def evaluate(self, dataTable, functionTable, performanceTable, arguments):
arguments = [x.evaluate(dataTable, functionTable, performanceTable) for x in arguments]
performanceTable.begin("built-in \"%s\"" % self.name)
fieldType = self.fieldTypeFromSignature(arguments)
left, right = arguments
dataColumn = DataColumn(fieldType, NP("arctan2", left.data, right.data), DataColumn.mapAnyMissingInvalid([left.mask, right.mask]))
performanceTable.end("built-in \"%s\"" % self.name)
return dataColumn
def evaluate(self, dataTable, functionTable, performanceTable,
arguments):
arguments = [
x.evaluate(dataTable, functionTable, performanceTable)
for x in arguments
]
performanceTable.begin("built-in \"%s\"" % self.name)
fieldType = self.fieldTypeFromSignature(arguments)
left, right = arguments
dataColumn = DataColumn(
fieldType, NP("arctan2", left.data, right.data),
DataColumn.mapAnyMissingInvalid([left.mask, right.mask]))
performanceTable.end("built-in \"%s\"" % self.name)
return dataColumn
def evaluate(self, dataTable, functionTable, performanceTable,
arguments):
arguments = [
x.evaluate(dataTable, functionTable, performanceTable)
for x in arguments
]
performanceTable.begin("built-in \"%s\"" % self.name)
fieldType = self.fieldTypeFromSignature(arguments)
dataColumn = DataColumn(
fieldType, NP("cos", arguments[0].data * arguments[1].data),
DataColumn.mapAnyMissingInvalid(
[arguments[0].mask, arguments[1].mask]))
performanceTable.end("built-in \"%s\"" % self.name)
return dataColumn
def evaluate(self, dataTable, functionTable, performanceTable, arguments):
arguments = [x.evaluate(dataTable, functionTable, performanceTable) for x in arguments]
performanceTable.begin("built-in \"%s\"" % self.name)
fieldType = self.fieldTypeFromSignature(arguments)
left, right = arguments
zeroDenominators = NP(NP(right.data == 0.0) * defs.INVALID)
if not zeroDenominators.any():
zeroDenominators = None
mask = DataColumn.mapAnyMissingInvalid([zeroDenominators, left.mask, right.mask])
dataColumn = DataColumn(fieldType, NP("floor_divide", left.data, right.data), mask)
performanceTable.end("built-in \"%s\"" % self.name)
return dataColumn
def evaluate(self, dataTable, functionTable, performanceTable, arguments):
arguments = [x.evaluate(dataTable, functionTable, performanceTable) for x in arguments]
performanceTable.begin("built-in \"%s\"" % self.name)
fieldType = self.fieldTypeFromSignature(arguments)
test, low, high = arguments
if test.fieldType.dataType == "object" or (test.fieldType.dataType == "string" and test.fieldType.optype == "continuous" and low.fieldType.optype == "continuous"):
ld = test.data
rd = low.data
data = NP("fromiter", (ld[i] >= rd[i] for i in xrange(len(dataTable))), dtype=fieldType.dtype, count=len(dataTable))
elif test.fieldType.dataType == "string":
ld = test.data
rd = low.data
l2s = test.fieldType.valueToString
r2s = low.fieldType.valueToString
data = NP("fromiter", (l2s(ld[i]) >= r2s(rd[i]) for i in xrange(len(dataTable))), dtype=fieldType.dtype, count=len(dataTable))
else:
data = NP("greater_equal", test.data, low.data)
if test.fieldType.dataType == "object" or (test.fieldType.dataType == "string" and test.fieldType.optype == "continuous" and high.fieldType.optype == "continuous"):
ld = test.data
rd = high.data
datahigh = NP("fromiter", (ld[i] <= rd[i] for i in xrange(len(dataTable))), dtype=fieldType.dtype, count=len(dataTable))
elif test.fieldType.dataType == "string":
ld = test.data
rd = high.data
l2s = test.fieldType.valueToString
r2s = high.fieldType.valueToString
datahigh = NP("fromiter", (l2s(ld[i]) <= r2s(rd[i]) for i in xrange(len(dataTable))), dtype=fieldType.dtype, count=len(dataTable))
else:
datahigh = NP("less_equal", test.data, high.data)
NP("logical_and", data, datahigh, data)
performanceTable.end("built-in \"%s\"" % self.name)
return DataColumn(fieldType, data, DataColumn.mapAnyMissingInvalid([test.mask, low.mask, high.mask]))
def evaluate(self, dataTable, functionTable, performanceTable,
arguments):
arguments = [
x.evaluate(dataTable, functionTable, performanceTable)
for x in arguments
]
performanceTable.begin("built-in \"%s\"" % self.name)
fieldType = self.fieldTypeFromSignature(arguments)
left, right = arguments
zeroDenominators = NP(NP(right.data == 0.0) * defs.INVALID)
if not zeroDenominators.any():
zeroDenominators = None
mask = DataColumn.mapAnyMissingInvalid(
[zeroDenominators, left.mask, right.mask])
dataColumn = DataColumn(fieldType,
NP("floor_divide", left.data, right.data),
mask)
performanceTable.end("built-in \"%s\"" % self.name)
return dataColumn
def evaluate(self, dataTable, functionTable, performanceTable,
arguments):
arguments = [
x.evaluate(dataTable, functionTable, performanceTable)
for x in arguments
]
performanceTable.begin("built-in \"%s\"" % self.name)
fieldType = self.fieldTypeFromSignature(arguments)
test, low, high = arguments
if test.fieldType.dataType == "object" or (
test.fieldType.dataType == "string"
and test.fieldType.optype == "continuous"
and low.fieldType.optype == "continuous"):
ld = test.data
rd = low.data
data = NP("fromiter",
(ld[i] >= rd[i] for i in xrange(len(dataTable))),
dtype=fieldType.dtype,
count=len(dataTable))
elif test.fieldType.dataType == "string":
ld = test.data
rd = low.data
l2s = test.fieldType.valueToString
r2s = low.fieldType.valueToString
data = NP("fromiter", (l2s(ld[i]) >= r2s(rd[i])
for i in xrange(len(dataTable))),
dtype=fieldType.dtype,
count=len(dataTable))
else:
data = NP("greater_equal", test.data, low.data)
if test.fieldType.dataType == "object" or (
test.fieldType.dataType == "string"
and test.fieldType.optype == "continuous"
and high.fieldType.optype == "continuous"):
ld = test.data
rd = high.data
datahigh = NP("fromiter",
(ld[i] <= rd[i] for i in xrange(len(dataTable))),
dtype=fieldType.dtype,
count=len(dataTable))
elif test.fieldType.dataType == "string":
ld = test.data
rd = high.data
l2s = test.fieldType.valueToString
r2s = high.fieldType.valueToString
datahigh = NP("fromiter", (l2s(ld[i]) <= r2s(rd[i])
for i in xrange(len(dataTable))),
dtype=fieldType.dtype,
count=len(dataTable))
else:
datahigh = NP("less_equal", test.data, high.data)
NP("logical_and", data, datahigh, data)
performanceTable.end("built-in \"%s\"" % self.name)
return DataColumn(
fieldType, data,
DataColumn.mapAnyMissingInvalid(
[test.mask, low.mask, high.mask]))
def evaluate(self, dataTable, functionTable, performanceTable, arguments):
arguments = [x.evaluate(dataTable, functionTable, performanceTable) for x in arguments]
performanceTable.begin("built-in \"%s\"" % self.name)
fieldType = self.fieldTypeFromSignature(arguments)
dataColumn = DataColumn(fieldType, NP("cos", arguments[0].data * arguments[1].data), DataColumn.mapAnyMissingInvalid([arguments[0].mask, arguments[1].mask]))
performanceTable.end("built-in \"%s\"" % self.name)
return dataColumn
