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149f6be..a7228f4 100755 --- a/_sources/docs/getting_started.ipynb +++ b/_sources/docs/getting_started.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "5d07c0c8", + "id": "b790aa9f", "metadata": {}, "source": [ "(getting_started)=\n", @@ -239,10 +239,25 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "ccbd30a9", + "execution_count": 1, + "id": "fc4574e5", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "

    " + ] + }, + "metadata": { + "filenames": { + "image/png": "C:\\Users\\maximiko\\Franklin\\indeco\\_build\\jupyter_execute\\docs\\getting_started_1_0.png" + } + }, + "output_type": "display_data" + } + ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", @@ -266,7 +281,7 @@ }, { "cell_type": "markdown", - "id": "6b4000fa", + "id": "af35cc45", "metadata": {}, "source": [ "Don\\'t worry about the details for now --- let\\'s just run it and see\n", @@ -375,6 +390,18 @@ "language": "python", "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": "3.8.8" + }, "source_map": [ 10, 243, diff --git a/_sources/docs/ground_zero.ipynb b/_sources/docs/ground_zero.ipynb index 2c5ca1d..eeae25f 100755 --- a/_sources/docs/ground_zero.ipynb +++ b/_sources/docs/ground_zero.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "c280e1a7", + "id": "8d23956d", "metadata": {}, "source": [ "(getting_started)=\n", diff --git a/_sources/docs/indecol.ipynb b/_sources/docs/indecol.ipynb index c68ad45..ea298bd 100755 --- a/_sources/docs/indecol.ipynb +++ b/_sources/docs/indecol.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "ce553f70", + "id": "311b70f9", "metadata": {}, "source": [ "(getting_started)=\n", diff --git a/_sources/docs/learn_more.ipynb b/_sources/docs/learn_more.ipynb index ad46ab9..7203d00 100755 --- a/_sources/docs/learn_more.ipynb +++ b/_sources/docs/learn_more.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "da756395", + "id": "89b64610", "metadata": {}, "source": [ "# Learn More\n", @@ -24,8 +24,8 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "b612462f", + "execution_count": 1, + "id": "e9a93737", "metadata": {}, "outputs": [], "source": [ @@ -38,7 +38,7 @@ }, { "cell_type": "markdown", - "id": "0b2a6f19", + "id": "19b82239", "metadata": {}, "source": [ "Now let\\'s take the inner product" @@ -46,17 +46,28 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "4dababd7", + "execution_count": 2, + "id": "3e85bb08", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "1.0408340855860843e-16" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "b @ c" ] }, { "cell_type": "markdown", - "id": "ca3ac4d0", + "id": "1276ebaf", "metadata": {}, "source": [ "The number you see here might vary slightly due to floating point arithmetic\n", @@ -82,10 +93,21 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "bbadb973", + "execution_count": 3, + "id": "251aa824", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "0.9544997361036417" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from scipy.stats import norm\n", "from scipy.integrate import quad\n", @@ -97,7 +119,7 @@ }, { "cell_type": "markdown", - "id": "9b4aa118", + "id": "e0aa67fa", "metadata": {}, "source": [ "SciPy includes many of the standard routines used in\n", @@ -158,10 +180,24 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "6e4a9be2", + "execution_count": 4, + "id": "f14279a1", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/latex": [ + "$\\displaystyle 3 x + y$" + ], + "text/plain": [ + "3*x + y" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from sympy import Symbol\n", "\n", @@ -171,7 +207,7 @@ }, { "cell_type": "markdown", - "id": "8045fc63", + "id": "b3c58d9b", "metadata": {}, "source": [ "We can manipulate expressions" @@ -179,10 +215,24 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "508534f0", + "execution_count": 5, + "id": "11ecded4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/latex": [ + "$\\displaystyle x^{2} + 2 x y + y^{2}$" + ], + "text/plain": [ + "x**2 + 2*x*y + y**2" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "expression = (x + y)**2\n", "expression.expand()" @@ -190,7 +240,7 @@ }, { "cell_type": "markdown", - "id": "5ddd07e4", + "id": "cb17db89", "metadata": {}, "source": [ "solve polynomials" @@ -198,10 +248,21 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "be0e4045", + "execution_count": 6, + "id": "40978a01", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[-1/2 - sqrt(7)*I/2, -1/2 + sqrt(7)*I/2]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from sympy import solve\n", "\n", @@ -210,7 +271,7 @@ }, { "cell_type": "markdown", - "id": "363b2533", + "id": "51176a10", "metadata": {}, "source": [ "and calculate limits, derivatives and integrals" @@ -218,10 +279,24 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "cbc7ffed", + "execution_count": 7, + "id": "5d65fb20", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/latex": [ + "$\\displaystyle \\infty$" + ], + "text/plain": [ + "oo" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from sympy import limit, sin, diff\n", "\n", @@ -230,27 +305,55 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "0164fc03", + "execution_count": 8, + "id": "395a5b39", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/latex": [ + "$\\displaystyle 1$" + ], + "text/plain": [ + "1" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "limit(sin(x) / x, x, 0)" ] }, { "cell_type": "code", - "execution_count": null, - "id": "3146bd05", + "execution_count": 9, + "id": "1d90d39c", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/latex": [ + "$\\displaystyle \\cos{\\left(x \\right)}$" + ], + "text/plain": [ + "cos(x)" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "diff(sin(x), x)" ] }, { "cell_type": "markdown", - "id": "9533f57a", + "id": "358e6e22", "metadata": {}, "source": [ "The beauty of importing this functionality into Python is that we are\n", @@ -272,10 +375,31 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "3e565096", + "execution_count": 10, + "id": "78dd32cc", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " price weight\n", + "2010-12-28 0.471435 -1.190976\n", + "2010-12-29 1.432707 -0.312652\n", + "2010-12-30 -0.720589 0.887163\n", + "2010-12-31 0.859588 -0.636524\n", + "2011-01-01 0.015696 -2.242685\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\maximiko\\Anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3442: UserWarning: Parsing '28/12/2010' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n", + " exec(code_obj, self.user_global_ns, self.user_ns)\n" + ] + } + ], "source": [ "import pandas as pd\n", "np.random.seed(1234)\n", @@ -289,17 +413,30 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "2bfeafc0", + "execution_count": 11, + "id": "1d7e8ac4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "price 0.411768\n", + "weight -0.699135\n", + "dtype: float64" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "df.mean()" ] }, { "cell_type": "markdown", - "id": "1840db38", + "id": "bb540801", "metadata": {}, "source": [ "## Further Reading\n", @@ -325,6 +462,18 @@ "language": "python", "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": "3.8.8" + }, "source_map": [ 10, 28, diff --git a/_sources/docs/motivation.ipynb b/_sources/docs/motivation.ipynb index d5de3cc..335d0cf 100755 --- a/_sources/docs/motivation.ipynb +++ b/_sources/docs/motivation.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "2c6e9ed6", + "id": "82536dd0", "metadata": {}, "source": [ "(getting_started)=\n", diff --git a/_sources/docs/python_by_example.ipynb b/_sources/docs/python_by_example.ipynb index 4767adc..5b8c966 100755 --- a/_sources/docs/python_by_example.ipynb +++ b/_sources/docs/python_by_example.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "2f5695bd", + "id": "625f3488", "metadata": {}, "source": [ "(python_by_example)=\n", @@ -47,8 +47,8 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "9b8dea36", + "execution_count": 1, + "id": "458e513d", "metadata": {}, "outputs": [], "source": [ @@ -57,7 +57,7 @@ }, { "cell_type": "markdown", - "id": "79ec574d", + "id": "1af0542b", "metadata": {}, "source": [ "## Version 1\n", @@ -69,10 +69,25 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "b46758cb", + "execution_count": 2, + "id": "4cf20070", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "filenames": { + "image/png": "C:\\Users\\maximiko\\Franklin\\indeco\\_build\\jupyter_execute\\docs\\python_by_example_3_0.png" + } + }, + "output_type": "display_data" + } + ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", @@ -84,7 +99,7 @@ }, { "cell_type": "markdown", - "id": "578f0989", + "id": "f3a9691b", "metadata": {}, "source": [ "Let\\'s break this program down and see how it works.\n", @@ -112,27 +127,49 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "aa7f9d41", + "execution_count": 3, + "id": "60b2879f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2.0" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.sqrt(4)" ] }, { "cell_type": "code", - "execution_count": null, - "id": "d989503f", + "execution_count": 4, + "id": "057bcbcd", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "1.3862943611198906" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.log(4)" ] }, { "cell_type": "markdown", - "id": "7c43a00d", + "id": "826e6f28", "metadata": {}, "source": [ "We could also use the following syntax:" @@ -140,10 +177,21 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "cfa08a4c", + "execution_count": 5, + "id": "c9f98f3a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2.0" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "import numpy\n", "\n", @@ -152,7 +200,7 @@ }, { "cell_type": "markdown", - "id": "46e72e8c", + "id": "1da570d6", "metadata": {}, "source": [ "But the former method (using the short name `np`) is convenient and more\n", @@ -208,10 +256,21 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "9d06d16e", + "execution_count": 6, + "id": "87289239", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2.0" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "import numpy as np\n", "\n", @@ -220,7 +279,7 @@ }, { "cell_type": "markdown", - "id": "1a7e9aa2", + "id": "3aff9400", "metadata": {}, "source": [ "Here\\'s another way to access NumPy\\'s square root function" @@ -228,10 +287,21 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "3dd95b2f", + "execution_count": 7, + "id": "6e850015", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2.0" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from numpy import sqrt\n", "\n", @@ -240,7 +310,7 @@ }, { "cell_type": "markdown", - "id": "39001c56", + "id": "d05f5610", "metadata": {}, "source": [ "This is also fine.\n", @@ -261,10 +331,25 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "098dfc88", + "execution_count": 8, + "id": "1250a428", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "filenames": { + "image/png": "C:\\Users\\maximiko\\Franklin\\indeco\\_build\\jupyter_execute\\docs\\python_by_example_14_0.png" + } + }, + "output_type": "display_data" + } + ], "source": [ "ϵ_values = np.random.randn(100)\n", "plt.plot(ϵ_values)\n", @@ -273,7 +358,7 @@ }, { "cell_type": "markdown", - "id": "a9cc4538", + "id": "618915d5", "metadata": {}, "source": [ "The first line generates 100 (quasi) independent standard normals and\n", @@ -305,10 +390,25 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "ff3e4b00", + "execution_count": 9, + "id": "212149cd", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "filenames": { + "image/png": "C:\\Users\\maximiko\\Franklin\\indeco\\_build\\jupyter_execute\\docs\\python_by_example_16_0.png" + } + }, + "output_type": "display_data" + } + ], "source": [ "ts_length = 100\n", "ϵ_values = [] # empty list\n", @@ -323,7 +423,7 @@ }, { "cell_type": "markdown", - "id": "c678d986", + "id": "7aa624a0", "metadata": {}, "source": [ "In brief,\n", @@ -354,10 +454,21 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "df8ca393", + "execution_count": 10, + "id": "d7676d81", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "list" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x = [10, 'foo', False]\n", "type(x)" @@ -365,7 +476,7 @@ }, { "cell_type": "markdown", - "id": "faa1cd93", + "id": "18dcd75b", "metadata": {}, "source": [ "The first element of `x` is an\n", @@ -380,20 +491,42 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "e526225a", + "execution_count": 11, + "id": "addd86f3", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[10, 'foo', False]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x" ] }, { "cell_type": "code", - "execution_count": null, - "id": "558f2907", + "execution_count": 12, + "id": "fd253649", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[10, 'foo', False, 2.5]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x.append(2.5)\n", "x" @@ -401,7 +534,7 @@ }, { "cell_type": "markdown", - "id": "cdfe4cdb", + "id": "dc0c305f", "metadata": {}, "source": [ "Here `append()` is what\\'s called a *method*, which is a function\n", @@ -420,37 +553,70 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "5b381711", + "execution_count": 13, + "id": "1b42149f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[10, 'foo', False, 2.5]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x" ] }, { "cell_type": "code", - "execution_count": null, - "id": "e8b4f539", + "execution_count": 14, + "id": "3f8718f0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2.5" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x.pop()" ] }, { "cell_type": "code", - "execution_count": null, - "id": "5ddb651b", + "execution_count": 15, + "id": "5ef904d0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[10, 'foo', False]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x" ] }, { "cell_type": "markdown", - "id": "6341e3c9", + "id": "752c9eb5", "metadata": {}, "source": [ "Lists in Python are zero-based (as in C, Java or Go), so the first\n", @@ -459,27 +625,49 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "fa848c34", + "execution_count": 16, + "id": "7edd005a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "10" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x[0] # first element of x" ] }, { "cell_type": "code", - "execution_count": null, - "id": "ac119e72", + "execution_count": 17, + "id": "15bfedc3", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "'foo'" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x[1] # second element of x" ] }, { "cell_type": "markdown", - "id": "778b8456", + "id": "2d05b582", "metadata": {}, "source": [ "### The For Loop\n", @@ -491,8 +679,8 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "64bed2be", + "execution_count": 18, + "id": "78368e2e", "metadata": {}, "outputs": [], "source": [ @@ -503,7 +691,7 @@ }, { "cell_type": "markdown", - "id": "688c6087", + "id": "ed9ea430", "metadata": {}, "source": [ "Python executes the two indented lines `ts_length` times before moving\n", @@ -524,10 +712,20 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "dc8c30e6", + "execution_count": 19, + "id": "b699db66", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The plural of dog is dogs\n", + "The plural of cat is cats\n", + "The plural of bird is birds\n" + ] + } + ], "source": [ "animals = ['dog', 'cat', 'bird']\n", "for animal in animals:\n", @@ -536,7 +734,7 @@ }, { "cell_type": "markdown", - "id": "ed632e45", + "id": "3c8482ce", "metadata": {}, "source": [ "This example helps to clarify how the `for` loop works: When we execute\n", @@ -601,10 +799,25 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "ae34ada2", + "execution_count": 20, + "id": "2205864c", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "filenames": { + "image/png": "C:\\Users\\maximiko\\Franklin\\indeco\\_build\\jupyter_execute\\docs\\python_by_example_34_0.png" + } + }, + "output_type": "display_data" + } + ], "source": [ "ts_length = 100\n", "ϵ_values = []\n", @@ -619,7 +832,7 @@ }, { "cell_type": "markdown", - "id": "c6c4ff98", + "id": "54ee91c7", "metadata": {}, "source": [ "Note that\n", @@ -654,10 +867,25 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "f0c416c5", + "execution_count": 21, + "id": "26643ccc", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "filenames": { + "image/png": "C:\\Users\\maximiko\\Franklin\\indeco\\_build\\jupyter_execute\\docs\\python_by_example_36_0.png" + } + }, + "output_type": "display_data" + } + ], "source": [ "r = 0.025 # interest rate\n", "T = 50 # end date\n", @@ -674,7 +902,7 @@ }, { "cell_type": "markdown", - "id": "aa453635", + "id": "a129d3c9", "metadata": {}, "source": [ "The statement `b = np.empty(T+1)` allocates storage in memory for `T+1`\n", @@ -713,8 +941,8 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "c3979f9f", + "execution_count": 22, + "id": "a0875a44", "metadata": {}, "outputs": [], "source": [ @@ -724,7 +952,7 @@ }, { "cell_type": "markdown", - "id": "8e4a0a22", + "id": "12c2d78a", "metadata": {}, "source": [ "Set $T=200$ and $\\alpha = 0.9$.\n", @@ -777,8 +1005,8 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "4876ad78", + "execution_count": 23, + "id": "56a396c8", "metadata": {}, "outputs": [], "source": [ @@ -787,10 +1015,21 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "7fd2402b", + "execution_count": 24, + "id": "5f7fc154", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-1\n", + "1\n", + "-1\n", + "1\n" + ] + } + ], "source": [ "for x in numbers:\n", " if x < 0:\n", @@ -801,7 +1040,7 @@ }, { "cell_type": "markdown", - "id": "017c667b", + "id": "b17961bd", "metadata": {}, "source": [ "Now, write a new solution to Exercise 3 that does not use an existing\n", @@ -822,8 +1061,8 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "8471e8c7", + "execution_count": 25, + "id": "6ae42dc5", "metadata": {}, "outputs": [], "source": [ @@ -832,7 +1071,7 @@ }, { "cell_type": "markdown", - "id": "fcf67d1e", + "id": "3d134ea1", "metadata": {}, "source": [ "Your hints are as follows:\n", @@ -854,10 +1093,25 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "f909929e", + "execution_count": 26, + "id": "a08d8431", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "filenames": { + "image/png": "C:\\Users\\maximiko\\Franklin\\indeco\\_build\\jupyter_execute\\docs\\python_by_example_45_0.png" + } + }, + "output_type": "display_data" + } + ], "source": [ "α = 0.9\n", "T = 200\n", @@ -873,7 +1127,7 @@ }, { "cell_type": "markdown", - "id": "e7139ddc", + "id": "d60aab20", "metadata": {}, "source": [ "### Exercise 2" @@ -881,10 +1135,25 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "10701d12", + "execution_count": 27, + "id": "fe15b331", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "filenames": { + "image/png": "C:\\Users\\maximiko\\Franklin\\indeco\\_build\\jupyter_execute\\docs\\python_by_example_47_0.png" + } + }, + "output_type": "display_data" + } + ], "source": [ "α_values = [0.0, 0.8, 0.98]\n", "T = 200\n", @@ -902,7 +1171,7 @@ }, { "cell_type": "markdown", - "id": "f294e39c", + "id": "1d5187d1", "metadata": {}, "source": [ "### Exercise 3\n", @@ -912,10 +1181,25 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "11126237", + "execution_count": 28, + "id": "d162b047", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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    " + ] + }, + "metadata": { + "filenames": { + "image/png": "C:\\Users\\maximiko\\Franklin\\indeco\\_build\\jupyter_execute\\docs\\python_by_example_49_0.png" + } + }, + "output_type": "display_data" + } + ], "source": [ "α = 0.9\n", "T = 200\n", @@ -931,7 +1215,7 @@ }, { "cell_type": "markdown", - "id": "28465284", + "id": "07ad0f37", "metadata": {}, "source": [ "### Exercise 4\n", @@ -941,10 +1225,25 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "bfa9d18c", + "execution_count": 29, + "id": "986884ea", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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NN/r6+RtvvBEjIyPiz6ZNm5p5eIHw00OE4BJeRkZtZkakEjHRifcEByIM4wvdITVDmz/uI9KdNC0QOXDgAN7znvfgK1/5CjKZjK9/c/3112N+fl78OXDgQLMOLzCih4hH6S7BlTOMjDp5V2YwkwAALBY4jccwfqhUuXy310g064UfeOABTE9PY9euXeJrlUoFP/nJT/CpT30KhUIB8bh9YU6n00in0806pIYQPUQ8SncJUTnDqRkGtV1VZQZSxi24zIEIw/iCUjOO5bucmulKmhaIvOpVr8Jjjz1m+9of/MEf4LTTTsMHPvCBmiCk0wmiiIz0UZt3DkQYIFes7apKDJmKyFKeAxGG8YNo8S57RBKsiHQzTQtEhoaGsGPHDtvXBgYGMDExUfP1bsDyiPhXRDgQYQAga1ZPOSkig2lOzTBMEKoOqZk0m1W7Gu6s6hPRVdWXIsITeBkLL4/IQJpTMwwTBErNOPYRYbNqV9I0RcSJO++8s5W/LlLIje3HI0Jm1QVWRBhYHhGniitOzTBMMERDM8fyXQ5EuhFWRHwSShFhsyoDySPiYVbl5ncM4w8xfVeumuEW710NByI+IUWEPSJMUNz6iABW+S4rIgzjj4pHi3fuI9KdcCDiE4q0fTU04z4ijETOVDvUWTOAZVZdYo8Iw/jCq8V7gRWRroQDEZ/kpQmq9eDUDCPj5REZZLMqw/hG13WRmonz0LuegQMRn4g+IgFavLNZlQGAnIeaJjqrcmqGYeoiDzS3p2ZMjwinZroSDkR8EkQRofkhi4UyyhWWClc6Xj1oBrowNVOp6px2ZNpCVZpSbZ81w2bVboYDEZ9YZtX6isiwGYgAwALvdFc8BQpEHCquhrowNXPNVx7ABR++HdOL+XYfCrPCkAMRTXp6cWqmu+FAxCcFIa/X/8iS8RgGTGMi7xwZL6OzqJrpokDkycMLyJeqeGEm2+5DYVYYUhyieES4j0g3w4GITyj36KePCACM9hvzZuay3F11pZP3KP0WfUS6KBAhdbDEaUemxVSqbqkZHnrXzXAg4pMgighgpWdYEWHyPjqr5kvVrnmw02IvPxQYphXYUjNO5btsVu1KOBDxST6ARwSwDKsciDB5jyCWzKpA9/hEaLEvVzgQYVqLHPvGHVu8d0cwz9jhQMQnVot3fx8Zd1dliIJHWi8Zj4lrqhvSM5WqjpIZgJRZEWFaTNUlNcNm1e6GAxGfWEPv/CkiIhDhpmYrGl3X63blHeoiw2qxbO04K1XefTKtxV6+a32dKtLKVZ1bJnQhHIj4JKgiMspt3n1zYDaLI/O5dh9GUyhID243f9FAF5XwyjvOEqdmmBYji3CaQ9UMAOTLHIh0GxyI+CRIHxHAMqvOcSDiSbZYxq/+y9143ad+Bl3vvQebPPvC7dqhNu/d0F21YFNEeu98MZ0NrRGyPwSwbxA5PdN9cCDiEyGv+yzfJbm9G3a57eSFmSwW82UcWyzYHnK9ApmcYxqQUBZPopu6q8pVCewRYVqNNXnX/vVYTEMqwT6RboUDEZ+IFu8+y3e7sT9EOzgwazXF6sXJmXLpriwly3RTd1W5KoFz8UyrodjX6V7KmIFIL25oeh0ORHwSZOgd0J0dM9vBwROWN6QXB1bVM6oC3TX4jhURpp1Q1UzcKRDh7qpdCwciPqhWdVEtkPFpVuXx7v6wBSI9uIAIRcTjuumu1Ax7RJj2UXVJzQDcS6Sb4UDEB/Li67d8lwKRpS7Y5baTgyes1EwvLiBeXVWJbkrNyOmzbukEy/QOFPvGHBURMzXTgxuaXocDER/IcrRfRaSbdrntRFZEerE9M5USegWw3XStyKoVKyJMqyFFxMluJRSRHlxHeh0ORHxAO/V4TEMi7u8jk5tU9WJZalT0uiJSKLkPvCOEelbo/AVUVgfZI8K0GrfyXcCqaOzFdaTX4UDEB6KHiE81BLAeLlUdyLFU6Mh8roQFKXXVkx6Rcv2yb2Fsznd+zxmbWZUbmjEthrKBTqmZNLd571o4EPGBn8oHlf5UXMiH3SC5twNZDQF6s+wuH0gR6fzrpMAt3pk2YqVmHAIRVkS6Fg5EfCB6iARQRDRNw2CKDateyP4QoDd3MgUfZtVuSs3I54hTM0yrqYrUTO33ePBd98KBiA+C9hAhrBkifGM4sRICET8ziiyzajekZtgjwrSPqkdqhs2q3QsHIj6wuqoGC0REo6oueMC0g5WVmvEo3810j3JWsHVW5UCEaS1WHxH38l1OzXQfHIj4gB6QQVIzgNzUjCN0Jw7MrgBFxMewxG66TvK2zqq84DOtxbN81/SIcB+R7oMDER/4MRw6MdhFkns7IEVkzXAaQK8qItRHpH5qplipdnwvFZsiwqkZpsXQJedYvsst3rsWDkR8YJlVA6ZmuLuqK7qu45DpETl59SCA3tzJWC3e6ysiQOerInKgVOHUDNNiODUTjG7pYcWBiA8ss2qwj2ugi6ohWs1CroxFs1z1pEkjEMn3sCLilZqJxzT0md/v9KBVVq1KnJphWgwNvePOqvV56sgCzvnb2/D5u59r96HUhQMRH/gxHDphdVfl1IzKATMtMzmYwlh/EkBvSqqiGV6dILZbjM3c4p1pJyI149jQjFMzMnfsnsZ8roQfPTXd7kOpCwciPmCzavQcnjPSMhtG+8QCUuhBSdVvM7yhLrlWuHyXaSeeqRlzfe5Fr1kYnju2DACYWS60+Ujqw4GID/w0pXKCUjOLHS63twNKw/SnEiLA60VJ1a8i0i29RGyBCE/fZVqMr6F3rIgAAPYdNwORpWKbj6Q+HIj4IB+yoRnJ7d0w3r3VUK43HtN6egHxY1YFLPWs04PWAqdmmDZCl5xnQ7MeVFbDQIHIbLbY8fcqByI+KIRo8Q4Ag2nTgMiBSA10Y8RsgUjvLSB+yncBYNT0yRzv8N1LnlMzbeX/PnAQ9+2bDfRv7tl7HL/3hV/ghZnlJh1V66h6Td/lFu+CuWwRs8vGWqLrxt87GQ5EfBBm6B0ADKaNh8siByI1UCCSiGkiwOv0Hhph8KuInGKWMO+eWmj6MTWCrIhwZ9XWcvBEFn/+fx7B+77xcKB/d8v9B3D3nuP44RNHm3NgLYSUVIc4RKzP7BGx1BBiZpkDka6HvAtBFZEBUxHh1EwtFcl01tOKCF07dYLY09cNAwCenlps+jE1QtGmiPTe+epkFnLGOjIb8KFC608vBPokwjlP32VFhCCjKnF8qbMNqxyI+KAg5PWA5bumItLpvSHaQVlSRHpZUrXUNO9b7TQzENk9tdjRJlB5t9npeedegwK/XKkSqFFVtmjcV8UeUAq8UzO96zULSo0i0uEpXw5EfCDmhQT1iLBZ1RXZrEoda3thoVTx24Nmy3g/+pJxFMpVPD+T9fzZdiIv8iVOzbQU2ZMTRD3Mmues0MEBrl88UzOJ3lVWg1IbiLAi0vWEVUQoNbNULHdNq91WYTer9q4iUvDpL4rFNLxo7RAAoyNip9IuReT4UgGfvevZjpeYm4nsyckFuFdyRWMj1AuBvldqRqwj5WCKUS/ynBmIbBjtAxA8nddqOBDxQVhFhFIzum7Jo4xBxZaaodbM3b9QylSrOormLtTPtWP5RDo5EJGn77Zusf/fP3seN37vaXzl3hda9js7DdmTEyQQobWn1AuKiO6uiNBGUdch7ruVSLWq43kzEDl/6xgA4LgSiCzmS7j9yaMdE5xyIOKDsFUzmWRM3DBcwmtHNquKqpkeU0Rk9cDPtXP6OkMRefpIZxpWK1Xdlo5ppZdlejEPAJjLdnbDt2YiK1C5ABub3ArxiPRJ91i+2P3vNSxHF/PIlSpIxDScvWkUQG1q5l9+tAfv+vIv8c0HD7bhCGvhQMQHhZBVM5qmdU2jqlZTER4R9KwiIqea/AQip601FJFOTc2oVRetTM3M50rmMfTGNfLv976AC2/8EfYc9R90yqmZIGnMXjSrOjU0SyViSMaNry8XV+56SxUzm8f7sWY4A6DWrHp4Lm/+7FJrD84FDkR84DfP78RQxkjPLBfKuP3Jo/iP+w9EemzdihWIxITJzNhxd/9iSVBKLxnXHHdwKqeZisjh+TzmO3Dnr84Cinr67uG5HC76yI/xLz/aU/M9Kl3thRJUAPivRw7jyHwevwjQnExOhflN9Varukjj9EK6gi45J48IYI1KWMkFAuQP2TY5gImBFIDaPiIUqHVKA0UORHwgFJE6JZhOkGF1drmIa7/2IP7im4/i8UPzkR5fNyIrIvLn2is7XkDqqlqnmRkxnEkKc9lTHegTUc9NJeKqmYcPzOHQXM5RLl7Im4pIj1RETC0YO9IgyoacCvPrEZHnN/WSIhJ3iesHUmYgsoI9efuOSYHIYBpAbWomaw7X7BTzNwciPhAeEZ8PFBlKzTy4/4RYyL/72JHoDq5LoQUlEYvZUl69VDljle76v82EYbUD0zPquYnarEpehv2z2ZrfZaVmuv/60HUdU/NGIBIk8C6H8IjIykkvBPleqRmAm0gC1mTzjWN9mBw0FJGFfNkWiLIi0oX47QXhBEmF9z43I7723ceOrPjysnLVWlA0ybDai4GIX0UEkAyrHdhhVX2QRR2I0O5d14Fnldz1Qg95ROayJfE+gphO5aoZv/eJ/PrtVkSWC2XsnW7Mk+BVvgvIU6xXbiAya86VmRhMYziTFGlhuYSXAjVWRLqEXLEiFtz+dBiPiHFjPHxgTnzt+ZlsRz5oWklVSs0AkObNdP+DhvDbVVWGUjPTi52xQMioakTUVTPyQ1N+YFWrupjX1AupGUrLAEFTM8H7iMiKSDs9Igdms7jsf/0Er/74XTVBZhC8yncBS4FeyYoIBRwTAynEYhrGTZ+IHHRQ6mp2uSjW4nbCgUgdDs0ZXS6H0gkMm8bTINCNQWWP9PfvrfD0TFkyqwK92Z5Z9J8JoKSN9huLhjwt88//zyP41X++u+2fDQWJtMOKumpGDkL3HLUeVouFMkhA7IXUDKVlALuHox5hzKpZqXqkXUbwQ3M5vPXz9+KQmTI4MBu+czB9BG7mb+ERWcGByAkzEBkzAxAnw2rW/HwqVR0nOmAyLwcidTh4wrh5Noz1hfr3JBUSV7/sJADAdx+fauzAupyKooj04uC7QoiU3mi/EexSvwxd1/HtRw7jySMLeCZAqWczoEBoIGW8n1KTPCIAsGfaeq+UlgF6QzGzKyLhPCJ+g9JsiNRMNsLS12pVxx/cfB8OzObE1xo5h9VqPY8IpWa6P2ANQ1UKLCgAmTQNq7PLBfEzWen66QSfCAcidTgkGX/CMCQFIkOZBK66aCtS8Rj2Ti+1/cHSTiz3u7Gg9GJTM1pwg6RmxkxFhBaT5WJFPEBoJ12t6njghROB/AVRQGkRUvWiVkTkh+seKTUz32OByJH5sKkZqWomhFnVTyDy+KF5nP03P8Q/fv9p38flxYlsEc+Y6tYpqwd9H4cbtG64xCEYXOFm1blcSahGpK5OmIZV6iViDE20/k0n+EQ4EKmDUERGG1dEdqwfwUhfEhefMgkA+OETK1cVcUvN9MKDhhAm5wBm1TFTEZnPlYzdjSSnHjV9I997fAq/edM9kT0s/ELnpl8KRKI0Xcu+hxdmsiINQ6W7QG+k7o7Oh1NEbJ1VfSsi1gPZTwDw2KF5lCo6fiGZ6xtBzJTSgHXmGtpYIGL81zU1E9Cs2m4Db9SQP2Qok0DK3NxZHhHa3Ng/Gw5EuoBDDaZmaAIvAJy1cQQA8OrT1wAAbn9qusGj615Us2ovDr4LMxqAdjFV3XgAy073aVPSf/KI0YdGnbDZbERqRgquo6yckR/KlaqO548bXgJqZgb0RqB6RErNBPG8lEMEIrmAZlVSUKKS6ytSS/aUebM3Ypr1m5rxo4h89AdP45y//WHDlTydhGxUJSaVXiJZJW3FqZkugFIzG0b7Q/37QWnRPnO90SPiVaevBmBU0tAMjZWGPH0XsEpcg5j3Oh1RvhsgNZNKxIQHYy5rD0SOmg8was88l2tt91UKAgal6rEo0zNqEEo+EZtHpAcC1aNtSs34CeJyxWjLOqnSJx6zSvSbm5ox1ls/Zt77951AtljBI1JFY7czqxhVgVqzKisiXUjDioicmtlgKCJrhjN4samO3PH0ylRF5Om7gKWI9EJ5JhG0syoxKvlE5EBkasFYMCg4Xmh5IGIs7v2pZikiVkt8wKqckVMzPaGIzFvGzbBmVb+BiKyc+AkA6AGeLVYiMa3KXrBUJIGI8d/6ZtX6x059WXqp54iTIiK6q1IgoioiHdAqgAMRD4rlKo6aikVYsyoFIgOpOLZNDIivU3rmtidXaCCidEhM93T5brDbTK6ckUvrpoUiYjzI5tukiJBiA0TbS4QemjT8b6/Zb0J+n+Wq3tKpv1GTLZaxIA3AbH4fkWDlu7KScHyxccm+LCmfQhFpJDWjmNxV6Nr0k5qhj7OXAhFaL8j0DlgeEUrNsCLSZRyZz0HXjQeJHGEG4cUbR/GSbeP4w0u2izQEYKVnfrr3WE89fP1So4iI1Ez3PmRUwnbklStnZpTUTKVqtQefz5Va2qGX3k9/0zwixuuTcriXFBEl4Orm4W1yDxEgfB8RCkT2z2TxmbuedX2YyoFFVa8fOMqBy/Hlxh9QVek+T0XQtFB4RFyeXEEUkUoPKiJUGTM+KHtE7FUz7BHpMigts360z7WlcD36UnH8xx9diPe8+hTb189YN4z1IxnkS1X8bO/xho+127D6iJAi0rupmaAzikgROZEt2apmTmRLOHgiKx5Ilare0uFeohw5ERcBZJQekZz5eVHa8rnjSyhXqjYFAWj+NVKp6nho/4mmVFTIPUSAgKkZKYigoO2ff7QHH/ne0/ivRw47/hs1hVMviLMrIo0HIk5m1Uaa0vlt8a7u+p0ghWkp3zuBiNpDBLBSvblSBYVyRXw2Th1X2wUHIh4cnGusdNcLTdPwKjM985NnjkX++p2OalbN9KBZ1WpoFuw2I0VkXvGIAPZRAUBr0zMUAKSTMRFARtmtkz6vbZMDSMY1lCo6phbyNe+x2dfIN+4/gDd8+h58+s69kb82KSLrRjIAAqZmHDqrktndzbismjbrBVdy4BLFTlk2q0bjEfFOzVgt3ut/rrQG9VLPEVJQ5dTMUDohzL3zuZJ4v1smjAKMmaVi22efcSDiASkiYf0h9TjZbPBzrAMi0lbjZlbtpTRVmBbvgNVL5IRSNQMAD+2fs/19PtvCQKRMQ/xiSJq722gVEercmhDB/8ETuZrUTLMVkScOG+XRTx6OfgIyKSJbTb9YkPciD72jgIGCNLf7JmggYlNEIliXojeres+aoem7vlIz5mst9lAgQt1TJ6TUTCymYaTP7E+ULYlzvGXcCESKlaqtRL4dcCDiwUERiIQr3a3HSm5HXGNWTfReQ7NCiKF3gFI1Y0qtFLA9uP+E7WdbqYjIfVEsRSR6j0gmGRP33METOVvVDND8a4TMwEfmoy+tJ0Vk66QRiBQrVd/BnPxz9FktiEDE+TPJlZS0Vr1ApBRtICIaF8ajDUTcUjOkiBTL1bpqHX2ePZWaWTauB1kRAYBRMxCZkxSRsYGU6Pzd7s0wByIe0MC7ZqRmgJXdjlj1iLAiYmGrmjEVke2rDPVM3aW3NDUjKSLN8YhYnxepkAdPZGveY7MH31GfFrnMNiooENk2aW1u/L4fp6qZwIpInYdzTvJWzESQmhGNC7WIGpr5LN8F6q+r9Hn68ZN0CzOkiAykbV8fEcM0LUVkIJXA5JC92Vm74EDEA9HMrEmpmSBdAHuN2kDEVER60KwatI8I7WaOLxVE7v+0dUMAaqtUWtlLhHbT6UQcCbPXh5wuaARd122KixWI5IRsTMFPqxSR40vFyIMeSs1skUr5/RpW1aqZalUXRl63z6TGrBogNRPFLtmxfDcKj4jLkysZjwnlpZ6Ru9cUkVyxIq4luWoGkBSRbFGkrfrTcVFR0+7KGQ5EXKhUdRwxd0bNUkSCzkXoJWqqZhKNO+o7jXxIsyopIi/MZMVwqhetHbL9zIiQWhtfQJYLZbz+X3+G93/jYc+fE51iEzEkzPrJckSpGflB2peKY5OZv953fFns/leZu7dmBqsL+ZLNM3B0PtqdIiki60f6hELgVwWUAxFdB2azRXEfuXWcVXf79dIVuag9IpIXjALyhgKROi3eAdmwWkcRqfaWR4TUkFQ8Zuv1A1hrynyuJEq0B9MJoZy0u3KGAxEXji7kUa7qSMQ0rBnONOV3+L1hehHV/Z4RDc3si9RCvrW9MqLEenCHU0ToATzSl6wJhk83FZIoUjO3P3UUjxyYw389esTz56xpwpZHJKo+IvLDOJOICUXk6SNWKopmZjQzWCU1RPw94vQMKVxjA0lRsu47EFGCCLkniVslUVBFRA5coizfjclm1QhSM17tFPwaVmkN6pX1l/wh4wOpms+HFBGjasbqkDw51BklvByIuEBpmXWjGddJj40yEKDUrNco+/CI7J1ews6/vQ1/eevjrT/ACMiHNKuqRrPxgVRNMHz6OqP7aBSByP/3iBGA1DNOWqmZmEjNROURoaArGdeQiFtmVZLXh9IJ9KWcg9UooUo5IkqfSLWqi0CgLxl3Db7dUIO+owv1p/hSqoWuQa9ApFrVba+zkC83HPTRMScks2ojila91AxgeB8APx4R4ziyxUqkXqd2QYrImEPzTbtHxPhcBlJxEdxzINKhiBkzTUrLAMCgecMUK9WeSkn4oVqTmqntI/L01ALKVR2PH5pv/QFGQCGkWXUok7CVJ471J22ByFA6IR7U8w2W3c3nSrY+Nl7XIcn/6aRlVo2q3bra/G3VYFqkLgBguC9p+YhaqIhEWTkjX9t9qbgIDvy2a1c/66ML1sPDSVXRdV289mif8SAqeJwvp+NQy8eD4mRW9ToGv6/nlZrx672Tg49eSI87zZkhRqSqGarS7E8nRCByLIJ2/o3AgYgLjU7d9cOANMV0pakiqiLi1FmVHk7dGqTJ5ssgyHX/ADA+kMaaYcsFv360z+oL0KAicvuTR21Sudfu3GZWJY9IVIoI7dxN1SMW02wm8aFMQvIRNVERmbMHHkfmIgxEpM82k4iLoMvvRGH1s5a7tDp9JvlSVXiM6HrxUkRko+pq04/T6LwZ+T6Pcuidd2rGX1sE+fPshfQMBSLjDoGIbFa1PCJxrBpKY6QvGWhCeDNo6m+/8cYbcf7552NoaAirV6/Gb/zGb2D37t3N/JWRcbDBqbt+SMRjYlfUCzdCENyqZuRdI+3yminFN5OwZlVAHVqVRH8qgaGMscCuH81EFoj816P21uBefgW5U2zUqRmnAYFyI8GRvqQViDSxxJsUka1m18koUzP02abiMcRimuM174VqDD4qe0QcPhN5boyfQISCwb5kXBiDG5Xsq46BSCMt3r0bmgH+2yK0QhH5zF3P4s//zyMt2Ux5BiL9zh6R1565Fo986DL861t3Nv34vGhqIHLXXXfh2muvxb333ovbbrsN5XIZl112GZaXl5v5ayPh4Amjh0izuqoSgyu0ckY1q9JDJm9TRCq2/3YTxXJV7Lj6k4k6P10LLRyAlfOl9IysiDRSvjuXLeLuPcacI1rYPQMRSRGJusV7XnoIEvK9N9yXbEnTOwpEdm0ZN/9eXxE5tljw9aDJKYGp5Yvy937UoG9qoV4gYlU5pX14RLJm87OBtOUdOLZUwFKhjMcPzWN6IS8CC780y6zq1uIdsDwi9dbUimSCX2xSCe+//ngv/u8DB/HvP3+hKa8vQ3NmvAIRu0ck+LrULJp6JN///vdtf7/55puxevVqPPDAA7jkkkua+asbhlIzG5voEQEMGfH4UnHFKSK1ZtVambqbAxG5WqEvFSw1A9gVEcr5rh3OYO/0UmSpmbueOYZyVcdpa4cws1zEscWCz9RMDMlYtC3enZq/yR2NhzOWfNyKQOS8rWP45oMHa4bUOf38pR+9ExecNI5/f+cFnj+rTmO2zKp+UzOqR8TbrEqBT38qbvXw8AgCKHDpU0yMv/v5X4gZR0PpBD7/9vNwwUkTvo65IptV4xGkZpQZVU748YhUqzrkYrxmrb/0eX/yx3vxpl2bMCJtMKKGGtA5mlX7rG7NdJ7708HXpWbR0sTQ/LxhOhwfH3f8fqFQwMLCgu1PO9B1XSxIzUzNAP6j915DNataMrWTR6T7UjO0u5THnwdhVApEKCh5zRlrMNKXxCWnrLIFImHLm/dOLwEAdm4Zs3bnHjv7vGRWjbp8N1es9dO4pWaaFZiWK1UReJy3ZQyAIXd7/b6HD8yhWKn6mkujBiLCoB2yasbuEXFXRPpTCXENeilYFDz3JxOi0dUPHp/CwwfmoGmGarZYKON7j0/5Ol5AGm6pRdvQzGsYup+2COpn2az1l97/fK6Ef23CEEUZp8m7BCkisvIzmO4cRaRlgYiu63j/+9+Piy++GDt27HD8mRtvvBEjIyPiz6ZNm1p1eDZmlovIl6rQNGDdSGtSMyvNrCokW6WhWbFcFUEKLdyFcrXreonIu8swjPXLZlVjYXn7S7fi4f/xGpy1cUQEIpWqHnoR3XfcSJFumxiwph+7PHTLFSvVlGlCZ1X1IQ2oqZlE01MzRxcLqOpGCfH2VYPoN8+dV+UMfYYnssW6aQsKOPqEIhK0j4jx+hRUzEkDD51KYkmC70vFfakR9OCWFZFHDhqbx9/etQkf+c0XAwCeObro63gBqXw3qoZmflIztKYWK3jqyAJ+9/O/wEPKjCZVyWtWd1U5/fO/f/a8SPk3gxkPj4hsfgeMoDIdYoPULFp2JNdddx0effRRfP3rX3f9meuvvx7z8/Piz4EDB1p1eDbIqLp6KB1qNxuEgRU6b6ZSUafvWg8gkjPl3Xk3qCJysCR2lyEDkVGHQASwqgUyyZh4uIRNz7wwYyyKWycH6rbYlyV9e/lutH1E+mxmVSU10+Tuu6SCrhvpQyymYe2I4ck5MuduWKVApKqjZjifimpeDmxWNYO+IYedrNNr5MRMkbjVw8PLrCqlcqjRFfF7F27BqWuMJnp7TCXND05m1Ubu5aoyLNMJ2az69fv246d7j+PWhw7ZfkYNoJuhiMjpn5NXD6JYqeKOp6cj/z0E+cXUoAMwWt/L3VYHUgnPyqNW05JA5N3vfje+/e1v44477sDGjRtdfy6dTmN4eNj2px0cavLUXZnBjCmZrbRARFlQMlLARws2yfXy1zqVXz4/i/P/4Uf49iNGFYq1qIeTP0dtVTO1OxxN0zDcgE9E13U8bz5Et070192dy+mDVDyGeNQeEQdFRO4lMiL3EWlSFRUFIutHTVOwqYZ6KSL0GQL1e27kRGpLVUSCpWaoekqmVNFrzoWsyvkpnc1KwTMpIgBw7uZR7NgwgpNXG4MXjy0WMJf1V9brVL5bruqBTa+En9SMPDpj95Sh3qjD/1QhrxmBiKyG7FhvPMvk3i9RIw+zc0JeUzrJHwI0ORDRdR3XXXcdvvWtb+HHP/4xtm3b1sxfFxnNnrors1In8NIGm7wGibjlO6CF2V7K29mKyM+fncHxpQLuNHc8WYcqkCDIZlUn8xkAjPQZC06YQGR2uYjFQhmaBmwa76+7O6dAIREzOp+SIlKKOhCR2uHLvUSG5fLdJqljh0QgYvzOdaSIeJTw7pMCkRN1Hs41qZmgfUQqFIg4Gx7VIDIneUSSPibfWoFLwhaI/P6FWwAYaWRaE5856k8VsTqh2r1SYStn6k3fBexmVUojqZ9NKxQROTBcZ35uR+uYn8NSrVrN69zSwbJSMtBB/hCgyYHItddei6985Sv42te+hqGhIUxNTWFqagq5XPTjtaPkUAt6iBB+2xH3GhVzIUhI7veMIr3LC3SnNzWjBzItaDkpPx8G8ogk45qjFA+goRLe52eMB+j6kT5kkvG6xkm1R4HoIxJxZ1X187r6ZSfh4pMn8SsnjUtVM81NzdDDlh4eh10UkYV8SeTlAWvWhxuuqRmfgUjFQxFxeh2bR8SHIkLXbH/SGDo42p/EpvE+XLFjnfiZU9YYqohfn4hsVpU75YYNJuXAxg1aU1+YyeKE6aNRP5saj0iTAxEKbo9GML/HiXy5ItJAbulgOd3bSaW7QJPLd2+66SYAwKWXXmr7+s0334yrrrqqmb+6IQ7NNb+9O7FSJ/CKBUoORJJxLEujrPMOXVY7FQqsaFeZbdAjQgvXhtE+11xuIyW8zx8nf4iRfqyXmjlmLqDU6CoRcdWMXJEj89YLNuOtF2w2vheBWXV2uYhv3H8Ab9y5oWZ+D/UMqVFEXDwicloGMKbhepEv2VWyoLNzqOLFrdpB/VyylB5MxpH2YVaVyzoH0wnc9r6XIyE1XgOAU9cM4c7dx7AnYCCSiGlIxq3rOKxh1Wrx7v4z5LuTg0T1M66pmmmCWVX+HevNa2m6SYqInHpyU2HlQCTsutQsmhqIdFulA9GKrqrESp3AKy9QhFqeKT8UW+ER2Tu9hLUjmVBlbSSb0/TSRlMzWycHcNPbdmLTuLtPSQ5E/vo/H8fTUwv4yrsu8DXtlxSRLRMDANynHxMUiJBkH4+6xXup/ucVRfnu1+/bj4/+YDfmckVcf8Xptu+pszqs1Izzw2OfEoicqOMRqS3ftZdMV6u6Z38MumcGFUUkphkpixpFpGAFw0E9IoAVdMqcYvpE/BpW5Q2HZjY1K5arDaRmyCPiZVZ1MPNGoIhUqnqgAaiyD4aqL5uVmpG74rpdQ9RLBFhhqZluhVIzm1qRmvE5F6HXUM2qgNTUzFwscy0MRD5/93N49cfvwrVffTDUvy9RICJSM40pIgBwxVnrsGPDiOv3KRB5/NAC/v3eF3D/8yeEOa8ecuku4EMRWbIrIsmoW7z7mMsThUeEKlvmHNIo9DAiDwaZ+9y6bqqBSD1FJKcEInJqZjFfwsv+6Q786dcfcv33FPQNSx4RTbPSZWoQKXs+AvUR8ZDtqXLGr0ekrGw4/CgzXojyXR8NzWTUgX5By3fv2XscL77hB/i/Dxz0eaT2IJ2C2hPZUlNSi34UWFtqhgORzmY+VxIVLOtbkppZmWZV8orFY7WBCOW28zaPSPNSM5+561n8/XeeAgA8d9x/aaIMpWaoH4z8EGgWFIh8X2ow5bdVNZXubjFnqmQcph/LqKmZyFu8+1FEIqiaIeXKadIsPYzIg0HH4jYdl1Iz5OGpr4jYgy1ZhXp6ahGH5nKe5Z00fVf2iAylE1aKRzl3ObOpXr/UR8Rr8i2peV7ngCpnji8V6r5foLZxYaOD7/ylZuorIkEbmv1i3yyWixXc+9yMzyO11JtETMNof1Kcg2NN8Iks+/Ckjcpm1Q5LzXAgokBqyPhAKnTpZRBEaqa4sgKRsoNZlYIy2pk5zZ2JmtuePIqPfO9p8fewjeXIrCpSM9JDoFlQ+a4sc/sxrsqlu9sm7akZt4e8UEQG7R6R6Mt33ZekKPqI0MPc6XqyFBHjnqRzl3W5N/eZwdw5m0cBQBgj3ag1q1oqFLXnXiyUXR/STuW7I/1JqfrGWRExUjP1m4n5UfEGbJUz9dW3ctWufDZ6Dv2kZpwesqpaFDQ1Q9dAOUDgXVbSUqvNCdrNKOH1c+7kqplWPNuCwIGIAnW+a4VRFZCG3jWps18nouu6VYYnBSJ0cywXqaOqlJppkiJy//OzAIALthljB8KahqlBG+Xl8xGkZurh1LjISxG54dtP4PJP/ARPHVm0le4CIcyq8eZ4RLxSM2rqLowHjQJGJ6mezj3dk7KZVO17oes69h0zW+RvNtrB11MIalIzQoWqYmbZejjN5Zxfhz7rwbR13uX+KqoiIvcRoVSaH49IvUqvU9f494nIqgAQgSLio3xXnmpONFq+S2tSkHL1qpKWInN0MwyrWR9pNXtqhhWRjkYMu2uBPwRYmVUz8r0st2qmm8NKzTRfEaHP/Qyz4VCxXA2VbiiZC1uxUkWxXBULg9eDtVGcAhGv7p63PnQIT08t4tqvGT4YKt0FrON0S0McV8yqVmfV5rV4V5E9Irqu43f+7V68+bM/D9Qci45XVQ9kRXJQUUSA2of8iWwJC2bQR4pIPY9IoabFu9VHZHbJuwxY13XH8l1bx1nXPiI+zao+m/CJDqs+FBG1Oq7xQIRSPd4/R8FkvwgmnRua0fJTb/2lz7IU4LjpvdMat0YoIs0IROorsGxW7SKOmxL0agfHeDNYiVUz8m4kHndQRExVIdcCjwh97nIpZ5hzIbc6zxbL0qLemkCErle31EylqosghUyW5A8BLP+FX7Nq5EPvlIe0E/IDd2a5iHufm8Uv9s2KCiA/uHlESJFMxWOi6khurqZ25qTPcP1IRnRg9V8145CakfuROAQ08udsS83IikjJCNA++M1H8bEf7BZet75kwtf03ZyPhxkAbF9lKCLPHa//uavVcaLNe4NVM16KCGA9aMnsrSqqarv8YrnqmS6iNSHI9S66yppr3OohY41pRi8RP6kZex8RVkQ6Gtq1ZFp0ouQBTWHbHncbsipqU0SknHypUrXlcf12n6zH9GLeJo3SA2i0LykWyTDqlHysy8VKJFUz9aCSwMF0Ale+eD0AiF26ymK+BDWTsdX0hwBWMzmn8l2jqsN4XTU1E5VHpOBHEZEmNMvt1J864n8Im1tqRvWHAMYunoKFnBKIiPb4kwMYG7DKqL0+D/eqmaotEHFqn16xBSJqasYKaJ49toRb7j+AT92xF48cmAMQvnzXjWGzo6/6mThRo4g0WjUjlIw6gYi5qTln06g4DlnppOMakR7OXv4wOndB1FKh3pjHSh6R6SZ4RJZ9mOPtfURYEeloaOedrqf9RYRc855tUvqh05BnMMhVM/3SJGJ1Z95oaqZQruCfb9+Diz9yBy77xE/E7kf4AjKJhiYhywvUcqEsdbVs3g2/eaIf//yWc3DzH5wvFjm31Aw1PetLxnHaWkNaf5EpsQPeXT7JH5JKxDBsPqhFi/fIh97VV0SK5apQLgHgqSMLvn+Pm1l10fzc1B4dtGCrgQu1fd841ifa8Vd1b7Owmn4SQU6pghnp/cw6pGbk68uWmulLWtVE5apjczujaiZe8zoqfsp3ATkgrH+fqOW7kaVm6gQi1APqwpMmxNfkc0jHlU7ExTXnpYTS94IEIqS+URC2xlREphejT83IXXHdGLWlZjpLEemssKgDoBsk3cTcvkwmGRMNiZYL5VDNtLqNSsU5EJEVEXVn3khn1ZmlAn7n3+4VvQ+KWWNHvW6kTwQiA+kEBtJxzC6HU0RkyXa5ULYW9SZfR68/ZwMAq4JhIed87DQyfnwghS+94yX43mNH8NvnbRLfz0hqg4pcMUM7UdHiXZ0eFpIgVTMAMCU1GQsSiFDgVBuI2I2qBD2k1NQMbVj6knEk4zEMZRJYzJcxmy26zgbKKeW7Vlt9q2oGcE7NyIqIfIwjfUnxb/OlilDEJgZSyJcqyJYqWDfaJ6oBvQKAZZ+pGStFVv/cq4GDn+odP69Xr6/YR954Ft5+4VZcdPIENA3QzYZv1INFThkNpBPISaqfE3T+g0ybVo26lP5tjkfE6orrRiYZEw3l2CPS4VAONdUiRUTTtBVnWLUpItLOpk+qmolSEfmftz2DZ44uYXIwJRZRWnRopzOUTjQ098ceiFQabvEeFFpgF10UkTlzpzzcl8Sa4QyuumibrTqCAgCnFJjoqir5pqJu8e6nakbuGCt3O33aZxM3wPIGqIGtWjFD9LmU8KobFlJFvHwiBUX1kauA5KoZp9eQP2f5IWIoIlZajRSZU9YM4gfvuwTf/OOXYsNon+XNcAkAqlXddd6PSr0BiU7HXZOaaXDoXb3UzMRgGhefMglN0xzLm+UZOKQwea2/dD8HUkSU0uU1TSzf9bPeaJomeolwaqbDIclenhTZbFZaCS89DDTNXr4rFJFCuSbwCGtWfeboIm65bz8A4NNv2yV2JfTApo62hiLSQCAip2aK5bqTMKOGeoq4eUTIdzDqUGkDWA9Hr9TMKmkiq2jxHkFqRteth6BXIJKMa6LK4bA0/+XQXA7zdXp4ELJZVS7/VZuZEW5VFyKFa64TpILMegQibmZVADhuU0Rq3wsddyKm2R42w5mErRkdBdjDmSQ2jvWL0mJRvuvyIJXTFvWCZ7e+JU6oJaxpj4DXD34VERk5BUYIRSSu+SoYoEA0SCpS/h0AsNpce+ZzpcirAP2m1a5+2Ul45WmrcZZHx+Z2wIGIQlFZYFrBSqucEV1VlV0NeUSy0uA7IuyN++HvPoWqDrz2zDV4ybZx8aChB/ZSwfQGSIFIqNRMxTk106pAhN6XmyJC3gHZsCbjNWvmuFIxA0Tb4l0OMr0+L3l3q85/eWrKX3qGgmDDvCgFIkp7d3E8rqkZc8Ni7vDHzc91ziMgcjOrqjhXzZgNAOMakvGYeLCrZtXFvPP7SNfxZsjvL1NnVlG6Ts8ZGdWsmo5IEQky88XJ/yQqWmJWILLo6RExUzMBUpFq+e5wxqpeitqw6qcrLgBcfclJ+OJV57d0o+2HzjqaDoAWxVaeqJWamlGHM9k8IorsG6ah2c/2Hsedu48hEdPwQXPAmfXALqNcqYoH72A6gcEG2u3LC9RyUUrNJFsjgVJqxs0sSQ9I90DEPoBNRm1mBsjlu417ROQHRKbOfUcPwcPKRFy/PhE5YJTf64KLR8TqruqiiCQVRcSjl0heKVFOxmOOD1THQEQoIsbvo4BNLt8tlKsiEFWVHTKrugUifoamEWpjOS/cyncbb/HuPxDpcwiyK1Jn54E6inS1qktVM8EVETrHmqZZTc0iNqy2okqvmXAgomBJrq07oSutzXulYl+ciP6IPSK3PXkUAPBbuzaKVuZDkpdCro4ZkD0iPsoSVeQc/lK+HakZa1fnVAZOgYjc1EhGNk6qOAUiVkOzxhUR+qyScU2UBbtBO0pSROi8+g1E5M6Yeek800NIrZqh86eWqooNi1BEvD0ium49zNJSSsYp8PLyiJDMf9aGEQylEzhpctA2lZiqpobVQKROH5EgIwnUxnJeqMMto6qaCRCHCB+PU9VMPGZ5RNw2IPK/C+IRUQMRoHk+Ecus2lneD79051E3kWJbFBHjRlkpE3grLiV4orNqobZqJoxHhHbN1DUVsCsiS2bgl0oYbvKoUjOzkvGw1WZVXTcCWlWap7bhflIzuq7bzIDqnBnA2plHYVYV/hAfwT8FTJRquujkCew7vuy7l4js5ZGvMTlFJ9OXdC7frTGr1vGIyNevnJLJJOMi8B3pS2I+V3L2iCizmb70jpcgX6pgKCMpIiWr986w4gWi9axS1R3H2fupunA6/kK56unrqSnf9TF8z4twqZnaVFIlQGpG3iAGCbzFOicd6+omVc6IBootqvaMGlZEFNqZmlkpHhE1b0zIioi68IdRRGjXTI2/AHt1yZIixzfi1ZFTFPJ0zXo526hIJ2JikXcyrFLKxs2sKhsn1aDPUkQsNYV25lGkZkht8NNEUPVuXbR9EgCw++iir3bz8oNEvsYo+FSVhLqpGTKrkiLikpqRjZ19SiBCnGJOtp3PlWrei5qaMUqGk+ZrOHlEnBURwHlXnwuQSpTPQT3DavOm74ZJzTgFIjGhgrmlZmQ1LJgiUjV/h6SIiO6qEQciheYP2WwmHIgoFM28MZtVm4eaNybkWTM1VQqhAhFDEVk3YrVvtykioodI3PxvNIoIVUBkkrG6+fao0DRNpGecfCJWasZbEQHsDxdd1y2z6qD1OcYjTM2QV8OrhwiRVn7m7E2jGEjFUSxXRdt1L0pS4CQHIosuqZl+kZqxXxN0PdKDddzsruo2gZd+VzxmmE0J+T2ftMrqdKs2Jis7yPzWa1hVM3TuVUVMbkfgpC7S2uMnlSh7W+pN0a0p321DasbLrJqQUjNuzQDlFG6wQMT4r10RaU53Vb8DCzsVDkQURB+RNigiXg11eol6ikipotfs7II2NCuUKyIgWC9NUpYDkWXROyJp/pdSQ415ROjB3epafcv/UnsdUR+REZfUjPxwkU2cS1KabFJWRGLRtXjPS0bJeqjerYnBFE4yZ588P5Ot++9tZlWnQCRt/3wyLlUztE7Q8dTrIyJKd5V1RQ4A1wxnhCKjBjS0u07Ga5/Aaamc1k0Rkf+dUxBAgZLfHbXlS/GniETdWTWIIpJJ1h6rnJqhjqNOXWkBIFeSUjMBrnehiEjHShsBt+q2sFjnrzvdFhyIKNBukBWR5qF2HCTkRZB8FrTA19t5qVDnzUwyhjHp4SubVa0mVnZFJIxpWJbSKRBpVVqGoIeYlyIy6mJWBeR5M9ZnTWmZwXTCtsiJFu9RBCJCEQmWmhlKJ5BOxMV14+cakc+TU2rGrWpGTRXSOkEP1npVM/Qe1R2r/J4nBlLiddQUD1VrOCkiaaniaVGYVe0BlaZpns3Egjbg89vUrMasSh6RkIGIHsYj4mDEFgqTpgnflFsvmigVkcEmbTr9TN/tZDgQUbB2Om0IRFZI1YzacZBIxmNiYae21bRIBFVEDs8Zgcj6kT6b8VLIsLlyzcOnkdSM/ECmAWatlkmtpmb2BVXXdczXMasCzr1EnCpmAGuiaBQt3nNF/2ZV+cE9Pmg8tNOSWbMe8nmS0331GpqpVTPqOkEBs5O/Q/73qqIjp2bGB9OuyoqVzqxdl6wHbVX4g9T3AXirEZa0729H7bfNu9rUi85VWEWkEqahWar2uhbelbjVbZQM3SpyV91SRa9bKUSUHTwifrq4evGdR4/g8k/8RIx0AIzPmN4bByI9gtjpxFt3Qq0H4AqpmvHId1MvEXqYk5Tpp520DFXMrBvN2L4u+m1IZtWBCMyqcoqC1qlWLwpy2kkmW6yIHbW/QERSREx1Z3LQrqQkI+ysKtIWAc2q46Z6IJeT1qOeIqI+wN1SM2oHZvpcdd1Z4ndrny4HX5MDKaHeqYqIWr5rP0ZrQrBbYzb5WB1TMz6Gptl/p09FRNl0NN7QjDwiwRURp/LdREwT6Uq3ZnTqufebjqw6VM00Goh845cH8PTUIr7/+JT4mr0rLqdmegKx0/FhnIuKRhppdSNuZlXAupFm1UAkoFnVMqr22b7u7BGxKyKNTt8lWp+acW5qRv6QVDzmPd3WocxxWVST2B9sVkOz6PqI1GtmBtgDkYmBtO1rfq4RW9VM0eqy6p6acR55r3ZgTsZjIlhTu77Kx6YaclWFx0rNKGbVir181+k15InEjopI3I8iEswjUk8RKStKTj2PSLWqu5pGje8b/603fVfGuXzXUitGTRVqLltyVDvUvkJ+m5qVHdJp5EEKO87jhZll87+WH4oUG03zZ/juRLrzqJtEuWLV4bdq6B3A5bsyVMFCgYicmvEriQLA4XlKzdgVEWePCCki1M+lMUWEaLUi4paaoTkzI/1Jz52kNbPEeki4lbMnImzxTg8IPw9BObUxIRQR/50+5aoZ+r1yStS1asZ11ox1PFsmjKqX52dqq3css6r9PcobnomBtGtjNEsRqV2XVEUolYg5+m2spma1ARsFIn7Hw6cd1DMnrPJd5RhcztVffPNRXPAPP8KTh50b1IUxq1LwLXuIZEWEUjPFSrXmPANWaSxR8pmOdPLC0fXl1U7ejVKlioPmFOX9s9Y1JnfFDaIUdRIciEjIcmErFZGV1uJdHQ0uQzvQmSW7WRUIJuceEakZuyIyLEmjiwV7akYOCIMEPYBziqLlVTMuRrj5Oj1ECKedo9vsJWv6bnQt3n01NLN5KoxrQ0wO9mVWre0jQrvTVDxW4+Fwm77rZGrfMt4PwL5bJfyYVcf6k65mVafdtdNrALW9UAgrCKi9VnMBKpcA/+kw1Q9Wr6HZQ/tPIFeq4Ev3PO/4/UbKd2VVqyJ9nv2puKgqckrPqKkZv+lIJy8cbXqK5WpgA/7huZwI/O2KSHdXzAAciNiQo/SWKiIu8m+v4tUTgXagZLqT+14EMaxazcycFZGqbtXyk4xNgUi5qgd29TvtkjrFrDpfp4cI4eQRcRt5kIjUI+Lsn3DCnpoJpojoum5LJZFZVShjDg/wPoeHGOBsaidF5AUHRYTSQDVmVVH+m0QiHhOB9+yy2kfEvXxXDUSc/CEAPKtmglQuyT9XVxEhVSDur3yX0qL/36OHHTdmdPoaLt+V/BuaponRB86BiKKI+NwQqc3cAHvqL2h6Ri5Pn14siGsyaMVTJ8KBiAQtZDHNWQJtFm4TPnsVpxuUUKP6oUxC7H6CNDUjs+p6RRHJJK3JpVMLxs8IRUT63UHSZNWqDicBpeUekT5nRWSuzuRdwjEQcZiPAjTHI+JHhZQf5MKsKkbL+9udq7/XrfcG4JyasaVwpUBk66ShiDj1M3H3iFBDNOO9jAnjpJsi4lA1o7ymmyKS9AgCgk4d96uIqGZVKxBxvpfpvssWK/j2w4drvq87GEDr4WSsVauQxOfuUDlT6xHxF4g4mfLjMU0Y8oMq4PuVAHf/rHGddXvpLsCBiI2iy+6v2fRJi13QlEA34scjQmSScVt5oh+WC2WhqKiKiKZZnRSPmCW+tEuJxzQRPAQxrLrljFteNZN2MavWGXhHOO0c1eFuRLIZHpGAfURqq2bqdPmsuAUiznNmADk1I6Wr5BSug0fEURFxeY/0kJww5/i4pWboc0469RFJ+FNE0h5m1aDDPv0qIuoDP+URwOi6LuY/AcAt9+93fb1A5bsOqpaqynr1ElHVsKCpGTVoGnSpbquHGuDSddbtXVUBDkRstGPODGC/gMI2+ukm1EFYMqoikknGA3kAAKtiZiiTcFyU6WtUIiw/gML4deSFSV502peaURWR+j1EAOfGT+q4e4LeZ5AGT24E6eppbwBGVTP+UjOqn4UCLreKGeOYEuK16SEoKy82RWTCUESOLhRqp/WWnFMf9J6p4saaWWN/IJYcelIQRtv42hJRFS+zKt1bfr1xgRURMqvWqdyRG5Y9enAeTxyet/0Mxb2ByneFIlLbWZXWIJGacSi9VtVR36kZF/VmMKQnkAIPeuukiOQ4NdNbFNowZwaw75KiSs98+s69+JOvPuBrEFir8TKrDjiY+ZwabXkhNzNzQl2oB2yBiKmIBGguJ0v+sg+j9VUztNNy9ojUM6umHT5nt50yzUuJQhEJYpR0Mqv6Nk66KCJuzczUY6Kfp9+TiGm2h8xof0qkReghQdBDUE2jvPbMtXj5qavwuxdsAQCMDVipmar02aqNwVRko2/dQMQjNePXG+dkbHZCVUTo3zn5VOiBr2nAZWesAQBbvwzA/eHuhaiacRh6F1MUESePiFpJ47t8t+q8zg1mwpXwkkF1x/oR29/ZrNpjFNukiMRjmvidTuVjYfj83fvw3cemfI9HbyWeZlVlV5pJxKw+ET4VEbdmZoS6UNsUkVQYRcRaVOVAxG+XyqgYEn1E7FU/or17XY9I7efsFpw3pY9IwNTMRI1HxPv6UFNoqlnVST3LJGNiB0oBk5efYuukcwmvW7C1abwfX3rHS/DSk40pwtSCv6rbTcfq9F2VtPS6as8XwkuNcFO+3MgoKtT0Qh73Pz9b83OWKZSOwb2zqhhCmUrgzPXDAICjC/aeLNVQqZnatVVVRLy6q4ZWRFyCx6EQiki1quMFM7i95FTjWnmBPSK9SbtSM4Dszo+mhJd2Km5jyduJl1nVWxHxGYiIihlnRURdqOVAJEx3VTmwkj0ufrtURgXtxouVqk0dmBcD7+p5RNxTMzV9RMT03ShavAfvIzKQsq4L36kZF0VkIe+emtE0raZyRu2qKuPmE8kLQ673e0wlYuJBNSP1EqG0klM6E7ArLa5VMyI1Uxs8WuXIfvuI2BWR677+EN70mZ/bWo8DXmZVJ0XEeK3BdALjZtptVumnEq5qpva6Vtuve3lEasp3fZasu42ysJoq+h98N7WQR7FcRSKm4cKTjEBkv+IR4UCkR2iXWRWQZ1pEk0qhRbkTAxEvs2qNIpKMB5olAlg9RNRmZoS6UMtlmwMhutzKnhdZHm31wjCQSoidorybFpN365XvOpiC3e4Jqiqr6rClEMIQxqw6LrWcD21WLdpTM07lu4B1HrPmFFYvYyf5RFRjIaVm/LzHteZ1S2ZqwLvFu3EsciASIjUTcOq4pYgYn+EBc3f+7PSS7efczKrlql5z3QhFJB0XRuSZmkAkfB8Rp+m7wiPS72wSBmoDEb+pGXXyMCEG3wVYYygNs2m8H9tWGcHuwRM5lCtVy6ya5NRMT9Cu1Awgl/A2rojI5YVOY8mn5vOebZSbjVeLd1UR6UvGramwvs2qpiIy6tcjEpf+P/jcH7n9tryr9jM7JUpi0u9fyFnX0by5uPptaFZwMqu6pGYAS34Pi1tFiROrh42H9FZTeZCPrZ4ioqZmLLOqe9UMUDtvxks5JUVkvxKIUNDjJ/20ccy4bg+esF7Dq3xXfd1hl/Oc9ErNlJxTcG6oJdMURMht5gEHs6r0+qpPRB65MDFI/VTs61eo6bsOqRn18xSpGY8+IvQr/aZmyi4bLgp4g3hESGHbMtGPtcMZpOIxlKs6jsznrTlBrIj0Bm6Lbivoc+hXEBbZHT6r3FjzuRIu/dgd+O3P/DzQa74ws4z/+cPdrqOyg6COBpeprZqJOZoovaDFSx3URsh9FpJxzbazbSQ1k4jHbItBq1MzgHNTs8B9RGSPiEuPDzmIbLSpmfCI+FhId24exRfefh7+8TdfLL7mVzFTjzNf4xHxVkTySmrGaZ3YIhQRe2qmIBqG1V9bNpiByCFT2QOsa8ypoZnxuvXNqmmRmnGqmglZvls2Wg7Q/ULTmokaRUQyw6qBIxnEB9IJoYjMLillzCFavNOxFstVoVKo3hWRmnGsmjE+L7q3/F7vFYcW70A4jwgpbFvG+xGPadg4blwj+2ezVmrGZ3v+ToQDEQm6QdsSiLh0cAyDvKNVGyMdmc8hX6ri6anFQKWX//Kjvfjkj/fiw999quHjsxr91H5P7SOSlhURn0FaVlrQnJBTM+ouOMzcH1qYknHN1hStHS72YTFLh9IIFbFQjUbYR0ROETTa5p3SkX4UEU3T8KrT19ga1fk1M6vXO11PXg3NAMt0nFXMqs6KiBGIHJ7L2VJFQSqDNowar0FzRQBLdXNTAuwekQaqZoI2NCsZ81koy3LMJXCgy0cOpNRU2pI0coGMyIuFsu3nwqRm5M+crmdrDSJFxLmzarWqi0CZUpu+G5pVolNEaLYMKW7yOAERiLRh4xMVHIhI0I6qle3diSgVEXmnofYjkB8y6u7Fi+eOG7nfWx86VONkD4q6S5JxUkSCmlXrmbeGbJ4Q50AkyG6lJD0k5NdrR4Mhem/U1Ix2eJrm/oAinD5n4RFRFjn53DWsiDQoLWf8KiJ1OqvSZFQVWuCzSvmu04Zl1WAa/ak4qjpwx9PH8L3HjmAxXwrUQp1SM4ekQEQ0NHNZm+Ty3YaqZvx6RCRFRH6g1qRmKnYFQ9M014BoSTIND2eSIug6Yba713Wrg3Gw6bvWZ0PXttrLaNSls6q8HluBSGOKCF1nQTwizx83FBHq3itM0bPLUtUMe0R6AjE/og2jlIUiEnUgouRYZcVlOkAgQjnvYqWKL/50H+ZzJfzZfzyCf/nRnsDH57ezqqYZi6fV0MzfTkRMEnW5Mb0UkcEQZlU5sLJVzbQhEFFTM5RKG84kHT9vmbRjQzNnlVB+KT8lvEuFMv7i/z6Cu545Zvu6ruuBPCLOx+23j4hdVcgpqRk3j0ifkprxMrVrmiYeEtd85QH88VcfxEd/sFtsAPysLRscPCIlj6F36uu6BiIiNWP/nKpV3XF2jheyIiIH7TWBiF676Ui7BCLLklk1FtNEc7eZZeM15cssSGpGbvhG57yifJ7ylG/5+qd0kaZZ14dfBVCoLi5VM34VkVKlKjaC5I0i5e3Z6WXurNprBG3qEyVW1UwUgYj1GqoLXL7J/CobS4Wyzb3+1V/sx5s/+3N888GD+Jcf7Qnclt5pPDYhBw+ZhDHW2trx1v9sdF0Xi4dbzlRWBlxTMwHOgzyQTFZE2hGIqKY78suQ1O2FV2pGfUBpmhaozfuPnjqK//jlQXzsB7ttXy9WquIBE9bc67dqhh7mdP7zparRVrxuasZuJK9X5v/S7RPG98115Kd7jwdKzWw0005TC3mhtlXqle8GaGimBmxyYOI7NSMrIl6BiGJWBWSviqKImF4MuofomqVruCqtM0ECEaC2a7CqiAymEyIokX0iOSntQZ+Nb0VESf8QIjXjc7Pz9JFF5EtVjPQlRSBy9qZRAMAvX5i11jsORHqDoIatKOmLMhCRHiRqzlMORKZdAhFd1/HBbz6KT9+5F4Clhoz1J3HqmkEsFcp4esroFxBmUq1bfT1gj+rp/y0PQP3fYzxcjP93V0TcUzNhzKrybnXA4fhbybiyeFMgOuYjEOlzMqt63BNB2ryT32Hv9JKtbDMvlauHVkQoUPXZ4l0OPgvlan2zqpKaqTcg7i9/9XT87IOvxM+vfyUA4Lljy2JX7yc1MzmYRioRQ1U3KtyMY/ff0MytDJkCI/VBKn9uvvuIuCkii0XbxsQpDeuWIqJ7jsyc6rUsByJawCcXBbkUZNNrkUqoaZpj5QwZVfvTCfEegg+9s3+d3h/1EfmXH+3Bn3z1AdeA/sH9JwAA52waFcd71oYR9KfimMuW8MyUoZZwaqZHaG9DM9MQF3FqRi1/y9kUEefUzIHZHG65/wA+9oPdyBUrwii1eWIA177iZADASZNW+WSQhzZQx6xqU0SoLbR/j4jcmt3twWZLzailvKnggYicv6fAJqa1R1mjxZtScjROfqxOMzPA2WvhZWKkhdmPIkIVILlSxVYNQtdjIqa5+h/qIUv9XuoceVnkQGQxX/admvHT0AwwArQNo32YGEzj5NWDAKwHoJ9AJGb+e8AK4ERnVdeqGeNY+pJx18/Rmr6rzMEx/65p7lU5tb/P2SOSK1VsaqKocpEOydUjopjMqVfMjGmAlU9tEI+Icbz2El6neVcjDpOPcyVLbaDPxm8TP7cUtKyIVKs6PvXjvfjuY1PYd3yp5jUA4CEzENm5eUx8LRmP4byt4wAsZYkVkR6h3gLTTPpS5o0ScWomV6rYHuCy7O6WmqHGTVUdeHpqQTTT2TLej9efswG3/slL8e13XxxqUi3gLlkC9pbatNj5NSMCQLZgSeBungiayQIAgynn1ExYsyrtSvpTiUCDuaJiTGkERYrI+IB36S7g1lnVvZKMHop+PCKHpeBj7zFrwW3UH6Iem5cqQucpk7QeKhRkJ+Oaa7BWG4j4V053SQ8PwP/7pECEgjavQZHyscjXtgr5n9Spr3JK2u81Kysi6lym46b3rFq1zKU2RaSuR8Q5NSMHvGFTM5TerTgMEbTavDsoIqmECPCCpmZcG5rlyzi2VBCBhFszywf3zwEAzt08avv6r5w0bvs7ByI9Qj3JtZlEW75rv6BlqdGmiLiYVeVg5ckjC2KmARmkzt08hsF0ItSAOMBbEdE0qwSW5OYgs2YoiFLLgGWGPRQRKzXj/zxYA8li4t+3yzg2oYyRp0XcT2pGHWSm61bazclkKdq8+zDv2QKRo1IgQo2+Gvi85IDAKxCRe3HQg+m5Y0YgsnYk4xq49itqZZBS111b7IGInz4iQG1TM7UluQq9rlt7dwBYYzaDo3QPEaZ/khy0qqZL8onIje5kBYM+t+ViBZ/68R48fGDO+LuiTKndVW2pmYAxvjAcm2uI0+yeUTMQlXslyXNcKPD2nZpx6XkyZFbNFMpVcf3JxyZzfKmA/bNZaBpwTk0gMmH7O5tVe4S2dlY1H75RV80A9vSMH4+I/DNPHF4Q7Zs3mbXrBO1cgnaD9Zq+C1iRPS2u6SCpGWkH40Y6ERM74try3eBVM7RDSsY0MWjPrb18sxGKiClnU4pmPEBqhrw4pYq1o/XyiNQr39V13VaKumd6Ufw/Xe+N7OaScU08mLwMqyXRATcmAp/njhsPAre5RPKxqakZPw/unTWBSEBF5IRdEXEt3zVf16tEm6ZRH5nP21JYYs5MAFVKrlRSuxCLQERWMOTUjPkevn7ffnzsh8/gH77zJABLqalVRGqrZoJ0VgUsRYRUB6fNECkissFfbgWQNN+E30GPbiqWvPnZPbUg/t9pfXvIVENOWT1YUw1FPhGCPSI9QlvNqkob6UZQF2M55+mnakYNROTUjEy/mFQb7JjLHqkZwFqI6DOxGpr5SM34cJBrmiZ2joOKciIUkWLZdzWQvFvdvmoQX33XBfjUW3f6+rdRU6OIBDCr0mJdqeooVaq2qgbH1IxPj8hCvmzzDeydrlVEGknNaJpmSxW4YSlX1iC7fccoEHEPHDNK1UzRQyVSOWlyQJSGapp/1cEq4SWPSB1FxHxdt9JdwJphkytVbJUhYs5MAI9ORjIIq8PbqKmZfF04pWbu3mOUch82Z+qQskr3pDr4rtpAakYd0mc1WrOOS3hE5NSM1AogmbArIn/3X0/iD7/8S9dZS27DPY0UrvEed0tDAp3WNzKqnrtprOZ7sk8E4NRMz9BORUS0kW6CIiI3NZNf/0S25LiDlG+Ip48siDz1Fmm+B2DNhckGNKtWPVIzgKyIKB4RH6mZZaUE0A3aOapNrOjfVXX/6pTabOqikydr1KNWQQFHtmh4g4IoIvKDNV+q2MqlnR5SlkfEO0CU0zIAsGd6SQR5or17g10h/UzgtTrgWr1p9vlRRESPn6rtd6R9PLhjMU2YDNMJ/x6MjWPG9UP3XkVKKznx4k2jSMVjeMm2ccfvA8ZnTOmOI1J6xq2NvxdyQKW2CCCPiJyasZtVjc+TlMRjSwWzTbz93vVKzQQURGoqwpz8G3J31aenFvDwgTmxtvWn4jVVM1/++fP44ZNHcUDq9yLjteGiDc9TR+RApHa9efAF06i6ZdTxd5BPJBYgyO1EuvfIm0A7zarWYK3Gh96p/TZmbS5w+/emHSpnCkr5ZqWqI5WIYfVQ2vZzYXpuAN4NzQCrcoUeFk7TM93wo4gAViCiekn6knGxyKmmPjdKdSoaWslQOiEeVrPLRbGI+1FEjAel8f/5UtXW3t3pXPlNzVAgcuqaQcQ043OlZnpRmFXp2IE6qRmpF4dQRMyZMOtH3RURKzVj9hEJmMogn0iQ90iKyJH5nKlQeauIOzeP4dEbLhNVbW6sNX0iR+at4DCMEiwHjscWi+bXjGM7RqmZirMioj4wi+UqFqTqJbr/1cF3svAQ1AieUTx4ZYcGcaRc3fvcDF73yZ/ht266B08cNlIn/Wm5akZHuVIV58TNT+a14aL0zO4p90CkXKni0YPzAAxfnhPkExnKJNtijo8KDkQk2mlWFYudz8FuXqj9NuZsHhH796YXa9MzTpH55vH+modRGD8FUL8CgBqRUapAmFV9le96d1UlLj55FYbSCZy9cdT29VhME62cnSZxOiFP3203mmZVf8wuFy1FxEcgIqc48qVKXRNj0mdqhgKRrRMDoiHTHtOwmo+oK2TaR/ddWRGhIILueXpAO2E1NDPNqgFTGRSIeBlJVdYMpRGPaShVdEwv5j0nVhN+VCUKuCgdAoRTghMxTQTs1COFzq2jIiIdttPvOTKfE8dBmwS6ZueyJZQrVctbFuI+U7szOyoiZiCy7/gyipUqylUd//XoYQBmakaqmpHXWDezvlP6h6BeIvLGUF23Hz00j1ypgqFMAievGnT8HeduGsV7XnUK/seVZzh+v1vgQEQiaJvjKOmLMjVTck/NqIqIUy8RJ+VB9YcAUs+NiM2qatWMnI+uhyylevHBK07DQ//jNdg6OVDzPXLPqwMD3ajXbKrV0AI+NZ8XgZmf1Axgr4ao94ASDc3qBCKHzIfe+tE+0Vdjr2lYjUoRUTtnOiHMqpJHhJCH6Kmo4xeEWdVnKuOCbeP4b699EW54nf+HRSIeE76VQydyIv3VqOpGPhG5ciZM1Yzc8ZiM0VRVp5pV4zHNtluXU1r0ZZqlAlhK61h/Snz/RLZkNSEL8RH0Je3XR0WvVWVHpXvktLVDACwVpi8VR0IEIkobeJeNmFd1oFPTOVXJ/v7jUwCAV7xotat6rGka3veaU/GbuzY6fr9b6IyVs0MQkmsby3cjSc0o8rScw1UvdifDKt1k8m5h84RDIBKiCyng3UcEsIIIYVZN+ldEgozETrjsaEcdTGteCCNhB6RmACsQedbs1xGPaZ79JWSsB3q1bnWI1eLdn0dkw2gfTlljBCJ7TMNqZB4RP4qIFDCqgYiXWZVM2bmaWTP+1glN03DtK07GK09b4+vnCbmpmVVu2tg1Rl6Yw7bUjP8qIBn6+Rkz8KCg/rhiVlU3HClhrE3gXLNV+QtmiiyViAnlIR6zup3OLhdFUBAmBaH2yHFSRHasH8b4QAqXnLoKt/7JRba+HQOpBJJSubo9EHFel7zWuSGHAYvya+q6ju89fgQAcMWOtfXfYJfDgYiEkFzbqIhE09DMeB9qBQVgLfz0PafBd/Tvz1g/LL622UERoYAhfEMz5+9TIEAPz0CKSNGeZw6D1eo5mCKS7IDUDGD5Qag6xdhZ+ju2fqlCxOoh4hwkBPWIyIqICEREaqaxe06YVT1SmxQwJuOarZ9HKhHzTF2pqZlWdWBebaaLji8VIlPdKDUjKyJhU9J0X5Lqto1SM4oioh4y/btXnLYa68xg63kzEFG721qG1YLluQgRiKQVVcupL8vEYBr3/eWr8OV3vAR9qTj+6JLt4nv96bjUmVa3qcZuinDZ43idFBH5NY22CTlkkjG8/EWr/L3JLoYDEQlaxFLx1pdBWR6R6Mp3qYGRLTVjLhqkcHgpImdtGBE7hi0eikhQFaeeWfX3L9yKP7rkJLzl/M0ArF16tljG//zhbrzrS7907Xy6LOr+wwciY/1WbtoP4iHRhpbuTkwoioifrqqEdU4rdRXChM++ClYgksEpqw3Jm4IkutYa7YHgy6wqmYplT8q6kYxnoFbTR0R8Ls1dJ4YzVgdO8eBsNDUzbPUSIcK2LVBVLFJEssUKlgtlxzkzAPDGnRvw8lNX4ZqXb8eqQcMAT9VLqnl8QirhjSY1Y3pEHBqaAfZ7+DVnrBGjLCYGUrYGfn5SM27lu4DzOAH5NSktc+mpq7u6P4hfOmPl7BCERyRAGVtU0I1Squi+O/e5QQslyc0nHMyq5PlwqpqhnxnKJPHq09dgtD9ZY+oErPLdsIqIm8y8abwf1//q6SKfnZamwn7yx3tx+1NH8fNnZxz/bVYaJR4W6idwogvNqoAVSMmKiF/oobtUKKNY8a4i89PivVypYsoMdjeM9omAdna5iFyxIlSGxst3/aRmrIZm8kPXKy0DWPdmsVJFuVJFIUTfjTCQuXUhX7KMthEpIkfmc6KEutHUDLF6KC2UpuNLBamzqP3fvXjjKL70jpfg9HXDWGVW4pFHRFUy5cF3dJkF7SEC1KZ3yx5BAhGPafjc7+/CX1z+Irzq9DXiPihXdFvA69b7yet3ODWek69dkZY5q/fTMgDQ+6FWAOSZC61G3qHlSpXQA8AA64JeQ4GIQ0Mz6gniqIiU6eEQw02/uxPFStVxt9SfDmdWdWt97IaT8fTEsnPaJApFhPoJzOcCmlU7xCNCZY8LZvmxn4oZYlBSuSiwcntAWakZ94f/0cUCqrqRDpkcTEPTjICtXNUxnytFWL4bpI+IZtv5evUQAWrvzTB9N8JAqUlDEQlfMSJDKmm+VMVctoSxgVTo/klqym4ok8TkYBoHT+RwfKkgAikvpXDSvFYpWK1JzUiD70gRCVOlqnpE/FbgnLx6CCebKh6pJ8VK1ZZGcVNn6Xc4bVDk95lKxFAsWyrLnqOLePbYMlLxGF552ur6b64HYEVEIqgbPkpS8ZjYOeQb9InQ+1hnLjqL+bJQWaxApH5qJpOMmyWdzg8J8dAK7RHxt6IMZZJ4z6tOwR9echJec4Zh+Jt18W8Ij0gDisjYQNDy3c6qmlEVED89RIh+MfSvUleyt6Rqd0WE0jLrRvoQM6snLDNwUQpEGvSIkFnVs2rGSqHJgU89RSSdiIlrNVushOpEGgahiORKdRua+SWTjIvUHRlWw1TNOP38YDqBSTPVcmyxaKVgPSKHVUpvItU7IQ++80p11ENNzYQJ7BLS9F05jeLW0JHWBacUtPw+Kf1D5bv37psFAFxw0nigku9upjNWzg6h0EZFRNO0yNq80/tYPZwWuwd6qOYURWQhX64xyFJqJ1NnYZJl/CD46Ymg8r7XnIq//NXTRUrJTRHJRtAyfMRh5oQXcqOsTmBCCTz8lu4CVnvtbKFcV7Knna5XHxHZH0KIz3e5FF0fkQCpmWTMblatF4homr23TJjZLGGQPSKlOi3eg7BOMazWMyW7IafT4uZnSoHI8aWCr/t81aD9s1c7IjcrNVMJUYVEz4VyVVcUEZeGZh5tCuQAY7tp4KZjo5b5Xr1teg0ORCRa5YZ3I6rBd7RQ9qUSYvYEVYDQDbR6KC0e1qoqkvdZUjnYJLOqF+NKt0WVrM8W714ENatWpJ12J6AqIIEUEZofVCzXlewTPlIzh6SKGUJMOZUUkVa0eHdXRLxTM4BVyXUiW2xZv6FhySOijhFoBDKsHjYDkbApafn9D6QM9XTVkJVK8aN8Tg7Zr81BF4/IzHJBSs1EUTUTXhGR0yiA+/rn6RGR1qftq+yBSFYM7uze2TFB6YyVswPQdV0qY2vPBUAljA0HIuTxkMoST2RL0HXdtvCLzoVKvwzLI+L9OfSLhmbBjrdeQzMvaHfvplYs+2zx7oVIHQStmulURSRI1YyYH1S/s2rcR2qGdt3rpYf9qKQutLLFe1lqaCbv/td5tHcnxHW3XBTpn2ZvWMgjspAvReYRAeQSXkrNhDOryusD7fCtCc4VccxeGUuqiiHUDQQFY0uFsuTrCHSYxnEpDe8qIXxdcpVYXrrOXD0iXlUzptqlacD2VYY6TRtIqxfSyrFwciBiUpJ6IbRLEelP2hsnhUWWWumhOrtctO0W+1JxW88IGVJNMnXy9mqL9zuensZr/9dP8Jg5H8GNRhbVMWUQlgrdxJEoIj7NqnLHzk5gVPWIBEjNyE3q6nlEkj5SM1R5JKsy8pTTXNQt3r36iIh+L2EUESugD+upCAo93Bfz5Ugrs6ga7YjZ8dZKNTWgiJhrAa2dpXJVMmu6v24qEcNYvxUoq9Ow5UoV6pvXSGpGtHgPsRlKJWSPiHWdhamaobTLtokBUUFDwY2Yl9Xk1F8nwYGIibyTatcUw0xETc3khXJcalcuy4mZRKymP4L178m0630jyD0nqlUd/+/hQ9h9dBG3P3XU898FNavKCIXHrWrGZ4t3L+hBmS/ZJVg3opTNoyCViNnKA4NUzciVUPWqQ0SLd4+GZjRunjwWgD31ZfURaUVqprbFe1p5ELox5pCaaboiYgtEokv/kTpFvUTCliPLGxVK01L79mKlKplVvV+HfCVA7QYiKb1eNWC1nYx8fei6HmoNsqpm7OW79Vu81/6OTeP9+PI7XoLP/f6uGrWGFZEVTFFawNphVgWsCDjbYGqGLuh0ImbbfVIUT+WLasdI69/72/HJNf+5UkW0dq6XWmokEJEHujm9Lj2IGumsOpROiGPzk54pOUzybDdy8BFEERkUKldFPKDqtXj36nszb6bQRqVAhP5/PleMrI9IxkfVjGyepAfehrE+X54D+jyPLRZAs9yancKlYLJS1bFk7pIjVUQoNRPSfCu/f/o8ReBQrro2NFORK2dqAxHrGmukfFeuqpIVvCCVbvaqGR9D7+qkbC85dRVOXj0kPve8SM00vpnqNjgQMaEHWDKuhTJRRoEYfBeZIhK3DG9SzwaKwMnjUZua8fdwyCStkuPlQlm0dq43eyYKRWRBqiQg5PfRiNSvadaMCz/pmUqHVc0A9kAkkCKSkhUR752/df24X69CEZFUB9mD08o+IrJZddeWMbztgs34i9ee5uv1KTUjt0ZvtnLan4qLe4SCnyjSf1QlRAMvw3tErJ+noImuFTkQqbeeyoGI2kdEDmwam75rXR+ypylIp1q5akYOeF1nzfhUcNSKHqGIrKBAZOVoP3Vot1EVkGdaNDb4TpbUSRJfyFsyOKWA+usoIpk6n4WmaRhIJbBYKGO5KCkidQKpRsyqI31JaJqxMM9lS7ZFjN5HPKY1/JAY6U9iZrmIE8s+FJEOS80AlrkyJaXg/CD3hqnnEfEz9JCM0LIiMiIZjumajK5818OsKgWMqUQM//CGs3y/PqVmjkgVZs1WTjVNw3AmYevwG4XqRpuTXKmCUqUavqGZdF3QdUOvUahUfZfpy6kZNRARnpOK3lD5rlzeXbYpIkGqZqygKMj03XrBo9psLYqmjN1G56ycbaadA+8Ia9x4gy3eJY/IsJDBy1LFjPEe3QKRgvJzXtCU26V8GbPLBcfXU2nErBqPaSLVoFbOyP6QMCV+MmNSiWk9yhH2eIgKUkHGAwy8A+y9YertlK0W/9ZCTG3DAaNqYMHBI0JByfGlolApGlZE/EzfrYQPGMlsO20GIql4rCXKqdrQqtEW74C9mdZivr4p2Q15fRhIR6OIuHlESuWqqEIJlZqRrmF5oxQkqLHPmrGus0K56ljC7qehGyBXGlXN46PBnStHEeFAxKTegK9WYJlHwysiuq4rqRmzBDAnNY9K2lMzqoLht3wXsBaOQ3NZsWOp1/K9kQ6JgLU7VX0iomImgp3EqGhqVl8RiarrZZRQIBKkhwhg7w1TbyrrgGRsBYzP4Q2fvgfv+tL9AIDFQllcE8N9tamZo1KaI7I+Ih5BfCPVTRSY0rTqVm1YqISXaHToHWA83GkNWLIFIuEVEeqLQSpRqVKVps96v84qD0WE7inDrGp8rRGzKmBXnAM1NJMqePKK8ubUwsCvIpSRgrdqVRepnkZVwm5i5Wg/dag34KsV9ClNd8JQlCLzmtSMEmDQhS4HDpWqLnapvgIR86H/wkxWfK1eakbkTkMGIuMDKTx7bLkmEBGKSAPt3YnRAE3NLLNq58T1QhEJ0EMEkKpmpNRMyjU1Yx96eGQ+h4cPzAEwrgFSQzLJmO1aoof6onm+NK3xDYC/1Ez4VvwU/NLDpVUblqF09IoIYHg6cqUKFvIlFMvh1r56ioif8l0AmLQpIkr5rhTYNJLSTcY1xDSgqlvXq6YFW4MooChWaqvplgtlm+oH+PfCyfdGoVwV638jLQi6jZXzTl341oMHUa7o2DhmlLS1q2IGgGsVSxBkadqemikhV6T+IMbvGXAo37WV+PpJzZiv8cKsFYjUa3BWDtFeWcatciZSRaTfv1lVtA7vIEXkxea05HM2jQb6d3RNFCtVLJlD89xTMzSXpmz7L2C0+KYgjoYIEiNKuWx/svFUmr+hd+HPk6ostU0RiSgdNJRJYHqxoKRmGvCImMpr2jE14/063oqI8Y+ruqVohblUaGZWrlQRG6+g6w8dS7lib/EOOPv6wgQi+VJFbKgaTVd2Eys6EDk8l8P7/+MRaBrwsd86G0B7Bt4RUSgisjSdisekqplyTTVMn0PVg73XSP0bgRaO/TZFpE5qpoGdDeDeSySKrqoE7YDnfJhVO23oHQBcuH0CD/31a0RA5RfZIEceHLd7Qm3xT4ELYDSco7+rO0Uqj6aFOgoJ2o9HpNRAL45R5T20TBFRPCJRVWZZzdJKCDvawqmPiFBEKhGV70rHRMcZJjUDGNdITnrQB30dEYhUaxURp3kzFZ9VPvGYhmRcQ6miG9Vq1IKAFZGVwQ+fmAJgVGDsmV4C0BmKiJ8mWm7IBkNN08TucyFfqpl06mRWJcOUXzMeSfn7AygijcyaAazdqTqBN8qyt5EA3VWjbL8dJUH9IYDxIEnFYyhWqlYg4hKQymkcwEq1AMDxxYJIBaqBCA2RI0WrUX+IcYz1+4jIQ++CkogbTeIWzeCqZYqIFIjEAqYSvBiSBuqFrRh0qppx6iNS75gnB1P4nZdsQiIWc+0jAljrYtj7jK4RUoCDBnUJ0dNEF+skoU7gDdo0LZOIo1Qp21LBXL67Qvjhk1YH0L3TiwDaXL4bwfRdVWYls2qxXBU9HSyzam25cL1umiok5dNwM8CHR6TB2Szy3A+ZrPCINH5ZW500/SginZeaaYSBdBzFbFUECm4PXdH8zFERKYgATU3FAIbCQK8fhQTtLzXTWHfSsf6UCERatU7IHXKjVNyGbYpIuD4iaSePiEMgUu+20DQNN77xxY7fkz0xliIS6DAFFPBSCjFoQCNXWy3l7euCOm9GnnrgR/lNJ+NYLJTF6IpYBL6pbqIl7/TTn/40tm3bhkwmg127duHuu+9uxa/15MRyEb/YNyv+vpcUkXaaVSNo8a52SRxIJcSNS1N2M0rVjD01Y/eR1IMWILlb4XKxbCvjVGnUrGopIvbFYFl4RCIwq5q+hnk/gUi1sQdcp0HXBaUy6lbNOHpEio7t3Qk5OIkkNZPwkZqphq+aAewKU6seEnK1UZSzjGRFJKxHRF4javqIlKtSaiL8ZxWLaWLDQscZ1k9E74/Wu6D3q7zRoGtdfU1CXg/9VDrR69Dmqj+VaNg31U00/W76xje+gfe+9734q7/6Kzz00EN42ctehiuuuAL79+9v9q/25MdPT9suFkottDMQEeW7irx88ERWlLzWQ0zeNXcrsZgmFrNps5NiRlFEbGbVgLsjp4e+rns/ECoNmlUnXDwiVmvkFptVG3w/nYZqGHS7FuSApVCu2BSR40sFEcSp/grA3nY+ktSM8Ih4Td+1ht6FQZ5J06p1QlZEokz90Tk2pnIbXwuemnHvrFqSPCKNxuekRJBaG/ZjoPdHCl7Qz1NWpOhap2ZsqiJiC0R8BBS0Xs+IQGTlpGWAFgQiH//4x/HOd74T73rXu3D66afjE5/4BDZt2oSbbrqp2b/akx+Y/pCTzBHMVXEzti8QoQVZDgxuf/IoLv7HO/CP339afK1a1V0VB6fmRCTDHl20KyJO5bt+27sTboYqr/SS39bHbghFpKZ8l8reoijftVIzXuoOYO/Y2Quo5c+unVWlxTJbqNg8IjN1FBE5OIkiNUPG6lJFtz0EZCyzamPVWkALFRHJIxJl514yq86YTQiB4EZ9eY2gdSAdwqxaD1IiaG2LyiMS1CwvKyKkvpJxXq2aqUhrhi+PiPlZnuBAJHqKxSIeeOABXHbZZbavX3bZZbjnnnua+as9yRUr+MmeYwCAd168zfa99ioitamSHz09DQD493tfwGK+hGpVx9tvvg8v/+idjikceeAdQSWApIioHhH5dQoiNePvc3DzY3i1/aZWJ2EXlHHX8t0oFRHjdxjtnL073Vqpmd4IRNTyZ7d7IhGPietsqVCuUURE+a6DR8SWmolQEQHcVZFGy6zlQKR1ZtXmKCKkYNB8KCC4UV9eY0RqJm6Wfwcwq9YjpRiRw6YsGvWIaJpWs9mYGEyZr6mkZirhApEZKTWzkmjq3XT8+HFUKhWsWbPG9vU1a9Zgamqq5ucLhQIWFhZsf5rBT/YcQ75UxYbRPrz2zLW273WCWVWumnn80DwAIzi59aFD+M5jR3D3nuPYP5vFs8eWal7DKd9LO9JpoYgY3xvwKN/1U7prvIbzz3mVIDc6JG5swJqVIQdRUVbNDKTi4oGltpJX6cTy3UZQFSWv3f+g1F11qWD5aWRFZNhREbEe6lGcL/kh6tZdtdHzJKdmWrVOyJ9dmGofN0Qgsmhc22GGfY4PpNCXjGP1UFpcI04t3htVCkVqpkGzqvBzFMgjEqZ6yv5vhCKipmb0cKmZlaqItCTsUiNYXdcdo9obb7wRf/M3f9P049m+agDvungbJgbTmBhIYSAVF1JbJ7R4pwdqsVzF7qlF8f2v3PuCbWATLfQyXqkZMdcjZU/N5EoVVKs6YjEtUHt3oDY1M9afxIlsqY4i0thOaTCdEHX3J7JF9KWMZnRRNjQzSkxTYme/frTP9WfLDZogOw318/OS7AfSCcwsF7FcqNQ0NKPzO9pfW0YsqySZCBbdRDyGREwzJqO6+JMaafEOAKMDrVdEbB6RSM2q9tRMmMCqP5XAt6+7CBmpIR0F7+WqLszBYVOwBAUiDZfvmtdxWI8IHYuskJJHRB1rQWuC3+6ttPGjlgRRVP51E029myYnJxGPx2vUj+np6RqVBACuv/56zM/Piz8HDhxoynGdvHoI//3KM/DHl26HpmnYPDEgvtfO1ExGamim6zqeObqIYqWKoXQCfck4njm6hOeOLYufd2o/7lR+q+bo6aKXo25SMPIBUzPyQyudiInmRF6VPxRLhW1opmmaY3fVKFu8A1JTszqG1d5TRFSzqvvnSdfQcqEsSlsBY0Gl3Z2jRyTi1IxxnN6GVQriw3otxtvsEYm2fNc4x/VKtOtxypohbBrvF3+XX4dmWzVuVrV7REI3NEvYN3phlBr12iFFRE3NVCn97PNYazwiK6irKtDkQCSVSmHXrl247bbbbF+/7bbb8NKXvrTm59PpNIaHh21/WsHmcWu32wmKCGDcdJSWOWvjCF539nrxPYrknR6QTqkZVRqnHWjGNgiKAhEKZPzdCPJDf3IwLXKbpDA9f3wZh6UeI4C1W2gk5y26q0ppkygVEfl3fO+xKU/DaqM77U6j1qxaPzWTLZZtioiuA1NmubhzIGI91CMLRJLuvUTkBlPhRwu0PjUzaOsjEr0iErVJXw5EckLBaNSsak/NhPeImIpIyM6qgP0cxDTLdK2mZoKucbRxpMAwqs1Ut9D0p+773/9+fP7zn8cXv/hFPPXUU3jf+96H/fv345prrmn2r/bNZjmib2MvCDkdki1W8BgFIhtG8HsXbkFMA9YMp3HFDsPX4j81Y38w07THWEyrMazSv/frEZFLPScHU7YmacuFMn71X+7GGz99jzIe3vhvFIGITRGJsMU7AFz10q0ADKPwZ+56zvXnxPTdHlFEBlWzqsc9QerJUsFevivjVL5rq5qJ6HxZ3VVrAxE5pRm238toG8yqyXhMXM/NMKsSkQUicadApMHXVJSuRst3rT4ijSki6URcuv6VhmYB1zihiGTZI9IU3vzmN2NmZgZ/+7d/iyNHjmDHjh347ne/iy1btjT7V/tGDkTaOWsmHtOQTsRQKBvttUkR2bFhBDs2jOD/XXsxxgdTuPmn+wA4N9ty6pKo7kjlhb8/FUe2WEG2ZNxIVvmuz6oZ6bUmBtNil5EtVnBkPm+8drGCuWxJlN1W9MZNbGMOvUSyonw3msv6irPW4b//2un4++88hX/8/tP4xb4ZnLdlDG/YuREbJM9Iifol9IwiYn1+9Vr9WxN4yzWLMeFoVpU9Ii1IzZSlKoawVTPjbWhoBhhBQ7ZYibh8119lVFA0TRMjAmjIZuPlu+QRMVWGBhuaWR6R4MclXzuZZExc/2q7gqCKCG38KF7mqpkm8Cd/8id4/vnnUSgU8MADD+CSSy5pxa/1zaYOUUQA4GxzWurn734OT5lG1R0bRgAYKZoNo31Wsy1Hjwh1VnVPzchSuOglUlA9Io0qIhXMSWkTkullibyRsj6nEt6oFREAeNfLTsI1L98OALhz9zF87IfP4LqvPWj7GdHivUf6iAxKsnC9B+5ASqqaMRWR9SMZ8f2hTMJxMZarZqLziLinZsg4CYRXFkbb0NAMsHwikTY0q1FEortn6LPJlcKnQGQsj0hj5bs1VTMhZw4RmWTcuv5rWrwHmz+lbvxWmiLSG1pyg9hSM20s3wWA9736VADA1+87gGLZMKpukY4P8B7I5lU1Q8hBRn/SuJFyqkfE50IrR+4Tg2lrh1CwD3Ci9vJBZzC4QfX7x81ARNd18R6i3k188IrT8F/vvhjXveJkAMChE5bnpVrVLfNtjwQi8udXTyEU0nS+jCUzENwimb+d/CGAEaDQ6Y9q0ZW7q1aruq0bsU0RCblDzyTjImhqtSICRDvLKJ2I24KpKN+PCEQaSIHIWJ1VGyzfTTbWWVU+FsAMRKTydZlyQD+SuvHjQGQFsnGsXyyK7R40dOH2CVxy6irx9zM3DNcoB5Rfd/aIODU08whEhLRYtv17v4pIKhETC+TkYBp9ZmCTLVVsRlIKRMryzrSBBYqqc44tFszjroqbvxlGrx0bRvDm8zcBsH/uUXgPOg25j0g9hZB+dnqxIFqFb520AhGnZmaAoYZRkBJ1aua5Y8s47x9ux8l/9V2c87c/xHtueUioVo1OsKX0TCvXCbp/ow50Ze9YlAoPXTOUrmhUEaHXo9YCjXZWpeMKsxGSg8F0IibNW3KeNeP3vdcqIpyaWXGkEjGsH+kT/99u/uK1LxL/f5aZlpGhBdwxNeOgiIz0KWZV6aJX59sELd8FrF3x5GBKPJhypi+EmJo3AgYpDmlIEaH6fQpEqCNhMq5hqEk1+PRAKJSrQjmS24n3zPRdmyLiHSTQuadAMxHTsHHM8s+4KSKAFVAHuda8oIDmq7/Yj9nlIqq6cY/8v4cPi9Rgo8EiBVatbHxIFS5RekTk1wWiDaySCeM+yEdkVq1VRML2ETHOWaWBTsiywmGkZiyVRTbkB63QYkWEAQDs2GCUCns1rmoVOzaM4Dd3bgQAXPqi1TXfp8XQURFx8ohkPDwiSXtEH3TWDGA9uCYG0pLnpGxLHdGcm6AzGNxQFRF6EK4eyjRtauVQ2konLJhjwKPwHnQastnXr0eEPv/BTAKTg5b/wysQecO5G3HqmkGcu2mskcMV0LHuO2702rnh188QQenMkhmoNniONo0ZadLJodombc2ClIuory/ZsBqpRyROHpGIyneVycphb2/1Wm48NWMpIrpu7yYd1AenVimyIrJC+affOhv/ee1F2Ll5tN2HAgD4p996Me7+i1fgopMna75HRj9nRYRatPtMzaTsqZmgLd4B4C3nb8KuLWPYuWXUahtfquCE7BGZNwORgDMY3FhFishSAbquY9p8EK4ZTod+zXrEYpbaspAzPq8ovAedRqBAxPzZKfP8DqYTQq0CgJE+9wf2e159Cn74vpfb5s40gvwwTcVjeMPOjeK1aaZKo4rI//j1M/DPbzkHl5yyqv4PRwQpF1E3zBtqVmomYVdZG1E+gVqzalhFRN1cNdrQTPYMAfb0TFBFRPVisSKyQhnpS+KcTaNN200HJR7TbNU8MrS45koVcXPmldSKLKlnknZjmn1qpr2PSN5BUanHu191Cr75xy9FfyohFBHDrFpbNRN0BoMbpIgUy1Us5Ms4ag70WzOc8fpnDUNBHSki5Wo03oNOQp4fVO8BRRU2C2bFzGA6gQlbIBJNkOEHOWh62SmTGOlLit8vp+4aYf1oH15/zoaW+oFoaGXU052H0s1JzVhm1Wga/aXU8t0GPSJEOEVESs0k4ojFNCs9I1XOBFZElCApigni3QQHIl2InCKYz5Vw375ZnHXDD3DTnc86mlUBKz2TisdsN6BsLgWCm1VV5PLdE8ty1YwRKMieikYe3Jlk3DZBlAb6rR5qniICWA9WSov1Wnt3QFVEvK8DVUIeUlIzbmbVZiAHz7961joA1vmaIUWkC8/TKauHAACbJ5w3JmGxpWYi7J+UptRMMaryXXt/mHamZhJKagaw+u7IlTO0zgVt8U7QurxSWFnvtkegioO5bAnz2RLuefY4ShUdP3rqqHi4qw+Qkb4Eji8VXOvVqUVx0D4iKvJEX7miZGa5gFIluomcgJGeWcyXcWyxIAKd1c1WRMyAbkENRHrEqArYPUR+UzNEbWqmlYqIcdypeAyvPmON7feTR6Qbz9OrT1+NH77vEmyTqpGiQDarpuLN6CMSvl+H0+tFNWuGaLyhmfF6g+kEji0W7KmZoH1ElPuMFRGmK6CKg7lcSfS12DO9ZA29UxURl1LJPknBAKwSOfXG8Euf5DmRUzO6bhhL6QaNIo0xKRlWjwqPSLNTM6ZHxExFRDE3p9OQW//X2ykPqoFIJolMMi6+7tTevVnQtU1pGcAKRI6L1Ez3LXmapuHUNUNNqJppjiJCgQPtQxq91+l9U1Y3bEpX3YRF4REBpMGPTopIyNRMVGMPuoXuuysZAFJTs2wJB81AZD5XwiFzwJy6sNBOXr3AKb8pUjMRKiLUR4RuxqmFvDCrRqKISIHItPCItCY1IxSRBie6diqkdNTrI6Ka6igAWW2eh7GB1lWX/NauDXj16avx3y63yt9rUzO9EzA2ir1qJsLyXUV1alSESikvEDa7VquIhCnflZrAmWus1UukNhAJW74b1eDObmFlvdseQvYqHJKm2x43Jeja1IypiLiUiamdVcMGIhTonMgWRZrnpMkB7JlewtH5PMbMAKpRJz1gr5whj0jTFRG31EyPPeAGUnEcQ32PiKqI0MPtg5efhnueNWbztIqTVw/h828/3/a14ZrUTG8FjI3Q7KoZIt7gZ64G+aFbvCubs0YbmtFaSuMm5Cnjwc2q9mOLauxBt8B3ZZdCkveJ5SKOzOdqvl+bmjEWnUzKWQJcLtjLd8PukCi3SUFIIqZh+6pBAEaviSjmzBCkiBw6kROlws02q7pVzfRcIGIGGPUke7WLLQUml525Fje87sy2P/itqhlDEemVpnNRYG9oFn0fEaLh8l1lLQp7q6mbqzCdnZ1SMzu3jAIA7tt3QnwvcPmu9Pn3JeM9U4HnFw5EuhSqRnjm6CJKUi8LQn2A0ILc52JWFZ1Vy42lZvoVt/dofxJrzSFoUwuFyM2qAPDEYWNKcSoRa7o5Uq2aKQmzam/dSiQN1wtI04m47eGuKiTths5XqUeVq0ZoVmpGVVca/cxVRaTR6btEuKF39hbvAPCSbRMAgF++MCvmGwkvXIgW7yuthwjAgUjXQorIk0cWHL+v7nAopVDbStjydMhVLWHbbqselJE+KxBpliLynNlJc81wuul9YIRZ1Wxo1ki76E6GlC0/kr1cOaNOdW03amDaawFjI9iqZiIMRNQHfqP3uuoRaXT6LhHF0DsAOHP9MPqSccxlS9gzvQQg+LrgNP9rJcF3ZZdCKYJnji4af68Z620/tTQRVW1hLxSRYkWkZYDwiog8BA8AxvpTwkB6dCFvjceOwiNiBiLkpl8z1Fx/CCCZVSk1U+nN1Az1RvAj2cvGOvU6bDdqIMKpGYtuVUSiKt8NVzUjl+/GzK/FsMv0Qt33/CyA4EPv5M9fVZVXAhyIdCmjpkGKJOeLTp60NfpRF5bXnLEGX7v6Alx/xWm2r8ulZ1Sn7/TvgyA3uRrtTwkD6dRCXlSZRFHuukrxgzTbqApYypJIzYhUU2/dStvMwHXTeP3ZS3LPg8F068p1/VCjiPTYeWqEZs+aIaIq3yXCilrJuGbzl4Q5Lvn6kTdr528dBwDct88IRMoBU9Capok1dyUqIisv9OoR1P4MJ68exMbDfTgwS+W7taVqL91eO7dG7iMiG1UbSXH0p+LiQT3anxQBwrTkEYkiEBlXSkPVwKQZDCvluxXTrNprO+13v+pkvOaMNY7Tn1W6KTXTa+epEYabNX236WbVcK9nPOzjDTVac1JEAOAl24xA5P59s9B1XXhFgqxzmWQchXKVPSJM96AOCtsw2idaQQP+FxaS1YvlqmhqFjYtQ8g+kbH+JNaagchSoSxSGlEEIsl4zBaMtEIRsVIzxthvUqR6qaEZYOyQz9406mvXKKdmOs2sqg58ZEXEIi2lUZuZmmn03ojKIwLYTfzhOqtKioikIp27eRTJuIaphTwOnsiFUn5Fy/gV1kME4ECka1EVkY1j/ThltVEmG49pvhtsyUHDrNl9MqxRlRhQUjMD6YSYWku19lE9uFdJ7cSb3cwMsHaRlaqO5WJFavG+cm8lOTUz1GGKSFyamAz0nqm4ETRNE4bVZnRWJRq912s9IuFfSw64wlXNyA3N7INFX7xxFADwi32zlhcuoCICcNUM00XUKCJjfTjZDESC7G7SiZi4sU+IQCRKRcRQLKjTpghEIqpukdMxrVBEMklrF7mQK/VsH5EgdLIiAthVkV7rgNsop6weRCKmYeNYdAP1ml6+2+CwzEZexy01AwDnbTUMqw/tPyE2KEFUF1JYVqIisvLecY+g5r7XjWRw6hojNRMkotY0Df2pBJYKZcyaLdnV7qtBkcfIU7+TVUNpPHtsWQyni0oRkSe9tkIR0TRj4ODxpSIW8iVWRGB5RDStM3dzI31J0X2411JojXLzH5yPuWwp0iA+3WSzakOpmYScmommfJdYZ36G87mSVB3o/7Wt1Ezn3UPNhgORLiWdiKMvaRivVg2lkUnGcdaGEbzr4m0iIPFLfyqOpUJZUkQae6jaq2aMQIQmstJwushSM5IisqoF5buAkZ45vlTEfLYkzLfJFfyAo0BkMJ1oeh+XMIzYFJHOO7520p9KRL4Dr0nNNHhNpBLKrJmGUjPWQz5UaiYmKyLOXarzpYrkEQmgTpuvN8CBCNNNjPYnkZuvYIPZGyQW0/Dfrzwj8OtQBD6z7DynJuzrAVZqhgKRqfm8ONYooEAkk4y1rIfFsGRYLfXg9N2g0MI51IFpGcAeiLBZtfk02yPSSGDTqCIivzd1Qnmf1BzSqg70/9oU2PStwNQM35VdDC2wG8bq93rwgi786UUjbdKocc0pEKGAgRSRqDwV9LprhjMt240PS23eKTWzkr0HQhHpMKMqYQtEWBFpOjWzZqI2q0bkEQmniLinZmhQXa5UCdWmYNA0fXea4bsVrLx33ENQ2mPjaGOBCAUO3398CgCE6TX066VrUzNU3bKQN1qjR2VWPWvDCOIxDeduGo3k9fxAystCrgSa8rOSH3CDUmqmE5GN3Ss5YGwVat+PqAORRpYOuyIS/FpIxD1SMxSIFMMFIu+4aBsyiThee+bawMfV7XTmysH4gvpznLRqoKHXoUCkUtWxZjiN977q1MZez7whM8mYuFnVZmNRKeQnrx7CfX/5KtFpthXIbd5p8VnJqZntZuAq97HpJOypmZV7nlpF1IpITafWyPqIhD+WZFyreV99KeN7eVkRCXCs520dx3lmh9aVBgciXcyfXfYinLNpFK8/Z0NDryOnUj76W2fXlAYHfj1zZzwmBQeTg/ZAJMpc/cRg86tlZOTUDO3WkivYe7Bryxh+8t9egXWjrTELB2XYlppZueepVURevquYVRvziMjlu+EVEScfXUZOzejBzaorGQ5EuphN4/246qJtDb/OhlGjh8Dv/coWXHLqqoZfjwIbWaWYHLIrFlGZVdsBNTVbyJUx2me8r/gKTs0AwOaJ6PpQRI2taqaLr7tuoWb6bqMt3iNMzcgVgY14RJwqC51TM2GOcuXBgQiD97z6FFx08gReHkEQAlgzYOS+HhMDqiLSvQ8EOTVDDc34Ade5jLAi0lKa31k1KkUk+OtQaqfPocSWyqDtZlW+3vzAgQiDkb4kXnX6mshe79IXrcJf/uppuPRFq8XXUokYRvuTmMsas2Ya3SW1k+E+47aZz5WsKZv8gOtYuI9Ia2m2R6SR12u0fPesDSO48sXrcOH2iZrvkSJSqugolCvm7wh5oCsMDkSYyEkn4vjDS7bXfH1yMC0CkW6+QUekCbzlCrd473TYrNpaoldEomxo1nhn1U+9dafj9zIp67WXCxSIdPFC10L4U2JahjygrpsbS5FHZDFfFtN3V3L5bqfDqZnWoqZSGg3+4jHN5gtpbPpuY31EvEjFrbldS4Vo2xT0OnxXMi1jUirh7WqzqlQ1Q7ngbg6seh254y6nZpqPqog0eq9rmn2aeGMekcYUES80TRPpmSWzXxJvUPzBqyfTMuQBdd18f9IOe6lQFrlglvw7l0Q8JpqtccDYfNSqmSjuDdkn0oioZVdEor8WyMS6XDQCkW72wrUSviuZliE3Nevm3KncgvmY2RafJf/OhoJH3qE2nygbkBGykhXV9N1mLEEZVRHhDYovePVkWobc1Kybn9vJeAynmN1Ef/bsDABecDodSqdxi/fmE4tptvshihRIVKmZTJMVEeqhtGh6RLo5Bd1K+K5kWoZdEenuG/TN528CABTLZtUM77Q7mrM3GjOJtq9qbI4S449UxF6MZFSpmSZ6RADUekS6fJ1rFRyIMC1j1WDvBCJv3LnRJkFzaqaz+fAbzsL9f/VqvGhtZ87D6TWiDkTk14vKrNqMIEFu8w6wIuIXXj2ZlmFLzXS5iWt8IIXX7rCmZPLOp7OJxTTR8ZdpPrYgPRJFJBqPiJyaaYoionRc7fZ1rlVwIMK0jAm5aqaLzarE77xkk/h/DkQYxiIqT4fz64V/nValZgheF/zR/U8DpmtIxmMYMyf79kIm48KTJrDVHPZG5aEMw0SfArF5RCKaNdOMIEENRDg14w9ePZmWMjmYxolsqSduUE3T8Mnf2YnvPHYErzx9df1/wDArBJunI+I+Io11Vm2yIpJiRSQMHIgwLWXVUBp7ppd65gY9a+MIzto40u7DYJiOggKRqB72yYT1Oo28ZLPLd1kRCUcPCORMN0GGVTZxMUzvQgpGZIFIPBolw+YRaULJPSsi4eBAhGkpOzePAgBO5TJKhulZhCIS0YYj1YxZM03YDGVURYQ3XL7g1AzTUq66aBt+/ez1mJBKeRmG6S0oEIlKEUgmZI9I+NeRzapcNdM5cCDCtBwOQhimt6FUSlQeiagUkWRcw4s3jmA+VxIVfFFS00eEAxFfcCDCMAzDRErkiojk52jk4a5pGm79k4tQqepN6Ybcz4FIKDgQYRiGYSIlHbEikoxHk5oBjOCgWQGC6hHhQMQfbFZlGIZhIiVqs2rUnVqbheoR4UDEHxyIMAzDMJESdR+RqIfoNQv2iISDAxGGYRgmUqLvIxJNQ7Nmw4pIODgQYRiGYSIlerNqNC3em02NR6SDj7WT4ECEYRiGiRQKRJphVu1kjwhXzYSDAxGGYRgmUihwaEZn1U5WGTg1Ew4ORBiGYZhISUc99E7yiHRwHMJm1ZBwIMIwDMNESvTTd7sjNSPPsgE4EPELByIMwzBMpHTq9N1mo2maLT3TyWmkToIDEYZhGCZSIu8jYjOrRvKSTUNOz3Ry0NRJcCDCMAzDREp/ypgeoqYqwtIt5buA3bDKgYg/eNYMwzAMEymXnDqJt12wGb921rpIXq9bGpoBdkUkqj4qvQ4HIgzDMEyk9KcS+Ic3nBXZ6yW7pMU7YFdEouqj0utwaoZhGIbpaFJd0tAMsAcirIj4gwMRhmEYpqOxe0TaeCA+yKRYEQkKByIMwzBMRyN7RDo/NWM9VlkR8QcHIgzDMExH0y2zZgDFI9Lhx9opcCDCMAzDdDSpRPekZvpSVg0IKyL+4ECEYRiG6Wi6VRHp9DRSp8CBCMMwDNPR2DwinR6IpIzHakzr/OZrnQIHIgzDMExH043lu6yG+Kdpgcjzzz+Pd77zndi2bRv6+vqwfft2fOhDH0KxWGzWr2QYhmF6EFv5bodvnzNmINLpAVMn0bTOqk8//TSq1So++9nP4uSTT8bjjz+Oq6++GsvLy/jYxz7WrF/LMAzD9BiyWbXzUzNGIMJGVf80LRC5/PLLcfnll4u/n3TSSdi9ezduuukmDkQYhmEY3wykE/jt8zaiqhv/38n0m4EINzPzT0vP6Pz8PMbHx12/XygUUCgUxN8XFhZacVgMwzBMh/NPv3V2uw/BF+QRYUXEPy3Ltj377LP45Cc/iWuuucb1Z2688UaMjIyIP5s2bWrV4TEMwzBMw2TYrBqYwIHIDTfcAE3TPP/88pe/tP2bw4cP4/LLL8eb3vQmvOtd73J97euvvx7z8/Piz4EDB4K/I4ZhGIZpE1w1E5zAqZnrrrsOb3nLWzx/ZuvWreL/Dx8+jFe84hW48MIL8bnPfc7z36XTaaTT6aCHxDAMwzAdwcSg8QwbziTbfCTdQ+BAZHJyEpOTk75+9tChQ3jFK16BXbt24eabb0Ys1uF1VwzDMAzTACevHsT/evPZOGlysN2H0jU0zax6+PBhXHrppdi8eTM+9rGP4dixY+J7a9eubdavZRiGYZi28oZzN7b7ELqKpgUiP/zhD7F3717s3bsXGzfaT4qu6836tQzDMAzDdBFNy5VcddVV0HXd8Q/DMAzDMAzAs2YYhmEYhmkjHIgwDMMwDNM2OBBhGIZhGKZtcCDCMAzDMEzb4ECEYRiGYZi2wYEIwzAMwzBtgwMRhmEYhmHaBgciDMMwDMO0DQ5EGIZhGIZpGxyIMAzDMAzTNjgQYRiGYRimbTRt6F0U0FyahYWFNh8JwzAMwzB+oee2n/lyHR2ILC4uAgA2bdrU5iNhGIZhGCYoi4uLGBkZ8fwZTe/gcbjVahWHDx/G0NAQNE2L9LUXFhawadMmHDhwAMPDw5G+difA76/76fX32OvvD+j998jvr/tp1nvUdR2Li4tYv349YjFvF0hHKyKxWAwbN25s6u8YHh7u2QsM4PfXC/T6e+z19wf0/nvk99f9NOM91lNCCDarMgzDMAzTNjgQYRiGYRimbazYQCSdTuNDH/oQ0ul0uw+lKfD76356/T32+vsDev898vvrfjrhPXa0WZVhGIZhmN5mxSoiDMMwDMO0Hw5EGIZhGIZpGxyIMAzDMAzTNjgQYRiGYRimbazIQOTTn/40tm3bhkwmg127duHuu+9u9yGF4sYbb8T555+PoaEhrF69Gr/xG7+B3bt3237mqquugqZptj+/8iu/0qYjDs4NN9xQc/xr164V39d1HTfccAPWr1+Pvr4+XHrppXjiiSfaeMTB2Lp1a8370zQN1157LYDuO38/+clP8Ou//utYv349NE3Df/7nf9q+7+d8FQoFvPvd78bk5CQGBgbwute9DgcPHmzhu/DG6z2WSiV84AMfwFlnnYWBgQGsX78ev//7v4/Dhw/bXuPSSy+tOa9vectbWvxOnKl3Dv1ck918DgE43pOapuGjH/2o+JlOPYd+nguddh+uuEDkG9/4Bt773vfir/7qr/DQQw/hZS97Ga644grs37+/3YcWmLvuugvXXnst7r33Xtx2220ol8u47LLLsLy8bPu5yy+/HEeOHBF/vvvd77bpiMNx5pln2o7/scceE9/7p3/6J3z84x/Hpz71Kdx///1Yu3YtXvOa14g5RZ3O/fffb3tvt912GwDgTW96k/iZbjp/y8vLOPvss/GpT33K8ft+ztd73/te3Hrrrbjlllvw05/+FEtLS7jyyitRqVRa9TY88XqP2WwWDz74IP76r/8aDz74IL71rW/hmWeewete97qan7366qtt5/Wzn/1sKw6/LvXOIVD/muzmcwjA9t6OHDmCL37xi9A0Db/5m79p+7lOPId+ngsddx/qK4yXvOQl+jXXXGP72mmnnaZ/8IMfbNMRRcf09LQOQL/rrrvE197+9rfrr3/969t3UA3yoQ99SD/77LMdv1etVvW1a9fqH/nIR8TX8vm8PjIyon/mM59p0RFGy3ve8x59+/bterVa1XW9u88fAP3WW28Vf/dzvubm5vRkMqnfcsst4mcOHTqkx2Ix/fvf/37Ljt0v6nt04r777tMB6C+88IL42stf/nL9Pe95T3MPLgKc3l+9a7IXz+HrX/96/ZWvfKXta91yDtXnQifehytKESkWi3jggQdw2WWX2b5+2WWX4Z577mnTUUXH/Pw8AGB8fNz29TvvvBOrV6/GqaeeiquvvhrT09PtOLzQ7NmzB+vXr8e2bdvwlre8Bc899xwAYN++fZiamrKdz3Q6jZe//OVdeT6LxSK+8pWv4B3veIdtyGO3nz/Cz/l64IEHUCqVbD+zfv167NixoyvPKWDcl5qmYXR01Pb1r371q5icnMSZZ56JP//zP+8aFQ/wviZ77RwePXoU3/nOd/DOd76z5nvdcA7V50In3ocdPfQuao4fP45KpYI1a9bYvr5mzRpMTU216aiiQdd1vP/978fFF1+MHTt2iK9fccUVeNOb3oQtW7Zg3759+Ou//mu88pWvxAMPPNAV3QIvuOACfPnLX8app56Ko0eP4u///u/x0pe+FE888YQ4Z07n84UXXmjH4TbEf/7nf2Jubg5XXXWV+Fq3nz8ZP+dramoKqVQKY2NjNT/TjfdoPp/HBz/4Qbz1rW+1DRR729vehm3btmHt2rV4/PHHcf311+ORRx4RqblOpt412Wvn8Etf+hKGhobwxje+0fb1bjiHTs+FTrwPV1QgQsi7TcA4WerXuo3rrrsOjz76KH7605/avv7mN79Z/P+OHTtw3nnnYcuWLfjOd75Tc2N1IldccYX4/7POOgsXXnghtm/fji996UvCINcr5/MLX/gCrrjiCqxfv158rdvPnxNhzlc3ntNSqYS3vOUtqFar+PSnP2373tVXXy3+f8eOHTjllFNw3nnn4cEHH8TOnTtbfaiBCHtNduM5BIAvfvGLeNvb3oZMJmP7ejecQ7fnAtBZ9+GKSs1MTk4iHo/XRHTT09M10WE38e53vxvf/va3cccdd2Djxo2eP7tu3Tps2bIFe/bsadHRRcvAwADOOuss7NmzR1TP9ML5fOGFF3D77bfjXe96l+fPdfP583O+1q5di2KxiBMnTrj+TDdQKpXw27/929i3bx9uu+22uuPVd+7ciWQy2ZXnVb0me+UcAsDdd9+N3bt3170vgc47h27PhU68D1dUIJJKpbBr164a6ey2227DS1/60jYdVXh0Xcd1112Hb33rW/jxj3+Mbdu21f03MzMzOHDgANatW9eCI4yeQqGAp556CuvWrROyqHw+i8Ui7rrrrq47nzfffDNWr16NX/u1X/P8uW4+f37O165du5BMJm0/c+TIETz++ONdc04pCNmzZw9uv/12TExM1P03TzzxBEqlUleeV/Wa7IVzSHzhC1/Arl27cPbZZ9f92U45h/WeCx15H0Zuf+1wbrnlFj2ZTOpf+MIX9CeffFJ/73vfqw8MDOjPP/98uw8tMH/8x3+sj4yM6Hfeead+5MgR8Sebzeq6ruuLi4v6n/3Zn+n33HOPvm/fPv2OO+7QL7zwQn3Dhg36wsJCm4/eH3/2Z3+m33nnnfpzzz2n33vvvfqVV16pDw0NifP1kY98RB8ZGdG/9a1v6Y899pj+O7/zO/q6deu65v3puq5XKhV98+bN+gc+8AHb17vx/C0uLuoPPfSQ/tBDD+kA9I9//OP6Qw89JCpG/Jyva665Rt+4caN+++236w8++KD+yle+Uj/77LP1crncrrdlw+s9lkol/XWve52+ceNG/eGHH7bdl4VCQdd1Xd+7d6/+N3/zN/r999+v79u3T//Od76jn3baafq5557bEe/R6/35vSa7+RwS8/Pzen9/v37TTTfV/PtOPof1ngu63nn34YoLRHRd1//1X/9V37Jli55KpfSdO3fayl27CQCOf26++WZd13U9m83ql112mb5q1So9mUzqmzdv1t/+9rfr+/fvb++BB+DNb36zvm7dOj2ZTOrr16/X3/jGN+pPPPGE+H61WtU/9KEP6WvXrtXT6bR+ySWX6I899lgbjzg4P/jBD3QA+u7du21f78bzd8cddzhek29/+9t1Xfd3vnK5nH7dddfp4+Pjel9fn37llVd21Hv2eo/79u1zvS/vuOMOXdd1ff/+/foll1yij4+P66lUSt++fbv+p3/6p/rMzEx735iJ1/vze0128zkkPvvZz+p9fX363Nxczb/v5HNY77mg6513H2rmgTMMwzAMw7ScFeURYRiGYRims+BAhGEYhmGYtsGBCMMwDMMwbYMDEYZhGIZh2gYHIgzDMAzDtA0ORBiGYRiGaRsciDAMwzAM0zY4EGEYhmEYpm1wIMIwDMMwTNvgQIRhGIZhmLbBgQjDMAzDMG2DAxGGYRiGYdrG/w/1IcIItnEt9QAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "filenames": { + "image/png": "C:\\Users\\maximiko\\Franklin\\indeco\\_build\\jupyter_execute\\docs\\python_by_example_51_0.png" + } + }, + "output_type": "display_data" + } + ], "source": [ "α = 0.9\n", "T = 200\n", @@ -964,7 +1263,7 @@ }, { "cell_type": "markdown", - "id": "e815b8d3", + "id": "f83385d3", "metadata": {}, "source": [ "Here\\'s a shorter way to write the same thing:" @@ -972,10 +1271,25 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "1177c7d2", + "execution_count": 30, + "id": "6e7219c6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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    " + ] + }, + "metadata": { + "filenames": { + "image/png": "C:\\Users\\maximiko\\Franklin\\indeco\\_build\\jupyter_execute\\docs\\python_by_example_53_0.png" + } + }, + "output_type": "display_data" + } + ], "source": [ "α = 0.9\n", "T = 200\n", @@ -992,7 +1306,7 @@ }, { "cell_type": "markdown", - "id": "7aa05612", + "id": "41b2ffb5", "metadata": {}, "source": [ "### Exercise 5\n", @@ -1015,10 +1329,18 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "55a6fb39", + "execution_count": 31, + "id": "d30935aa", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "3.14844\n" + ] + } + ], "source": [ "n = 100000\n", "\n", @@ -1047,6 +1369,18 @@ "language": "python", "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": "3.8.8" + }, "source_map": [ 10, 51, diff --git a/_sources/docs/research_methods.ipynb b/_sources/docs/research_methods.ipynb index e338bbf..43beb70 100755 --- a/_sources/docs/research_methods.ipynb +++ b/_sources/docs/research_methods.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "0d84c1be", + "id": "0a26058d", "metadata": {}, "source": [ "(getting_started)=\n", diff --git a/_static/IndustrialEcology_logo_tiny.jpg b/_static/IndustrialEcology_logo_tiny.jpg deleted file mode 100755 index cbedc7578210145ca31cf9fa92e1d094e3a46fcc..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 47614 zcmeFYbyQr>vM@S8fZ!6`gS)#Ed~kOXWC(79OALo#1B1KU;5JBty9AfP-7RQ{JbveQ z?z!i?>%RNG_pSB*d%b4O?B2Vps;hT(b=mw`{IdxlQ}lDN0{~Q2*#XZ1|JnYW00(fPSJyMo32r0D;FT>R2N@_ZLPh zYd3E%Df*|G{>_4myN1TU5dXKU<>K-eU;h{l_R}GJRP21ij}j1n~k>%$kj_#L5lwA3Ae3-t+*hsfC!(wps<*t z2(O|bAD^h)D*<^S1tmpMVL5(2VUhp9@!!D;3-F4`3CoFz@QNw%@hJ+5@$ri(DvG?~ ze|jN`uY`I316I`)>}BO@1NslT4o`Id2`lsUJoVk&oc}`twC&xz+`#s3 z?sW2c!gQ=g4z9LtzF@Y$UeDj$Du6s4d_cBJo^CF5|5#sfhyRBD|1;lz!`l9ztQpVK zWO)7(j(-!D|G4!efqz~8OZ1;Q|Jpnt*QXuh`Ls3uoB?qEA@Bg(uBR=C^alY51t9;c zp*&roJbU^^d4~GzuZD_-`j3W&hK~Lm9UTn=0}~Si1N(n%NGK>MsLxO_(9ke&urRQ2 z@Nl0R9^O9&{qqO=@816k_pjccE&#!Eqy(e{6eI!wG650_0n(p7z|xbRKt=(eApNHb zL4S^lhJl3q3|Akk=z7x!ej-&=;DvVPqyvYUus548VSx`V#^IfDGV#mw+`&0Z6Yy7@4e4 z!1Vuj{=ZlQW2||DSew{Xo|Z-7i~`8I8*`oZt44vd@5e(zTuft?~BiW`6RVIGPsZ~uG?4j{!lGLT-fBxrxk2`L+| zX4xm1yVJJkY3jY7*t=%AVb680Dss75HSQzYjS18o+*SmiHCc?UsfE0cqQRHK%5
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.admonition-title:before{color:rgba(var(--pst-color-admonition-note),1);content:var(--pst-icon-admonition-note)}div.deprecated{margin-bottom:10px;margin-top:10px;padding:7px;background-color:#f3e5e5;border:1px solid #eed3d7;border-radius:.5rem}div.deprecated p{color:#b94a48;display:inline}.topic{background-color:#eee}.seealso dd{margin-top:0;margin-bottom:0}.viewcode-back{font-family:var(--pst-font-family-base)}.viewcode-block:target{background-color:#f4debf;border-top:1px solid #ac9;border-bottom:1px solid #ac9}span.guilabel{border:1px solid #7fbbe3;background:#e7f2fa;font-size:80%;font-weight:700;border-radius:4px;padding:2.4px 6px;margin:auto 2px}table.field-list{border-collapse:separate;border-spacing:10px;margin-left:1px}table.field-list th.field-name{padding:1px 8px 1px 5px;white-space:nowrap;background-color:#eee}table.field-list td.field-body p{font-style:italic}table.field-list td.field-body p>strong{font-style:normal}table.field-list td.field-body 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li>a:hover{color:rgba(var(--pst-color-sidebar-link-hover),1);text-decoration:none;background-color:transparent}.bd-sidebar .nav li>a.reference.external:after{font-family:Font Awesome\ 5 Free;font-weight:900;content:"\f35d";font-size:.75em;margin-left:.3em}.bd-sidebar .nav .active:hover>a,.bd-sidebar .nav .active>a{font-weight:600;color:rgba(var(--pst-color-sidebar-link-active),1)}.toc-h2{font-size:.85rem}.toc-h3{font-size:.75rem}.toc-h4{font-size:.65rem}.toc-entry>.nav-link.active{font-weight:600;color:#130654;color:rgba(var(--pst-color-toc-link-active),1);background-color:transparent;border-left:2px solid rgba(var(--pst-color-toc-link-active),1)}.nav-link:hover{border-style:none}#navbar-main-elements li.nav-item i{font-size:.7rem;padding-left:2px;vertical-align:middle}.bd-toc .nav .nav{display:none}.bd-toc .nav .nav.visible,.bd-toc .nav>.active>ul{display:block}.prev-next-bottom{margin:20px 0}.prev-next-bottom a.left-prev,.prev-next-bottom a.right-next{padding:10px;border:1px solid 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a{color:#130754}.xr-wrap[hidden]{display:block!important}.toctree-checkbox{position:absolute;display:none}.toctree-checkbox~ul{display:none}.toctree-checkbox~label i{transform:rotate(0deg)}.toctree-checkbox:checked~ul{display:block}.toctree-checkbox:checked~label i{transform:rotate(180deg)}.bd-sidebar li{position:relative}.bd-sidebar label{position:absolute;top:0;right:0;height:30px;width:30px;cursor:pointer;display:flex;justify-content:center;align-items:center}.bd-sidebar label:hover{background:rgba(var(--pst-color-sidebar-expander-background-hover),1)}.bd-sidebar label i{display:inline-block;font-size:.75rem;text-align:center}.bd-sidebar label i:hover{color:rgba(var(--pst-color-sidebar-link-hover),1)}.bd-sidebar li.has-children>.reference{padding-right:30px}div.doctest>div.highlight span.gp,span.linenos,table.highlighttable td.linenos{user-select:none!important;-webkit-user-select:text!important;-webkit-user-select:none!important;-moz-user-select:none!important;-ms-user-select:none!important} \ No newline at end of file diff --git a/_static/css/theme.css b/_static/css/theme.css deleted file mode 100755 index 280d96f..0000000 --- a/_static/css/theme.css +++ /dev/null @@ -1,117 +0,0 @@ -:root { - /***************************************************************************** - * Theme config - **/ - --pst-header-height: 60px; - - /***************************************************************************** - * Font size - **/ - --pst-font-size-base: 15px; /* base font size - applied at body / html level */ - - /* heading font sizes */ - --pst-font-size-h1: 36px; - --pst-font-size-h2: 32px; - --pst-font-size-h3: 26px; - --pst-font-size-h4: 21px; - --pst-font-size-h5: 18px; - --pst-font-size-h6: 16px; - - /* smaller then heading font sizes*/ - --pst-font-size-milli: 12px; - - --pst-sidebar-font-size: .9em; - --pst-sidebar-caption-font-size: .9em; - - /***************************************************************************** - * Font family - **/ - /* These are adapted from https://systemfontstack.com/ */ - --pst-font-family-base-system: -apple-system, BlinkMacSystemFont, Segoe UI, "Helvetica Neue", - Arial, sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol; - --pst-font-family-monospace-system: "SFMono-Regular", Menlo, Consolas, Monaco, - Liberation Mono, Lucida Console, monospace; - - --pst-font-family-base: var(--pst-font-family-base-system); - --pst-font-family-heading: var(--pst-font-family-base); - --pst-font-family-monospace: var(--pst-font-family-monospace-system); - - /***************************************************************************** - * Color - * - * Colors are defined in rgb string way, "red, green, blue" - **/ - --pst-color-primary: 19, 6, 84; - --pst-color-success: 40, 167, 69; - --pst-color-info: 0, 123, 255; /*23, 162, 184;*/ - --pst-color-warning: 255, 193, 7; - --pst-color-danger: 220, 53, 69; - --pst-color-text-base: 51, 51, 51; - - --pst-color-h1: var(--pst-color-primary); - --pst-color-h2: var(--pst-color-primary); - --pst-color-h3: var(--pst-color-text-base); - --pst-color-h4: var(--pst-color-text-base); - --pst-color-h5: var(--pst-color-text-base); - --pst-color-h6: var(--pst-color-text-base); - --pst-color-paragraph: var(--pst-color-text-base); - --pst-color-link: 0, 91, 129; - --pst-color-link-hover: 227, 46, 0; - --pst-color-headerlink: 198, 15, 15; - --pst-color-headerlink-hover: 255, 255, 255; - --pst-color-preformatted-text: 34, 34, 34; - --pst-color-preformatted-background: 250, 250, 250; - --pst-color-inline-code: 232, 62, 140; - - --pst-color-active-navigation: 19, 6, 84; - --pst-color-navbar-link: 77, 77, 77; - --pst-color-navbar-link-hover: var(--pst-color-active-navigation); - --pst-color-navbar-link-active: var(--pst-color-active-navigation); - --pst-color-sidebar-link: 77, 77, 77; - --pst-color-sidebar-link-hover: var(--pst-color-active-navigation); - --pst-color-sidebar-link-active: var(--pst-color-active-navigation); - --pst-color-sidebar-expander-background-hover: 244, 244, 244; - --pst-color-sidebar-caption: 77, 77, 77; - --pst-color-toc-link: 119, 117, 122; - --pst-color-toc-link-hover: var(--pst-color-active-navigation); - --pst-color-toc-link-active: var(--pst-color-active-navigation); - - /***************************************************************************** - * Icon - **/ - - /* font awesome icons*/ - --pst-icon-check-circle: '\f058'; - --pst-icon-info-circle: '\f05a'; - --pst-icon-exclamation-triangle: '\f071'; - --pst-icon-exclamation-circle: '\f06a'; - --pst-icon-times-circle: '\f057'; - --pst-icon-lightbulb: '\f0eb'; - - /***************************************************************************** - * Admonitions - **/ - - --pst-color-admonition-default: var(--pst-color-info); - --pst-color-admonition-note: var(--pst-color-info); - --pst-color-admonition-attention: var(--pst-color-warning); - --pst-color-admonition-caution: var(--pst-color-warning); - --pst-color-admonition-warning: var(--pst-color-warning); - --pst-color-admonition-danger: var(--pst-color-danger); - --pst-color-admonition-error: var(--pst-color-danger); - --pst-color-admonition-hint: var(--pst-color-success); - --pst-color-admonition-tip: var(--pst-color-success); - --pst-color-admonition-important: var(--pst-color-success); - - --pst-icon-admonition-default: var(--pst-icon-info-circle); - --pst-icon-admonition-note: var(--pst-icon-info-circle); - --pst-icon-admonition-attention: var(--pst-icon-exclamation-circle); - --pst-icon-admonition-caution: var(--pst-icon-exclamation-triangle); - --pst-icon-admonition-warning: var(--pst-icon-exclamation-triangle); - --pst-icon-admonition-danger: var(--pst-icon-exclamation-triangle); - --pst-icon-admonition-error: var(--pst-icon-times-circle); - --pst-icon-admonition-hint: var(--pst-icon-lightbulb); - --pst-icon-admonition-tip: var(--pst-icon-lightbulb); - --pst-icon-admonition-important: var(--pst-icon-exclamation-circle); - -} diff --git a/_static/js/index.1c5a1a01449ed65a7b51.js b/_static/js/index.1c5a1a01449ed65a7b51.js deleted file mode 100755 index 5e8d90e..0000000 --- a/_static/js/index.1c5a1a01449ed65a7b51.js +++ /dev/null @@ -1,32 +0,0 @@ -!function(t){var e={};function n(i){if(e[i])return e[i].exports;var o=e[i]={i:i,l:!1,exports:{}};return t[i].call(o.exports,o,o.exports,n),o.l=!0,o.exports}n.m=t,n.c=e,n.d=function(t,e,i){n.o(t,e)||Object.defineProperty(t,e,{enumerable:!0,get:i})},n.r=function(t){"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(t,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(t,"__esModule",{value:!0})},n.t=function(t,e){if(1&e&&(t=n(t)),8&e)return t;if(4&e&&"object"==typeof t&&t&&t.__esModule)return t;var i=Object.create(null);if(n.r(i),Object.defineProperty(i,"default",{enumerable:!0,value:t}),2&e&&"string"!=typeof 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factory) { - typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() : - typeof define === 'function' && define.amd ? define('underscore', factory) : - (global = global || self, (function () { - var current = global._; - var exports = global._ = factory(); - exports.noConflict = function () { global._ = current; return exports; }; - }())); -}(this, (function () { - // Underscore.js 1.12.0 - // https://underscorejs.org - // (c) 2009-2020 Jeremy Ashkenas, DocumentCloud and Investigative Reporters & Editors - // Underscore may be freely distributed under the MIT license. - - // Current version. - var VERSION = '1.12.0'; - - // Establish the root object, `window` (`self`) in the browser, `global` - // on the server, or `this` in some virtual machines. We use `self` - // instead of `window` for `WebWorker` support. - var root = typeof self == 'object' && self.self === self && self || - typeof global == 'object' && global.global === global && global || - Function('return this')() || - {}; - - // Save bytes in the minified (but not gzipped) version: - var ArrayProto = Array.prototype, ObjProto = Object.prototype; - var SymbolProto = typeof Symbol !== 'undefined' ? Symbol.prototype : null; - - // Create quick reference variables for speed access to core prototypes. - var push = ArrayProto.push, - slice = ArrayProto.slice, - toString = ObjProto.toString, - hasOwnProperty = ObjProto.hasOwnProperty; - - // Modern feature detection. - var supportsArrayBuffer = typeof ArrayBuffer !== 'undefined', - supportsDataView = typeof DataView !== 'undefined'; - - // All **ECMAScript 5+** native function implementations that we hope to use - // are declared here. - var nativeIsArray = Array.isArray, - nativeKeys = Object.keys, - nativeCreate = Object.create, - nativeIsView = supportsArrayBuffer && ArrayBuffer.isView; - - // Create references to these builtin functions because we override them. - var _isNaN = isNaN, - _isFinite = isFinite; - - // Keys in IE < 9 that won't be iterated by `for key in ...` and thus missed. - var hasEnumBug = !{toString: null}.propertyIsEnumerable('toString'); - var nonEnumerableProps = ['valueOf', 'isPrototypeOf', 'toString', - 'propertyIsEnumerable', 'hasOwnProperty', 'toLocaleString']; - - // The largest integer that can be represented exactly. - var MAX_ARRAY_INDEX = Math.pow(2, 53) - 1; - - // Some functions take a variable number of arguments, or a few expected - // arguments at the beginning and then a variable number of values to operate - // on. This helper accumulates all remaining arguments past the function’s - // argument length (or an explicit `startIndex`), into an array that becomes - // the last argument. Similar to ES6’s "rest parameter". - function restArguments(func, startIndex) { - startIndex = startIndex == null ? func.length - 1 : +startIndex; - return function() { - var length = Math.max(arguments.length - startIndex, 0), - rest = Array(length), - index = 0; - for (; index < length; index++) { - rest[index] = arguments[index + startIndex]; - } - switch (startIndex) { - case 0: return func.call(this, rest); - case 1: return func.call(this, arguments[0], rest); - case 2: return func.call(this, arguments[0], arguments[1], rest); - } - var args = Array(startIndex + 1); - for (index = 0; index < startIndex; index++) { - args[index] = arguments[index]; - } - args[startIndex] = rest; - return func.apply(this, args); - }; - } - - // Is a given variable an object? - function isObject(obj) { - var type = typeof obj; - return type === 'function' || type === 'object' && !!obj; - } - - // Is a given value equal to null? - function isNull(obj) { - return obj === null; - } - - // Is a given variable undefined? - function isUndefined(obj) { - return obj === void 0; - } - - // Is a given value a boolean? - function isBoolean(obj) { - return obj === true || obj === false || toString.call(obj) === '[object Boolean]'; - } - - // Is a given value a DOM element? - function isElement(obj) { - return !!(obj && obj.nodeType === 1); - } - - // Internal function for creating a `toString`-based type tester. - function tagTester(name) { - var tag = '[object ' + name + ']'; - return function(obj) { - return toString.call(obj) === tag; - }; - } - - var isString = tagTester('String'); - - var isNumber = tagTester('Number'); - - var isDate = tagTester('Date'); - - var isRegExp = tagTester('RegExp'); - - var isError = tagTester('Error'); - - var isSymbol = tagTester('Symbol'); - - var isArrayBuffer = tagTester('ArrayBuffer'); - - var isFunction = tagTester('Function'); - - // Optimize `isFunction` if appropriate. Work around some `typeof` bugs in old - // v8, IE 11 (#1621), Safari 8 (#1929), and PhantomJS (#2236). - var nodelist = root.document && root.document.childNodes; - if (typeof /./ != 'function' && typeof Int8Array != 'object' && typeof nodelist != 'function') { - isFunction = function(obj) { - return typeof obj == 'function' || false; - }; - } - - var isFunction$1 = isFunction; - - var hasObjectTag = tagTester('Object'); - - // In IE 10 - Edge 13, `DataView` has string tag `'[object Object]'`. - // In IE 11, the most common among them, this problem also applies to - // `Map`, `WeakMap` and `Set`. - var hasStringTagBug = ( - supportsDataView && hasObjectTag(new DataView(new ArrayBuffer(8))) - ), - isIE11 = (typeof Map !== 'undefined' && hasObjectTag(new Map)); - - var isDataView = tagTester('DataView'); - - // In IE 10 - Edge 13, we need a different heuristic - // to determine whether an object is a `DataView`. - function ie10IsDataView(obj) { - return obj != null && isFunction$1(obj.getInt8) && isArrayBuffer(obj.buffer); - } - - var isDataView$1 = (hasStringTagBug ? ie10IsDataView : isDataView); - - // Is a given value an array? - // Delegates to ECMA5's native `Array.isArray`. - var isArray = nativeIsArray || tagTester('Array'); - - // Internal function to check whether `key` is an own property name of `obj`. - function has(obj, key) { - return obj != null && hasOwnProperty.call(obj, key); - } - - var isArguments = tagTester('Arguments'); - - // Define a fallback version of the method in browsers (ahem, IE < 9), where - // there isn't any inspectable "Arguments" type. - (function() { - if (!isArguments(arguments)) { - isArguments = function(obj) { - return has(obj, 'callee'); - }; - } - }()); - - var isArguments$1 = isArguments; - - // Is a given object a finite number? - function isFinite$1(obj) { - return !isSymbol(obj) && _isFinite(obj) && !isNaN(parseFloat(obj)); - } - - // Is the given value `NaN`? - function isNaN$1(obj) { - return isNumber(obj) && _isNaN(obj); - } - - // Predicate-generating function. Often useful outside of Underscore. - function constant(value) { - return function() { - return value; - }; - } - - // Common internal logic for `isArrayLike` and `isBufferLike`. - function createSizePropertyCheck(getSizeProperty) { - return function(collection) { - var sizeProperty = getSizeProperty(collection); - return typeof sizeProperty == 'number' && sizeProperty >= 0 && sizeProperty <= MAX_ARRAY_INDEX; - } - } - - // Internal helper to generate a function to obtain property `key` from `obj`. - function shallowProperty(key) { - return function(obj) { - return obj == null ? void 0 : obj[key]; - }; - } - - // Internal helper to obtain the `byteLength` property of an object. - var getByteLength = shallowProperty('byteLength'); - - // Internal helper to determine whether we should spend extensive checks against - // `ArrayBuffer` et al. - var isBufferLike = createSizePropertyCheck(getByteLength); - - // Is a given value a typed array? - var typedArrayPattern = /\[object ((I|Ui)nt(8|16|32)|Float(32|64)|Uint8Clamped|Big(I|Ui)nt64)Array\]/; - function isTypedArray(obj) { - // `ArrayBuffer.isView` is the most future-proof, so use it when available. - // Otherwise, fall back on the above regular expression. - return nativeIsView ? (nativeIsView(obj) && !isDataView$1(obj)) : - isBufferLike(obj) && typedArrayPattern.test(toString.call(obj)); - } - - var isTypedArray$1 = supportsArrayBuffer ? isTypedArray : constant(false); - - // Internal helper to obtain the `length` property of an object. - var getLength = shallowProperty('length'); - - // Internal helper to create a simple lookup structure. - // `collectNonEnumProps` used to depend on `_.contains`, but this led to - // circular imports. `emulatedSet` is a one-off solution that only works for - // arrays of strings. - function emulatedSet(keys) { - var hash = {}; - for (var l = keys.length, i = 0; i < l; ++i) hash[keys[i]] = true; - return { - contains: function(key) { return hash[key]; }, - push: function(key) { - hash[key] = true; - return keys.push(key); - } - }; - } - - // Internal helper. Checks `keys` for the presence of keys in IE < 9 that won't - // be iterated by `for key in ...` and thus missed. Extends `keys` in place if - // needed. - function collectNonEnumProps(obj, keys) { - keys = emulatedSet(keys); - var nonEnumIdx = nonEnumerableProps.length; - var constructor = obj.constructor; - var proto = isFunction$1(constructor) && constructor.prototype || ObjProto; - - // Constructor is a special case. - var prop = 'constructor'; - if (has(obj, prop) && !keys.contains(prop)) keys.push(prop); - - while (nonEnumIdx--) { - prop = nonEnumerableProps[nonEnumIdx]; - if (prop in obj && obj[prop] !== proto[prop] && !keys.contains(prop)) { - keys.push(prop); - } - } - } - - // Retrieve the names of an object's own properties. - // Delegates to **ECMAScript 5**'s native `Object.keys`. - function keys(obj) { - if (!isObject(obj)) return []; - if (nativeKeys) return nativeKeys(obj); - var keys = []; - for (var key in obj) if (has(obj, key)) keys.push(key); - // Ahem, IE < 9. - if (hasEnumBug) collectNonEnumProps(obj, keys); - return keys; - } - - // Is a given array, string, or object empty? - // An "empty" object has no enumerable own-properties. - function isEmpty(obj) { - if (obj == null) return true; - // Skip the more expensive `toString`-based type checks if `obj` has no - // `.length`. - var length = getLength(obj); - if (typeof length == 'number' && ( - isArray(obj) || isString(obj) || isArguments$1(obj) - )) return length === 0; - return getLength(keys(obj)) === 0; - } - - // Returns whether an object has a given set of `key:value` pairs. - function isMatch(object, attrs) { - var _keys = keys(attrs), length = _keys.length; - if (object == null) return !length; - var obj = Object(object); - for (var i = 0; i < length; i++) { - var key = _keys[i]; - if (attrs[key] !== obj[key] || !(key in obj)) return false; - } - return true; - } - - // If Underscore is called as a function, it returns a wrapped object that can - // be used OO-style. This wrapper holds altered versions of all functions added - // through `_.mixin`. Wrapped objects may be chained. - function _(obj) { - if (obj instanceof _) return obj; - if (!(this instanceof _)) return new _(obj); - this._wrapped = obj; - } - - _.VERSION = VERSION; - - // Extracts the result from a wrapped and chained object. - _.prototype.value = function() { - return this._wrapped; - }; - - // Provide unwrapping proxies for some methods used in engine operations - // such as arithmetic and JSON stringification. - _.prototype.valueOf = _.prototype.toJSON = _.prototype.value; - - _.prototype.toString = function() { - return String(this._wrapped); - }; - - // Internal function to wrap or shallow-copy an ArrayBuffer, - // typed array or DataView to a new view, reusing the buffer. - function toBufferView(bufferSource) { - return new Uint8Array( - bufferSource.buffer || bufferSource, - bufferSource.byteOffset || 0, - getByteLength(bufferSource) - ); - } - - // We use this string twice, so give it a name for minification. - var tagDataView = '[object DataView]'; - - // Internal recursive comparison function for `_.isEqual`. - function eq(a, b, aStack, bStack) { - // Identical objects are equal. `0 === -0`, but they aren't identical. - // See the [Harmony `egal` proposal](https://wiki.ecmascript.org/doku.php?id=harmony:egal). - if (a === b) return a !== 0 || 1 / a === 1 / b; - // `null` or `undefined` only equal to itself (strict comparison). - if (a == null || b == null) return false; - // `NaN`s are equivalent, but non-reflexive. - if (a !== a) return b !== b; - // Exhaust primitive checks - var type = typeof a; - if (type !== 'function' && type !== 'object' && typeof b != 'object') return false; - return deepEq(a, b, aStack, bStack); - } - - // Internal recursive comparison function for `_.isEqual`. - function deepEq(a, b, aStack, bStack) { - // Unwrap any wrapped objects. - if (a instanceof _) a = a._wrapped; - if (b instanceof _) b = b._wrapped; - // Compare `[[Class]]` names. - var className = toString.call(a); - if (className !== toString.call(b)) return false; - // Work around a bug in IE 10 - Edge 13. - if (hasStringTagBug && className == '[object Object]' && isDataView$1(a)) { - if (!isDataView$1(b)) return false; - className = tagDataView; - } - switch (className) { - // These types are compared by value. - case '[object RegExp]': - // RegExps are coerced to strings for comparison (Note: '' + /a/i === '/a/i') - case '[object String]': - // Primitives and their corresponding object wrappers are equivalent; thus, `"5"` is - // equivalent to `new String("5")`. - return '' + a === '' + b; - case '[object Number]': - // `NaN`s are equivalent, but non-reflexive. - // Object(NaN) is equivalent to NaN. - if (+a !== +a) return +b !== +b; - // An `egal` comparison is performed for other numeric values. - return +a === 0 ? 1 / +a === 1 / b : +a === +b; - case '[object Date]': - case '[object Boolean]': - // Coerce dates and booleans to numeric primitive values. Dates are compared by their - // millisecond representations. Note that invalid dates with millisecond representations - // of `NaN` are not equivalent. - return +a === +b; - case '[object Symbol]': - return SymbolProto.valueOf.call(a) === SymbolProto.valueOf.call(b); - case '[object ArrayBuffer]': - case tagDataView: - // Coerce to typed array so we can fall through. - return deepEq(toBufferView(a), toBufferView(b), aStack, bStack); - } - - var areArrays = className === '[object Array]'; - if (!areArrays && isTypedArray$1(a)) { - var byteLength = getByteLength(a); - if (byteLength !== getByteLength(b)) return false; - if (a.buffer === b.buffer && a.byteOffset === b.byteOffset) return true; - areArrays = true; - } - if (!areArrays) { - if (typeof a != 'object' || typeof b != 'object') return false; - - // Objects with different constructors are not equivalent, but `Object`s or `Array`s - // from different frames are. - var aCtor = a.constructor, bCtor = b.constructor; - if (aCtor !== bCtor && !(isFunction$1(aCtor) && aCtor instanceof aCtor && - isFunction$1(bCtor) && bCtor instanceof bCtor) - && ('constructor' in a && 'constructor' in b)) { - return false; - } - } - // Assume equality for cyclic structures. The algorithm for detecting cyclic - // structures is adapted from ES 5.1 section 15.12.3, abstract operation `JO`. - - // Initializing stack of traversed objects. - // It's done here since we only need them for objects and arrays comparison. - aStack = aStack || []; - bStack = bStack || []; - var length = aStack.length; - while (length--) { - // Linear search. Performance is inversely proportional to the number of - // unique nested structures. - if (aStack[length] === a) return bStack[length] === b; - } - - // Add the first object to the stack of traversed objects. - aStack.push(a); - bStack.push(b); - - // Recursively compare objects and arrays. - if (areArrays) { - // Compare array lengths to determine if a deep comparison is necessary. - length = a.length; - if (length !== b.length) return false; - // Deep compare the contents, ignoring non-numeric properties. - while (length--) { - if (!eq(a[length], b[length], aStack, bStack)) return false; - } - } else { - // Deep compare objects. - var _keys = keys(a), key; - length = _keys.length; - // Ensure that both objects contain the same number of properties before comparing deep equality. - if (keys(b).length !== length) return false; - while (length--) { - // Deep compare each member - key = _keys[length]; - if (!(has(b, key) && eq(a[key], b[key], aStack, bStack))) return false; - } - } - // Remove the first object from the stack of traversed objects. - aStack.pop(); - bStack.pop(); - return true; - } - - // Perform a deep comparison to check if two objects are equal. - function isEqual(a, b) { - return eq(a, b); - } - - // Retrieve all the enumerable property names of an object. - function allKeys(obj) { - if (!isObject(obj)) return []; - var keys = []; - for (var key in obj) keys.push(key); - // Ahem, IE < 9. - if (hasEnumBug) collectNonEnumProps(obj, keys); - return keys; - } - - // Since the regular `Object.prototype.toString` type tests don't work for - // some types in IE 11, we use a fingerprinting heuristic instead, based - // on the methods. It's not great, but it's the best we got. - // The fingerprint method lists are defined below. - function ie11fingerprint(methods) { - var length = getLength(methods); - return function(obj) { - if (obj == null) return false; - // `Map`, `WeakMap` and `Set` have no enumerable keys. - var keys = allKeys(obj); - if (getLength(keys)) return false; - for (var i = 0; i < length; i++) { - if (!isFunction$1(obj[methods[i]])) return false; - } - // If we are testing against `WeakMap`, we need to ensure that - // `obj` doesn't have a `forEach` method in order to distinguish - // it from a regular `Map`. - return methods !== weakMapMethods || !isFunction$1(obj[forEachName]); - }; - } - - // In the interest of compact minification, we write - // each string in the fingerprints only once. - var forEachName = 'forEach', - hasName = 'has', - commonInit = ['clear', 'delete'], - mapTail = ['get', hasName, 'set']; - - // `Map`, `WeakMap` and `Set` each have slightly different - // combinations of the above sublists. - var mapMethods = commonInit.concat(forEachName, mapTail), - weakMapMethods = commonInit.concat(mapTail), - setMethods = ['add'].concat(commonInit, forEachName, hasName); - - var isMap = isIE11 ? ie11fingerprint(mapMethods) : tagTester('Map'); - - var isWeakMap = isIE11 ? ie11fingerprint(weakMapMethods) : tagTester('WeakMap'); - - var isSet = isIE11 ? ie11fingerprint(setMethods) : tagTester('Set'); - - var isWeakSet = tagTester('WeakSet'); - - // Retrieve the values of an object's properties. - function values(obj) { - var _keys = keys(obj); - var length = _keys.length; - var values = Array(length); - for (var i = 0; i < length; i++) { - values[i] = obj[_keys[i]]; - } - return values; - } - - // Convert an object into a list of `[key, value]` pairs. - // The opposite of `_.object` with one argument. - function pairs(obj) { - var _keys = keys(obj); - var length = _keys.length; - var pairs = Array(length); - for (var i = 0; i < length; i++) { - pairs[i] = [_keys[i], obj[_keys[i]]]; - } - return pairs; - } - - // Invert the keys and values of an object. The values must be serializable. - function invert(obj) { - var result = {}; - var _keys = keys(obj); - for (var i = 0, length = _keys.length; i < length; i++) { - result[obj[_keys[i]]] = _keys[i]; - } - return result; - } - - // Return a sorted list of the function names available on the object. - function functions(obj) { - var names = []; - for (var key in obj) { - if (isFunction$1(obj[key])) names.push(key); - } - return names.sort(); - } - - // An internal function for creating assigner functions. - function createAssigner(keysFunc, defaults) { - return function(obj) { - var length = arguments.length; - if (defaults) obj = Object(obj); - if (length < 2 || obj == null) return obj; - for (var index = 1; index < length; index++) { - var source = arguments[index], - keys = keysFunc(source), - l = keys.length; - for (var i = 0; i < l; i++) { - var key = keys[i]; - if (!defaults || obj[key] === void 0) obj[key] = source[key]; - } - } - return obj; - }; - } - - // Extend a given object with all the properties in passed-in object(s). - var extend = createAssigner(allKeys); - - // Assigns a given object with all the own properties in the passed-in - // object(s). - // (https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Object/assign) - var extendOwn = createAssigner(keys); - - // Fill in a given object with default properties. - var defaults = createAssigner(allKeys, true); - - // Create a naked function reference for surrogate-prototype-swapping. - function ctor() { - return function(){}; - } - - // An internal function for creating a new object that inherits from another. - function baseCreate(prototype) { - if (!isObject(prototype)) return {}; - if (nativeCreate) return nativeCreate(prototype); - var Ctor = ctor(); - Ctor.prototype = prototype; - var result = new Ctor; - Ctor.prototype = null; - return result; - } - - // Creates an object that inherits from the given prototype object. - // If additional properties are provided then they will be added to the - // created object. - function create(prototype, props) { - var result = baseCreate(prototype); - if (props) extendOwn(result, props); - return result; - } - - // Create a (shallow-cloned) duplicate of an object. - function clone(obj) { - if (!isObject(obj)) return obj; - return isArray(obj) ? obj.slice() : extend({}, obj); - } - - // Invokes `interceptor` with the `obj` and then returns `obj`. - // The primary purpose of this method is to "tap into" a method chain, in - // order to perform operations on intermediate results within the chain. - function tap(obj, interceptor) { - interceptor(obj); - return obj; - } - - // Normalize a (deep) property `path` to array. - // Like `_.iteratee`, this function can be customized. - function toPath(path) { - return isArray(path) ? path : [path]; - } - _.toPath = toPath; - - // Internal wrapper for `_.toPath` to enable minification. - // Similar to `cb` for `_.iteratee`. - function toPath$1(path) { - return _.toPath(path); - } - - // Internal function to obtain a nested property in `obj` along `path`. - function deepGet(obj, path) { - var length = path.length; - for (var i = 0; i < length; i++) { - if (obj == null) return void 0; - obj = obj[path[i]]; - } - return length ? obj : void 0; - } - - // Get the value of the (deep) property on `path` from `object`. - // If any property in `path` does not exist or if the value is - // `undefined`, return `defaultValue` instead. - // The `path` is normalized through `_.toPath`. - function get(object, path, defaultValue) { - var value = deepGet(object, toPath$1(path)); - return isUndefined(value) ? defaultValue : value; - } - - // Shortcut function for checking if an object has a given property directly on - // itself (in other words, not on a prototype). Unlike the internal `has` - // function, this public version can also traverse nested properties. - function has$1(obj, path) { - path = toPath$1(path); - var length = path.length; - for (var i = 0; i < length; i++) { - var key = path[i]; - if (!has(obj, key)) return false; - obj = obj[key]; - } - return !!length; - } - - // Keep the identity function around for default iteratees. - function identity(value) { - return value; - } - - // Returns a predicate for checking whether an object has a given set of - // `key:value` pairs. - function matcher(attrs) { - attrs = extendOwn({}, attrs); - return function(obj) { - return isMatch(obj, attrs); - }; - } - - // Creates a function that, when passed an object, will traverse that object’s - // properties down the given `path`, specified as an array of keys or indices. - function property(path) { - path = toPath$1(path); - return function(obj) { - return deepGet(obj, path); - }; - } - - // Internal function that returns an efficient (for current engines) version - // of the passed-in callback, to be repeatedly applied in other Underscore - // functions. - function optimizeCb(func, context, argCount) { - if (context === void 0) return func; - switch (argCount == null ? 3 : argCount) { - case 1: return function(value) { - return func.call(context, value); - }; - // The 2-argument case is omitted because we’re not using it. - case 3: return function(value, index, collection) { - return func.call(context, value, index, collection); - }; - case 4: return function(accumulator, value, index, collection) { - return func.call(context, accumulator, value, index, collection); - }; - } - return function() { - return func.apply(context, arguments); - }; - } - - // An internal function to generate callbacks that can be applied to each - // element in a collection, returning the desired result — either `_.identity`, - // an arbitrary callback, a property matcher, or a property accessor. - function baseIteratee(value, context, argCount) { - if (value == null) return identity; - if (isFunction$1(value)) return optimizeCb(value, context, argCount); - if (isObject(value) && !isArray(value)) return matcher(value); - return property(value); - } - - // External wrapper for our callback generator. Users may customize - // `_.iteratee` if they want additional predicate/iteratee shorthand styles. - // This abstraction hides the internal-only `argCount` argument. - function iteratee(value, context) { - return baseIteratee(value, context, Infinity); - } - _.iteratee = iteratee; - - // The function we call internally to generate a callback. It invokes - // `_.iteratee` if overridden, otherwise `baseIteratee`. - function cb(value, context, argCount) { - if (_.iteratee !== iteratee) return _.iteratee(value, context); - return baseIteratee(value, context, argCount); - } - - // Returns the results of applying the `iteratee` to each element of `obj`. - // In contrast to `_.map` it returns an object. - function mapObject(obj, iteratee, context) { - iteratee = cb(iteratee, context); - var _keys = keys(obj), - length = _keys.length, - results = {}; - for (var index = 0; index < length; index++) { - var currentKey = _keys[index]; - results[currentKey] = iteratee(obj[currentKey], currentKey, obj); - } - return results; - } - - // Predicate-generating function. Often useful outside of Underscore. - function noop(){} - - // Generates a function for a given object that returns a given property. - function propertyOf(obj) { - if (obj == null) return noop; - return function(path) { - return get(obj, path); - }; - } - - // Run a function **n** times. - function times(n, iteratee, context) { - var accum = Array(Math.max(0, n)); - iteratee = optimizeCb(iteratee, context, 1); - for (var i = 0; i < n; i++) accum[i] = iteratee(i); - return accum; - } - - // Return a random integer between `min` and `max` (inclusive). - function random(min, max) { - if (max == null) { - max = min; - min = 0; - } - return min + Math.floor(Math.random() * (max - min + 1)); - } - - // A (possibly faster) way to get the current timestamp as an integer. - var now = Date.now || function() { - return new Date().getTime(); - }; - - // Internal helper to generate functions for escaping and unescaping strings - // to/from HTML interpolation. - function createEscaper(map) { - var escaper = function(match) { - return map[match]; - }; - // Regexes for identifying a key that needs to be escaped. - var source = '(?:' + keys(map).join('|') + ')'; - var testRegexp = RegExp(source); - var replaceRegexp = RegExp(source, 'g'); - return function(string) { - string = string == null ? '' : '' + string; - return testRegexp.test(string) ? string.replace(replaceRegexp, escaper) : string; - }; - } - - // Internal list of HTML entities for escaping. - var escapeMap = { - '&': '&', - '<': '<', - '>': '>', - '"': '"', - "'": ''', - '`': '`' - }; - - // Function for escaping strings to HTML interpolation. - var _escape = createEscaper(escapeMap); - - // Internal list of HTML entities for unescaping. - var unescapeMap = invert(escapeMap); - - // Function for unescaping strings from HTML interpolation. - var _unescape = createEscaper(unescapeMap); - - // By default, Underscore uses ERB-style template delimiters. Change the - // following template settings to use alternative delimiters. - var templateSettings = _.templateSettings = { - evaluate: /<%([\s\S]+?)%>/g, - interpolate: /<%=([\s\S]+?)%>/g, - escape: /<%-([\s\S]+?)%>/g - }; - - // When customizing `_.templateSettings`, if you don't want to define an - // interpolation, evaluation or escaping regex, we need one that is - // guaranteed not to match. - var noMatch = /(.)^/; - - // Certain characters need to be escaped so that they can be put into a - // string literal. - var escapes = { - "'": "'", - '\\': '\\', - '\r': 'r', - '\n': 'n', - '\u2028': 'u2028', - '\u2029': 'u2029' - }; - - var escapeRegExp = /\\|'|\r|\n|\u2028|\u2029/g; - - function escapeChar(match) { - return '\\' + escapes[match]; - } - - // JavaScript micro-templating, similar to John Resig's implementation. - // Underscore templating handles arbitrary delimiters, preserves whitespace, - // and correctly escapes quotes within interpolated code. - // NB: `oldSettings` only exists for backwards compatibility. - function template(text, settings, oldSettings) { - if (!settings && oldSettings) settings = oldSettings; - settings = defaults({}, settings, _.templateSettings); - - // Combine delimiters into one regular expression via alternation. - var matcher = RegExp([ - (settings.escape || noMatch).source, - (settings.interpolate || noMatch).source, - (settings.evaluate || noMatch).source - ].join('|') + '|$', 'g'); - - // Compile the template source, escaping string literals appropriately. - var index = 0; - var source = "__p+='"; - text.replace(matcher, function(match, escape, interpolate, evaluate, offset) { - source += text.slice(index, offset).replace(escapeRegExp, escapeChar); - index = offset + match.length; - - if (escape) { - source += "'+\n((__t=(" + escape + "))==null?'':_.escape(__t))+\n'"; - } else if (interpolate) { - source += "'+\n((__t=(" + interpolate + "))==null?'':__t)+\n'"; - } else if (evaluate) { - source += "';\n" + evaluate + "\n__p+='"; - } - - // Adobe VMs need the match returned to produce the correct offset. - return match; - }); - source += "';\n"; - - // If a variable is not specified, place data values in local scope. - if (!settings.variable) source = 'with(obj||{}){\n' + source + '}\n'; - - source = "var __t,__p='',__j=Array.prototype.join," + - "print=function(){__p+=__j.call(arguments,'');};\n" + - source + 'return __p;\n'; - - var render; - try { - render = new Function(settings.variable || 'obj', '_', source); - } catch (e) { - e.source = source; - throw e; - } - - var template = function(data) { - return render.call(this, data, _); - }; - - // Provide the compiled source as a convenience for precompilation. - var argument = settings.variable || 'obj'; - template.source = 'function(' + argument + '){\n' + source + '}'; - - return template; - } - - // Traverses the children of `obj` along `path`. If a child is a function, it - // is invoked with its parent as context. Returns the value of the final - // child, or `fallback` if any child is undefined. - function result(obj, path, fallback) { - path = toPath$1(path); - var length = path.length; - if (!length) { - return isFunction$1(fallback) ? fallback.call(obj) : fallback; - } - for (var i = 0; i < length; i++) { - var prop = obj == null ? void 0 : obj[path[i]]; - if (prop === void 0) { - prop = fallback; - i = length; // Ensure we don't continue iterating. - } - obj = isFunction$1(prop) ? prop.call(obj) : prop; - } - return obj; - } - - // Generate a unique integer id (unique within the entire client session). - // Useful for temporary DOM ids. - var idCounter = 0; - function uniqueId(prefix) { - var id = ++idCounter + ''; - return prefix ? prefix + id : id; - } - - // Start chaining a wrapped Underscore object. - function chain(obj) { - var instance = _(obj); - instance._chain = true; - return instance; - } - - // Internal function to execute `sourceFunc` bound to `context` with optional - // `args`. Determines whether to execute a function as a constructor or as a - // normal function. - function executeBound(sourceFunc, boundFunc, context, callingContext, args) { - if (!(callingContext instanceof boundFunc)) return sourceFunc.apply(context, args); - var self = baseCreate(sourceFunc.prototype); - var result = sourceFunc.apply(self, args); - if (isObject(result)) return result; - return self; - } - - // Partially apply a function by creating a version that has had some of its - // arguments pre-filled, without changing its dynamic `this` context. `_` acts - // as a placeholder by default, allowing any combination of arguments to be - // pre-filled. Set `_.partial.placeholder` for a custom placeholder argument. - var partial = restArguments(function(func, boundArgs) { - var placeholder = partial.placeholder; - var bound = function() { - var position = 0, length = boundArgs.length; - var args = Array(length); - for (var i = 0; i < length; i++) { - args[i] = boundArgs[i] === placeholder ? arguments[position++] : boundArgs[i]; - } - while (position < arguments.length) args.push(arguments[position++]); - return executeBound(func, bound, this, this, args); - }; - return bound; - }); - - partial.placeholder = _; - - // Create a function bound to a given object (assigning `this`, and arguments, - // optionally). - var bind = restArguments(function(func, context, args) { - if (!isFunction$1(func)) throw new TypeError('Bind must be called on a function'); - var bound = restArguments(function(callArgs) { - return executeBound(func, bound, context, this, args.concat(callArgs)); - }); - return bound; - }); - - // Internal helper for collection methods to determine whether a collection - // should be iterated as an array or as an object. - // Related: https://people.mozilla.org/~jorendorff/es6-draft.html#sec-tolength - // Avoids a very nasty iOS 8 JIT bug on ARM-64. #2094 - var isArrayLike = createSizePropertyCheck(getLength); - - // Internal implementation of a recursive `flatten` function. - function flatten(input, depth, strict, output) { - output = output || []; - if (!depth && depth !== 0) { - depth = Infinity; - } else if (depth <= 0) { - return output.concat(input); - } - var idx = output.length; - for (var i = 0, length = getLength(input); i < length; i++) { - var value = input[i]; - if (isArrayLike(value) && (isArray(value) || isArguments$1(value))) { - // Flatten current level of array or arguments object. - if (depth > 1) { - flatten(value, depth - 1, strict, output); - idx = output.length; - } else { - var j = 0, len = value.length; - while (j < len) output[idx++] = value[j++]; - } - } else if (!strict) { - output[idx++] = value; - } - } - return output; - } - - // Bind a number of an object's methods to that object. Remaining arguments - // are the method names to be bound. Useful for ensuring that all callbacks - // defined on an object belong to it. - var bindAll = restArguments(function(obj, keys) { - keys = flatten(keys, false, false); - var index = keys.length; - if (index < 1) throw new Error('bindAll must be passed function names'); - while (index--) { - var key = keys[index]; - obj[key] = bind(obj[key], obj); - } - return obj; - }); - - // Memoize an expensive function by storing its results. - function memoize(func, hasher) { - var memoize = function(key) { - var cache = memoize.cache; - var address = '' + (hasher ? hasher.apply(this, arguments) : key); - if (!has(cache, address)) cache[address] = func.apply(this, arguments); - return cache[address]; - }; - memoize.cache = {}; - return memoize; - } - - // Delays a function for the given number of milliseconds, and then calls - // it with the arguments supplied. - var delay = restArguments(function(func, wait, args) { - return setTimeout(function() { - return func.apply(null, args); - }, wait); - }); - - // Defers a function, scheduling it to run after the current call stack has - // cleared. - var defer = partial(delay, _, 1); - - // Returns a function, that, when invoked, will only be triggered at most once - // during a given window of time. Normally, the throttled function will run - // as much as it can, without ever going more than once per `wait` duration; - // but if you'd like to disable the execution on the leading edge, pass - // `{leading: false}`. To disable execution on the trailing edge, ditto. - function throttle(func, wait, options) { - var timeout, context, args, result; - var previous = 0; - if (!options) options = {}; - - var later = function() { - previous = options.leading === false ? 0 : now(); - timeout = null; - result = func.apply(context, args); - if (!timeout) context = args = null; - }; - - var throttled = function() { - var _now = now(); - if (!previous && options.leading === false) previous = _now; - var remaining = wait - (_now - previous); - context = this; - args = arguments; - if (remaining <= 0 || remaining > wait) { - if (timeout) { - clearTimeout(timeout); - timeout = null; - } - previous = _now; - result = func.apply(context, args); - if (!timeout) context = args = null; - } else if (!timeout && options.trailing !== false) { - timeout = setTimeout(later, remaining); - } - return result; - }; - - throttled.cancel = function() { - clearTimeout(timeout); - previous = 0; - timeout = context = args = null; - }; - - return throttled; - } - - // When a sequence of calls of the returned function ends, the argument - // function is triggered. The end of a sequence is defined by the `wait` - // parameter. If `immediate` is passed, the argument function will be - // triggered at the beginning of the sequence instead of at the end. - function debounce(func, wait, immediate) { - var timeout, previous, args, result, context; - - var later = function() { - var passed = now() - previous; - if (wait > passed) { - timeout = setTimeout(later, wait - passed); - } else { - timeout = null; - if (!immediate) result = func.apply(context, args); - // This check is needed because `func` can recursively invoke `debounced`. - if (!timeout) args = context = null; - } - }; - - var debounced = restArguments(function(_args) { - context = this; - args = _args; - previous = now(); - if (!timeout) { - timeout = setTimeout(later, wait); - if (immediate) result = func.apply(context, args); - } - return result; - }); - - debounced.cancel = function() { - clearTimeout(timeout); - timeout = args = context = null; - }; - - return debounced; - } - - // Returns the first function passed as an argument to the second, - // allowing you to adjust arguments, run code before and after, and - // conditionally execute the original function. - function wrap(func, wrapper) { - return partial(wrapper, func); - } - - // Returns a negated version of the passed-in predicate. - function negate(predicate) { - return function() { - return !predicate.apply(this, arguments); - }; - } - - // Returns a function that is the composition of a list of functions, each - // consuming the return value of the function that follows. - function compose() { - var args = arguments; - var start = args.length - 1; - return function() { - var i = start; - var result = args[start].apply(this, arguments); - while (i--) result = args[i].call(this, result); - return result; - }; - } - - // Returns a function that will only be executed on and after the Nth call. - function after(times, func) { - return function() { - if (--times < 1) { - return func.apply(this, arguments); - } - }; - } - - // Returns a function that will only be executed up to (but not including) the - // Nth call. - function before(times, func) { - var memo; - return function() { - if (--times > 0) { - memo = func.apply(this, arguments); - } - if (times <= 1) func = null; - return memo; - }; - } - - // Returns a function that will be executed at most one time, no matter how - // often you call it. Useful for lazy initialization. - var once = partial(before, 2); - - // Returns the first key on an object that passes a truth test. - function findKey(obj, predicate, context) { - predicate = cb(predicate, context); - var _keys = keys(obj), key; - for (var i = 0, length = _keys.length; i < length; i++) { - key = _keys[i]; - if (predicate(obj[key], key, obj)) return key; - } - } - - // Internal function to generate `_.findIndex` and `_.findLastIndex`. - function createPredicateIndexFinder(dir) { - return function(array, predicate, context) { - predicate = cb(predicate, context); - var length = getLength(array); - var index = dir > 0 ? 0 : length - 1; - for (; index >= 0 && index < length; index += dir) { - if (predicate(array[index], index, array)) return index; - } - return -1; - }; - } - - // Returns the first index on an array-like that passes a truth test. - var findIndex = createPredicateIndexFinder(1); - - // Returns the last index on an array-like that passes a truth test. - var findLastIndex = createPredicateIndexFinder(-1); - - // Use a comparator function to figure out the smallest index at which - // an object should be inserted so as to maintain order. Uses binary search. - function sortedIndex(array, obj, iteratee, context) { - iteratee = cb(iteratee, context, 1); - var value = iteratee(obj); - var low = 0, high = getLength(array); - while (low < high) { - var mid = Math.floor((low + high) / 2); - if (iteratee(array[mid]) < value) low = mid + 1; else high = mid; - } - return low; - } - - // Internal function to generate the `_.indexOf` and `_.lastIndexOf` functions. - function createIndexFinder(dir, predicateFind, sortedIndex) { - return function(array, item, idx) { - var i = 0, length = getLength(array); - if (typeof idx == 'number') { - if (dir > 0) { - i = idx >= 0 ? idx : Math.max(idx + length, i); - } else { - length = idx >= 0 ? Math.min(idx + 1, length) : idx + length + 1; - } - } else if (sortedIndex && idx && length) { - idx = sortedIndex(array, item); - return array[idx] === item ? idx : -1; - } - if (item !== item) { - idx = predicateFind(slice.call(array, i, length), isNaN$1); - return idx >= 0 ? idx + i : -1; - } - for (idx = dir > 0 ? i : length - 1; idx >= 0 && idx < length; idx += dir) { - if (array[idx] === item) return idx; - } - return -1; - }; - } - - // Return the position of the first occurrence of an item in an array, - // or -1 if the item is not included in the array. - // If the array is large and already in sort order, pass `true` - // for **isSorted** to use binary search. - var indexOf = createIndexFinder(1, findIndex, sortedIndex); - - // Return the position of the last occurrence of an item in an array, - // or -1 if the item is not included in the array. - var lastIndexOf = createIndexFinder(-1, findLastIndex); - - // Return the first value which passes a truth test. - function find(obj, predicate, context) { - var keyFinder = isArrayLike(obj) ? findIndex : findKey; - var key = keyFinder(obj, predicate, context); - if (key !== void 0 && key !== -1) return obj[key]; - } - - // Convenience version of a common use case of `_.find`: getting the first - // object containing specific `key:value` pairs. - function findWhere(obj, attrs) { - return find(obj, matcher(attrs)); - } - - // The cornerstone for collection functions, an `each` - // implementation, aka `forEach`. - // Handles raw objects in addition to array-likes. Treats all - // sparse array-likes as if they were dense. - function each(obj, iteratee, context) { - iteratee = optimizeCb(iteratee, context); - var i, length; - if (isArrayLike(obj)) { - for (i = 0, length = obj.length; i < length; i++) { - iteratee(obj[i], i, obj); - } - } else { - var _keys = keys(obj); - for (i = 0, length = _keys.length; i < length; i++) { - iteratee(obj[_keys[i]], _keys[i], obj); - } - } - return obj; - } - - // Return the results of applying the iteratee to each element. - function map(obj, iteratee, context) { - iteratee = cb(iteratee, context); - var _keys = !isArrayLike(obj) && keys(obj), - length = (_keys || obj).length, - results = Array(length); - for (var index = 0; index < length; index++) { - var currentKey = _keys ? _keys[index] : index; - results[index] = iteratee(obj[currentKey], currentKey, obj); - } - return results; - } - - // Internal helper to create a reducing function, iterating left or right. - function createReduce(dir) { - // Wrap code that reassigns argument variables in a separate function than - // the one that accesses `arguments.length` to avoid a perf hit. (#1991) - var reducer = function(obj, iteratee, memo, initial) { - var _keys = !isArrayLike(obj) && keys(obj), - length = (_keys || obj).length, - index = dir > 0 ? 0 : length - 1; - if (!initial) { - memo = obj[_keys ? _keys[index] : index]; - index += dir; - } - for (; index >= 0 && index < length; index += dir) { - var currentKey = _keys ? _keys[index] : index; - memo = iteratee(memo, obj[currentKey], currentKey, obj); - } - return memo; - }; - - return function(obj, iteratee, memo, context) { - var initial = arguments.length >= 3; - return reducer(obj, optimizeCb(iteratee, context, 4), memo, initial); - }; - } - - // **Reduce** builds up a single result from a list of values, aka `inject`, - // or `foldl`. - var reduce = createReduce(1); - - // The right-associative version of reduce, also known as `foldr`. - var reduceRight = createReduce(-1); - - // Return all the elements that pass a truth test. - function filter(obj, predicate, context) { - var results = []; - predicate = cb(predicate, context); - each(obj, function(value, index, list) { - if (predicate(value, index, list)) results.push(value); - }); - return results; - } - - // Return all the elements for which a truth test fails. - function reject(obj, predicate, context) { - return filter(obj, negate(cb(predicate)), context); - } - - // Determine whether all of the elements pass a truth test. - function every(obj, predicate, context) { - predicate = cb(predicate, context); - var _keys = !isArrayLike(obj) && keys(obj), - length = (_keys || obj).length; - for (var index = 0; index < length; index++) { - var currentKey = _keys ? _keys[index] : index; - if (!predicate(obj[currentKey], currentKey, obj)) return false; - } - return true; - } - - // Determine if at least one element in the object passes a truth test. - function some(obj, predicate, context) { - predicate = cb(predicate, context); - var _keys = !isArrayLike(obj) && keys(obj), - length = (_keys || obj).length; - for (var index = 0; index < length; index++) { - var currentKey = _keys ? _keys[index] : index; - if (predicate(obj[currentKey], currentKey, obj)) return true; - } - return false; - } - - // Determine if the array or object contains a given item (using `===`). - function contains(obj, item, fromIndex, guard) { - if (!isArrayLike(obj)) obj = values(obj); - if (typeof fromIndex != 'number' || guard) fromIndex = 0; - return indexOf(obj, item, fromIndex) >= 0; - } - - // Invoke a method (with arguments) on every item in a collection. - var invoke = restArguments(function(obj, path, args) { - var contextPath, func; - if (isFunction$1(path)) { - func = path; - } else { - path = toPath$1(path); - contextPath = path.slice(0, -1); - path = path[path.length - 1]; - } - return map(obj, function(context) { - var method = func; - if (!method) { - if (contextPath && contextPath.length) { - context = deepGet(context, contextPath); - } - if (context == null) return void 0; - method = context[path]; - } - return method == null ? method : method.apply(context, args); - }); - }); - - // Convenience version of a common use case of `_.map`: fetching a property. - function pluck(obj, key) { - return map(obj, property(key)); - } - - // Convenience version of a common use case of `_.filter`: selecting only - // objects containing specific `key:value` pairs. - function where(obj, attrs) { - return filter(obj, matcher(attrs)); - } - - // Return the maximum element (or element-based computation). - function max(obj, iteratee, context) { - var result = -Infinity, lastComputed = -Infinity, - value, computed; - if (iteratee == null || typeof iteratee == 'number' && typeof obj[0] != 'object' && obj != null) { - obj = isArrayLike(obj) ? obj : values(obj); - for (var i = 0, length = obj.length; i < length; i++) { - value = obj[i]; - if (value != null && value > result) { - result = value; - } - } - } else { - iteratee = cb(iteratee, context); - each(obj, function(v, index, list) { - computed = iteratee(v, index, list); - if (computed > lastComputed || computed === -Infinity && result === -Infinity) { - result = v; - lastComputed = computed; - } - }); - } - return result; - } - - // Return the minimum element (or element-based computation). - function min(obj, iteratee, context) { - var result = Infinity, lastComputed = Infinity, - value, computed; - if (iteratee == null || typeof iteratee == 'number' && typeof obj[0] != 'object' && obj != null) { - obj = isArrayLike(obj) ? obj : values(obj); - for (var i = 0, length = obj.length; i < length; i++) { - value = obj[i]; - if (value != null && value < result) { - result = value; - } - } - } else { - iteratee = cb(iteratee, context); - each(obj, function(v, index, list) { - computed = iteratee(v, index, list); - if (computed < lastComputed || computed === Infinity && result === Infinity) { - result = v; - lastComputed = computed; - } - }); - } - return result; - } - - // Sample **n** random values from a collection using the modern version of the - // [Fisher-Yates shuffle](https://en.wikipedia.org/wiki/Fisher–Yates_shuffle). - // If **n** is not specified, returns a single random element. - // The internal `guard` argument allows it to work with `_.map`. - function sample(obj, n, guard) { - if (n == null || guard) { - if (!isArrayLike(obj)) obj = values(obj); - return obj[random(obj.length - 1)]; - } - var sample = isArrayLike(obj) ? clone(obj) : values(obj); - var length = getLength(sample); - n = Math.max(Math.min(n, length), 0); - var last = length - 1; - for (var index = 0; index < n; index++) { - var rand = random(index, last); - var temp = sample[index]; - sample[index] = sample[rand]; - sample[rand] = temp; - } - return sample.slice(0, n); - } - - // Shuffle a collection. - function shuffle(obj) { - return sample(obj, Infinity); - } - - // Sort the object's values by a criterion produced by an iteratee. - function sortBy(obj, iteratee, context) { - var index = 0; - iteratee = cb(iteratee, context); - return pluck(map(obj, function(value, key, list) { - return { - value: value, - index: index++, - criteria: iteratee(value, key, list) - }; - }).sort(function(left, right) { - var a = left.criteria; - var b = right.criteria; - if (a !== b) { - if (a > b || a === void 0) return 1; - if (a < b || b === void 0) return -1; - } - return left.index - right.index; - }), 'value'); - } - - // An internal function used for aggregate "group by" operations. - function group(behavior, partition) { - return function(obj, iteratee, context) { - var result = partition ? [[], []] : {}; - iteratee = cb(iteratee, context); - each(obj, function(value, index) { - var key = iteratee(value, index, obj); - behavior(result, value, key); - }); - return result; - }; - } - - // Groups the object's values by a criterion. Pass either a string attribute - // to group by, or a function that returns the criterion. - var groupBy = group(function(result, value, key) { - if (has(result, key)) result[key].push(value); else result[key] = [value]; - }); - - // Indexes the object's values by a criterion, similar to `_.groupBy`, but for - // when you know that your index values will be unique. - var indexBy = group(function(result, value, key) { - result[key] = value; - }); - - // Counts instances of an object that group by a certain criterion. Pass - // either a string attribute to count by, or a function that returns the - // criterion. - var countBy = group(function(result, value, key) { - if (has(result, key)) result[key]++; else result[key] = 1; - }); - - // Split a collection into two arrays: one whose elements all pass the given - // truth test, and one whose elements all do not pass the truth test. - var partition = group(function(result, value, pass) { - result[pass ? 0 : 1].push(value); - }, true); - - // Safely create a real, live array from anything iterable. - var reStrSymbol = /[^\ud800-\udfff]|[\ud800-\udbff][\udc00-\udfff]|[\ud800-\udfff]/g; - function toArray(obj) { - if (!obj) return []; - if (isArray(obj)) return slice.call(obj); - if (isString(obj)) { - // Keep surrogate pair characters together. - return obj.match(reStrSymbol); - } - if (isArrayLike(obj)) return map(obj, identity); - return values(obj); - } - - // Return the number of elements in a collection. - function size(obj) { - if (obj == null) return 0; - return isArrayLike(obj) ? obj.length : keys(obj).length; - } - - // Internal `_.pick` helper function to determine whether `key` is an enumerable - // property name of `obj`. - function keyInObj(value, key, obj) { - return key in obj; - } - - // Return a copy of the object only containing the allowed properties. - var pick = restArguments(function(obj, keys) { - var result = {}, iteratee = keys[0]; - if (obj == null) return result; - if (isFunction$1(iteratee)) { - if (keys.length > 1) iteratee = optimizeCb(iteratee, keys[1]); - keys = allKeys(obj); - } else { - iteratee = keyInObj; - keys = flatten(keys, false, false); - obj = Object(obj); - } - for (var i = 0, length = keys.length; i < length; i++) { - var key = keys[i]; - var value = obj[key]; - if (iteratee(value, key, obj)) result[key] = value; - } - return result; - }); - - // Return a copy of the object without the disallowed properties. - var omit = restArguments(function(obj, keys) { - var iteratee = keys[0], context; - if (isFunction$1(iteratee)) { - iteratee = negate(iteratee); - if (keys.length > 1) context = keys[1]; - } else { - keys = map(flatten(keys, false, false), String); - iteratee = function(value, key) { - return !contains(keys, key); - }; - } - return pick(obj, iteratee, context); - }); - - // Returns everything but the last entry of the array. Especially useful on - // the arguments object. Passing **n** will return all the values in - // the array, excluding the last N. - function initial(array, n, guard) { - return slice.call(array, 0, Math.max(0, array.length - (n == null || guard ? 1 : n))); - } - - // Get the first element of an array. Passing **n** will return the first N - // values in the array. The **guard** check allows it to work with `_.map`. - function first(array, n, guard) { - if (array == null || array.length < 1) return n == null || guard ? void 0 : []; - if (n == null || guard) return array[0]; - return initial(array, array.length - n); - } - - // Returns everything but the first entry of the `array`. Especially useful on - // the `arguments` object. Passing an **n** will return the rest N values in the - // `array`. - function rest(array, n, guard) { - return slice.call(array, n == null || guard ? 1 : n); - } - - // Get the last element of an array. Passing **n** will return the last N - // values in the array. - function last(array, n, guard) { - if (array == null || array.length < 1) return n == null || guard ? void 0 : []; - if (n == null || guard) return array[array.length - 1]; - return rest(array, Math.max(0, array.length - n)); - } - - // Trim out all falsy values from an array. - function compact(array) { - return filter(array, Boolean); - } - - // Flatten out an array, either recursively (by default), or up to `depth`. - // Passing `true` or `false` as `depth` means `1` or `Infinity`, respectively. - function flatten$1(array, depth) { - return flatten(array, depth, false); - } - - // Take the difference between one array and a number of other arrays. - // Only the elements present in just the first array will remain. - var difference = restArguments(function(array, rest) { - rest = flatten(rest, true, true); - return filter(array, function(value){ - return !contains(rest, value); - }); - }); - - // Return a version of the array that does not contain the specified value(s). - var without = restArguments(function(array, otherArrays) { - return difference(array, otherArrays); - }); - - // Produce a duplicate-free version of the array. If the array has already - // been sorted, you have the option of using a faster algorithm. - // The faster algorithm will not work with an iteratee if the iteratee - // is not a one-to-one function, so providing an iteratee will disable - // the faster algorithm. - function uniq(array, isSorted, iteratee, context) { - if (!isBoolean(isSorted)) { - context = iteratee; - iteratee = isSorted; - isSorted = false; - } - if (iteratee != null) iteratee = cb(iteratee, context); - var result = []; - var seen = []; - for (var i = 0, length = getLength(array); i < length; i++) { - var value = array[i], - computed = iteratee ? iteratee(value, i, array) : value; - if (isSorted && !iteratee) { - if (!i || seen !== computed) result.push(value); - seen = computed; - } else if (iteratee) { - if (!contains(seen, computed)) { - seen.push(computed); - result.push(value); - } - } else if (!contains(result, value)) { - result.push(value); - } - } - return result; - } - - // Produce an array that contains the union: each distinct element from all of - // the passed-in arrays. - var union = restArguments(function(arrays) { - return uniq(flatten(arrays, true, true)); - }); - - // Produce an array that contains every item shared between all the - // passed-in arrays. - function intersection(array) { - var result = []; - var argsLength = arguments.length; - for (var i = 0, length = getLength(array); i < length; i++) { - var item = array[i]; - if (contains(result, item)) continue; - var j; - for (j = 1; j < argsLength; j++) { - if (!contains(arguments[j], item)) break; - } - if (j === argsLength) result.push(item); - } - return result; - } - - // Complement of zip. Unzip accepts an array of arrays and groups - // each array's elements on shared indices. - function unzip(array) { - var length = array && max(array, getLength).length || 0; - var result = Array(length); - - for (var index = 0; index < length; index++) { - result[index] = pluck(array, index); - } - return result; - } - - // Zip together multiple lists into a single array -- elements that share - // an index go together. - var zip = restArguments(unzip); - - // Converts lists into objects. Pass either a single array of `[key, value]` - // pairs, or two parallel arrays of the same length -- one of keys, and one of - // the corresponding values. Passing by pairs is the reverse of `_.pairs`. - function object(list, values) { - var result = {}; - for (var i = 0, length = getLength(list); i < length; i++) { - if (values) { - result[list[i]] = values[i]; - } else { - result[list[i][0]] = list[i][1]; - } - } - return result; - } - - // Generate an integer Array containing an arithmetic progression. A port of - // the native Python `range()` function. See - // [the Python documentation](https://docs.python.org/library/functions.html#range). - function range(start, stop, step) { - if (stop == null) { - stop = start || 0; - start = 0; - } - if (!step) { - step = stop < start ? -1 : 1; - } - - var length = Math.max(Math.ceil((stop - start) / step), 0); - var range = Array(length); - - for (var idx = 0; idx < length; idx++, start += step) { - range[idx] = start; - } - - return range; - } - - // Chunk a single array into multiple arrays, each containing `count` or fewer - // items. - function chunk(array, count) { - if (count == null || count < 1) return []; - var result = []; - var i = 0, length = array.length; - while (i < length) { - result.push(slice.call(array, i, i += count)); - } - return result; - } - - // Helper function to continue chaining intermediate results. - function chainResult(instance, obj) { - return instance._chain ? _(obj).chain() : obj; - } - - // Add your own custom functions to the Underscore object. - function mixin(obj) { - each(functions(obj), function(name) { - var func = _[name] = obj[name]; - _.prototype[name] = function() { - var args = [this._wrapped]; - push.apply(args, arguments); - return chainResult(this, func.apply(_, args)); - }; - }); - return _; - } - - // Add all mutator `Array` functions to the wrapper. - each(['pop', 'push', 'reverse', 'shift', 'sort', 'splice', 'unshift'], function(name) { - var method = ArrayProto[name]; - _.prototype[name] = function() { - var obj = this._wrapped; - if (obj != null) { - method.apply(obj, arguments); - if ((name === 'shift' || name === 'splice') && obj.length === 0) { - delete obj[0]; - } - } - return chainResult(this, obj); - }; - }); - - // Add all accessor `Array` functions to the wrapper. - each(['concat', 'join', 'slice'], function(name) { - var method = ArrayProto[name]; - _.prototype[name] = function() { - var obj = this._wrapped; - if (obj != null) obj = method.apply(obj, arguments); - return chainResult(this, obj); - }; - }); - - // Named Exports - - var allExports = { - __proto__: null, - VERSION: VERSION, - restArguments: restArguments, - isObject: isObject, - isNull: isNull, - isUndefined: isUndefined, - isBoolean: isBoolean, - isElement: isElement, - isString: isString, - isNumber: isNumber, - isDate: isDate, - isRegExp: isRegExp, - isError: isError, - isSymbol: isSymbol, - isArrayBuffer: isArrayBuffer, - isDataView: isDataView$1, - isArray: isArray, - isFunction: isFunction$1, - isArguments: isArguments$1, - isFinite: isFinite$1, - isNaN: isNaN$1, - isTypedArray: isTypedArray$1, - isEmpty: isEmpty, - isMatch: isMatch, - isEqual: isEqual, - isMap: isMap, - isWeakMap: isWeakMap, - isSet: isSet, - isWeakSet: isWeakSet, - keys: keys, - allKeys: allKeys, - values: values, - pairs: pairs, - invert: invert, - functions: functions, - methods: functions, - extend: extend, - extendOwn: extendOwn, - assign: extendOwn, - defaults: defaults, - create: create, - clone: clone, - tap: tap, - get: get, - has: has$1, - mapObject: mapObject, - identity: identity, - constant: constant, - noop: noop, - toPath: toPath, - property: property, - propertyOf: propertyOf, - matcher: matcher, - matches: matcher, - times: times, - random: random, - now: now, - escape: _escape, - unescape: _unescape, - templateSettings: templateSettings, - template: template, - result: result, - uniqueId: uniqueId, - chain: chain, - iteratee: iteratee, - partial: partial, - bind: bind, - bindAll: bindAll, - memoize: memoize, - delay: delay, - defer: defer, - throttle: throttle, - debounce: debounce, - wrap: wrap, - negate: negate, - compose: compose, - after: after, - before: before, - once: once, - findKey: findKey, - findIndex: findIndex, - findLastIndex: findLastIndex, - sortedIndex: sortedIndex, - indexOf: indexOf, - lastIndexOf: lastIndexOf, - find: find, - detect: find, - findWhere: findWhere, - each: each, - forEach: each, - map: map, - collect: map, - reduce: reduce, - foldl: reduce, - inject: reduce, - reduceRight: reduceRight, - foldr: reduceRight, - filter: filter, - select: filter, - reject: reject, - every: every, - all: every, - some: some, - any: some, - contains: contains, - includes: contains, - include: contains, - invoke: invoke, - pluck: pluck, - where: where, - max: max, - min: min, - shuffle: shuffle, - sample: sample, - sortBy: sortBy, - groupBy: groupBy, - indexBy: indexBy, - countBy: countBy, - partition: partition, - toArray: toArray, - size: size, - pick: pick, - omit: omit, - first: first, - head: first, - take: first, - initial: initial, - last: last, - rest: rest, - tail: rest, - drop: rest, - compact: compact, - flatten: flatten$1, - without: without, - uniq: uniq, - unique: uniq, - union: union, - intersection: intersection, - difference: difference, - unzip: unzip, - transpose: unzip, - zip: zip, - object: object, - range: range, - chunk: chunk, - mixin: mixin, - 'default': _ - }; - - // Default Export - - // Add all of the Underscore functions to the wrapper object. - var _$1 = mixin(allExports); - // Legacy Node.js API. - _$1._ = _$1; - - return _$1; - -}))); -//# sourceMappingURL=underscore.js.map diff --git a/docs/getting_started.html b/docs/getting_started.html index 0213e92..81edec8 100755 --- a/docs/getting_started.html +++ b/docs/getting_started.html @@ -792,9 +792,9 @@

    Inserting Unicode (e.g., Greek Letters)
    -
    import numpy as np
+
    import numpy as np
 import matplotlib.pyplot as plt
-%matplotlib inline
+%matplotlib inline
 
 # Fixing random state for reproducibility
 np.random.seed(19680801)
@@ -813,6 +813,9 @@ 
    Inserting Unicode (e.g., Greek Letters)
+../_images/getting_started_1_0.png
+
    
 
    
 
    Don’t worry about the details for now — let’s just run it and see
 what happens.
    
diff --git a/docs/learn_more.html b/docs/learn_more.html
index 3907883..cd32c87 100755
--- a/docs/learn_more.html
+++ b/docs/learn_more.html
@@ -488,7 +488,7 @@ 
    NumPy
 
    For example, let’s build some arrays
    
 
    
 
    
-
    import numpy as np                     # Load the library
+
    import numpy as np                     # Load the library
 
 a = np.linspace(-np.pi, np.pi, 100)    # Create even grid from -π to π
 b = np.cos(a)                          # Apply cosine to each element of a
@@ -500,7 +500,12 @@ 
    NumPy
 
    Now let’s take the inner product
    
 
    
 
    
-
    b @ c
+
    b @ c
+
    
+
    
+
    
+
    
+
    1.0408340855860843e-16
 
    
 
    
 
    
@@ -519,7 +524,7 @@ 
    SciPy
 the standard normal density.
    
 
    
 
    
-
    from scipy.stats import norm
+
    from scipy.stats import norm
 from scipy.integrate import quad
 
 ϕ = norm()
@@ -528,6 +533,11 @@ 
    SciPy
 
    
 
    
 
    
+
    
+
    0.9544997361036417
+
    
+
    
+
    
 
    
 
    SciPy includes many of the standard routines used in