def test_nullables(self):
schema = test_schema + "nullables"
pdf = PanDatFactory(table_with_stuffs=[["field one"], ["field two"]])
pdf.set_data_type("table_with_stuffs", "field one")
pdf.set_data_type("table_with_stuffs",
"field two",
number_allowed=False,
strings_allowed='*',
nullable=True)
tdf = TicDatFactory.create_from_full_schema(
pdf.schema(include_ancillary_info=True))
tic_dat = tdf.TicDat(
table_with_stuffs=[[101, "022"], [202, None], [303, "111"]])
dat = tdf.copy_to_pandas(tic_dat, drop_pk_columns=False)
self.assertFalse(tdf.find_data_type_failures(tic_dat))
self.assertFalse(pdf.find_data_type_failures(dat))
pdf.pgsql.write_schema(self.engine, schema)
pdf.pgsql.write_data(dat, self.engine, schema)
dat_1 = pdf.pgsql.create_pan_dat(self.engine, schema)
self.assertTrue(
pdf._same_data(dat, dat_1, nans_are_same_for_data_rows=True))
tic_dat_1 = tdf.pgsql.create_tic_dat(self.engine, schema)
self.assertTrue(
tdf._same_data(tic_dat,
tic_dat_1,
nans_are_same_for_data_rows=True))
def copy_from_ampl_variables(self, ampl_variables):
"""
copies the solution results from ampl_variables into a new PanDat object
:param ampl_variables: a dict mapping from (table_name, field_name) -> amplpy.variable.Variable
(amplpy.variable.Variable is the type object returned by
AMPL.getVariable)
table_name should refer to a table in the schema that has
primary key fields.
field_name can refer to a data field for table_name, or it
can be falsey. If the latter, then AMPL variables that
pass the filter (see below) will simply populate the primary key
of the table_name.
Note that by default, only non-zero data is copied over.
If you want to override this filter, then instead of mapping to
amplpy.variable.Variable you should map to a
(amplpy.variable.Variable, filter) where filter accepts a data value
and returns a boolean.
:return: a deep copy of the ampl_variables into a PanDat object
"""
# note that the possibility for multiple table_names with different field_names can make
# for a messy join problem. The easiest solution here is to just use the TicDatFactory logic
from ticdat import TicDatFactory
tdf = TicDatFactory.create_from_full_schema(self.schema(include_ancillary_info=True))
_rtn = tdf.copy_from_ampl_variables(ampl_variables)
_rtn = tdf.copy_to_pandas(_rtn, drop_pk_columns=False)
for t in self.all_tables:
getattr(_rtn, t).reset_index(drop=True, inplace=True)
rtn = self.PanDat(**{t:getattr(_rtn, t) for t in self.all_tables})
return rtn
def testIssue45(self):
schema = test_schema + "issue45"
pdf = PanDatFactory(data=[["a"], ["b"]])
pdf.set_data_type("data",
"b",
number_allowed=False,
strings_allowed='*')
tdf = TicDatFactory.create_from_full_schema(
pdf.schema(include_ancillary_info=True))
tic_dat = tdf.TicDat(data=[[2, "1"], [4, "3"], [44, "022"]])
dat = tdf.copy_to_pandas(tic_dat, drop_pk_columns=False)
self.assertFalse(tdf.find_data_type_failures(tic_dat))
self.assertFalse(pdf.find_data_type_failures(dat))
pdf.pgsql.write_schema(self.engine,
schema,
forced_field_types={("data", "a"): "integer"})
pdf.pgsql.write_data(dat, self.engine, schema)
def two_checks():
dat_1 = pdf.pgsql.create_pan_dat(self.engine, schema)
self.assertTrue(pdf._same_data(dat, dat_1))
tic_dat_1 = tdf.pgsql.create_tic_dat(self.engine, schema)
self.assertTrue(tdf._same_data(tic_dat, tic_dat_1))
two_checks()
tdf.pgsql.write_data(tic_dat, self.engine, schema)
two_checks()
