From 00bcd4c3c7012006e8160bafa6deacbef90da90a Mon Sep 17 00:00:00 2001
From: Joseph Weston <joseph.weston08@gmail.com>
Date: Wed, 23 Aug 2017 07:55:52 +0000
Subject: [PATCH] remove superfluous notebooks
---
Learner-timing.ipynb | 80 -----------
Learner-widgets.ipynb | 132 ------------------
...er-parallel-plotter.ipynb => learner.ipynb | 10 +-
3 files changed, 8 insertions(+), 214 deletions(-)
delete mode 100644 Learner-timing.ipynb
delete mode 100644 Learner-widgets.ipynb
rename Learner-parallel-plotter.ipynb => learner.ipynb (95%)
diff --git a/Learner-timing.ipynb b/Learner-timing.ipynb
deleted file mode 100644
index 85bbf2dd..00000000
--- a/Learner-timing.ipynb
+++ /dev/null
@@ -1,80 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Timing"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import holoviews as hv\n",
- "hv.notebook_extension()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import learner\n",
- "from time import time"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "times = []\n",
- "xs = np.random.random((1000, 1000))\n",
- "ys = np.random.random((1000, 1000))\n",
- "for (i, (x, y)) in enumerate(zip(xs, ys)):\n",
- " learner = learner.Learner1D(x[:i+2], y[:i+2])\n",
- " start = time()\n",
- " learner.choose_points(n=1)\n",
- " stop = time()\n",
- " times.append(stop-start)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "hv.Curve(times)"
- ]
- }
- ],
- "metadata": {
- "anaconda-cloud": {},
- "kernelspec": {
- "display_name": "Python [conda env:py36]",
- "language": "python",
- "name": "conda-env-py36-py"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.6.0"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 1
-}
diff --git a/Learner-widgets.ipynb b/Learner-widgets.ipynb
deleted file mode 100644
index dc2e5ee1..00000000
--- a/Learner-widgets.ipynb
+++ /dev/null
@@ -1,132 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Adaptive"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import holoviews as hv\n",
- "hv.notebook_extension()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import learner\n",
- "import importlib\n",
- "importlib.reload(learner)\n",
- "\n",
- "def func(x):\n",
- " \"\"\"Function with a sharp peak on a smooth background\"\"\"\n",
- " x = np.asarray(x)\n",
- " a = 0.01\n",
- " return x + a**2/(a**2 + x**2)\n",
- "\n",
- "def plot(learner, nan_is_zero=False, interpolation=False):\n",
- " if interpolation:\n",
- " learner.interpolate()\n",
- " d = learner.interp_data\n",
- " else:\n",
- " d = learner.data\n",
- "\n",
- " xy = [(k, d[k]) for k in sorted(d)]\n",
- " x, y = np.array(xy, dtype=float).T\n",
- "\n",
- " if nan_is_zero:\n",
- " y = np.nan_to_num(y)\n",
- " return hv.Scatter((x, y))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# With direct results"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "hm = {}\n",
- "xs = np.linspace(-1, 1, 5)\n",
- "ys = func(xs)\n",
- "learner = learner.Learner1D(xs, ys)\n",
- "hm[0] = plot(learner)\n",
- "\n",
- "for i in range(1, 30):\n",
- " xs = learner.choose_points(n=1, add_to_data=True)\n",
- " ys = func(xs)\n",
- " learner.add_data(xs, ys)\n",
- " hm[i] = plot(learner, nan_is_zero=True)\n",
- " \n",
- "hv.HoloMap(hm)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# With `concurrent.futures`\n",
- "\n",
- "It's plotting the points without a result at zero"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "hm = {}\n",
- "xs = np.linspace(-1, 1, 5)\n",
- "ys = func(xs)\n",
- "learner = learner.Learner1D(xs, ys)\n",
- "hm[0] = plot(learner)\n",
- "\n",
- "for i in range(1, 20):\n",
- " xs = learner.choose_points(n=1)\n",
- " # Do not calculate ys here (as if it's a `concurrent.futures`)\n",
- " hm[i] = plot(learner, interpolation=True)\n",
- " \n",
- "hv.HoloMap(hm)"
- ]
- }
- ],
- "metadata": {
- "anaconda-cloud": {},
- "kernelspec": {
- "display_name": "Python [conda env:py36]",
- "language": "python",
- "name": "conda-env-py36-py"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.6.0"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 1
-}
diff --git a/Learner-parallel-plotter.ipynb b/learner.ipynb
similarity index 95%
rename from Learner-parallel-plotter.ipynb
rename to learner.ipynb
index 10693ad4..cec53176 100644
--- a/Learner-parallel-plotter.ipynb
+++ b/learner.ipynb
@@ -10,7 +10,9 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
"outputs": [],
"source": [
"import adaptive\n",
@@ -42,6 +44,7 @@
"cell_type": "code",
"execution_count": null,
"metadata": {
+ "collapsed": true,
"scrolled": false
},
"outputs": [],
@@ -54,7 +57,9 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
"outputs": [],
"source": [
"# Same function evaluated on homogeneous grid with same amount of points\n",
@@ -105,6 +110,7 @@
"cell_type": "code",
"execution_count": null,
"metadata": {
+ "collapsed": true,
"scrolled": false
},
"outputs": [],
--
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