From bb92a906d8c02e4ab134bb58ba9095b7025af75f Mon Sep 17 00:00:00 2001 From: dedwar65 Date: Tue, 27 Feb 2024 15:02:43 -0500 Subject: [PATCH] show bug --- .../ConsBequestModel/example.ConsPortfolioComp.ipynb | 10 +++++----- .../ConsBequestModel/example_ConsIndShockComp.ipynb | 2 +- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/examples/ConsBequestModel/example.ConsPortfolioComp.ipynb b/examples/ConsBequestModel/example.ConsPortfolioComp.ipynb index 9f0586459..719fd8cc8 100644 --- a/examples/ConsBequestModel/example.ConsPortfolioComp.ipynb +++ b/examples/ConsBequestModel/example.ConsPortfolioComp.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 5, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -19,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -30,7 +30,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -40,7 +40,7 @@ "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[21], line 7\u001b[0m\n\u001b[1;32m 4\u001b[0m beq_type\u001b[38;5;241m.\u001b[39mTermBeqFac \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m 5\u001b[0m beq_type\u001b[38;5;241m.\u001b[39mBeqFac \u001b[38;5;241m=\u001b[39m [\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m----> 7\u001b[0m \u001b[43mbeq_type\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msolve\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "Cell \u001b[0;32mIn[3], line 7\u001b[0m\n\u001b[1;32m 4\u001b[0m beq_type\u001b[38;5;241m.\u001b[39mTermBeqFac \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m 5\u001b[0m beq_type\u001b[38;5;241m.\u001b[39mBeqFac \u001b[38;5;241m=\u001b[39m [\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m----> 7\u001b[0m \u001b[43mbeq_type\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msolve\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/mambaforge/envs/hark/lib/python3.9/site-packages/HARK/core.py:519\u001b[0m, in \u001b[0;36mAgentType.solve\u001b[0;34m(self, verbose)\u001b[0m\n\u001b[1;32m 513\u001b[0m \u001b[38;5;66;03m# Ignore floating point \"errors\". Numpy calls it \"errors\", but really it's excep-\u001b[39;00m\n\u001b[1;32m 514\u001b[0m \u001b[38;5;66;03m# tions with well-defined answers such as 1.0/0.0 that is np.inf, -1.0/0.0 that is\u001b[39;00m\n\u001b[1;32m 515\u001b[0m \u001b[38;5;66;03m# -np.inf, np.inf/np.inf is np.nan and so on.\u001b[39;00m\n\u001b[1;32m 516\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m np\u001b[38;5;241m.\u001b[39merrstate(\n\u001b[1;32m 517\u001b[0m divide\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m, over\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m, under\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m, invalid\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 518\u001b[0m ):\n\u001b[0;32m--> 519\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpre_solve\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# Do pre-solution stuff\u001b[39;00m\n\u001b[1;32m 520\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msolution \u001b[38;5;241m=\u001b[39m solve_agent(\n\u001b[1;32m 521\u001b[0m \u001b[38;5;28mself\u001b[39m, verbose\n\u001b[1;32m 522\u001b[0m ) \u001b[38;5;66;03m# Solve the model by backward induction\u001b[39;00m\n\u001b[1;32m 523\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpost_solve()\n", "File \u001b[0;32m~/mambaforge/envs/hark/lib/python3.9/site-packages/HARK/ConsumptionSaving/ConsPortfolioModel.py:188\u001b[0m, in \u001b[0;36mPortfolioConsumerType.pre_solve\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 186\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpre_solve\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 187\u001b[0m AgentType\u001b[38;5;241m.\u001b[39mpre_solve(\u001b[38;5;28mself\u001b[39m)\n\u001b[0;32m--> 188\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupdate_solution_terminal\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/mambaforge/envs/hark/lib/python3.9/site-packages/HARK/ConsumptionSaving/ConsBequestModel.py:141\u001b[0m, in \u001b[0;36mBequestWarmGlowPortfolioType.update_solution_terminal\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 138\u001b[0m BequestWarmGlowConsumerType\u001b[38;5;241m.\u001b[39mupdate_solution_terminal(\u001b[38;5;28mself\u001b[39m)\n\u001b[1;32m 140\u001b[0m \u001b[38;5;66;03m# Consume all market resources: c_T = m_T\u001b[39;00m\n\u001b[0;32m--> 141\u001b[0m cFuncAdj_terminal \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msolution_terminal\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcFunc\u001b[49m\n\u001b[1;32m 142\u001b[0m cFuncFxd_terminal \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m m, s: \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msolution_terminal\u001b[38;5;241m.\u001b[39mcFunc(m)\n\u001b[1;32m 144\u001b[0m \u001b[38;5;66;03m# Risky share is irrelevant-- no end-of-period assets; set to zero\u001b[39;00m\n", @@ -52,7 +52,7 @@ "beq_type = BequestWarmGlowPortfolioType(\n", " **init_portfolio)\n", "\n", - "beq_type.TermBeqFac = 1\n", + "beq_type.TermBeqFac = 0\n", "beq_type.BeqFac = [0]\n", "\n", "beq_type.solve()\n", diff --git a/examples/ConsBequestModel/example_ConsIndShockComp.ipynb b/examples/ConsBequestModel/example_ConsIndShockComp.ipynb index 201d8549d..7d5343fab 100644 --- a/examples/ConsBequestModel/example_ConsIndShockComp.ipynb +++ b/examples/ConsBequestModel/example_ConsIndShockComp.ipynb @@ -45,7 +45,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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