diff --git a/README.ipynb b/README.ipynb
index cc63344824ee816c9a56311051d13e68e0fdf43c..4ca6affcd6b1cea0c8f5c5d18811aa104a3ffb88 100644
--- a/README.ipynb
+++ b/README.ipynb
@@ -3,13 +3,13 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "1d05699b",
+ "id": "26e42746",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-10-12T13:31:47.500867Z",
- "iopub.status.busy": "2022-10-12T13:31:47.500064Z",
- "iopub.status.idle": "2022-10-12T13:31:47.512502Z",
- "shell.execute_reply": "2022-10-12T13:31:47.511595Z"
+ "iopub.execute_input": "2022-10-12T14:41:38.853343Z",
+ "iopub.status.busy": "2022-10-12T14:41:38.852566Z",
+ "iopub.status.idle": "2022-10-12T14:41:38.864329Z",
+ "shell.execute_reply": "2022-10-12T14:41:38.863589Z"
},
"jupyter": {
"source_hidden": true
@@ -52,7 +52,7 @@
"For more information, you can contact us at : \n",
"[<img width=\"200px\" style=\"vertical-align:middle\" src=\"fidle/img/00-Mail_contact.svg\"></img>](#top)\n",
"\n",
- "Current Version : <!-- VERSION_BEGIN -->2.1b3<!-- VERSION_END -->\n",
+ "Current Version : <!-- VERSION_BEGIN -->2.1b4<!-- VERSION_END -->\n",
"\n",
"\n",
"## Course materials\n",
@@ -67,7 +67,7 @@
"## Jupyter notebooks\n",
"\n",
"<!-- TOC_BEGIN -->\n",
- "<!-- Automatically generated on : 12/10/22 15:31:46 -->\n",
+ "<!-- Automatically generated on : 12/10/22 16:41:37 -->\n",
"\n",
"### Linear and logistic regression\n",
"- **[LINR1](LinearReg/01-Linear-Regression.ipynb)** - [Linear regression with direct resolution](LinearReg/01-Linear-Regression.ipynb) \n",
@@ -229,7 +229,7 @@
"from IPython.display import display,Markdown\n",
"display(Markdown(open('README.md', 'r').read()))\n",
"#\n",
- "# This README is visible under Jupiter Lab ;-)# Automatically generated on : 12/10/22 15:31:46"
+ "# This README is visible under Jupiter Lab ;-)# Automatically generated on : 12/10/22 16:41:37"
]
}
],
diff --git a/README.md b/README.md
index 2bbd6913cdcf9208ca442f67bdc94fc5f14751f9..bb5a0c2f2e5223f23566bbac307a9c446aab3b6f 100644
--- a/README.md
+++ b/README.md
@@ -31,7 +31,7 @@ For more information, see **https://fidle.cnrs.fr** :
For more information, you can contact us at :
[<img width="200px" style="vertical-align:middle" src="fidle/img/00-Mail_contact.svg"></img>](#top)
-Current Version : <!-- VERSION_BEGIN -->2.1b3<!-- VERSION_END -->
+Current Version : <!-- VERSION_BEGIN -->2.1b4<!-- VERSION_END -->
## Course materials
@@ -46,7 +46,7 @@ Have a look about **[How to get and install](https://fidle.cnrs.fr/installation)
## Jupyter notebooks
<!-- TOC_BEGIN -->
-<!-- Automatically generated on : 12/10/22 15:31:46 -->
+<!-- Automatically generated on : 12/10/22 16:41:37 -->
### Linear and logistic regression
- **[LINR1](LinearReg/01-Linear-Regression.ipynb)** - [Linear regression with direct resolution](LinearReg/01-Linear-Regression.ipynb)
diff --git a/VAE/02-VAE-with-MNIST.ipynb b/VAE/02-VAE-with-MNIST.ipynb
index 9242044b2e5ee5b792d4fa604a60c0aaf938a877..813d4082c76093e036efc2032389134ce9d5a257 100644
--- a/VAE/02-VAE-with-MNIST.ipynb
+++ b/VAE/02-VAE-with-MNIST.ipynb
@@ -89,7 +89,7 @@
"metadata": {},
"outputs": [],
"source": [
- "latent_dim = 2\n",
+ "latent_dim = 6\n",
"loss_weights = [1,.001] # [1, .001] give good results\n",
"\n",
"scale = .2\n",
diff --git a/VAE/03-VAE-with-MNIST-post.ipynb b/VAE/03-VAE-with-MNIST-post.ipynb
index 621ce30f33c58f0eb06bfe5bec658cdd47c5704d..cca90efe40889c04ae0bc67ee939d84f54109c24 100644
--- a/VAE/03-VAE-with-MNIST-post.ipynb
+++ b/VAE/03-VAE-with-MNIST-post.ipynb
@@ -55,6 +55,8 @@
"import scipy.stats\n",
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
+ "from barviz import Simplex\n",
+ "from barviz import Collection\n",
"\n",
"import sys\n",
"import fidle\n",
@@ -149,14 +151,18 @@
"\n",
"# ---- Get latent points and reconstructed images\n",
"\n",
- "z_mean, z_var, z = vae.encoder.predict(x_show)\n",
- "x_reconst = vae.decoder.predict(z)\n",
+ "z_mean, z_var, z = vae.encoder.predict(x_show, verbose=0)\n",
+ "x_reconst = vae.decoder.predict(z, verbose=0)\n",
+ "\n",
+ "latent_dim = z.shape[1]\n",
"\n",
"# ---- Show it\n",
"\n",
"labels=[ str(np.round(z[i],1)) for i in range(10) ]\n",
- "fidle.scrawler.images(x_show, labels, indices='all', columns=10, x_size=2,y_size=2, save_as='01-original')\n",
- "fidle.scrawler.images(x_reconst, None , indices='all', columns=10, x_size=2,y_size=2, save_as='02-reconstruct')\n"
+ "fidle.utils.subtitle('Originals :')\n",
+ "fidle.scrawler.images(x_show, None, indices='all', columns=10, x_size=2,y_size=2, save_as='01-original')\n",
+ "fidle.utils.subtitle('Reconstructed :')\n",
+ "fidle.scrawler.images(x_reconst, None, indices='all', columns=10, x_size=2,y_size=2, save_as='02-reconstruct')\n"
]
},
{
@@ -180,10 +186,22 @@
"\n",
"# ---- Get latent points\n",
"\n",
- "z_mean, z_var, z = vae.encoder.predict(x_show)\n",
- "\n",
- "# ---- Show them\n",
- "\n",
+ "z_mean, z_var, z = vae.encoder.predict(x_show, verbose=0)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 5.1 - Classic 2d visualisaton"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
"fig = plt.figure(figsize=(14, 10))\n",
"plt.scatter(z[:, 0] , z[:, 1], c=y_show, cmap= 'tab10', alpha=0.5, s=30)\n",
"plt.colorbar()\n",
@@ -195,7 +213,39 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "## Step 6 - Generate from latent space"
+ "### 5.2 - Simplex visualisaton"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# ---- Softmax rescale\n",
+ "#\n",
+ "zs = np.exp(z)/np.sum(np.exp(z),axis=1,keepdims=True)\n",
+ "# zc = zs * 1/np.max(zs)\n",
+ "\n",
+ "# ---- Create collection\n",
+ "#\n",
+ "c = Collection(zs, colors=y_show, labels=y_show)\n",
+ "c.attrs.markers_colormap = {'colorscale':'Rainbow','cmin':0,'cmax':latent_dim}\n",
+ "c.attrs.markers_size = 4\n",
+ "c.attrs.markers_border_width = 0\n",
+ "c.attrs.markers_opacity = 0.7\n",
+ "\n",
+ "s = Simplex.build(latent_dim)\n",
+ "s.attrs.width = 1000\n",
+ "s.attrs.height = 1000\n",
+ "s.plot(c)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Step 6 - Generate from latent space (latent_dim==2)"
]
},
{
@@ -204,29 +254,35 @@
"metadata": {},
"outputs": [],
"source": [
- "grid_size = 14\n",
- "grid_scale = 1.\n",
+ "if latent_dim>2:\n",
+ "\n",
+ " print('Sorry, This part can only work if the latent space is of dimension 2')\n",
+ "\n",
+ "else:\n",
+ "\n",
+ " grid_size = 14\n",
+ " grid_scale = 1.\n",
"\n",
- "# ---- Draw a ppf grid\n",
+ " # ---- Draw a ppf grid\n",
"\n",
- "grid=[]\n",
- "for y in scipy.stats.norm.ppf(np.linspace(0.99, 0.01, grid_size),scale=grid_scale):\n",
- " for x in scipy.stats.norm.ppf(np.linspace(0.01, 0.99, grid_size),scale=grid_scale):\n",
- " grid.append( (x,y) )\n",
- "grid=np.array(grid)\n",
+ " grid=[]\n",
+ " for y in scipy.stats.norm.ppf(np.linspace(0.99, 0.01, grid_size),scale=grid_scale):\n",
+ " for x in scipy.stats.norm.ppf(np.linspace(0.01, 0.99, grid_size),scale=grid_scale):\n",
+ " grid.append( (x,y) )\n",
+ " grid=np.array(grid)\n",
"\n",
- "# ---- Draw latentspoints and grid\n",
+ " # ---- Draw latentspoints and grid\n",
"\n",
- "fig = plt.figure(figsize=(12, 10))\n",
- "plt.scatter(z[:, 0] , z[:, 1], c=y_show, cmap= 'tab10', alpha=0.5, s=20)\n",
- "plt.scatter(grid[:, 0] , grid[:, 1], c = 'black', s=60, linewidth=2, marker='+', alpha=1)\n",
- "fidle.scrawler.save_fig('04-Latent-grid')\n",
- "plt.show()\n",
+ " fig = plt.figure(figsize=(12, 10))\n",
+ " plt.scatter(z[:, 0] , z[:, 1], c=y_show, cmap= 'tab10', alpha=0.5, s=20)\n",
+ " plt.scatter(grid[:, 0] , grid[:, 1], c = 'black', s=60, linewidth=2, marker='+', alpha=1)\n",
+ " fidle.scrawler.save_fig('04-Latent-grid')\n",
+ " plt.show()\n",
"\n",
- "# ---- Plot grid corresponding images\n",
+ " # ---- Plot grid corresponding images\n",
"\n",
- "x_reconst = vae.decoder.predict([grid])\n",
- "fidle.scrawler.images(x_reconst, indices='all', columns=grid_size, x_size=0.5,y_size=0.5, y_padding=0,spines_alpha=0.1, save_as='05-Latent-morphing')\n",
+ " x_reconst = vae.decoder.predict([grid])\n",
+ " fidle.scrawler.images(x_reconst, indices='all', columns=grid_size, x_size=0.5,y_size=0.5, y_padding=0,spines_alpha=0.1, save_as='05-Latent-morphing')\n",
"\n"
]
},
diff --git a/fidle/about.yml b/fidle/about.yml
index b2e247278985823f0931162a492d6e044448d325..00946f5929ce8cec053c50578474884ae239859c 100644
--- a/fidle/about.yml
+++ b/fidle/about.yml
@@ -13,7 +13,7 @@
#
# This file describes the notebooks used by the Fidle training.
-version: 2.1b3
+version: 2.1b4
content: notebooks
name: Notebooks Fidle
description: All notebooks used by the Fidle training
diff --git a/fidle/ci/default.yml b/fidle/ci/default.yml
index e005b6bb1e96219f45c5028d2e7c1c606a7b9736..2f23ed0d8311f8fab43be46f42806a18e577853f 100644
--- a/fidle/ci/default.yml
+++ b/fidle/ci/default.yml
@@ -1,6 +1,6 @@
campain:
version: '1.0'
- description: Automatically generated ci profile (12/10/22 15:31:46)
+ description: Automatically generated ci profile (12/10/22 16:41:37)
directory: ./campains/default
existing_notebook: 'remove # remove|skip'
report_template: 'fidle # fidle|default'