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37 changes: 11 additions & 26 deletions labs/04_machine-learning/04_PCA-analysis_key.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@
"metadata": {},
"source": [
"## Protein structures\n",
"+ Write a function that loads in the `x`, `y`, and `z` coordinates for all `CA` atoms from a pdb file."
"+ Write a function that loads in the `x`, `y`, and `z` coordinates for all `CA` atoms from a pdb file and returns all the coordinates in an numpy array. (Hint: the shape of this array should be (number-of-`CA`-atoms, 3).)"
]
},
{
Expand Down Expand Up @@ -64,9 +64,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"metadata": {},
"outputs": [],
"source": [
"hm1 = load_pdb(\"homolog-1.pdb\")\n",
Expand All @@ -83,9 +81,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"plt.plot(hm1[:,0],hm1[:,1])\n",
Expand Down Expand Up @@ -120,15 +116,13 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"+ Plot the transformed coordinates on top of one another."
"+ Plot the first 2 transformed coordinates on top of one another."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"plt.plot(t_hm1[:,0],t_hm1[:,1])\n",
Expand All @@ -146,7 +140,6 @@
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
Expand All @@ -166,9 +159,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"import pandas\n",
Expand All @@ -184,7 +175,7 @@
"pca_fit = pca.fit(X)\n",
"Q = pca_fit.transform(X)\n",
"\n",
"a = X.shape[0]/num_data_sets\n",
"a = int(X.shape[0]/num_data_sets)\n",
"for i in range(X.shape[1]):\n",
" plt.plot(X[(i*a):((i+1)*a),3],\n",
" X[(i*a):((i+1)*a),4],\"o\")\n",
Expand All @@ -210,9 +201,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"pca_fit.explained_variance_ratio_"
Expand Down Expand Up @@ -240,9 +229,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"for i in range(Q.shape[1]):\n",
Expand Down Expand Up @@ -310,9 +297,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"f = open(\"pca_dataset.csv\")\n",
Expand Down Expand Up @@ -341,7 +326,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
"version": "3.4.3"
}
},
"nbformat": 4,
Expand Down