{ "cells": [ { "cell_type": "markdown", "id": "4f54c2a2", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "# Advanced features\n", "\n", "This tutorial covers usage of advanced features of ReservoirPy for Reservoir Computing architectures:\n", "\n", "- Input-to-readout connections and other complicated connections\n", "- Feedback connections\n", "- Generation and long term forecasting\n", "- Custom weight matrices\n", "- Parallelization\n", "- \"Deep\" architectures\n", "\n", "To go further, the [examples/](https://github.com/reservoirpy/reservoirpy/tree/master/examples) folder of ReservoirPy GitHub repository contains example of complex use cases from the literature." ] }, { "cell_type": "code", "execution_count": 1, "id": "0d2443fc", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "import reservoirpy as rpy\n", "\n", "rpy.set_seed(42) # make everything reproducible!" ] }, { "cell_type": "markdown", "id": "2fc77e03", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "During this tutorial, we will be using the same task as introduced in the \"Getting started\" tutorial: we create 100 samples of a sine wave, and divide these 100 timesteps between a 50 timesteps training timeseries and 50 timesteps testing timeseries." ] }, { "cell_type": "code", "execution_count": 2, "id": "b560ac9a", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "X = np.sin(np.linspace(0, 6*np.pi, 100)).reshape(-1, 1)\n", "\n", "X_train = X[:50]\n", "Y_train = X[1:51]\n", "\n", "plt.figure(figsize=(10, 3))\n", "plt.title(\"A sine wave.\")\n", "plt.ylabel(\"$sin(t)$\")\n", "plt.xlabel(\"$t$\")\n", "plt.plot(X)\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "6b1f9975", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## Input-to-readout connections\n", "\n", "More advanced ESNs may include direct connections from input to readout. This can be achieved using the `Input` node and advanced features of model creation: connection chaining with the `>>` operator and connection merge using the `&` operator.\n", "\n", "![ESN model with input-to-readout connection](../_static/user_guide/model/input_to_readout.svg)" ] }, { "cell_type": "code", "execution_count": 3, "id": "2ace1eb4", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "from reservoirpy.nodes import Reservoir, Ridge, Input\n", "\n", "data = Input()\n", "reservoir = Reservoir(100, lr=0.5, sr=0.9)\n", "readout = Ridge(ridge=1e-7)\n", "\n", "esn_model = data >> reservoir >> readout & data >> readout" ] }, { "cell_type": "markdown", "id": "ad0c3ced", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "The `&` operator can be used to merge two Model together.\n", "Here, we first connect the input to the reservoir and the reservoir to the readout. As models are a subclass of nodes, it is also possible to apply the `>>` on models, allowing chaining. When a model is connected to a node, all output nodes of the model are automatically connected to the node. A new model storing all the nodes involved in the process, along with all their connections, is created.\n", "\n", "```python\n", "connection_1 = data >> reservoir >> readout\n", "```\n", "\n", "Then, we define another model connecting the input to the readout.\n", "\n", "```python\n", "connection_2 = data >> readout\n", "```\n", "\n", "Finally, we merge all connections into a single model:\n", "\n", "```python\n", "esn_model = connection_1 & connection_2\n", "```" ] }, { "cell_type": "markdown", "id": "3fd5a77b", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "A same model can be obtained using another syntax, taking advantage of many-to-one and one-to-many connections. These type of connections are created using iterables of nodes:" ] }, { "cell_type": "code", "execution_count": 4, "id": "19546020", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "esn_model = [data, data >> reservoir] >> readout" ] }, { "cell_type": "markdown", "id": "1fca0b7d", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "In that case, we plug two models into the readout: `data` alone and `data >> reservoir`. This is equivalent to the syntax of the first example." ] }, { "cell_type": "code", "execution_count": 5, "id": "dd665838", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "text/plain": [ "[Input, Ridge, Reservoir]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "esn_model.nodes" ] }, { "cell_type": "markdown", "id": "a438950b", "metadata": {}, "source": [ "Note that the same can be achieved using the `ESN` class seen previously, using the `input_to_readout` argument:" ] }, { "cell_type": "code", "execution_count": 6, "id": "e155d6f2", "metadata": {}, "outputs": [], "source": [ "from reservoirpy import ESN\n", "\n", "esn_model2 = ESN(units=100, ridge=1e-7, input_to_readout=True)" ] }, { "cell_type": "markdown", "id": "ef6c0ec4", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## Feedback connections\n", "\n", "Feedback connections are another important feature of ESNs. All nodes in ReservoirPy can be connected through feedback connections. Once a feedback connection is established between two nodes, the feedback receiver will receive the state of the feedback sender. When running on a timeseries, **this access will hence allow the receiver to access the output of the sender, with a time delay of one timestep**.\n", "\n", "To declare a feedback connection between two nodes, you can use the `<<` operator. This operator will create a model with\n", "a delayed connection from the right operand to the left.\n", "\n", "![ESN model with feedback connection](../_static/user_guide/model/feedback.svg)\n", "\n", "Let's add a feedback connection between our readout and our reservoir." ] }, { "cell_type": "code", "execution_count": 7, "id": "1c7bf09d", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "from reservoirpy.nodes import Reservoir, Ridge\n", "\n", "reservoir = Reservoir(100, lr=0.5, sr=0.9)\n", "readout = Ridge(ridge=1e-7)\n", "\n", "# Echo State Network with feedback\n", "esn_model = reservoir >> readout # regular feed-forward connection\n", "esn_model &= reservoir << readout # feedback (delayed) connection" ] }, { "cell_type": "markdown", "id": "b8bc73df", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Once all nodes are initialized - after training the model for instance - feedback is available:" ] }, { "cell_type": "code", "execution_count": 8, "id": "93cc36fd", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Stored feedback: {(Ridge, 1, Reservoir): array([[-1.00263582]])}\n" ] } ], "source": [ "esn_model = esn_model.fit(X_train, Y_train)\n", "esn_model(X[0])\n", "\n", "print(\"Stored feedback:\", esn_model.feedback_buffers)" ] }, { "cell_type": "markdown", "id": "f5540222", "metadata": {}, "source": [ "Note that the same can be achieved using the `ESN` class seen previously, using the `feedback` argument:" ] }, { "cell_type": "code", "execution_count": 9, "id": "b902c58e", "metadata": {}, "outputs": [], "source": [ "from reservoirpy import ESN\n", "\n", "esn_model2 = ESN(units=100, ridge=1e-7, feedback=True)" ] }, { "cell_type": "markdown", "id": "5f07fbe3", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### Forced feedbacks" ] }, { "cell_type": "markdown", "id": "15e4311b", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Note that adding feedback changes the training procedure: the readout needs the reservoir activity in order to fit its model,\n", "and the reservoir needs the readout output to have a proper activity. We then need **teacher forcing** to obtain convergence: teacher vectors $y$ are used as feedback for the reservoir while readout is not trained." ] }, { "cell_type": "markdown", "id": "77fda069", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## Generation and long term forecasting\n", "\n", "In this section, we will see how to use ReservoirPy nodes and models to perform long term forecasting or timeseries generation.\n", "\n", "We will take a simple ESN as an example:" ] }, { "cell_type": "code", "execution_count": 10, "id": "639a4bc4", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "from reservoirpy.nodes import Reservoir, Ridge\n", "\n", "reservoir = Reservoir(100, lr=0.5, sr=0.9)\n", "ridge = Ridge(ridge=1e-7)\n", "\n", "esn_model = reservoir >> ridge" ] }, { "cell_type": "markdown", "id": "a704abb2", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Imagine that we now desire to predict the 100 next steps of the timeseries, given its 10 last steps.\n", "\n", "In order to achieve this kind of prediction with an ESN, we first train the model on the simple one-timestep-ahead prediction task defined in the sections above:" ] }, { "cell_type": "code", "execution_count": 11, "id": "6ba41ead", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "esn_model = esn_model.fit(X_train, Y_train, warmup=10)" ] }, { "cell_type": "markdown", "id": "e727630d", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Now that our ESN is trained on that simple task, we reset its internal state and feed it with the 10 last steps of the training timeseries.\n", "\n", "Based on this state, we will now predict the next step in the timeseries. Then, this predicted step will be fed to the ESN again, and so on 100 times, to generate the 100 following timesteps. In other words, the ESN is running over its own predictions." ] }, { "cell_type": "code", "execution_count": 12, "id": "3b01685b", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "Y_pred = np.empty((100, 1))\n", "x = Y_train[-1]\n", "\n", "for i in range(100):\n", " x = esn_model(x)\n", " Y_pred[i] = x" ] }, { "cell_type": "code", "execution_count": 13, "id": "d54e36bb", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10, 3))\n", "plt.title(\"100 timesteps of a sine wave.\")\n", "plt.xlabel(\"$t$\")\n", "plt.plot(Y_pred, label=\"Generated sin(t)\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "d024d5f3", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "The long term forecasting ability of ESNs are one of their most impressive features. You have seen in this section how to perform this kind of generative task using a for-loop and an ESN call method." ] }, { "cell_type": "markdown", "id": "b41c8016", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## Custom weight matrices" ] }, { "cell_type": "markdown", "id": "f066e7b8", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### From reservoirpy.mat_gen module\n", "\n", "The `reservoirpy.mat_gen` module contains ready-to-use initializers able to create weights from any `scipy.stats` distribution, along with some more specialized initializations functions.\n", "\n", "Below are some examples:" ] }, { "cell_type": "code", "execution_count": 14, "id": "6b7fe027", "metadata": {}, "outputs": [], "source": [ "# Random sparse matrix initializer from uniform distribution,\n", "# with spectral radius to 0.9 and connectivity of 0.1.\n", "\n", "from reservoirpy.mat_gen import uniform\n", "# Matrix creation can be delayed...\n", "initializer = uniform(sr=0.9, connectivity=0.1)\n", "matrix = initializer(100, 100)\n", "\n", "# ...or can be performed right away.\n", "matrix = uniform(100, 100, sr=0.9, connectivity=0.1)" ] }, { "cell_type": "code", "execution_count": 15, "id": "77a89330", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "# Dense matrix from Gaussian distribution,\n", "# with mean of 0 and variance of 0.5\n", "from reservoirpy.mat_gen import normal\n", "\n", "matrix = normal(50, 100, loc=0, scale=0.5)\n", "\n", "# Sparse matrix from uniform distribution in [-0.5, 0.5],\n", "# with connectivity of 0.9 and input_scaling of 0.3.\n", "from reservoirpy.mat_gen import uniform\n", "\n", "matrix = uniform(\n", " 200, 60, low=0.5, high=0.5,\n", " connectivity=0.9, input_scaling=0.3)\n", "\n", "# Sparse matrix from a Bernoulli random variable\n", "# giving 1 with probability p and -1 with probability 1-p,\n", "# with p=0.5 (by default) with connectivity of 0.2\n", "# and fixed seed, in Numpy format.\n", "from reservoirpy.mat_gen import bernoulli\n", "\n", "matrix = bernoulli(10, 60, connectivity=0.2, sparsity_type=\"dense\")" ] }, { "cell_type": "markdown", "id": "dc4b0989", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "This functions can be tuned and integrated to any Node accepting initializer functions. In particular, they can be used to tune parameters distribution in a reservoir." ] }, { "cell_type": "markdown", "id": "416f6269", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### From Numpy arrays or Scipy sparse matrices\n", "\n", "In addition to initializer functions, parameters can be initialized using Numpy arrays or Scipy sparse matrices of correct shape." ] }, { "cell_type": "code", "execution_count": 16, "id": "441611b9", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "from reservoirpy.nodes import Reservoir\n", "\n", "W_matrix = np.random.normal(0, 1, size=(100, 100))\n", "bias_vector = np.ones((100, 1))\n", "\n", "reservoir = Reservoir(W=W_matrix, bias=bias_vector)\n", "\n", "states = reservoir(X[0])" ] }, { "cell_type": "markdown", "id": "36ac7f33", "metadata": {}, "source": [ "### From custom initializer functions\n", "\n", "Readouts and reservoirs hold parameters stored as NumPy array or SciPy sparse matrices. These parameters can be initialized at first run of the node. This initialization is performed by calling initializer functions, which take as parameters the shape of the parameter matrix and return an array or a SciPy sparse matrix. Initializer functions can be passed as parameter to reservoirs or readouts:" ] }, { "cell_type": "code", "execution_count": 17, "id": "e8b2f6cc", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from reservoirpy.nodes import Reservoir\n", "\n", "def bernoulli_w(n, m, **kwargs):\n", " return np.random.choice([-1, 1], size=(n, m))\n", "\n", "reservoir = Reservoir(10, W=bernoulli_w)\n", "\n", "reservoir(X[0])\n", "\n", "plt.figure(figsize=(5, 5))\n", "plt.title(\"Weights in $W$\")\n", "plt.imshow(reservoir.W)\n", "plt.colorbar()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "45b157dc", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## \"Deep\" architectures\n", "\n", "Nodes can be combined in any way to create deeper structure than just a reservoir and a readout.\n", "Connecting nodes together can be done by chaining the `>>` and the ``&`` operator.\n", "\n", "- The `>>` operator allows to compose nodes to form a chain model. Data flows from node to node in the chain.\n", "\n", "- The `&` operator allows to merge models together, to create parallel pathways. Merging two chains of nodes will create a new model containing all the nodes in the two chains along with all the connections between them.\n", "\n", "Below are examples of so called *deep echo state networks*, from schema to code, illustrating the use of these two operators. More extensive explanations about complex models can be found in the [From Nodes to Models](https://reservoirpy.readthedocs.io/en/latest/user_guide/model.html) documentation.\n", "\n", "### Training and running on multiple reservoirs\n", "\n", "When training or running a model that has multiple inputs or trainable nodes, a `dict` (indexed by `Node` names) should be used to dispatch timeseries to the different nodes. Similarly, models with multiple outputs will return a `dict` of all the `Node`'s outputs." ] }, { "cell_type": "code", "execution_count": 18, "id": "b1b6dcb9", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "\n", "X1 = X2 = X3 = np.sin(np.linspace(0, 12*np.pi, 200)).reshape(-1, 1)\n", "Y1 = Y2 = np.sin(np.linspace(0, 4*np.pi, 200)).reshape(-1, 1)" ] }, { "cell_type": "markdown", "id": "3e7ef3f9", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### Example 1 - Hierarchical ESN\n", "\n", "![Hierarchical ESN model](../_static/user_guide/tutorials/deep1.svg.png)" ] }, { "cell_type": "code", "execution_count": 19, "id": "73677aa9", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "from reservoirpy.nodes import Reservoir, Ridge, Input\n", "\n", "\n", "reservoir1 = Reservoir(100, name=\"res1-1\")\n", "reservoir2 = Reservoir(100, name=\"res2-1\")\n", "\n", "readout1 = Ridge(ridge=1e-5, name=\"readout1-1\")\n", "readout2 = Ridge(ridge=1e-5, name=\"readout2-1\")\n", "\n", "model = reservoir1 >> readout1 >> reservoir2 >> readout2" ] }, { "cell_type": "markdown", "id": "93f44a1a", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "This model can be trained by explicitly delivering targets to each readout using a dictionary:" ] }, { "cell_type": "code", "execution_count": 20, "id": "5dc19b8d", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "model = model.fit(X1, {\"readout1-1\": Y1, \"readout2-1\": Y2})" ] }, { "cell_type": "markdown", "id": "0c5152db", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### Example 2 - Deep ESN\n", "\n", "![Deep ESN model](../_static/user_guide/tutorials/deep2.svg.png)" ] }, { "cell_type": "code", "execution_count": 21, "id": "420d2fc5", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/paul/Bureau/reservoir/reservoirpy/reservoirpy/nodes/readouts/ridge.py:17: LinAlgWarning: Ill-conditioned matrix (rcond=3.89348e-20): result may not be accurate.\n", " return linalg.solve(XXT + ridge, YXT.T, assume_a=\"sym\")\n" ] }, { "data": { "text/plain": [ "'Model-18': Model('data', 'res1-2', 'Concat-4', 'res2-2', 'Concat-5', 'res3-2', 'Concat-3', 'readout-2')" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from reservoirpy.nodes import Reservoir, Ridge, Input\n", "\n", "data = Input(name=\"data\")\n", "reservoir1 = Reservoir(100, name=\"res1-2\")\n", "reservoir2 = Reservoir(100, name=\"res2-2\")\n", "reservoir3 = Reservoir(100, name=\"res3-2\")\n", "\n", "readout = Ridge(name=\"readout-2\")\n", "\n", "model = reservoir1 >> reservoir2 >> reservoir3 & \\\n", " data >> [reservoir1, reservoir2, reservoir3] >> readout\n", "\n", "model.fit(X1, Y1)" ] }, { "cell_type": "markdown", "id": "10ef4554", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### Example 3 - Multi-inputs\n", "\n", "![Multi-inputs model](../_static/user_guide/tutorials/deep3.svg.png)" ] }, { "cell_type": "code", "execution_count": 22, "id": "7ca0ecad", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(500, 1) (500, 1)\n" ] } ], "source": [ "import numpy as np\n", "from reservoirpy.nodes import Reservoir, Ridge\n", "\n", "reservoir1 = Reservoir(100, name=\"res1-3\")\n", "reservoir2 = Reservoir(100, name=\"res2-3\")\n", "reservoir3 = Reservoir(100, name=\"res3-3\")\n", "\n", "readout1 = Ridge(name=\"readout1\")\n", "readout2 = Ridge(name=\"readout2\")\n", "\n", "model = [reservoir1, reservoir2] >> readout1 & \\\n", " [reservoir2, reservoir3] >> readout2\n", "\n", "model.fit(\n", " {\"res1-3\": X1, \"res2-3\": X2, \"res3-3\": X3},\n", " {\"readout1\": Y1, \"readout2\": Y2},\n", ")\n", "\n", "out = model.run({\"res1-3\": X1, \"res2-3\": X2, \"res3-3\": X3})\n", "# out = {\"readout1\": out1, \"readout2\": out2}\n", "\n", "out1 = out[\"readout1\"]\n", "out2 = out[\"readout2\"]\n", "\n", "print(out1.shape, out2.shape)" ] }, { "cell_type": "markdown", "id": "0252fc3d", "metadata": {}, "source": [ "## Working with incomplete target data\n", "\n", "You may encounter situations where you have target data with missing values (NaN). \n", "\n", "This case is covered by the `Model.fit()` and `Node.fit()` methods.\n", "\n", "When training or running the model, for the steps where target values are missing, the input values will still be fed to the reservoir - thus updating the reservoir states - but the readout will not be fitted. \n", "\n", "This property can be used to ignore target data that you do not want the readout to be trained on. \n", "\n", "### Example : signal command which corrupted target\n", "\n", "In this example, input data is the command for the frequency of a sine wave which will be our target data. In real life, response to command may not be perfect and there could be absurd values. We typically would not want to train our model on the corrupted values. " ] }, { "cell_type": "code", "execution_count": 23, "id": "73f9d9dd", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Parameters\n", "T = 20000 # number of time steps\n", "dt = 0.01 # temporal resolution in seconds\n", "t = np.arange(T) * dt # time\n", "np.random.seed(42) # for reproducibility\n", "# frequency command signal X(t) :\n", "X = 0.5 * np.sin(2 * np.pi * 0.1 * t) + 0.2\n", "\n", "# Y response signal Y(t)\n", "phase = 2 * np.pi * np.cumsum(X) * dt\n", "Y = np.sin(phase)\n", "corrupted_indices = np.random.choice(T, size=int(0.0005 * T), replace=False)\n", "corruption_len = 50\n", "for i in corrupted_indices:\n", " if i < T - corruption_len:\n", " Y[i : i + corruption_len] = np.random.uniform(5, 10, size=corruption_len)\n", "\n", "plt.figure(figsize=(12, 4))\n", "plt.subplot(2, 1, 1)\n", "plt.plot(t, X)\n", "plt.title(\"Frequency command X(t)\")\n", "plt.ylabel(\"Frequency (Hz)\")\n", "\n", "plt.subplot(2, 1, 2)\n", "plt.plot(t, Y)\n", "plt.title(\"Y(t) signal : sinus controlled by X(t)\")\n", "plt.xlabel(\"Time (s)\")\n", "plt.ylabel(\"Amplitude\")\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 24, "id": "c6a4c8f6", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Predicted Y(t) vs True Y(t)')" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from reservoirpy.nodes import Reservoir, Ridge\n", "train_test_split = int(0.75*T) # 75% for training, 25% for testing\n", "X_train = X[:train_test_split].reshape(-1, 1)\n", "X_test = X[train_test_split:].reshape(-1, 1)\n", "Y_train = Y[:train_test_split].reshape(-1, 1)\n", "Y_test = Y[train_test_split:].reshape(-1, 1)\n", "\n", "reservoir = Reservoir(100, lr=1, sr=0.9)\n", "readout = Ridge(ridge=1e-7)\n", "esn_model = reservoir >> readout\n", "esn_model = esn_model.fit(X_train, Y_train)\n", "\n", "pred = esn_model.run(X_test)\n", "plt.figure(figsize=(12, 4))\n", "plt.plot(t[train_test_split:], Y_test, label=\"True Y(t)\")\n", "plt.plot(t[train_test_split:], pred, label=\"Predicted Y(t)\")\n", "plt.legend()\n", "plt.ylim(-1.5, 2)\n", "plt.title(\"Predicted Y(t) vs True Y(t)\")\n", "plt.show()\n" ] }, { "cell_type": "markdown", "id": "910a42da", "metadata": {}, "source": [ "During the training, corrupted values affect how the ESN learn to predict target values. \n", "\n", "Predicted target data here tends to have higher peaks due to the training on the corrupted target, which we do not want. " ] }, { "cell_type": "code", "execution_count": 25, "id": "f6a986bd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Predicted Y(t) after ignoring corrupted data vs True Y(t)')" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for i in range(len(Y)):\n", " if Y[i] > 1 or Y[i] < -1:\n", " Y[i] = np.nan # ignore corrupted data\n", "Y_train = Y[:train_test_split].reshape(-1, 1)\n", "Y_test = Y[train_test_split:].reshape(-1, 1)\n", "esn_model = esn_model.fit(X_train, Y_train)\n", "pred = esn_model.run(X_test)\n", "plt.figure(figsize=(12, 4))\n", "plt.plot(t[train_test_split:], Y_test, label=\"True Y(t)\")\n", "plt.plot(t[train_test_split:], pred, label=\"Predicted Y(t)\")\n", "plt.legend()\n", "plt.ylim(-1.5, 2)\n", "plt.title(\"Predicted Y(t) after ignoring corrupted data vs True Y(t)\")\n", "plt.show()\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 5 }