manual update to notebook collection

YaohanChen · Jul 26, 2019 · 0e29c79 · 0e29c79
1 parent aa30b71
commit 0e29c79
Show file tree

Hide file tree

Showing 90 changed files with 17,221 additions and 33,542 deletions.
diff --git a/about_py.ipynb b/about_py.ipynb
diff --git a/additive_functionals.ipynb b/additive_functionals.ipynb
diff --git a/aiyagari.ipynb b/aiyagari.ipynb
diff --git a/amss.ipynb b/amss.ipynb
diff --git a/amss2.ipynb b/amss2.ipynb
diff --git a/amss3.ipynb b/amss3.ipynb
diff --git a/arellano.ipynb b/arellano.ipynb
diff --git a/arma.ipynb b/arma.ipynb
diff --git a/black_litterman.ipynb b/black_litterman.ipynb
diff --git a/calvo.ipynb b/calvo.ipynb
diff --git a/career.ipynb b/career.ipynb
diff --git a/cass_koopmans.ipynb b/cass_koopmans.ipynb
diff --git a/cattle_cycles.ipynb b/cattle_cycles.ipynb
diff --git a/chang_credible.ipynb b/chang_credible.ipynb
diff --git a/chang_ramsey.ipynb b/chang_ramsey.ipynb
diff --git a/classical_filtering.ipynb b/classical_filtering.ipynb
diff --git a/coase.ipynb b/coase.ipynb
diff --git a/coleman_policy_iter.ipynb b/coleman_policy_iter.ipynb
diff --git a/complex_and_trig.ipynb b/complex_and_trig.ipynb
diff --git a/debugging.ipynb b/debugging.ipynb
diff --git a/discrete_dp.ipynb b/discrete_dp.ipynb
diff --git a/dyn_stack.ipynb b/dyn_stack.ipynb
diff --git a/egm_policy_iter.ipynb b/egm_policy_iter.ipynb
diff --git a/estspec.ipynb b/estspec.ipynb
diff --git a/finite_markov.ipynb b/finite_markov.ipynb
diff --git a/geom_series.ipynb b/geom_series.ipynb
diff --git a/getting_started.ipynb b/getting_started.ipynb
diff --git a/growth_in_dles.ipynb b/growth_in_dles.ipynb
diff --git a/harrison_kreps.ipynb b/harrison_kreps.ipynb
diff --git a/hs_invertibility_example.ipynb b/hs_invertibility_example.ipynb
diff --git a/hs_recursive_models.ipynb b/hs_recursive_models.ipynb
diff --git a/ifp.ipynb b/ifp.ipynb
diff --git a/irfs_in_hall_model.ipynb b/irfs_in_hall_model.ipynb
diff --git a/jv.ipynb b/jv.ipynb
diff --git a/kalman.ipynb b/kalman.ipynb
diff --git a/lake_model.ipynb b/lake_model.ipynb
diff --git a/linear_algebra.ipynb b/linear_algebra.ipynb
diff --git a/linear_models.ipynb b/linear_models.ipynb
diff --git a/lln_clt.ipynb b/lln_clt.ipynb
diff --git a/lqcontrol.ipynb b/lqcontrol.ipynb
diff --git a/lqramsey.ipynb b/lqramsey.ipynb
diff --git a/lu_tricks.ipynb b/lu_tricks.ipynb
diff --git a/lucas_asset_pricing_dles.ipynb b/lucas_asset_pricing_dles.ipynb
diff --git a/lucas_model.ipynb b/lucas_model.ipynb
diff --git a/markov_asset.ipynb b/markov_asset.ipynb
diff --git a/markov_jump_lq.ipynb b/markov_jump_lq.ipynb
diff --git a/markov_perf.ipynb b/markov_perf.ipynb
diff --git a/matplotlib.ipynb b/matplotlib.ipynb
diff --git a/matsuyama.ipynb b/matsuyama.ipynb
diff --git a/mccall_model.ipynb b/mccall_model.ipynb
diff --git a/mccall_model_with_separation.ipynb b/mccall_model_with_separation.ipynb
diff --git a/mle.ipynb b/mle.ipynb
diff --git a/multiplicative_functionals.ipynb b/multiplicative_functionals.ipynb
diff --git a/muth_kalman.ipynb b/muth_kalman.ipynb
diff --git a/numba.ipynb b/numba.ipynb
diff --git a/numpy.ipynb b/numpy.ipynb
diff --git a/odu.ipynb b/odu.ipynb
diff --git a/ols.ipynb b/ols.ipynb
diff --git a/oop_intro.ipynb b/oop_intro.ipynb
diff --git a/opt_tax_recur.ipynb b/opt_tax_recur.ipynb
diff --git a/optgrowth.ipynb b/optgrowth.ipynb
diff --git a/orth_proj.ipynb b/orth_proj.ipynb
diff --git a/pandas.ipynb b/pandas.ipynb
diff --git a/pandas_panel.ipynb b/pandas_panel.ipynb
diff --git a/perm_income.ipynb b/perm_income.ipynb
diff --git a/perm_income_cons.ipynb b/perm_income_cons.ipynb
diff --git a/permanent_income_dles.ipynb b/permanent_income_dles.ipynb
diff --git a/python_advanced_features.ipynb b/python_advanced_features.ipynb
diff --git a/python_by_example.ipynb b/python_by_example.ipynb
diff --git a/python_essentials.ipynb b/python_essentials.ipynb
diff --git a/python_oop.ipynb b/python_oop.ipynb
diff --git a/rational_expectations.ipynb b/rational_expectations.ipynb
diff --git a/rob_markov_perf.ipynb b/rob_markov_perf.ipynb
diff --git a/robustness.ipynb b/robustness.ipynb
diff --git a/rosen_schooling_model.ipynb b/rosen_schooling_model.ipynb
diff --git a/samuelson.ipynb b/samuelson.ipynb
diff --git a/schelling.ipynb b/schelling.ipynb
diff --git a/sci_libs.ipynb b/sci_libs.ipynb
diff --git a/scipy.ipynb b/scipy.ipynb
diff --git a/short_path.ipynb b/short_path.ipynb
@@ -33,7 +33,7 @@
     "  - [Overview](#Overview)  \n",
     "  - [Outline of the Problem](#Outline-of-the-Problem)  \n",
     "  - [Finding Least-Cost Paths](#Finding-Least-Cost-Paths)  \n",
-    "  - [Solving for $ J $](#Solving-for-$-J-$)  \n",
+    "  - [Solving for Minimum Cost-to-Go](#Solving-for-Minimum-Cost-to-Go)  \n",
     "  - [Exercises](#Exercises)  \n",
     "  - [Solutions](#Solutions)  "
    ]
@@ -59,9 +59,9 @@
     "- routing packets on the internet  \n",
     "\n",
     "\n",
-    "For us, the shortest path problem also provides a nice introduction to the logic of **dynamic programming**\n",
+    "For us, the shortest path problem also provides a nice introduction to the logic of **dynamic programming**.\n",
     "\n",
-    "Dynamic programming is an extremely powerful optimization technique that we apply in many lectures on this site"
+    "Dynamic programming is an extremely powerful optimization technique that we apply in many lectures on this site."
    ]
   },
   {
@@ -70,23 +70,23 @@
    "source": [
     "## Outline of the Problem\n",
     "\n",
-    "The shortest path problem is one of finding how to traverse a [graph](https://en.wikipedia.org/wiki/Graph_%28mathematics%29) from one specified node to another at minimum cost\n",
+    "The shortest path problem is one of finding how to traverse a [graph](https://en.wikipedia.org/wiki/Graph_%28mathematics%29) from one specified node to another at minimum cost.\n",
     "\n",
     "Consider the following graph\n",
     "\n",
-    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/figures/graph.png\" style=\"width:100%;height:100%\">\n",
+    "<img src=\"_static/lecture_specific/short_path/graph.png\" style=\"\">\n",
     "\n",
     "  \n",
     "We wish to travel from node (vertex) A to node G at minimum cost\n",
     "\n",
-    "- Arrows (edges) indicate the movements we can take  \n",
-    "- Numbers on edges indicate the cost of traveling that edge  \n",
+    "- Arrows (edges) indicate the movements we can take.  \n",
+    "- Numbers on edges indicate the cost of traveling that edge.  \n",
     "\n",
     "\n",
     "Possible interpretations of the graph include\n",
     "\n",
-    "- Minimum cost for supplier to reach a destination  \n",
-    "- Routing of packets on the internet (minimize time)  \n",
+    "- Minimum cost for supplier to reach a destination.  \n",
+    "- Routing of packets on the internet (minimize time).  \n",
     "- Etc., etc.  \n",
     "\n",
     "\n",
@@ -95,13 +95,13 @@
     "- A, C, F, G at cost 8  \n",
     "\n",
     "\n",
-    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/figures/graph4.png\" style=\"width:100%;height:100%\">\n",
+    "<img src=\"_static/lecture_specific/short_path/graph4.png\" style=\"\">\n",
     "\n",
     "  \n",
     "- A, D, F, G at cost 8  \n",
     "\n",
     "\n",
-    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/figures/graph3.png\" style=\"width:100%;height:100%\">"
+    "<img src=\"_static/lecture_specific/short_path/graph3.png\" style=\"\">"
    ]
   },
   {
@@ -110,16 +110,16 @@
    "source": [
     "## Finding Least-Cost Paths\n",
     "\n",
-    "For large graphs we need a systematic solution\n",
+    "For large graphs, we need a systematic solution.\n",
     "\n",
-    "Let $ J(v) $ denote the minimum cost-to-go from node $ v $, understood as the total cost from $ v $ if we take the best route\n",
+    "Let $ J(v) $ denote the minimum cost-to-go from node $ v $, understood as the total cost from $ v $ if we take the best route.\n",
     "\n",
     "Suppose that we know $ J(v) $ for each node $ v $, as shown below for the graph from the preceding example\n",
     "\n",
-    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/figures/graph2.png\" style=\"width:100%;height:100%\">\n",
+    "<img src=\"_static/lecture_specific/short_path/graph2.png\" style=\"\">\n",
     "\n",
     "  \n",
-    "Note that $ J(G) = 0 $\n",
+    "Note that $ J(G) = 0 $.\n",
     "\n",
     "The best path can now be found as follows\n",
     "\n",
@@ -135,11 +135,11 @@
     "\n",
     "where\n",
     "\n",
-    "- $ F_v $ is the set of nodes that can be reached from $ v $ in one step  \n",
-    "- $ c(v, w) $ is the cost of traveling from $ v $ to $ w $  \n",
+    "- $ F_v $ is the set of nodes that can be reached from $ v $ in one step.  \n",
+    "- $ c(v, w) $ is the cost of traveling from $ v $ to $ w $.  \n",
     "\n",
     "\n",
-    "Hence, if we know the function $ J $, then finding the best path is almost trivial\n",
+    "Hence, if we know the function $ J $, then finding the best path is almost trivial.\n",
     "\n",
     "But how to find $ J $?\n",
     "\n",
@@ -152,14 +152,14 @@
     "J(v) = \\min_{w \\in F_v} \\{ c(v, w) + J(w) \\} \\tag{2}\n",
     "$$\n",
     "\n",
-    "This is known as the *Bellman equation*, after the mathematician Richard Bellman"
+    "This is known as the *Bellman equation*, after the mathematician Richard Bellman."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Solving for $ J $\n",
+    "## Solving for Minimum Cost-to-Go\n",
     "\n",
     "The standard algorithm for finding $ J $ is to start with\n",
     "\n",
@@ -169,7 +169,7 @@
     "J_0(v) = M \\text{ if } v \\not= \\text{ destination, else } J_0(v) = 0 \\tag{3}\n",
     "$$\n",
     "\n",
-    "where $ M $ is some large number\n",
+    "where $ M $ is some large number.\n",
     "\n",
     "Now we use the following algorithm\n",
     "\n",
@@ -178,7 +178,7 @@
     "1. If $ J_{n+1} $ and $ J_n $ are not equal then increment $ n $, go to 2  \n",
     "\n",
     "\n",
-    "In general, this sequence converges to $ J $—the proof is omitted"
+    "In general, this sequence converges to $ J $—the proof is omitted."
    ]
   },
   {
@@ -198,27 +198,19 @@
     "### Exercise 1\n",
     "\n",
     "Use the algorithm given above to find the optimal path (and its cost) for the\n",
-    "following graph\n",
+    "following graph.\n",
     "\n",
     "You can put it in a Jupyter notebook cell and hit Shift-Enter — it\n",
-    "will be saved in the local directory as file graph.txt"
+    "will be saved in the local directory as file graph.txt."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "hide-output": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Writing graph.txt\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%%file graph.txt\n",
     "node0, node1 0.04, node8 11.11, node14 72.21\n",
@@ -334,11 +326,11 @@
     "- node14 at cost 72.21  \n",
     "\n",
     "\n",
-    "and so on\n",
+    "and so on.\n",
     "\n",
-    "According to our calculations, the optimal path and its cost are like [this](https://github.com/QuantEcon/QuantEcon.lectures.code/blob/master/short_path/graph_out.txt)\n",
+    "According to our calculations, the optimal path and its cost are like [this](https://github.com/QuantEcon/QuantEcon.lectures.code/blob/master/short_path/graph_out.txt).\n",
     "\n",
-    "Your code should replicate this result"
+    "Your code should replicate this result."
    ]
   },
   {
@@ -357,48 +349,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "hide-output": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "node0\n",
-      "node8\n",
-      "node11\n",
-      "node18\n",
-      "node23\n",
-      "node33\n",
-      "node41\n",
-      "node53\n",
-      "node56\n",
-      "node57\n",
-      "node60\n",
-      "node67\n",
-      "node70\n",
-      "node73\n",
-      "node76\n",
-      "node85\n",
-      "node87\n",
-      "node88\n",
-      "node93\n",
-      "node94\n",
-      "node96\n",
-      "node97\n",
-      "node98\n",
-      "node99\n",
-      "\n",
-      "Cost:  160.55000000000007\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "def read_graph(in_file):\n",
     "    \"\"\" Read in the graph from the data file.  The graph is stored\n",
-    "    as a dictionary, where the keys are the nodes, and the values\n",
+    "    as a dictionary, where the keys are the nodes and the values\n",
     "    are a list of pairs (d, c), where d is a node and c is a number.\n",
     "    If (d, c) is in the list for node n, then d can be reached from\n",
     "    n at cost c.\n",
@@ -477,20 +436,8 @@
    "language": "python3",
    "name": "python3"
   },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.0"
-  },
   "title": "Shortest Paths"
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}