diff options
| author | Danijel Andjelkovic <adanijel99@gmail.com> | 2022-03-30 12:41:53 +0200 |
|---|---|---|
| committer | Danijel Andjelkovic <adanijel99@gmail.com> | 2022-03-30 12:41:53 +0200 |
| commit | ad9193d35e5ae2f6847492f1867963fc1672ee3e (patch) | |
| tree | be3b3a54bc42696e73f3c3092a9f52db8355c07f | |
| parent | 6af8655c2d1a24c0c3ba851bb28d72f9d06c83b0 (diff) | |
| parent | 476393d1530b261b8a145db2533262979558e064 (diff) | |
Merge branch 'dev' of http://gitlab.pmf.kg.ac.rs/igrannonica/neuronstellar into dev
22 files changed, 376 insertions, 630 deletions
diff --git a/backend/api/api/Controllers/DatasetController.cs b/backend/api/api/Controllers/DatasetController.cs index bae05ba9..d9803744 100644 --- a/backend/api/api/Controllers/DatasetController.cs +++ b/backend/api/api/Controllers/DatasetController.cs @@ -24,7 +24,7 @@ namespace api.Controllers // GET: api/<DatasetController>/mydatasets [HttpGet("mydatasets")] - [Authorize(Roles = "User")] + [Authorize(Roles = "User,Guest")] public ActionResult<List<Dataset>> Get() { string username; @@ -39,6 +39,9 @@ namespace api.Controllers } else return BadRequest(); + //U slucaju da je korisnik gost vrati dataSetove igrannonice + if (username == "") + return _datasetService.GetGuestDatasets(); //ako bude trebao ID, samo iz baze uzeti diff --git a/backend/api/api/Controllers/ModelController.cs b/backend/api/api/Controllers/ModelController.cs index 4bc094cd..355eb9f4 100644 --- a/backend/api/api/Controllers/ModelController.cs +++ b/backend/api/api/Controllers/ModelController.cs @@ -30,7 +30,7 @@ namespace api.Controllers } [HttpPost("sendModel")] - [Authorize(Roles = "User")] + [Authorize(Roles = "User,Guest")] public async Task<ActionResult<string>> Test([FromBody] Model model) { var dataset = _datasetService.GetOneDataset(model.datasetId); diff --git a/backend/api/api/Controllers/PredictorController.cs b/backend/api/api/Controllers/PredictorController.cs index 7f8f1692..63c5d2bf 100644 --- a/backend/api/api/Controllers/PredictorController.cs +++ b/backend/api/api/Controllers/PredictorController.cs @@ -74,6 +74,36 @@ namespace api.Controllers return _predictorService.SearchPredictors(name, username); } + //SEARCH za predictore (public ili private sa ovim imenom ) + // GET api/<PredictorController>/search/{name} + [HttpGet("{id}")] + [Authorize(Roles = "User")] + public ActionResult<Predictor> GetPredictor(string id) + { + string username; + var header = Request.Headers[HeaderNames.Authorization]; + if (AuthenticationHeaderValue.TryParse(header, out var headerValue)) + { + var scheme = headerValue.Scheme; + var parameter = headerValue.Parameter; + username = jwtToken.TokenToUsername(parameter); + if (username == null) + return null; + } + else + return BadRequest(); + + //ako bude trebao ID, samo iz baze uzeti + + Predictor predictor = _predictorService.GetPredictor(username, id); + + if (predictor == null) + return NotFound($"Predictor with id = {id} not found"); + + return predictor; + } + + //da li da se odvoji search za public i posebno za private? // GET api/<PredictorController>/{name} [HttpGet("{name}")] diff --git a/backend/api/api/Controllers/UserController.cs b/backend/api/api/Controllers/UserController.cs index 0287f3cb..741382b8 100644 --- a/backend/api/api/Controllers/UserController.cs +++ b/backend/api/api/Controllers/UserController.cs @@ -135,8 +135,7 @@ namespace api.Controllers else return BadRequest(); - userService.Update(username, user); - return NoContent(); + return Ok(userService.Update(username, user)); } // DELETE api/<UserController>/5 diff --git a/backend/api/api/Services/DatasetService.cs b/backend/api/api/Services/DatasetService.cs index 45ed18a9..2ff271f3 100644 --- a/backend/api/api/Services/DatasetService.cs +++ b/backend/api/api/Services/DatasetService.cs @@ -36,6 +36,13 @@ namespace api.Services { return _dataset.Find(dataset => dataset.username == username).ToList(); } + public List<Dataset> GetGuestDatasets() + { + //Join Igranonica public datasetove sa svim temp uploadanim datasetovima + List<Dataset> datasets= _dataset.Find(dataset => dataset.username == "Igrannonica" && dataset.isPublic == true).ToList(); + datasets.AddRange(_dataset.Find(dataset => dataset.username == "").ToList()); + return datasets; + } //poslednji datasetovi public List<Dataset> SortDatasets(string username, bool ascdsc, int latest) diff --git a/backend/api/api/Services/IDatasetService.cs b/backend/api/api/Services/IDatasetService.cs index dbe43321..8e62ba43 100644 --- a/backend/api/api/Services/IDatasetService.cs +++ b/backend/api/api/Services/IDatasetService.cs @@ -14,5 +14,6 @@ namespace api.Services Dataset Create(Dataset dataset); void Update(string username, string name, Dataset dataset); void Delete(string username, string name); + public List<Dataset> GetGuestDatasets(); } } diff --git a/backend/api/api/Services/IPredictorService.cs b/backend/api/api/Services/IPredictorService.cs index 2017add2..729dd0b6 100644 --- a/backend/api/api/Services/IPredictorService.cs +++ b/backend/api/api/Services/IPredictorService.cs @@ -6,6 +6,7 @@ namespace api.Services public interface IPredictorService { Predictor GetOnePredictor(string username, string name); + Predictor GetPredictor(string username, string GetPredictor); List<Predictor> SearchPredictors(string name, string username); List<Predictor> GetMyPredictors(string username); List<Predictor> SortPredictors(string username, bool ascdsc, int latest); diff --git a/backend/api/api/Services/IUserService.cs b/backend/api/api/Services/IUserService.cs index 1cb6a609..e4a23213 100644 --- a/backend/api/api/Services/IUserService.cs +++ b/backend/api/api/Services/IUserService.cs @@ -8,7 +8,7 @@ namespace api.Services List<User> Get();// daje sve korisnike User GetUserUsername(string username); //daje korisnika po korisnickom imenu User Create(User user); // kreira korisnika - void Update(string username, User user); //apdejtuje korisnika po idu + bool Update(string username, User user); //apdejtuje korisnika po idu void Delete(string username);//brise korisnika } } diff --git a/backend/api/api/Services/PredictorService.cs b/backend/api/api/Services/PredictorService.cs index 05860126..01bc8359 100644 --- a/backend/api/api/Services/PredictorService.cs +++ b/backend/api/api/Services/PredictorService.cs @@ -40,6 +40,11 @@ namespace api.Services return _predictor.Find(predictor => predictor.username == username && predictor.name == name).FirstOrDefault(); } + public Predictor GetPredictor(string username, string id) + { + return _predictor.Find(predictor => predictor.username == username && predictor._id == id).FirstOrDefault(); + + } //last private models public List<Predictor> SortPredictors(string username, bool ascdsc, int latest) { diff --git a/backend/api/api/Services/UserService.cs b/backend/api/api/Services/UserService.cs index f613f923..607bb04b 100644 --- a/backend/api/api/Services/UserService.cs +++ b/backend/api/api/Services/UserService.cs @@ -7,11 +7,22 @@ namespace api.Services public class UserService : IUserService { private readonly IMongoCollection<User> _users; + private readonly IMongoClient _client; + private readonly IMongoCollection<Model> _models; + private readonly IMongoCollection<Dataset> _datasets; + private readonly IMongoCollection<FileModel> _fileModels; + private readonly IMongoCollection<Predictor> _predictors; + public UserService(IUserStoreDatabaseSettings settings, IMongoClient mongoClient) { var database = mongoClient.GetDatabase(settings.DatabaseName); _users = database.GetCollection<User>(settings.CollectionName); + _models = database.GetCollection<Model>(settings.ModelCollectionName); + _datasets= database.GetCollection<Dataset>(settings.DatasetCollectionName); + _fileModels = database.GetCollection<FileModel>(settings.FilesCollectionName); + _predictors= database.GetCollection<Predictor>(settings.PredictorCollectionName); + _client = mongoClient; } public User Create(User user) { @@ -26,10 +37,46 @@ namespace api.Services { return _users.Find(user => user.Username == username).FirstOrDefault(); } - public void Update(string username, User user) + public bool Update(string username, User user) { //username koji postoji u bazi - _users.ReplaceOne(user => user.Username == username, user); + using (var session = _client.StartSession()) + { + + if(_users.Find(u => u.Username == user.Username).FirstOrDefault()!=null) + { + return false; + } + + //Trenutan MongoDB Server ne podrzava transakcije.Omoguciti Podrsku + //session.StartTransaction(); + try + { + _users.ReplaceOne(user => user.Username == username, user); + if (username != user.Username) + { + var builderModel = Builders<Model>.Update; + var builderDataset = Builders<Dataset>.Update; + var builderFileModel = Builders<FileModel>.Update; + var builderPredictor = Builders<Predictor>.Update; + _models.UpdateMany(x => x.username == username, builderModel.Set(x => x.username, user.Username)); + _datasets.UpdateMany(x => x.username == username, builderDataset.Set(x => x.username, user.Username)); + _fileModels.UpdateMany(x => x.username == username, builderFileModel.Set(x => x.username, user.Username)); + _predictors.UpdateMany(x => x.username == username, builderPredictor.Set(x => x.username, user.Username)); + } + + //session.AbortTransaction(); + + + //session.CommitTransaction(); + } + catch (Exception e) + { + //session.AbortTransaction(); + return false; + } + return true; + } } public void Delete(string username) { diff --git a/backend/microservice/regression.py b/backend/microservice/regression.py new file mode 100644 index 00000000..f039292c --- /dev/null +++ b/backend/microservice/regression.py @@ -0,0 +1,53 @@ +import numpy as np +from tensorflow.keras.datasets import boston_housing +from sklearn.preprocessing import StandardScaler +from tensorflow.keras.models import load_model + +x_new = np.random.rand(X_train.shape[1]) +x_new = x_new.reshape(1,-1) +# x_new.shape +y_pred = model.predict(x_new) +if y_pred < 0.5: + print('0') +else: + print('1') + +(X_train, y_train), (X_test, y_test) = boston_housing.load_data() + +X_train.shape +X_test.shape +X_train[0] +y_test + +scaler = StandardScaler() +scaler.fit(X_train) +X_train = scaler.transform(X_train) +X_test = scaler.transform(X_test) + +X_train[0] +X_test + +model = Sequential() +model.add(Dense(input_dim=X_train.shape[1], units=100, activation='relu')) +# model.add(Dense(input_dim=X_train.shape[1], units=50, activation='relu')) +model.add(Dense(units=1)) +model.summary() + +model.compile(optimizer='adam', loss='mse', metrics=['mae']) +history = model.fit(X_train, y_train, batch_size=32, epochs=20, validation_split=0.2) + +plt.plot(history.epoch, history.history['loss']) +plt.plot(history.epoch, history.history['val_loss']) + +plt.plot(history.epoch, history.history['mae']) +plt.plot(history.epoch, history.history['val_mae']) + +model.evaluate(X_test, y_test) +model.save('models/boston.h5') +old_model = load_model('models/boston.h5') + +x_new = np.random.rand(X_train.shape[1]) +x_new = x_new.reshape(1, -1) +x_new.shape +# Za nove podatke koristi se predict tako da se dobije predvidjena vrednost za y +old_model.predict(x_new)
\ No newline at end of file diff --git a/backend/microservice/regressionFCNN.ipynb b/backend/microservice/regressionFCNN.ipynb deleted file mode 100644 index 470a9831..00000000 --- a/backend/microservice/regressionFCNN.ipynb +++ /dev/null @@ -1,595 +0,0 @@ -{ - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "name": "regressionFCNN.ipynb", - "provenance": [], - "collapsed_sections": [] - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" - }, - "accelerator": "GPU" - }, - "cells": [ - { - "cell_type": "markdown", - "source": [ - "Dataset - Boston Housing" - ], - "metadata": { - "id": "8vzWlOHFi6el" - } - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "id": "OnfiK4W-g9NC" - }, - "outputs": [], - "source": [ - "import numpy as np" - ] - }, - { - "cell_type": "code", - "source": [ - "from tensorflow.keras.datasets import boston_housing" - ], - "metadata": { - "id": "f_siGNjyhNG4" - }, - "execution_count": 4, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "(X_train, y_train), (X_test, y_test) = boston_housing.load_data()" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "v6rzMZSahNEp", - "outputId": "b6f076c9-e69a-42b6-b1ca-d2c942efb684" - }, - "execution_count": 5, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/boston_housing.npz\n", - "57344/57026 [==============================] - 0s 0us/step\n", - "65536/57026 [==================================] - 0s 0us/step\n" - ] - } - ] - }, - { - "cell_type": "code", - "source": [ - "X_train.shape" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "wJDkN70phNB5", - "outputId": "fef03e1d-595f-4e0c-9e48-cac1b7cf0c66" - }, - "execution_count": 6, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "(404, 13)" - ] - }, - "metadata": {}, - "execution_count": 6 - } - ] - }, - { - "cell_type": "code", - "source": [ - "X_test.shape" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "sZCvrECthM--", - "outputId": "c1b12abe-13d5-4b46-a67e-90aa7b613b4f" - }, - "execution_count": 7, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "(102, 13)" - ] - }, - "metadata": {}, - "execution_count": 7 - } - ] - }, - { - "cell_type": "code", - "source": [ - "X_train[0]" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "9i8Ix3ZkhM8U", - "outputId": "1be03f2d-faf3-4856-9eb7-bc550d77c91e" - }, - "execution_count": 8, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "array([ 1.23247, 0. , 8.14 , 0. , 0.538 , 6.142 ,\n", - " 91.7 , 3.9769 , 4. , 307. , 21. , 396.9 ,\n", - " 18.72 ])" - ] - }, - "metadata": {}, - "execution_count": 8 - } - ] - }, - { - "cell_type": "code", - "source": [ - "y_test" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "1a-jNd6KhM5a", - "outputId": "a54ce6e6-6462-4a0f-99c1-c13ebc47844a" - }, - "execution_count": 9, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "array([ 7.2, 18.8, 19. , 27. , 22.2, 24.5, 31.2, 22.9, 20.5, 23.2, 18.6,\n", - " 14.5, 17.8, 50. , 20.8, 24.3, 24.2, 19.8, 19.1, 22.7, 12. , 10.2,\n", - " 20. , 18.5, 20.9, 23. , 27.5, 30.1, 9.5, 22. , 21.2, 14.1, 33.1,\n", - " 23.4, 20.1, 7.4, 15.4, 23.8, 20.1, 24.5, 33. , 28.4, 14.1, 46.7,\n", - " 32.5, 29.6, 28.4, 19.8, 20.2, 25. , 35.4, 20.3, 9.7, 14.5, 34.9,\n", - " 26.6, 7.2, 50. , 32.4, 21.6, 29.8, 13.1, 27.5, 21.2, 23.1, 21.9,\n", - " 13. , 23.2, 8.1, 5.6, 21.7, 29.6, 19.6, 7. , 26.4, 18.9, 20.9,\n", - " 28.1, 35.4, 10.2, 24.3, 43.1, 17.6, 15.4, 16.2, 27.1, 21.4, 21.5,\n", - " 22.4, 25. , 16.6, 18.6, 22. , 42.8, 35.1, 21.5, 36. , 21.9, 24.1,\n", - " 50. , 26.7, 25. ])" - ] - }, - "metadata": {}, - "execution_count": 9 - } - ] - }, - { - "cell_type": "code", - "source": [ - "from sklearn.preprocessing import StandardScaler" - ], - "metadata": { - "id": "c9ETzZu-hMzb" - }, - "execution_count": 10, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "scaler = StandardScaler()\n", - "scaler.fit(X_train)\n", - "X_train = scaler.transform(X_train)\n", - "X_test = scaler.transform(X_test)" - ], - "metadata": { - "id": "VUb0qQR7hepF" - }, - "execution_count": 11, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "X_train[0]" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "Qhjccz_whemx", - "outputId": "083f4f0b-1295-43c9-b6ac-2160f909dc50" - }, - "execution_count": 12, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "array([-0.27224633, -0.48361547, -0.43576161, -0.25683275, -0.1652266 ,\n", - " -0.1764426 , 0.81306188, 0.1166983 , -0.62624905, -0.59517003,\n", - " 1.14850044, 0.44807713, 0.8252202 ])" - ] - }, - "metadata": {}, - "execution_count": 12 - } - ] - }, - { - "cell_type": "code", - "source": [ - "X_test" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "lQcbYns7hejc", - "outputId": "32eccf17-3220-44f8-bfa7-ae6300a3f41e" - }, - "execution_count": 13, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "array([[ 1.55369355, -0.48361547, 1.0283258 , ..., 0.78447637,\n", - " -3.48459553, 2.25092074],\n", - " [-0.39242675, -0.48361547, -0.16087773, ..., -0.30759583,\n", - " 0.42733126, 0.47880119],\n", - " [-0.39982927, -0.48361547, -0.86940196, ..., 0.78447637,\n", - " 0.44807713, -0.41415936],\n", - " ...,\n", - " [-0.20709507, -0.48361547, 1.24588095, ..., -1.71818909,\n", - " 0.37051949, -1.49344089],\n", - " [-0.36698601, -0.48361547, -0.72093526, ..., -0.48960787,\n", - " 0.39275481, -0.41829982],\n", - " [-0.0889679 , -0.48361547, 1.24588095, ..., -1.71818909,\n", - " -1.21946544, -0.40449827]])" - ] - }, - "metadata": {}, - "execution_count": 13 - } - ] - }, - { - "cell_type": "code", - "source": [ - "from tensorflow.keras.models import Sequential\n", - "from tensorflow.keras.layers import Dense" - ], - "metadata": { - "id": "WbQA9y9BioPi" - }, - "execution_count": 15, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "model = Sequential()\n", - "model.add(Dense(input_dim=X_train.shape[1], units=100, activation='relu'))\n", - "# model.add(Dense(input_dim=X_train.shape[1], units=50, activation='relu'))\n", - "model.add(Dense(units=1))\n", - "model.summary()" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "eiH9Y1P8heg4", - "outputId": "62018b2b-f765-43a9-f487-6e3fd733e6e7" - }, - "execution_count": 16, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Model: \"sequential\"\n", - "_________________________________________________________________\n", - " Layer (type) Output Shape Param # \n", - "=================================================================\n", - " dense (Dense) (None, 100) 1400 \n", - " \n", - " dense_1 (Dense) (None, 1) 101 \n", - " \n", - "=================================================================\n", - "Total params: 1,501\n", - "Trainable params: 1,501\n", - "Non-trainable params: 0\n", - "_________________________________________________________________\n" - ] - } - ] - }, - { - "cell_type": "code", - "source": [ - "model.compile(optimizer='adam', loss='mse', metrics=['mae'])" - ], - "metadata": { - "id": "lr0HPSnyhedp" - }, - "execution_count": 17, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "history = model.fit(X_train, y_train, batch_size=32, epochs=20, validation_split=0.2)" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "DmNuBukshp9P", - "outputId": "804ec2d0-ba5c-4f29-d0ce-ea9ce7ca5a6a" - }, - "execution_count": 18, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Epoch 1/20\n", - "11/11 [==============================] - 3s 22ms/step - loss: 557.1730 - mae: 21.9147 - val_loss: 609.2063 - val_mae: 23.0475\n", - "Epoch 2/20\n", - "11/11 [==============================] - 0s 7ms/step - loss: 532.9012 - mae: 21.3854 - val_loss: 585.1005 - val_mae: 22.5338\n", - "Epoch 3/20\n", - "11/11 [==============================] - 0s 6ms/step - loss: 509.3247 - mae: 20.8655 - val_loss: 560.5905 - val_mae: 22.0077\n", - "Epoch 4/20\n", - "11/11 [==============================] - 0s 6ms/step - loss: 486.2475 - mae: 20.3399 - val_loss: 535.8640 - val_mae: 21.4625\n", - "Epoch 5/20\n", - "11/11 [==============================] - 0s 7ms/step - loss: 461.9990 - mae: 19.7867 - val_loss: 509.6354 - val_mae: 20.8769\n", - "Epoch 6/20\n", - "11/11 [==============================] - 0s 7ms/step - loss: 436.3251 - mae: 19.1894 - val_loss: 481.8866 - val_mae: 20.2395\n", - "Epoch 7/20\n", - "11/11 [==============================] - 0s 8ms/step - loss: 410.0367 - mae: 18.5537 - val_loss: 453.0820 - val_mae: 19.5479\n", - "Epoch 8/20\n", - "11/11 [==============================] - 0s 6ms/step - loss: 382.7516 - mae: 17.8715 - val_loss: 423.8254 - val_mae: 18.8088\n", - "Epoch 9/20\n", - "11/11 [==============================] - 0s 6ms/step - loss: 354.5889 - mae: 17.1212 - val_loss: 392.0852 - val_mae: 17.9759\n", - "Epoch 10/20\n", - "11/11 [==============================] - 0s 7ms/step - loss: 325.2735 - mae: 16.2985 - val_loss: 360.8828 - val_mae: 17.1014\n", - "Epoch 11/20\n", - "11/11 [==============================] - 0s 7ms/step - loss: 295.4146 - mae: 15.4205 - val_loss: 329.8161 - val_mae: 16.1668\n", - "Epoch 12/20\n", - "11/11 [==============================] - 0s 7ms/step - loss: 266.6942 - mae: 14.5040 - val_loss: 299.9690 - val_mae: 15.2050\n", - "Epoch 13/20\n", - "11/11 [==============================] - 0s 6ms/step - loss: 238.4964 - mae: 13.5476 - val_loss: 270.8452 - val_mae: 14.2164\n", - "Epoch 14/20\n", - "11/11 [==============================] - 0s 6ms/step - loss: 211.5596 - mae: 12.5503 - val_loss: 243.2032 - val_mae: 13.1773\n", - "Epoch 15/20\n", - "11/11 [==============================] - 0s 7ms/step - loss: 186.9801 - mae: 11.5573 - val_loss: 217.9993 - val_mae: 12.1424\n", - "Epoch 16/20\n", - "11/11 [==============================] - 0s 6ms/step - loss: 165.2683 - mae: 10.6563 - val_loss: 195.9235 - val_mae: 11.2217\n", - "Epoch 17/20\n", - "11/11 [==============================] - 0s 7ms/step - loss: 145.9631 - mae: 9.8479 - val_loss: 176.3322 - val_mae: 10.4139\n", - "Epoch 18/20\n", - "11/11 [==============================] - 0s 6ms/step - loss: 129.5782 - mae: 9.1388 - val_loss: 159.7129 - val_mae: 9.7597\n", - "Epoch 19/20\n", - "11/11 [==============================] - 0s 6ms/step - loss: 115.6311 - mae: 8.5268 - val_loss: 144.8544 - val_mae: 9.1716\n", - "Epoch 20/20\n", - "11/11 [==============================] - 0s 7ms/step - loss: 103.5382 - mae: 7.9529 - val_loss: 131.3257 - val_mae: 8.6467\n" - ] - } - ] - }, - { - "cell_type": "code", - "source": [ - "from matplotlib import pyplot as plt" - ], - "metadata": { - "id": "8nhJUJKLiyVW" - }, - "execution_count": 20, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "plt.plot(history.epoch, history.history['loss'])\n", - "plt.plot(history.epoch, history.history['val_loss'])" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 283 - }, - "id": "dfYbEqEahs7a", - "outputId": "ae03afb2-ce90-4d04-8ae1-6d08dd6c4d54" - }, - "execution_count": 21, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "[<matplotlib.lines.Line2D at 0x7f54e056a4d0>]" - ] - }, - "metadata": {}, - "execution_count": 21 - }, - { - "output_type": "display_data", - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": { - "needs_background": "light" - } - } - ] - }, - { - "cell_type": "code", - "source": [ - "plt.plot(history.epoch, history.history['mae'])\n", - "plt.plot(history.epoch, history.history['val_mae'])" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 283 - }, - "id": "rr6zjCGFhtu4", - "outputId": "8deb985f-28fa-4f87-c55c-25c577247769" - }, - "execution_count": 22, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "[<matplotlib.lines.Line2D at 0x7f54e0132d50>]" - ] - }, - "metadata": {}, - "execution_count": 22 - }, - { - "output_type": "display_data", - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 432x288 with 1 Axes>" - ] - }, - "metadata": { - "needs_background": "light" - } - } - ] - }, - { - "cell_type": "code", - "source": [ - "model.evaluate(X_test, y_test)" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "-MmP-D5phwcq", - "outputId": "9c1fbb91-1614-47d8-ccff-a34fbf56e949" - }, - "execution_count": 23, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "4/4 [==============================] - 0s 4ms/step - loss: 113.3174 - mae: 8.8532\n" - ] - }, - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "[113.3174057006836, 8.853187561035156]" - ] - }, - "metadata": {}, - "execution_count": 23 - } - ] - }, - { - "cell_type": "code", - "source": [ - "model.save('models/boston.hdf5')\n", - "# model.save_weight()" - ], - "metadata": { - "id": "OAySS7O0hy4-" - }, - "execution_count": 24, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "from tensorflow.keras.models import load_model" - ], - "metadata": { - "id": "xQmG2F0Ph08v" - }, - "execution_count": 25, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "old_model = load_model('models/boston.hdf5')" - ], - "metadata": { - "id": "Qp_jE9Fxh3cl" - }, - "execution_count": 26, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "x_new = np.random.rand(X_train.shape[1])\n", - "x_new = x_new.reshape(1, -1)\n", - "x_new.shape\n", - "# Za nove podatke koristi se predict tako da se dobije predvidjena vrednost za y\n", - "old_model.predict(x_new)" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "yOyueyFmh4CJ", - "outputId": "d56f0b37-cedc-4456-a527-499b9ff68d7d" - }, - "execution_count": 27, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "array([[5.2812877]], dtype=float32)" - ] - }, - "metadata": {}, - "execution_count": 27 - } - ] - } - ] -}
\ No newline at end of file diff --git a/frontend/src/app/_data/Model.ts b/frontend/src/app/_data/Model.ts index 32247bbd..7a82cc5c 100644 --- a/frontend/src/app/_data/Model.ts +++ b/frontend/src/app/_data/Model.ts @@ -28,7 +28,7 @@ export default class Model { public outputLayerActivationFunction: ActivationFunction = ActivationFunction.Sigmoid, public username: string = '', public nullValues: NullValueOptions = NullValueOptions.DeleteRows, - public nullValuesReplacers = [], + public nullValuesReplacers: NullValReplacer[] = [], public metrics: Metric[] = [], // TODO add to add-model form public epochs: number = 5 // TODO add to add-model form ) { } @@ -115,9 +115,15 @@ export enum ReplaceWith { Median = 'Medijana' } +export class NullValReplacer { + "column": string; + "option": NullValueOptions; + "value" : any; +} + export enum Metric { MSE = 'mse', MAE = 'mae', RMSE = 'rmse' //... -}
\ No newline at end of file +} diff --git a/frontend/src/app/_elements/annvisual/annvisual.component.ts b/frontend/src/app/_elements/annvisual/annvisual.component.ts index ff5b45d6..8588537e 100644 --- a/frontend/src/app/_elements/annvisual/annvisual.component.ts +++ b/frontend/src/app/_elements/annvisual/annvisual.component.ts @@ -19,13 +19,13 @@ export class AnnvisualComponent implements OnInit { let hiddenlayerstring:string=''; let digraphstring:string='digraph {'; - for(let i=0;i<this.model.inputNeurons;i++) + for(let i=0;i<this.model.inputColumns.length;i++) { inputlayerstring=inputlayerstring+'i'+i+','; } inputlayerstring=inputlayerstring.slice(0,-1); - digraphstring=digraphstring+'->'; + digraphstring=digraphstring+inputlayerstring+'->'; for(let j=0;j<this.model.hiddenLayers;j++) { @@ -33,15 +33,18 @@ export class AnnvisualComponent implements OnInit { { hiddenlayerstring=hiddenlayerstring+'h'+j+'_'+i+','; } - hiddenlayerstring=hiddenlayerstring.slice(0,1); + hiddenlayerstring=hiddenlayerstring.slice(0,-1); digraphstring=digraphstring+hiddenlayerstring+'->'; hiddenlayerstring=''; } digraphstring=digraphstring+'o}'; - alert(digraphstring); + graphviz('#graph').renderDot(digraphstring); } - + //'digraph {i0,i1,i2->h1,h2,h3->h21,h22,h23->o}' } + + + diff --git a/frontend/src/app/_pages/add-model/add-model.component.html b/frontend/src/app/_pages/add-model/add-model.component.html index 662d34de..28c84570 100644 --- a/frontend/src/app/_pages/add-model/add-model.component.html +++ b/frontend/src/app/_pages/add-model/add-model.component.html @@ -65,7 +65,7 @@ <!-- ULAZNE/IZLAZNE KOLONE --> <span id="selectInAndOuts"></span> - <div *ngIf="selectedDataset"> + <div *ngIf="selectedDataset && (showMyDatasets || (!showMyDatasets && datasetLoaded))"> <!--postignuto da se kod newdataseta ucita tabela pa ulazi/izlazi. ostalo srediti to kod mydatasets(dopuna 2. uslova)--> <div class="row"> <div class="col d-flex justify-content-center"> <h3>Izaberite ulazne kolone:</h3> @@ -118,12 +118,15 @@ <div> <label for="columnReplacers" class="form-label">Unesite zamenu za svaku kolonu:</label> <div id="columnReplacers"> + <!--Ulazne kolone - popunjavanje null vrednosti --> <div *ngFor="let column of selectedDataset.header; let i = index" class="my-3"> <div class="input-group row" *ngIf="getInputById('cb_'+column).checked"> <span class="input-group-text col-2 text-center"> - {{column}} + {{column}} <span class="small" style="color:gray;">({{calculateSumOfNullValuesInCol(column)}} null)</span> </span> - <input type="text" class="form-control col-2"> + <input type="text" class="form-control col-1" [id]="'fillText_'+column"> + <input type="radio" [id]="'fillCol_'+column" class="col-1" + [name]="'delOp_'+column"> <!--OVDE SREDI IZGLED--> <select [id]="'replaceOptions'+i" class="form-control col-2" *ngIf="isNumber(datasetFile[1][i])"> <option @@ -147,6 +150,39 @@ checked></label> </div> </div> + <!--Izlazna kolona - popunjavanje null vrednosti --> + <div *ngFor="let column of selectedDataset.header; let i = index" class="my-3"> <!--moze bez for petlje (this.selectedOutputColumnVal je id), al ne moze ova fja array column onda--> + <div class="input-group row" *ngIf="getInputById('rb_'+column).checked"> + <span class="input-group-text col-2 text-center"> + {{column}} <span class="small" style="color:gray;">({{calculateSumOfNullValuesInCol(column)}} null)</span> + </span> + <input type="text" class="form-control col-1" [id]="'fillText_'+column"> + <input type="radio" [id]="'fillCol_'+column" class="col-1" + [name]="'delOp_'+column"> <!--OVDE SREDI IZGLED--> + <select [id]="'replaceOptions'+i" class="form-control col-2" + *ngIf="isNumber(datasetFile[1][i])"> + <option + *ngFor="let option of Object.keys(ReplaceWith); let optionName of Object.values(ReplaceWith)" + [value]="option"> + {{ optionName }} + </option> + </select> + <select [id]="'replaceOptions'+i" class="form-control col-2" + *ngIf="!isNumber(datasetFile[1][i])"> + <option *ngFor="let option of arrayColumn(datasetFile, i)" + [value]="option"> + {{ option }} + </option> + </select> + <label class="form-control col-2" [for]="'delCol_'+column">Izbriši kolonu + <input type="radio" [id]="'delCol_'+column" + [name]="'delOp_'+column"></label> + <label class="form-control col-2" [for]="'delRows_'+column">Izbriši redove + <input type="radio" [id]="'delRows_'+column" [name]="'delOp_'+column" + checked></label> + </div> + </div> + </div> </div> </div> @@ -348,4 +384,6 @@ </div> </div> -</div>
\ No newline at end of file +</div> + +<button (click)="calculateMeanColValue('Age');calculateMedianColValue('Age');">DUGME</button>
\ No newline at end of file diff --git a/frontend/src/app/_pages/add-model/add-model.component.ts b/frontend/src/app/_pages/add-model/add-model.component.ts index 77a506d5..d47e7426 100644 --- a/frontend/src/app/_pages/add-model/add-model.component.ts +++ b/frontend/src/app/_pages/add-model/add-model.component.ts @@ -1,5 +1,5 @@ import { Component, OnInit, ViewChild } from '@angular/core'; -import Model, { ReplaceWith } from 'src/app/_data/Model'; +import Model, { NullValReplacer, ReplaceWith } from 'src/app/_data/Model'; import { ProblemType, Encoding, ActivationFunction, LossFunction, Optimizer, NullValueOptions } from 'src/app/_data/Model'; import { DatasetLoadComponent } from 'src/app/_elements/dataset-load/dataset-load.component'; import { ModelsService } from 'src/app/_services/models.service'; @@ -154,6 +154,8 @@ export class AddModelComponent implements OnInit { this.tempTestSetDistribution = 90; this.newModel.username = shared.username; + this.newModel.nullValuesReplacers = this.getNullValuesReplacersArray(); + this.models.addModel(this.newModel).subscribe((response) => { callback(response); }, (error) => { @@ -174,7 +176,7 @@ export class AddModelComponent implements OnInit { for (let i = 0; i < checkboxes.length; i++) { let thatCb = <HTMLInputElement>checkboxes[i]; - if (thatCb.checked == true && thatCb.disabled == false) + if (thatCb.checked == true) // && thatCb.disabled == false ne treba nam ovo vise this.newModel.inputColumns.push(thatCb.value); } //console.log(this.checkedInputCols); @@ -231,22 +233,21 @@ export class AddModelComponent implements OnInit { this.datasets.getDatasetFile(dataset.fileId).subscribe((file: string | undefined) => { if (file) { this.datasetFile = this.csv.csvToArray(file, (dataset.delimiter == "razmak") ? " " : (dataset.delimiter == "") ? "," : dataset.delimiter); - for (let i = this.datasetFile.length - 1; i >= 0; i--) { //moguce da je vise redova na kraju fajla prazno i sl. + /*for (let i = this.datasetFile.length - 1; i >= 0; i--) { //moguce da je vise redova na kraju fajla prazno i sl. if (this.datasetFile[i].length != this.datasetFile[0].length) this.datasetFile[i].pop(); else break; //nema potrebe dalje - } + }*/ console.log(this.datasetFile); + this.resetCbsAndRbs(); + //this.refreshThreeNullValueRadioOptions(); } }); //this.datasetHasHeader = false; - - this.resetCbsAndRbs(); } scrollToNextForm() { - console.log("USAO U SCROLL"); (<HTMLSelectElement>document.getElementById("selectInAndOuts")).scrollIntoView({ behavior: "smooth", block: "start", @@ -292,12 +293,116 @@ export class AddModelComponent implements OnInit { }); } + refreshThreeNullValueRadioOptions() { + //console.log((<HTMLInputElement>document.getElementById("delRows")).checked); + const input = document.getElementById('delRows'); + console.log(input); // 👉️ input#subscribe + +// ✅ Works + //input.checked = true; + (<HTMLInputElement>document.getElementById("delRows")).checked = true; + (<HTMLInputElement>document.getElementById("delCols")).checked = false; + (<HTMLInputElement>document.getElementById("replace")).checked = false; + } + + isChecked(someId: string) { //proveri ako je element sa datim ID-em cekiran + //console.log(someId); + //console.log((<HTMLInputElement>document.getElementById(someId)).checked); + return (<HTMLInputElement>document.getElementById(someId)).checked; + } + isNumber(value: string | number): boolean { return ((value != null) && (value !== '') && !isNaN(Number(value.toString()))); } + findIndexOfCol(colName: string) : number { + if (this.datasetFile) + for (let i = 0; i < this.datasetFile[0].length; i++) + if (colName === this.datasetFile[0][i]) + return i; + return -1; + } + calculateSumOfNullValuesInCol(colName: string): number { + //console.log(this.datasetFile); + if (this.datasetFile) { + let colIndex = this.findIndexOfCol(colName); + let sumOfNulls = 0; + for (let i = 1; i < this.datasetFile.length; i++) + if (this.datasetFile[i][colIndex] == '') + ++sumOfNulls; + //console.log(sumOfNulls); + return sumOfNulls; + } + return -1; + } + calculateMeanColValue(colName: string): number { + if (this.datasetFile) { + let colIndex = this.findIndexOfCol(colName); + let sum = 0; + let n = 0; + for (let i = 1; i < this.datasetFile.length; i++) + if (this.datasetFile[i][colIndex] != '') { + sum += Number(this.datasetFile[i][colIndex]); + ++n; + } + console.log(sum / n); + return sum / n; + } + return 0; + } + calculateMedianColValue(colName: string): number { + if (this.datasetFile) { + let array = []; + let colIndex = this.findIndexOfCol(colName); + for (let i = 1; i < this.datasetFile.length; i++) + if (this.datasetFile[i][colIndex] != '') + array.push(Number(this.datasetFile[i][colIndex])); + + array.sort(); + if (array.length % 2 == 0) + return array[array.length / 2 - 1] / 2; + else + return array[(array.length - 1) / 2]; + } + return 0; + } + + getNullValuesReplacersArray() : NullValReplacer[] { + /*let array: NullValReplacer[] = []; + + //za svaku kolonu + if (this.datasetFile) { + + if ((<HTMLInputElement>document.getElementById("delRows")).checked) { //obrisi sve redove + this.newModel.nullValues = NullValueOptions.DeleteRows; + } + else if ((<HTMLInputElement>document.getElementById("delCols")).checked) { + this.newModel.nullValues = NullValueOptions.DeleteColumns; + } + else if ((<HTMLInputElement>document.getElementById("replace")).checked) { + this.newModel.nullValues = NullValueOptions.Replace;*/ + + //for petlje + + //} + + //proveri ova prva tri rba, ako je 3. cekiran, ide for petlja + //if ((<HTMLInputElement>document.getElementById("delCol_" + column)).checked) + + //for (let i = 0; i < this.datasetFile[0].length; i++) { //svi hederi + //let column = this.datasetFile[0][i]; + + //if ((<HTMLInputElement>document.getElementById("delCol_" + column)).checked) //obrisi celu kolonu + //var e = (<HTMLInputElement>document.getElementById("organization")).value; + //} + //} + + + return []; + } + getInputById(id: string): HTMLInputElement { return document.getElementById(id) as HTMLInputElement; } diff --git a/frontend/src/app/_pages/filter-datasets/filter-datasets.component.ts b/frontend/src/app/_pages/filter-datasets/filter-datasets.component.ts index f6b78ded..b75decf2 100644 --- a/frontend/src/app/_pages/filter-datasets/filter-datasets.component.ts +++ b/frontend/src/app/_pages/filter-datasets/filter-datasets.component.ts @@ -32,9 +32,18 @@ export class FilterDatasetsComponent implements OnInit { newDataset.isPublic = false; newDataset.lastUpdated = new Date(); newDataset.username = decodedToken.name; + let name=prompt("Unesite naziv dataset-a",newDataset.name); + newDataset.name=name as string; + if(name!=null && name!="") this.datasets.addDataset(newDataset).subscribe((response:string)=>{ console.log(response); + alert("Uspenso ste dodali dataset sa imenom "+newDataset.name); + },(error)=>{ + alert("Vec imate dataset sa istim imenom molim vas unesite drugo ime"); + + }); + }; } diff --git a/frontend/src/app/_pages/my-models/my-models.component.html b/frontend/src/app/_pages/my-models/my-models.component.html index b6926771..e2533d89 100644 --- a/frontend/src/app/_pages/my-models/my-models.component.html +++ b/frontend/src/app/_pages/my-models/my-models.component.html @@ -8,6 +8,7 @@ <div class="row"> <div class="col-sm-4" style="margin-bottom: 10px;" *ngFor="let model of myModels"> <app-item-model [model]="model"></app-item-model> + <app-annvisual align-items-center [model]="model" style="width: 100%;"></app-annvisual> <div style="width: 25%; margin: auto;"> <button mat-raised-button color="primary" (click)="deleteThisModel(model)" style="margin-top: 3px; width: 100%;">Obriši</button> diff --git a/frontend/src/app/_services/auth.service.ts b/frontend/src/app/_services/auth.service.ts index 449b8802..ccfbe15f 100644 --- a/frontend/src/app/_services/auth.service.ts +++ b/frontend/src/app/_services/auth.service.ts @@ -24,10 +24,16 @@ export class AuthService { return this.http.post(`${API_SETTINGS.apiURL}/auth/register`, { ...user }, { responseType: 'text' }); } + getGuestToken(){ + return this.http.post(`${API_SETTINGS.apiURL}/auth/guestToken`, {}, { responseType: 'text' }); + } + isAuthenticated(): boolean { if (this.cookie.check('token')) { var token = this.cookie.get('token'); - return !jwtHelper.isTokenExpired(token); + var property=jwtHelper.decodeToken(this.cookie.get('token')); + var username=property['name']; + return !jwtHelper.isTokenExpired(token) && username!=""; } return false; } @@ -41,12 +47,30 @@ export class AuthService { if (!exp) { exp = new Date(); } - this.refresher = setTimeout(() => { - console.log('refreshing token!'); - this.http.post(`${API_SETTINGS.apiURL}/auth/renewJwt`, {}, { headers: this.authHeader(), responseType: 'text' }).subscribe((response) => { - this.authenticate(response); - }); - }, exp.getTime() - new Date().getTime() - 60000); + var property=jwtHelper.decodeToken(this.cookie.get('token')); + var username=property['name']; + if(username!=""){ + this.refresher = setTimeout(() => { + console.log('refreshing token!'); + this.http.post(`${API_SETTINGS.apiURL}/auth/renewJwt`, {}, { headers: this.authHeader(), responseType: 'text' }).subscribe((response) => { + this.authenticate(response); + }); + }, exp.getTime() - new Date().getTime() - 60000); + } + else{ + this.refresher = setTimeout(() => { + console.log('refreshing token!'); + this.getGuestToken().subscribe((response) => { + this.authenticate(response); + }); + }, exp.getTime() - new Date().getTime() - 60000); + } + } + + addGuestToken(){ + this.getGuestToken().subscribe((token)=>{ + this.authenticate(token); + }); } authenticate(token: string) { @@ -74,6 +98,7 @@ export class AuthService { if (this.refresher) clearTimeout(this.refresher); this.shared.loggedIn = false; + this.addGuestToken(); } authHeader() { diff --git a/frontend/src/app/_services/csv-parse.service.ts b/frontend/src/app/_services/csv-parse.service.ts index d53f504e..b9b761a0 100644 --- a/frontend/src/app/_services/csv-parse.service.ts +++ b/frontend/src/app/_services/csv-parse.service.ts @@ -45,7 +45,8 @@ export class CsvParseService { strMatchedValue = arrMatches[3]; } - arrData[arrData.length - 1].push(strMatchedValue); + if (strMatchedValue.length > 0) + arrData[arrData.length - 1].push(strMatchedValue); } return (arrData); diff --git a/frontend/src/app/app.component.ts b/frontend/src/app/app.component.ts index f5ae5786..8c6f8452 100644 --- a/frontend/src/app/app.component.ts +++ b/frontend/src/app/app.component.ts @@ -2,6 +2,7 @@ import { Component, OnInit } from '@angular/core'; import { Title } from '@angular/platform-browser'; import { Router, NavigationEnd, ActivatedRoute } from '@angular/router'; import { filter, map } from 'rxjs'; +import { AuthService } from './_services/auth.service'; @Component({ selector: 'app-root', @@ -10,7 +11,7 @@ import { filter, map } from 'rxjs'; }) export class AppComponent implements OnInit { - constructor(private router: Router, private titleService: Title) { } + constructor(private router: Router, private titleService: Title,private authService:AuthService) { } ngOnInit() { this.router.events @@ -33,5 +34,9 @@ export class AppComponent implements OnInit { this.titleService.setTitle(`${title} - Igrannonica`); } }); + if(!this.authService.isAuthenticated()) + { + this.authService.addGuestToken(); + } } } diff --git a/frontend/src/app/app.module.ts b/frontend/src/app/app.module.ts index 5d7af9d2..4efab17e 100644 --- a/frontend/src/app/app.module.ts +++ b/frontend/src/app/app.module.ts @@ -38,6 +38,7 @@ import { DatatableComponent } from './_elements/datatable/datatable.component'; import { FilterDatasetsComponent } from './_pages/filter-datasets/filter-datasets.component'; import { ReactiveBackgroundComponent } from './_elements/reactive-background/reactive-background.component'; import { ItemModelComponent } from './_elements/item-model/item-model.component'; +import { AnnvisualComponent } from './_elements/annvisual/annvisual.component'; @NgModule({ declarations: [ @@ -65,7 +66,8 @@ import { ItemModelComponent } from './_elements/item-model/item-model.component' DatatableComponent, FilterDatasetsComponent, ReactiveBackgroundComponent, - ItemModelComponent + ItemModelComponent, + AnnvisualComponent ], imports: [ BrowserModule, |