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 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()
def test_parameters_pd(self):
schema = test_schema + "_parameters_pd"
pdf = PanDatFactory(parameters=[["Key"], ["Value"]])
pdf.add_parameter("Something", 100)
pdf.add_parameter("Different",
'boo',
strings_allowed='*',
number_allowed=False)
dat = TicDatFactory(**pdf.schema()).TicDat(
parameters=[["Something", float("inf")], ["Different", "inf"]])
dat = TicDatFactory(**pdf.schema()).copy_to_pandas(
dat, drop_pk_columns=False)
pdf.pgsql.write_schema(self.engine, schema)
pdf.pgsql.write_data(dat, self.engine, schema)
dat_ = pdf.pgsql.create_pan_dat(self.engine, schema)
self.assertTrue(pdf._same_data(dat, dat_))
var Buy {j in FOOD} >= 0;
var Consume {i in CAT } >= n_min [i], <= n_max [i];
minimize Total_Cost: sum {j in FOOD} cost[j] * Buy[j];
subject to Diet {i in CAT}:
Consume[i] = sum {j in FOOD} (amt[j,i] + other_amt[j,i]) * Buy[j];
"""
_diet_input_pdf = PanDatFactory(
categories=[["Name"], ["Min Nutrition", "Max Nutrition"]],
foods=[["Name"], ["Cost"]],
nutrition_quantities=[["Food", "Category"], ["Quantity",
"Other Quantity"]])
_diet_pan_dat_from_dict = lambda pd_dict: _pan_dat_maker_from_dict(
_diet_input_pdf.schema(), pd_dict)
_diet_dat = _pan_dat_maker_from_dict(
_diet_input_pdf.schema(), {
'categories': {
u'calories': {
'Max Nutrition': 2200.0,
'Min Nutrition': 1800
},
u'fat': {
'Max Nutrition': 65.0,
'Min Nutrition': 0
},
u'protein': {
'Max Nutrition': float('inf'),
'Min Nutrition': 91
},