: x.get(tag, None), inputs)
self.order = map(lambda val: keys.index(val), vals)
Operator.__init__(self, inputs, [inputs[i] for i in self.order])
def __init__(self, inputs, *vals, **kwargs):
tag = kwargs.get('tag', 'uuid')
keys = map(lambda x: x.get(tag, None), inputs)
self.order = map(lambda val: keys.index(val), vals)
Operator.__init__(self, inputs, [inputs[i] for i in self.order])
def __init__(self, inputs, days="1,2,3,4,5"):
self.days = map(int, days.split(','))
self.tzs = map(lambda x: dtutil.gettz(x['Properties/Timezone']),
inputs)
Operator.__init__(self, inputs, OP_N_TO_N)
