Merge pull request #125 from ContextLab/args-refactor

BIG refactor: merging

docs/_build/html/.buildinfo

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+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 27f69a987af6cebd72c9ce04198515dc
+tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/_build/html/_downloads/animate.ipynb

@@ -0,0 +1,54 @@
+{
+  "nbformat_minor": 0, 
+  "nbformat": 4, 
+  "cells": [
+    {
+      "execution_count": null, 
+      "cell_type": "code", 
+      "source": [
+        "%matplotlib inline"
+      ], 
+      "outputs": [], 
+      "metadata": {
+        "collapsed": false
+      }
+    }, 
+    {
+      "source": [
+        "\n# Hyperalign a list of arrays and create an animated plot\n\n\nThe sample data is a list of 2D arrays, where each array is fMRI brain activity\nfrom one subject.  The rows are timepoints and the columns are neural\n'features'.  First, the matrices are hyperaligned using hyp.tools.align.\n\n"
+      ], 
+      "cell_type": "markdown", 
+      "metadata": {}
+    }, 
+    {
+      "execution_count": null, 
+      "cell_type": "code", 
+      "source": [
+        "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata = hyp.tools.load('weights')\naligned_w = hyp.tools.align(data)\n\nw1 = np.mean(aligned_w[:17],0)\nw2 = np.mean(aligned_w[18:],0)\n\nhyp.plot([w1, w2], animate=True)"
+      ], 
+      "outputs": [], 
+      "metadata": {
+        "collapsed": false
+      }
+    }
+  ], 
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 2", 
+      "name": "python2", 
+      "language": "python"
+    }, 
+    "language_info": {
+      "mimetype": "text/x-python", 
+      "nbconvert_exporter": "python", 
+      "name": "python", 
+      "file_extension": ".py", 
+      "version": "2.7.11", 
+      "pygments_lexer": "ipython2", 
+      "codemirror_mode": {
+        "version": 2, 
+        "name": "ipython"
+      }
+    }
+  }
+}

docs/_build/html/_downloads/animate.py

@@ -0,0 +1,25 @@
+# -*- coding: utf-8 -*-
+"""
+=============================
+Hyperalign a list of arrays and create an animated plot
+=============================
+
+The sample data is a list of 2D arrays, where each array is fMRI brain activity
+from one subject.  The rows are timepoints and the columns are neural
+'features'.  First, the matrices are hyperaligned using hyp.tools.align.
+"""
+
+# Code source: Andrew Heusser
+# License: MIT
+
+import hypertools as hyp
+import scipy.io as sio
+import numpy as np
+
+data = hyp.tools.load('weights')
+aligned_w = hyp.tools.align(data)
+
+w1 = np.mean(aligned_w[:17],0)
+w2 = np.mean(aligned_w[18:],0)
+
+hyp.plot([w1, w2], animate=True)

docs/_build/html/_downloads/animate1.ipynb

@@ -0,0 +1,54 @@
+{
+  "nbformat_minor": 0, 
+  "nbformat": 4, 
+  "cells": [
+    {
+      "execution_count": null, 
+      "cell_type": "code", 
+      "source": [
+        "%matplotlib inline"
+      ], 
+      "outputs": [], 
+      "metadata": {
+        "collapsed": false
+      }
+    }, 
+    {
+      "source": [
+        "\n# Hyperalign a list of arrays and create an animated plot\n\n\nThe sample data is a list of 2D arrays, where each array is fMRI brain activity\nfrom one subject.  The rows are timepoints and the columns are neural\n'features'.  First, the matrices are hyperaligned using hyp.tools.align.\n\n"
+      ], 
+      "cell_type": "markdown", 
+      "metadata": {}
+    }, 
+    {
+      "execution_count": null, 
+      "cell_type": "code", 
+      "source": [
+        "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata = hyp.tools.load('weights')\naligned_w = hyp.tools.align(data)\n\nw1 = np.mean(aligned_w[:17],0)\nw2 = np.mean(aligned_w[18:],0)\n\nhyp.plot([w1,w2], animate=True)"
+      ], 
+      "outputs": [], 
+      "metadata": {
+        "collapsed": false
+      }
+    }
+  ], 
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 2", 
+      "name": "python2", 
+      "language": "python"
+    }, 
+    "language_info": {
+      "mimetype": "text/x-python", 
+      "nbconvert_exporter": "python", 
+      "name": "python", 
+      "file_extension": ".py", 
+      "version": "2.7.11", 
+      "pygments_lexer": "ipython2", 
+      "codemirror_mode": {
+        "version": 2, 
+        "name": "ipython"
+      }
+    }
+  }
+}

docs/_build/html/_downloads/animate1.py

@@ -0,0 +1,25 @@
+# -*- coding: utf-8 -*-
+"""
+=============================
+Hyperalign a list of arrays and create an animated plot
+=============================
+
+The sample data is a list of 2D arrays, where each array is fMRI brain activity
+from one subject.  The rows are timepoints and the columns are neural
+'features'.  First, the matrices are hyperaligned using hyp.tools.align.
+"""
+
+# Code source: Andrew Heusser
+# License: MIT
+
+import hypertools as hyp
+import scipy.io as sio
+import numpy as np
+
+data = hyp.tools.load('weights')
+aligned_w = hyp.tools.align(data)
+
+w1 = np.mean(aligned_w[:17],0)
+w2 = np.mean(aligned_w[18:],0)
+
+hyp.plot([w1,w2], animate=True)

docs/_build/html/_downloads/animate_spin.ipynb

@@ -0,0 +1,54 @@
+{
+  "nbformat_minor": 0, 
+  "nbformat": 4, 
+  "cells": [
+    {
+      "execution_count": null, 
+      "cell_type": "code", 
+      "source": [
+        "%matplotlib inline"
+      ], 
+      "outputs": [], 
+      "metadata": {
+        "collapsed": false
+      }
+    }, 
+    {
+      "source": [
+        "\n# Create a rotating static plot\n\n\nIn addition to plotting dynamic timeseries data, the spin feature can be used to\nvisualize static data in an animated rotating plot.\n\n"
+      ], 
+      "cell_type": "markdown", 
+      "metadata": {}
+    }, 
+    {
+      "execution_count": null, 
+      "cell_type": "code", 
+      "source": [
+        "# Code source: Andrew Heusser\n# License: MIT\n\n# load\nimport hypertools as hyp\n\n# load data\ndata = hyp.tools.load('weights_sample')\n\n# plot\nhyp.plot(data, '.', animate='spin')"
+      ], 
+      "outputs": [], 
+      "metadata": {
+        "collapsed": false
+      }
+    }
+  ], 
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 2", 
+      "name": "python2", 
+      "language": "python"
+    }, 
+    "language_info": {
+      "mimetype": "text/x-python", 
+      "nbconvert_exporter": "python", 
+      "name": "python", 
+      "file_extension": ".py", 
+      "version": "2.7.11", 
+      "pygments_lexer": "ipython2", 
+      "codemirror_mode": {
+        "version": 2, 
+        "name": "ipython"
+      }
+    }
+  }
+}

docs/_build/html/_downloads/animate_spin.py

@@ -0,0 +1,21 @@
+# -*- coding: utf-8 -*-
+"""
+=============================
+Create a rotating static plot
+=============================
+
+In addition to plotting dynamic timeseries data, the spin feature can be used to
+visualize static data in an animated rotating plot.
+"""
+
+# Code source: Andrew Heusser
+# License: MIT
+
+# load
+import hypertools as hyp
+
+# load data
+data = hyp.tools.load('weights_sample')
+
+# plot
+hyp.plot(data, '.', animate='spin')

docs/_build/html/_downloads/animate_spin1.ipynb

@@ -0,0 +1,54 @@
+{
+  "nbformat_minor": 0, 
+  "nbformat": 4, 
+  "cells": [
+    {
+      "execution_count": null, 
+      "cell_type": "code", 
+      "source": [
+        "%matplotlib inline"
+      ], 
+      "outputs": [], 
+      "metadata": {
+        "collapsed": false
+      }
+    }, 
+    {
+      "source": [
+        "\n# Create a rotating static plot\n\n\nIn addition to plotting dynamic timeseries data, the spin feature can be used to\nvisualize static data in an animated rotating plot.\n\n"
+      ], 
+      "cell_type": "markdown", 
+      "metadata": {}
+    }, 
+    {
+      "execution_count": null, 
+      "cell_type": "code", 
+      "source": [
+        "# Code source: Andrew Heusser\n# License: MIT\n\n# load\nimport hypertools as hyp\n\n# load data\ndata = hyp.tools.load('weights_sample')\n\n# plot\nhyp.plot(data, '.', animate='spin')"
+      ], 
+      "outputs": [], 
+      "metadata": {
+        "collapsed": false
+      }
+    }
+  ], 
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 2", 
+      "name": "python2", 
+      "language": "python"
+    }, 
+    "language_info": {
+      "mimetype": "text/x-python", 
+      "nbconvert_exporter": "python", 
+      "name": "python", 
+      "file_extension": ".py", 
+      "version": "2.7.11", 
+      "pygments_lexer": "ipython2", 
+      "codemirror_mode": {
+        "version": 2, 
+        "name": "ipython"
+      }
+    }
+  }
+}

docs/_build/html/_downloads/animate_spin1.py

@@ -0,0 +1,21 @@
+# -*- coding: utf-8 -*-
+"""
+=============================
+Create a rotating static plot
+=============================
+
+In addition to plotting dynamic timeseries data, the spin feature can be used to
+visualize static data in an animated rotating plot.
+"""
+
+# Code source: Andrew Heusser
+# License: MIT
+
+# load
+import hypertools as hyp
+
+# load data
+data = hyp.tools.load('weights_sample')
+
+# plot
+hyp.plot(data, '.', animate='spin')

docs/_build/html/_downloads/explore.ipynb

@@ -0,0 +1,54 @@
+{
+  "nbformat_minor": 0, 
+  "nbformat": 4, 
+  "cells": [
+    {
+      "execution_count": null, 
+      "cell_type": "code", 
+      "source": [
+        "%matplotlib inline"
+      ], 
+      "outputs": [], 
+      "metadata": {
+        "collapsed": false
+      }
+    }, 
+    {
+      "source": [
+        "\n=============================\nExplore mode!\n=============================\n\nExplore mode is an experimental feature that allows you to (not surprisingly)\nexplore the points in your dataset.  When you hover over the points, a label\nwill pop up that will help you identify the datapoint.  You can customize the\nlabels by passing a list of labels to the `label(s)` kwarg. Alternatively, if\nyou don't pass a list of labels, the labels will be the index of the datapoint,\nalong with the PCA coordinate.\n\n"
+      ], 
+      "cell_type": "markdown", 
+      "metadata": {}
+    }, 
+    {
+      "execution_count": null, 
+      "cell_type": "code", 
+      "source": [
+        "# Code source: Andrew Heusser\n# License: MIT\n\nimport hypertools as hyp\nimport scipy.io as sio\nimport numpy as np\n\ndata = hyp.tools.load('weights_sample')\n\nhyp.plot(data, '.', explore=True)"
+      ], 
+      "outputs": [], 
+      "metadata": {
+        "collapsed": false
+      }
+    }
+  ], 
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 2", 
+      "name": "python2", 
+      "language": "python"
+    }, 
+    "language_info": {
+      "mimetype": "text/x-python", 
+      "nbconvert_exporter": "python", 
+      "name": "python", 
+      "file_extension": ".py", 
+      "version": "2.7.11", 
+      "pygments_lexer": "ipython2", 
+      "codemirror_mode": {
+        "version": 2, 
+        "name": "ipython"
+      }
+    }
+  }
+}