# Check if a field is arrayed
# i.e. there can be multiple values
# selected for it.
field_array_max = r.get('array_max')
if field_array_max == 0:
field_array_max = 1
for i in range(field_instance_max):
for a in range(field_array_max):
field_canonical_name = helpers.gen_field_name(field_id, i, a, args.human)
dummy_values = helpers.gen_dummy_data_for_field(
field_id,
TOTAL_PATIENTS)
if args.human:
dummy_values = helpers.decode_values(dummy_values, field_id)
if args.jitter > 0:
dummy_values = helpers.insert_missingness(
dummy_values,
args.jitter)
df_output[field_canonical_name] = dummy_values
df_output.to_csv(args.out, index=False)
print("Wrote %s shape (%d,%d)." % (
args.out,
df_output.shape[0],
df_output.shape[1]))
def test_missing():
a = np.random.randint(0, 100, 100).tolist()
new_a = helpers.insert_missingness(a, 10)
assert pytest.approx(new_a.count(np.nan), 2) == 10