Hacktoberfest 2026: los issues que los mantenedores marcaron para octubre, abiertos y aptos para principiantes. Explorar issues de Hacktoberfest

(test) [cagan_adaptive] DRAFT report from tool-onboarding (action-translation)

Abierto
  • ¿Algo no está bien?
#677 5 comentarios 0 reacciones 0 asignados Ver en GitHub

Los mantenedores suelen responder en 1 día

Nadie ha tomado este issue todavía.

Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
28/100
Tipo de issue
Documentación
Claridad
Bastante claro
Estado de actividad
Estancado
Stack tecnológico
jupyter-notebook, python
Área
documentation, localization

Línea de trabajo

Comienza con cagan_adaptive.md y compara las secciones y los bloques de código indicados entre lecture-python-intro y lecture-intro.zh-cn, empezando por §§4–7 y la tabla de Code Action. Revisa cada diferencia y determina si debe sincronizarse, retroportarse, aceptarse o revisarse manualmente. Hecho significa que las decisiones de traducción están resueltas y no queda ninguna diferencia indicada sin explicación.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

cagan_adaptive.md

Property Value
Source lecture-python-intro
Target lecture-intro.zh-cn
Source Date 2024-07-19
Target Date 2025-03-12
Direction ← Target newer
Status ⚠️ Review
Recommendation MANUAL REVIEW (complex changes detected)

Summary

8 aligned, 12 issues in 4 sections

Section Type Status Issue Links
§1 Section ✅ - -
§2 Section ✅ - -
§3 Section ✅ - -
§4 Title ⚠️ DIFFERS Differs View / Action
§5 Title ⚠️ DIFFERS Differs View / Action
§5 Content ⚠️ DIFFERS Differs View / Action
§5 Code B1 ⚠️ DIFFERS Function names View / Action
§5 Code B2 ⚠️ DIFFERS Code differs View / Action
§5 Code B3 ⚠️ DIFFERS Function names View / Action
§6 Code B4 ⚠️ DIFFERS Code differs View / Action
§7 Content ⚠️ DIFFERS Differs View / Action
§7 Code T7 🔵 INSERTED Extra View / Action
§7 Code B5 ⚠️ DIFFERS Code differs View / Action
§7 Code T8 🔵 INSERTED Extra View / Action
§7 Code B6 ⚠️ DIFFERS Code differs View / Action
§8 Section ✅ - -
§9 Section ✅ - -
§10 Section ✅ - -
§11 Section ✅ - -
§12 Section ✅ - -

Code Action
Source Target Status Recommendation Details
1 1 ⚠️ DIFFERS BACKPORT View
2 2 ⚠️ DIFFERS BACKPORT View
3 3 ⚠️ DIFFERS BACKPORT View
4 4 ⚠️ DIFFERS BACKPORT View
- 7 🔵 INSERTED BACKPORT View
5 5 ⚠️ DIFFERS BACKPORT View
- 8 🔵 INSERTED BACKPORT View
6 6 ⚠️ DIFFERS BACKPORT View

Recommendation: BACKPORT

Target code appears improved. Review for backport to source.

Action:

  • SYNC code from source
  • BACKPORT improvements to source (unanimous)
  • ACCEPT current target code
  • MANUAL review needed

Section Review

📅 Target is newer (2025-03-12 vs 2024-07-19) - translation may contain improvements

§4 Harvesting insights from our matrix formulation
§4 Title: Harvesting insights from our matrix formulation → 求解模型

Status: ⚠️ DIFFERS | Issue: Differs

Notes:

  • Issue: "Harvesting insights from our matrix formulation" is metaphorical and exploratory, while "求解模型" (Solving the model) is more direct and procedural, losing the nuance of extracting understanding from the mathematical structure
  • Fix: Consider "从矩阵表达式中获得洞见" or "矩阵公式推导及求解" to better capture the original emphasis on gaining insights through the formulation process

Action:

  • SYNC (recommended)
  • BACKPORT
  • ACCEPT
  • MANUAL
§5 Forecast errors and model computation
§5 Title: Forecast errors and model computation → 预期与实际通货膨胀的差异

Status: ⚠️ DIFFERS | Issue: Differs

Notes:

  • Issue: "Forecast errors and model computation" encompasses both the conceptual issue of forecast errors and computational aspects, while "预期与实际通货膨胀的差异" (Differences between expected and actual inflation) focuses only on one aspect
  • Fix: Use "预测误差与模型计算" to maintain both concepts

Action:

  • SYNC
  • BACKPORT
  • ACCEPT
  • MANUAL (recommended)
§5 Content: Forecast errors and model computation → 预期与实际通货膨胀的差异

Status: ⚠️ DIFFERS | Issue: Differs

Notes:

  • Issue: Target adds extensive explanatory paragraphs (explaining adaptive expectations characteristics, contrasting with rational expectations) that are not present in the concise source text
  • Fix: Remove the added interpretive paragraphs to match the source's brevity and direct transition to code

Action:

  • SYNC
  • BACKPORT
  • ACCEPT
  • MANUAL (recommended)

Code Block 1 - ⚠️ DIFFERS | Function names differ

Source:

Cagan_Adaptive = namedtuple("Cagan_Adaptive", 
                        ["α", "m0", "Eπ0", "T", "λ"])

def create_cagan_adaptive_model(α = 5, m0 = 1, Eπ0 = 0.5, T=80, λ = 0.9):
    return Cagan_Adaptive(α, m0, Eπ0, T, λ)

md = create_cagan_adaptive_model()

Target:

Cagan_Adaptive = namedtuple("Cagan_Adaptive", 
                        ["α", "m0", "Eπ0", "T", "λ"])

def create_cagan_model(α, m0, Eπ0, T, λ):
    return Cagan_Adaptive(α, m0, Eπ0, T, λ)

Code Block 2 - ⚠️ DIFFERS | Code logic differs

Source:

def solve_cagan_adaptive(model, μ_seq):
    " Solve the Cagan model in finite time. "
    α, m0, Eπ0, T, λ = model
    
    A = np.eye(T+2, T+2) - λ*np.eye(T+2, T+2, k=-1)
    B = np.eye(T+2, T+1, k=-1)
    C = -α*np.eye(T+1, T+2) + α*np.eye(T+1, T+2, k=1)
    Eπ0_seq = np.append(Eπ0, np.zeros(T+1))

    # Eπ_seq is of length T+2
    Eπ_seq = np.linalg.solve(A - (1-λ)*B @ C, (1-λ) * B @ μ_seq + Eπ0_seq)

    # π_seq is of length T+1
    π_seq = μ_seq + C @ Eπ_seq

    D = np.eye(T+1, T+1) - np.eye(T+1, T+1, k=-1) # D is the coefficient matrix in Equation (14.8)
    m0_seq = np.append(m0, np.zeros(T))

    # m_seq is of length T+2
    m_seq = np.linalg.solve(D, μ_seq + m0_seq)
    m_seq = np.append(m0, m_seq)

    # p_seq is of length T+2
    p_seq = m_seq + α * Eπ_seq

    return π_seq, Eπ_seq, m_seq, p_seq

Target:

# 参数
T = 80
T1 = 60
α = 5
λ = 0.9
m0 = 1

μ0 = 0.5
μ_star = 0

md = create_cagan_model(α=α, m0=m0, Eπ0=μ0, T=T, λ=λ)

Code Block 3 - ⚠️ DIFFERS | Function names differ

Source:

def solve_and_plot(model, μ_seq):
    
    π_seq, Eπ_seq, m_seq, p_seq = solve_cagan_adaptive(model, μ_seq)
    
    T_seq = range(model.T+2)
    
    fig, ax = plt.subplots(5, 1, figsize=[5, 12], dpi=200)
    ax[0].plot(T_seq[:-1], μ_seq)
    ax[1].plot(T_seq[:-1], π_seq, label=r'$\pi_t$')
    ax[1].plot(T_seq, Eπ_seq, label=r'$\pi^{*}_{t}$')
    ax[2].plot(T_seq, m_seq - p_seq)
    ax[3].plot(T_seq, m_seq)
    ax[4].plot(T_seq, p_seq)
    
    y_labs = [r'$\mu$', r'$\pi$', r'$m - p$', r'$m$', r'$p$']
    subplot_title = [r'Money supply growth', r'Inflation', r'Real balances', r'Money supply', r'Price level']

    for i in range(5):
        ax[i].set_xlabel(r'$t$')
        ax[i].set_ylabel(y_labs[i])
        ax[i].set_title(subplot_title[i])

    ax[1].legend()
    plt.tight_layout()
    plt.show()
    
    return π_seq, Eπ_seq, m_seq, p_seq

Target:

def solve(model, μ_seq):
    "在求解有限视界的凯根模型"
    
    model_params = model.α, model.m0, model.Eπ0, model.T, model.λ
    α, m0, Eπ0, T, λ = model_params
    
    A = np.eye(T+2, T+2) - λ*np.eye(T+2, T+2, k=-1)
    B = np.eye(T+2, T+1, k=-1)
    C = -α*np.eye(T+1, T+2) + α*np.eye(T+1, T+2, k=1)
    Eπ0_seq = np.append(Eπ0, np.zeros(T+1))

    # Eπ_seq 的长度为 T+2
    Eπ_seq = np.linalg.inv(A - (1-λ)*B @ C) @ ((1-λ) * B @ μ_seq + Eπ0_seq)

    # π_seq 的长度为 T+1
    π_seq = μ_seq + C @ Eπ_seq

    D = np.eye(T+1, T+1) - np.eye(T+1, T+1, k=-1)
    m0_seq = np.append(m0, np.zeros(T))

    # m_seq 的长度为 T+2
    m_seq = np.linalg.inv(D) @ (μ_seq + m0_seq)
    m_seq = np.append(m0, m_seq)

    # p_seq 的长度为 T+2
    p_seq = m_seq + α * Eπ_seq

    return π_seq, Eπ_seq, m_seq, p_seq

Code Block 4 - ⚠️ DIFFERS | Code logic differs

Source:

print(np.abs((md.λ - md.α*(1-md.λ))/(1 - md.α*(1-md.λ))))

Target:

def solve_and_plot(model, μ_seq):
    
    π_seq, Eπ_seq, m_seq, p_seq = solve(model, μ_seq)
    
    T_seq = range(model.T+2)
    
    fig, ax = plt.subplots(5, 1, figsize=[5, 12], dpi=200)
    ax[0].plot(T_seq[:-1], μ_seq)
    ax[1].plot(T_seq[:-1], π_seq, label=r'$\pi_t$')
    ax[1].plot(T_seq, Eπ_seq, label=r'$\pi^{*}_{t}$')
    ax[2].plot(T_seq, m_seq - p_seq)
    ax[3].plot(T_seq, m_seq)
    ax[4].plot(T_seq, p_seq)
    
    y_labs = [r'$\mu$', r'$\pi$', r'$m - p$', r'$m$', r'$p$']

    for i in range(5):
        ax[i].set_xlabel(r'$t$')
        ax[i].set_ylabel(y_labs[i])

    ax[1].legend()
    plt.tight_layout()
    plt.show()
    
    return π_seq, Eπ_seq, m_seq, p_seq
§7 (Code block 2 - model creation)
§7 Content: (Code block 2 - model creation) → (Code block 2 - model creation with parameters)

Status: ⚠️ DIFFERS | Issue: Differs

Notes:

  • Issue: Target version inserts additional explanatory code block defining parameters (T, T1, α, λ, m0, μ0, μ_star) and instantiating model with md = create_cagan_model(...) before the solve functions, while source shows model creation without parameter definitions at this point
  • Fix: Remove the inserted parameter definition block to align with source structure where parameters appear later in the experiments section

Action:

  • SYNC
  • BACKPORT
  • ACCEPT
  • MANUAL (recommended)

Code Block T7 - 🔵 INSERTED | Extra block in target

Target:

μ_seq_1 = np.append(μ0*np.ones(T1), μ_star*np.ones(T+1-T1))

# 求解并绘图
π_seq_1, Eπ_seq_1, m_seq_1, p_seq_1 = solve_and_plot(md, μ_seq_1)

This block exists only in target - not in source.

Code Block 5 - ⚠️ DIFFERS | Code logic differs

Source:

# Parameters for the experiment 1
T1 = 60
μ0 = 0.5
μ_star = 0

μ_seq_1 = np.append(μ0*np.ones(T1), μ_star*np.ones(md.T+1-T1))

# solve and plot
π_seq_1, Eπ_seq_1, m_seq_1, p_seq_1 = solve_and_plot(md, μ_seq_1)

Target:

print(np.abs((λ - α*(1-λ))/(1 - α*(1-λ))))

Code Block T8 - 🔵 INSERTED | Extra block in target

Target:

# 参数
ϕ = 0.9
μ_seq_2 = np.array([ϕ**t * μ0 + (1-ϕ**t)*μ_star for t in range(T)])
μ_seq_2 = np.append(μ_seq_2, μ_star)


# 求解并绘图
π_seq_2, Eπ_seq_2, m_seq_2, p_seq_2 = solve_and_plot(md, μ_seq_2)

This block exists only in target - not in source.

Code Block 6 - ⚠️ DIFFERS | Code logic differs

Source:

# parameters
ϕ = 0.9
μ_seq_2 = np.array([ϕ**t * μ0 + (1-ϕ**t)*μ_star for t in range(md.T)])
μ_seq_2 = np.append(μ_seq_2, μ_star)


# solve and plot
π_seq_2, Eπ_seq_2, m_seq_2, p_seq_2 = solve_and_plot(md, μ_seq_2)

Target:

print(λ - α*(1-λ))
Lenguaje dominante
Jupyter Notebook
Estrellas
65
Forks
31
Merge medio
2 d 15 h
PR fusionados (30 d)
11

Preparar el entorno

Este proyecto no incluye contenedor de desarrollo, Dockerfile ni guía de contribución, así que la configuración corre por tu cuenta: empieza por su README y consulta nuestra guía para la primera contribución para los pasos generales.

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

Más de QuantEcon/lecture-python-intro

Todos los issues de QuantEcon/lecture-python-intro

Issues similares

Más issues de Documentation

Recibe los nuevos issues en tu correo

Un resumen breve de issues de GitHub para principiantes.