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🌐 [translation-sync] [ifp_advanced] Align K with the (c, a) convention used across the EGM lectures #212

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🌐 [translation-sync] [ifp_advanced] Align K with the (c, a) convention used across the EGM lectures #212

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5de7b18
Update translation: lectures/ifp_advanced.md
mmcky Jul 29, 2026
dcfe162
Update translation: .translate/state/ifp_advanced.md.yml
mmcky Jul 29, 2026
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4 changes: 2 additions & 2 deletions .translate/state/ifp_advanced.md.yml
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
source-sha: a4fbd8653600ac99163bfd5d4f7d98c1e613042e
synced-at: "2026-07-26"
source-sha: 60af4806201dc1bc99275122aea5b7dc7bd02a52
synced-at: "2026-07-29"
model: claude-sonnet-5
mode: UPDATE
section-count: 7
Expand Down
20 changes: 10 additions & 10 deletions lectures/ifp_advanced.md
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Original file line number Diff line number Diff line change
Expand Up @@ -366,8 +366,8 @@ def Y(z, η, a_y, b_y):

```{code-cell} ipython3
def K(
a_in: jnp.array, # a_in[i, z] 是资产网格
c_in: jnp.array, # c_in[i, z] = a_in[i, z] 处的消费
a_in: jnp.array, # a_in[i, z] 是资产网格
ifp: IFP
):
"""
Expand Down Expand Up @@ -408,7 +408,7 @@ def K(
c_out = c_out.at[0, :].set(0)
a_out = a_out.at[0, :].set(0)

return a_out, c_out
return c_out, a_out
```

下一个函数使用 JAX 通过时间迭代求解最优消费政策的近似：
Expand Down Expand Up @@ -464,15 +464,15 @@ a_init = σ_init.copy()
让我们用 JAX 生成一个近似解：

```{code-cell} ipython3
a_star, σ_star = solve_model(ifp, a_init, σ_init)
σ_star, a_star = solve_model(ifp, σ_init, a_init)
```

让我们再用计时器试一次。

```{code-cell} python3
with qe.Timer(precision=8):
a_star, σ_star = solve_model(ifp, a_init, σ_init)
a_star.block_until_ready()
σ_star, a_star = solve_model(ifp, σ_init, a_init)
σ_star.block_until_ready()
```

## 模拟
Expand Down Expand Up @@ -614,7 +614,7 @@ s_grid = ifp.s_grid
n_z = len(ifp.P)
a_init = s_grid[:, None] * jnp.ones(n_z)
c_init = a_init
a_vec, c_vec = solve_model(ifp, a_init, c_init)
c_vec, a_vec = solve_model(ifp, c_init, a_init)
assets = compute_asset_stationary(c_vec, a_vec, ifp, num_households=200_000)

# 为图形计算基尼系数
Expand Down Expand Up @@ -700,8 +700,8 @@ for a_r in a_r_vals:
n_z_temp = len(ifp_temp.P)
a_init_temp = s_grid_temp[:, None] * jnp.ones(n_z_temp)
c_init_temp = a_init_temp
a_vec_temp, c_vec_temp = solve_model(
ifp_temp, a_init_temp, c_init_temp
c_vec_temp, a_vec_temp = solve_model(
ifp_temp, c_init_temp, a_init_temp
)

# 模拟家庭
Expand Down Expand Up @@ -772,8 +772,8 @@ for a_y in a_y_vals:
n_z_temp = len(ifp_temp.P)
a_init_temp = s_grid_temp[:, None] * jnp.ones(n_z_temp)
c_init_temp = a_init_temp
a_vec_temp, c_vec_temp = solve_model(
ifp_temp, a_init_temp, c_init_temp
c_vec_temp, a_vec_temp = solve_model(
ifp_temp, c_init_temp, a_init_temp
)

# 模拟家庭
Expand Down
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