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Create new disutility params #170

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Create new disutility params #170

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619f6e5
Heterogenous disutility.
MaxBlesch Mar 30, 2023
97f661e
Updated u update vault.
MaxBlesch Mar 30, 2023
bb4a4f2
Updated u update vault.
MaxBlesch Mar 30, 2023
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15 changes: 10 additions & 5 deletions soepy/pre_processing/model_processing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -98,11 +98,16 @@ def group_parameters(model_params_dict_expanded):
dtype=float,
)

for key_ in list(model_params_dict_expanded["disutil_work"].keys()):
if "child" in key_:
model_params_dict_flat[key_] = model_params_dict_expanded["disutil_work"][
key_
]
for i in ["child_0_2_", "child_3_5_", "child_6_10_"]:
for j in ["f", "p"]:
model_params_dict_flat[i + j] = np.array(
[
model_params_dict_expanded["disutil_work"][i + j + "_educ_low"],
model_params_dict_expanded["disutil_work"][i + j + "_educ_middle"],
model_params_dict_expanded["disutil_work"][i + j + "_educ_high"],
],
dtype=float,
)

for i in ["no", "yes"]:
for j in ["f", "p"]:
Expand Down
32 changes: 23 additions & 9 deletions soepy/shared/shared_auxiliary.py
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Original file line number Diff line number Diff line change
Expand Up @@ -93,9 +93,11 @@ def calculate_log_wage_systematic(


@numba.guvectorize(
["f8[:],f8[:],f8[:],f8[:],f8[:],f8[:],f8,f8,f8,f8,f8,f8,i8[:], f8, f8[:], f8[:]"],
[
"f8[:],f8[:],f8[:],f8[:],f8[:],f8[:],f8[:],f8[:],f8[:],f8[:],f8[:],f8[:],i8[:], f8, f8[:], f8[:]"
],
"(num_unobs_types),(num_unobs_types), (num_edu_types),(num_edu_types),"
"(num_edu_types),(num_edu_types), (),(),(),(),(),(),(num_state_vars),"
"(num_edu_types),(num_edu_types), (num_edu_types),(num_edu_types),(num_edu_types),(num_edu_types),(num_edu_types),(num_edu_types),(num_state_vars),"
"(),(num_choices)->(num_choices)",
nopython=True,
target="cpu",
Expand Down Expand Up @@ -129,24 +131,36 @@ def calculate_non_consumption_utility(
non_consumption_utility_state[2] += no_kids_f[educ_level]
elif child_bin == 1:
non_consumption_utility_state[1] += (
yes_kids_f[educ_level] + yes_kids_p[educ_level] + child_0_2_f + child_0_2_p
yes_kids_f[educ_level]
+ yes_kids_p[educ_level]
+ child_0_2_f[educ_level]
+ child_0_2_p[educ_level]
)

non_consumption_utility_state[2] += yes_kids_f[educ_level] + child_0_2_f
non_consumption_utility_state[2] += (
yes_kids_f[educ_level] + child_0_2_f[educ_level]
)
elif child_bin == 2:
non_consumption_utility_state[1] += (
yes_kids_f[educ_level] + yes_kids_p[educ_level] + child_3_5_f + child_3_5_p
yes_kids_f[educ_level]
+ yes_kids_p[educ_level]
+ child_3_5_f[educ_level]
+ child_3_5_p[educ_level]
)
non_consumption_utility_state[2] += (
yes_kids_f[educ_level] + child_3_5_f[educ_level]
)
non_consumption_utility_state[2] += yes_kids_f[educ_level] + child_3_5_f

elif child_bin == 3:
non_consumption_utility_state[1] += (
yes_kids_f[educ_level]
+ yes_kids_p[educ_level]
+ child_6_10_f
+ child_6_10_p
+ child_6_10_f[educ_level]
+ child_6_10_p[educ_level]
)
non_consumption_utility_state[2] += (
yes_kids_f[educ_level] + child_6_10_f[educ_level]
)
non_consumption_utility_state[2] += yes_kids_f[educ_level] + child_6_10_f
else: # Mothers with kids older than 10 only get fixed disutility
non_consumption_utility_state[1] += (
yes_kids_f[educ_level] + yes_kids_p[educ_level]
Expand Down
28 changes: 20 additions & 8 deletions soepy/test/random_init.py
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Original file line number Diff line number Diff line change
Expand Up @@ -192,10 +192,16 @@ def random_init(constr=None):
model_params_init_dict["yes_kids_f_educ_low"],
model_params_init_dict["yes_kids_f_educ_middle"],
model_params_init_dict["yes_kids_f_educ_high"],
model_params_init_dict["child_0_2_f"],
model_params_init_dict["child_3_5_f"],
model_params_init_dict["child_6_10_f"],
) = np.random.uniform(0.001, 0.2, 9).tolist()
model_params_init_dict["child_0_2_f_educ_high"],
model_params_init_dict["child_3_5_f_educ_high"],
model_params_init_dict["child_6_10_f_educ_high"],
model_params_init_dict["child_0_2_f_educ_middle"],
model_params_init_dict["child_3_5_f_educ_middle"],
model_params_init_dict["child_6_10_f_educ_middle"],
model_params_init_dict["child_0_2_f_educ_low"],
model_params_init_dict["child_3_5_f_educ_low"],
model_params_init_dict["child_6_10_f_educ_low"],
) = np.random.uniform(0.001, 0.2, 15).tolist()

(
model_params_init_dict["no_kids_p_educ_low"],
Expand All @@ -204,10 +210,16 @@ def random_init(constr=None):
model_params_init_dict["yes_kids_p_educ_low"],
model_params_init_dict["yes_kids_p_educ_middle"],
model_params_init_dict["yes_kids_p_educ_high"],
model_params_init_dict["child_0_2_p"],
model_params_init_dict["child_3_5_p"],
model_params_init_dict["child_6_10_p"],
) = np.random.uniform(-1.5, -0.001, 9).tolist()
model_params_init_dict["child_0_2_p_educ_high"],
model_params_init_dict["child_3_5_p_educ_high"],
model_params_init_dict["child_6_10_p_educ_high"],
model_params_init_dict["child_0_2_p_educ_middle"],
model_params_init_dict["child_3_5_p_educ_middle"],
model_params_init_dict["child_6_10_p_educ_middle"],
model_params_init_dict["child_0_2_p_educ_low"],
model_params_init_dict["child_3_5_p_educ_low"],
model_params_init_dict["child_6_10_p_educ_low"],
) = np.random.uniform(-1.5, -0.001, 15).tolist()

model_params_init_dict["delta"] = np.random.uniform(0.8, 0.99)
model_params_init_dict["mu"] = np.random.uniform(-0.7, -0.4)
Expand Down
Binary file modified soepy/test/resources/regression_vault.soepy.pkl
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19 changes: 12 additions & 7 deletions soepy/test/test_childless.py
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Original file line number Diff line number Diff line change
Expand Up @@ -69,16 +69,21 @@ def input_data():
)

params_ind_list = [
("disutil_work", "yes_kids_f_educ_middle"),
("disutil_work", "yes_kids_p_educ_middle"),
("disutil_work", "yes_kids_p_educ_low"),
("disutil_work", "yes_kids_p_educ_high"),
("disutil_work", "child_0_2_f"),
("disutil_work", "child_3_5_f"),
("disutil_work", "yes_kids_f_educ_"),
("disutil_work", "yes_kids_p_educ_"),
("disutil_work", "child_0_2_f_educ_"),
("disutil_work", "child_3_5_f_educ_"),
("disutil_work", "child_6_10_f_educ_"),
("disutil_work", "child_0_2_p_educ_"),
("disutil_work", "child_3_5_p_educ_"),
("disutil_work", "child_6_10_p_educ_"),
]

for param_ind in params_ind_list:
model_params_df.loc[param_ind, "value"] *= factor
for educ in ["low", "middle", "high"]:
model_params_df.loc[
(param_ind[0], param_ind[1] + educ), "value"
] *= factor

model_spec = read_model_spec_init(model_spec_init_dict, model_params_df)

Expand Down