update notebooks with new jupyter_download_nb_image option

Author: mmcky

about_py.ipynb

@@ -108,7 +108,7 @@
     "\n",
     "The following chart, produced using Stack Overflow Trends, shows one measure of the relative popularity of Python\n",
     "\n",
-    "<img src=\"_static/lecture_specific/about_py/python_vs_rest.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/about_py/python_vs_rest.png\" style=\"\">\n",
     "\n",
     "  \n",
     "The figure indicates not only that Python is widely used but also that adoption of Python has accelerated significantly since 2012.\n",
@@ -120,7 +120,7 @@
     "\n",
     "(The corresponding time path for MATLAB is shown for comparison)\n",
     "\n",
-    "<img src=\"_static/lecture_specific/about_py/pandas_vs_matlab.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/about_py/pandas_vs_matlab.png\" style=\"\">\n",
     "\n",
     "  \n",
     "Note that pandas takes off in 2012, which is the same year that we seek\n",
@@ -308,17 +308,17 @@
     "\n",
     "Example 2D plot with embedded LaTeX annotations\n",
     "\n",
-    "<img src=\"_static/lecture_specific/about_py/qs.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/about_py/qs.png\" style=\"\">\n",
     "\n",
     "  \n",
     "Example contour plot\n",
     "\n",
-    "<img src=\"_static/lecture_specific/about_py/bn_density1.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/about_py/bn_density1.png\" style=\"\">\n",
     "\n",
     "  \n",
     "Example 3D plot\n",
     "\n",
-    "<img src=\"_static/lecture_specific/about_py/career_vf.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/about_py/career_vf.png\" style=\"\">\n",
     "\n",
     "  \n",
     "More examples can be found in the [Matplotlib thumbnail gallery](http://matplotlib.org/gallery.html).\n",

amss3.ipynb

@@ -828,7 +828,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"_static/lecture_specific/amss3/amss3_g1.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/amss3/amss3_g1.png\" style=\"\">\n",
     "\n",
     "  \n",
     "The long simulation apparently  indicates eventual convergence to an ergodic distribution.\n",
@@ -841,7 +841,7 @@
     "\n",
     "We obtain the following graph for the histogram of the last 100,000 observations on the par value of government debt.\n",
     "\n",
-    "<img src=\"_static/lecture_specific/amss3/amss3_g3.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/amss3/amss3_g3.png\" style=\"\">\n",
     "\n",
     "  \n",
     "The  black vertical line denotes the sample mean for the last 100,000 observations included in the histogram; the  green vertical line denotes the\n",
@@ -884,7 +884,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"_static/lecture_specific/amss3/amss3_g2.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/amss3/amss3_g2.png\" style=\"\">\n",
     "\n",
     "  \n",
     "For the short samples early in our simulated sample of  102,000 observations, fluctuations in government debt and the tax rate\n",

arellano.ipynb

@@ -670,7 +670,7 @@
     "\n",
     "The first figure shows the bond price schedule and replicates Figure 3 of Arellano, where $ y_L $ and $ Y_H $ are particular below average and above average values of output $ y $.\n",
     "\n",
-    "<img src=\"_static/lecture_specific/arellano/arellano_bond_prices.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/arellano/arellano_bond_prices.png\" style=\"\">\n",
     "\n",
     "  \n",
     "- $ y_L $ is 5% below the mean of the $ y $ grid values  \n",
@@ -681,7 +681,7 @@
     "\n",
     "Here’s the same relationships computed on a finer grid (`ny, nB = 51, 551`)\n",
     "\n",
-    "<img src=\"_static/lecture_specific/arellano/arellano_bond_prices_2.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/arellano/arellano_bond_prices_2.png\" style=\"\">\n",
     "\n",
     "  \n",
     "In either case, the figure shows that\n",
@@ -692,7 +692,7 @@
     "\n",
     "The next figure plots value functions and replicates the right hand panel of Figure 4 of [[Are08]](https://lectures.quantecon.org/zreferences.html#arellano2008default).\n",
     "\n",
-    "<img src=\"_static/lecture_specific/arellano/arellano_value_funcs.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/arellano/arellano_value_funcs.png\" style=\"\">\n",
     "\n",
     "  \n",
     "We can use the results of the computation to study the default probability\n",
@@ -701,7 +701,7 @@
     "The next plot shows these default probabilities over $ (B', y) $ as a heat\n",
     "map.\n",
     "\n",
-    "<img src=\"_static/lecture_specific/arellano/arellano_default_probs.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/arellano/arellano_default_probs.png\" style=\"\">\n",
     "\n",
     "  \n",
     "As anticipated, the probability that the government chooses to default in the\n",
@@ -711,7 +711,7 @@
     "\n",
     "The grey vertical bars correspond to periods when the economy is excluded from financial markets because of a past default.\n",
     "\n",
-    "<img src=\"_static/lecture_specific/arellano/arellano_time_series.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/arellano/arellano_time_series.png\" style=\"\">\n",
     "\n",
     "  \n",
     "One notable feature of the simulated data is the nonlinear response of interest rates.\n",

career.ipynb

@@ -508,7 +508,7 @@
     "\n",
     "In particular, modulo randomness, reproduce the following figure (where the horizontal axis represents time)\n",
     "\n",
-    "<img src=\"_static/lecture_specific/career/career_solutions_ex1_py.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/career/career_solutions_ex1_py.png\" style=\"\">\n",
     "\n",
     "  \n",
     "Hint: To generate the draws from the distributions $ F $ and $ G $, use `quantecon.random.draw()`.\n",

coase.ipynb

@@ -199,7 +199,7 @@
     "\n",
     "The subcontracting scheme by which tasks are allocated across firms is illustrated in the figure below\n",
     "\n",
-    "<img src=\"_static/lecture_specific/coase/subcontracting.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/coase/subcontracting.png\" style=\"\">\n",
     "\n",
     "  \n",
     "In this example,\n",
@@ -220,7 +220,7 @@
     "\n",
     "The length of the interval of stages (range of tasks) carried out by firm $ i $ is denoted by $ \\ell_i $.\n",
     "\n",
-    "<img src=\"_static/lecture_specific/coase/allocation.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/coase/allocation.png\" style=\"\">\n",
     "\n",
     "  \n",
     "Each firm chooses only its *upstream* boundary, treating its downstream boundary as given.\n",

coleman_policy_iter.ipynb

@@ -336,7 +336,7 @@
     "\n",
     "Here’s the picture\n",
     "\n",
-    "<img src=\"_static/lecture_specific/coleman_policy_iter/col_pol_composition.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/coleman_policy_iter/col_pol_composition.png\" style=\"\">\n",
     "\n",
     "  \n",
     "Now let another function $ h \\colon Y \\to Y $ where $ Y $ is another set.\n",
@@ -364,13 +364,13 @@
     "\n",
     "Here’s a commutative diagram that illustrates\n",
     "\n",
-    "<img src=\"_static/lecture_specific/coleman_policy_iter/col_pol_bij1.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/coleman_policy_iter/col_pol_bij1.png\" style=\"\">\n",
     "\n",
     "  \n",
     "Here’s a similar figure that traces out the action of the maps on a point\n",
     "$ x \\in X $\n",
     "\n",
-    "<img src=\"_static/lecture_specific/coleman_policy_iter/col_pol_bij2.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/coleman_policy_iter/col_pol_bij2.png\" style=\"\">\n",
     "\n",
     "  \n",
     "Now, it’s easy to check from [(8)](#equation-cpi-ghcom) that $ g^2 = \\tau^{-1} \\circ h^2 \\circ \\tau $ holds.\n",

discrete_dp.ipynb

@@ -814,7 +814,7 @@
    "source": [
     "Here’s the same information in a bar graph\n",
     "\n",
-    "<img src=\"_static/lecture_specific/discrete_dp/finite_dp_simple_og.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/discrete_dp/finite_dp_simple_og.png\" style=\"\">\n",
     "\n",
     "  \n",
     "What happens if the agent is more patient?"
@@ -839,7 +839,7 @@
    "source": [
     "If we look at the bar graph we can see the rightward shift in probability mass\n",
     "\n",
-    "<img src=\"_static/lecture_specific/discrete_dp/finite_dp_simple_og2.png\" style=\"\">"
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/discrete_dp/finite_dp_simple_og2.png\" style=\"\">"
    ]
   },
   {

estspec.ipynb

@@ -287,7 +287,7 @@
     "\n",
     "However, if we try again with `n = 1200` the outcome is not much better\n",
     "\n",
-    "<img src=\"_static/lecture_specific/estspec/periodogram1.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/estspec/periodogram1.png\" style=\"\">\n",
     "\n",
     "  \n",
     "The periodogram is far too irregular relative to the underlying spectral density.\n",
@@ -398,7 +398,7 @@
     "\n",
     "\n",
     "<a id='fig-window-smoothing'></a>\n",
-    "<img src=\"_static/lecture_specific/estspec/window_smoothing.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/estspec/window_smoothing.png\" style=\"\">\n",
     "\n",
     "  \n",
     "In looking at the figure, we can see that for this model and data size, the\n",
@@ -530,7 +530,7 @@
     "\n",
     "\n",
     "<a id='fig-ar-smoothed-periodogram'></a>\n",
-    "<img src=\"_static/lecture_specific/estspec/ar_smoothed_periodogram.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/estspec/ar_smoothed_periodogram.png\" style=\"\">\n",
     "\n",
     "  \n",
     "In all cases, periodograms are fit with the “hamming” window and window length of 65.\n",

finite_markov.ipynb

@@ -251,7 +251,7 @@
     "\n",
     "This Markov process can also be represented as a directed graph, with edges labeled by transition probabilities\n",
     "\n",
-    "<img src=\"_static/lecture_specific/finite_markov/hamilton_graph.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/finite_markov/hamilton_graph.png\" style=\"\">\n",
     "\n",
     "  \n",
     "Here “ng” is normal growth, “mr” is mild recession, etc."
@@ -632,7 +632,7 @@
     "In particular\n",
     "\n",
     "$$\n",
-    "\\mathbb P \\{X_{t+m} = y \\} = P^m(x, y) = (x, y) \\text{-th element of } P^m\n",
+    "\\mathbb P \\{X_{t+m} = y \\,|\\, X_t = x \\} = P^m(x, y) = (x, y) \\text{-th element of } P^m\n",
     "$$"
    ]
   },
@@ -737,7 +737,7 @@
     "For example, consider the following transition probabilities for wealth of a fictitious set of\n",
     "households\n",
     "\n",
-    "<img src=\"_static/lecture_specific/finite_markov/mc_irreducibility1.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/finite_markov/mc_irreducibility1.png\" style=\"\">\n",
     "\n",
     "  \n",
     "We can translate this into a stochastic matrix, putting zeros where\n",
@@ -782,7 +782,7 @@
    "source": [
     "Here’s a more pessimistic scenario, where the poor are poor forever\n",
     "\n",
-    "<img src=\"_static/lecture_specific/finite_markov/mc_irreducibility2.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/finite_markov/mc_irreducibility2.png\" style=\"\">\n",
     "\n",
     "  \n",
     "This stochastic matrix is not irreducible, since, for example, rich is not accessible from poor.\n",
@@ -845,7 +845,7 @@
     "\n",
     "Here’s a trivial example with three states\n",
     "\n",
-    "<img src=\"_static/lecture_specific/finite_markov/mc_aperiodicity1.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/finite_markov/mc_aperiodicity1.png\" style=\"\">\n",
     "\n",
     "  \n",
     "The chain cycles with period 3:"
@@ -884,7 +884,7 @@
     "\n",
     "For example, the stochastic matrix associated with the transition probabilities below is periodic because, for example, state $ a $ has period 2\n",
     "\n",
-    "<img src=\"_static/lecture_specific/finite_markov/mc_aperiodicity2.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/finite_markov/mc_aperiodicity2.png\" style=\"\">\n",
     "\n",
     "  \n",
     "We can confirm that the stochastic matrix is periodic as follows"
@@ -1373,7 +1373,7 @@
     "The result should look something like the following — modulo randomness, of\n",
     "course\n",
     "\n",
-    "<img src=\"_static/lecture_specific/finite_markov/mc_ex1_plot.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/finite_markov/mc_ex1_plot.png\" style=\"\">\n",
     "\n",
     "  \n",
     "(You don’t need to add the fancy touches to the graph—see the solution if you’re interested)\n",
@@ -1410,7 +1410,7 @@
     "\n",
     "To illustrate the idea, consider the following diagram\n",
     "\n",
-    "<img src=\"_static/lecture_specific/finite_markov/web_graph.png\" style=\"\">\n",
+    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/py/_static/lecture_specific/finite_markov/web_graph.png\" style=\"\">\n",
     "\n",
     "  \n",
     "Imagine that this is a miniature version of the WWW, with\n",