diff --git a/examples/mnist.ipyg b/examples/mnist.ipyg index 0b852e0f..e42bb432 100644 --- a/examples/mnist.ipyg +++ b/examples/mnist.ipyg @@ -5,11 +5,9 @@ "id": 2443477874008, "title": "Model Train", "block_type": "OCBCodeBlock", - "source": "model.fit(x=x_train,y=y_train, epochs=4)\r\n", - "stdout": "Epoch 1/4\n\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1875/1875 [==============================] - 10s 4ms/step - loss: 0.2116 - accuracy: 0.9367\nEpoch 2/4\n\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1875/1875 [==============================] - 7s 4ms/step - loss: 0.0853 - accuracy: 0.9738\nEpoch 3/4\n\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1875/1875 [==============================] - 7s 4ms/step - loss: 0.0597 - accuracy: 0.9813\nEpoch 4/4\n\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1875/1875 [==============================] - 7s 4ms/step - loss: 0.0472 - accuracy: 0.9848\n", "splitter_pos": [ 85, - 259 + 261 ], "position": [ 1062.374999999999, @@ -21,8 +19,7 @@ "title_metadata": { "color": "white", "font": "Ubuntu", - "size": 10, - "padding": 4.0 + "size": 10 } }, "sockets": [ @@ -31,13 +28,13 @@ "type": "input", "position": [ 0.0, - 42.0 + 44.0 ], "metadata": { "color": "#e02c2c", "linecolor": "#FF000000", "linewidth": 1.0, - "radius": 6.0 + "radius": 10.0 } }, { @@ -45,26 +42,26 @@ "type": "output", "position": [ 1064.0, - 42.0 + 44.0 ], "metadata": { "color": "#35bc31", "linecolor": "#FF000000", "linewidth": 1.0, - "radius": 6.0 + "radius": 10.0 } } - ] + ], + "source": "model.fit(x=x_train,y=y_train, epochs=4)\r\n", + "stdout": "Epoch 1/4\n\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1875/1875 [==============================] - 10s 4ms/step - loss: 0.2116 - accuracy: 0.9367\nEpoch 2/4\n\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1875/1875 [==============================] - 7s 4ms/step - loss: 0.0853 - accuracy: 0.9738\nEpoch 3/4\n\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1875/1875 [==============================] - 7s 4ms/step - loss: 0.0597 - accuracy: 0.9813\nEpoch 4/4\n\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1875/1875 [==============================] - 7s 4ms/step - loss: 0.0472 - accuracy: 0.9848\n" }, { "id": 2443477924600, "title": "Keras Model Predict", "block_type": "OCBCodeBlock", - "source": "rd_index = np.random.randint(len(x_test))\r\nprediction = np.argmax(model.predict(x_test[rd_index].reshape(1, 28, 28, 1)))\r\nplt.imshow(x_test[rd_index], cmap='gray')\r\nplt.title(\"Predicted: \" + str(prediction))", - "stdout": 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E4wARsS4iPomI7cB9wCmta6aZNWooZ+MF3A8sj4g7qqaPq3rbN4A3mt88M2uWmkM2S+oBXgReB7YXk78HXExlFz6AVcDlxcm81LI8ZHMdJk2alKyvWLGitLZ69erkvD09Pcl6f3/yn9S6UNmQzUM5G/8SMNjMP2u0UWbWPv4GnVkmHHazTDjsZplw2M0y4bCbZcJhN8tEzX72pq7M/exmLVfWz+4tu1kmHHazTDjsZplw2M0y4bCbZcJhN8uEw26WiXYP2bwBqL7A+pBiWjfq1rZ1a7vAbatXM9t2ZFmhrV+q+dTKpb5uvTddt7atW9sFblu92tU278abZcJhN8tEp8M+p8PrT+nWtnVru8Btq1db2tbRY3Yza59Ob9nNrE0cdrNMdCTsks6T9JaklZKu70QbykhaJen1Yhjqjo5PV4yht17SG1XTxkh6VtLbxc9Bx9jrUNu6YhjvxDDjHf3sOj38eduP2SXtDawAvgKsAZYAF0fEm21tSAlJq4BpEdHxL2BI+jLwEfDjiDi+mHYLsDEibi7+oxwdEd/tkrbdCHzU6WG8i9GKxlUPMw5cAFxKBz+7RLsuog2fWye27KcAKyPinYjYCjwCzOhAO7peRLwAbBwweQYwt3g+l8ofS9uVtK0rRER/RCwtnm8Gdgwz3tHPLtGutuhE2McD71a9XkN3jfcewM8lvSJpdqcbM4ixVcNsvQeM7WRjBlFzGO92GjDMeNd8dvUMf94on6D7tJ6IOAn4E+CqYne1K0XlGKyb+k6HNIx3uwwyzPhOnfzs6h3+vFGdCPta4Iiq14cX07pCRKwtfq4HnqD7hqJet2ME3eLn+g63Z6duGsZ7sGHG6YLPrpPDn3ci7EuAYyUdJWkE8C3gqQ6041MkHVicOEHSgcA5dN9Q1E8BM4vnM4EnO9iWXXTLMN5lw4zT4c+u48OfR0TbH8B0KmfkfwP8XSfaUNKuScCvi8eyTrcNeJjKbt3HVM5tzAIOBhYDbwPPAWO6qG0/oTK092tUgjWuQ23robKL/hrwavGY3unPLtGutnxu/rqsWSZ8gs4sEw67WSYcdrNMOOxmmXDYzTLhsJtlwmE3y8T/Aadu5JsoV8cdAAAAAElFTkSuQmCC\n", "splitter_pos": [ 0, - 278 + 280 ], "position": [ 2330.066406249998, @@ -76,8 +73,7 @@ "title_metadata": { "color": "white", "font": "Ubuntu", - "size": 10, - "padding": 4.0 + "size": 10 } }, "sockets": [ @@ -86,26 +82,26 @@ "type": "input", "position": [ 0.0, - 42.0 + 44.0 ], "metadata": { "color": "#FF55FFF0", "linecolor": "#FF000000", "linewidth": 1.0, - "radius": 6.0 + "radius": 10.0 } } - ] + ], + "source": "rd_index = np.random.randint(len(x_test))\r\nprediction = np.argmax(model.predict(x_test[rd_index].reshape(1, 28, 28, 1)))\r\nplt.imshow(x_test[rd_index], cmap='gray')\r\nplt.title(\"Predicted: \" + str(prediction))", + "stdout": "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\n" }, { "id": 2443477997032, "title": "Keras Model eval", "block_type": "OCBCodeBlock", - "source": "metrics = model.evaluate(x_test, y_test)\r\nprint(f\"mean_loss:{metrics[0]:.2f}, mean_acc:{metrics[1]:.2f}\")\r\n", - "stdout": "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r313/313 [==============================] - 1s 2ms/step - loss: 0.0552 - accuracy: 0.9823\nmean_loss:0.06, mean_acc:0.98\n", "splitter_pos": [ - 76, - 76 + 77, + 77 ], "position": [ 2295.17578125, @@ -117,8 +113,7 @@ "title_metadata": { "color": "white", "font": "Ubuntu", - "size": 10, - "padding": 4.0 + "size": 10 } }, "sockets": [ @@ -127,25 +122,25 @@ "type": "input", "position": [ 0.0, - 42.0 + 44.0 ], "metadata": { "color": "#FF55FFF0", "linecolor": "#FF000000", "linewidth": 1.0, - "radius": 6.0 + "radius": 10.0 } } - ] + ], + "source": "metrics = model.evaluate(x_test, y_test)\r\nprint(f\"mean_loss:{metrics[0]:.2f}, mean_acc:{metrics[1]:.2f}\")\r\n", + "stdout": "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r313/313 [==============================] - 1s 2ms/step - loss: 0.0552 - accuracy: 0.9823\nmean_loss:0.06, mean_acc:0.98\n" }, { "id": 2443478874872, "title": "Load MNIST Dataset", "block_type": "OCBCodeBlock", - "source": "from tensorflow.keras.datasets import mnist\r\n(x_train, y_train), (x_test, y_test) = mnist.load_data()\r\n", - "stdout": "", "splitter_pos": [ - 86, + 88, 0 ], "position": [ @@ -158,8 +153,7 @@ "title_metadata": { "color": "white", "font": "Ubuntu", - "size": 10, - "padding": 4.0 + "size": 10 } }, "sockets": [ @@ -168,26 +162,26 @@ "type": "output", "position": [ 850.0, - 42.0 + 44.0 ], "metadata": { "color": "#FF55FFF0", "linecolor": "#FF000000", "linewidth": 1.0, - "radius": 6.0 + "radius": 10.0 } } - ] + ], + "source": "from tensorflow.keras.datasets import mnist\r\n(x_train, y_train), (x_test, y_test) = mnist.load_data()\r\n", + "stdout": "" }, { "id": 2443478982728, "title": "Normalize Image Dataset", "block_type": "OCBCodeBlock", - "source": "x_train = x_train.astype('float32') / 255.0\r\nx_test = x_test.astype('float32') / 255.0\r\n\r\nx_train = x_train.reshape(x_train.shape[0], 28, 28, 1)\r\nx_test = x_test.reshape(x_test.shape[0], 28, 28, 1)\r\n\r\nprint('train:', x_train.shape, '|test:', x_test.shape)\r\n", - "stdout": "train: (60000, 28, 28, 1) |test: (10000, 28, 28, 1)\n", "splitter_pos": [ - 206, - 85 + 199, + 94 ], "position": [ 44.48828125000068, @@ -199,8 +193,7 @@ "title_metadata": { "color": "white", "font": "Ubuntu", - "size": 10, - "padding": 4.0 + "size": 10 } }, "sockets": [ @@ -209,13 +202,13 @@ "type": "input", "position": [ 0.0, - 42.0 + 44.0 ], "metadata": { "color": "#FF55FFF0", "linecolor": "#FF000000", "linewidth": 1.0, - "radius": 6.0 + "radius": 10.0 } }, { @@ -223,25 +216,25 @@ "type": "output", "position": [ 855.0, - 42.0 + 44.0 ], "metadata": { "color": "#FF55FFF0", "linecolor": "#FF000000", "linewidth": 1.0, - "radius": 6.0 + "radius": 10.0 } } - ] + ], + "source": "x_train = x_train.astype('float32') / 255.0\r\nx_test = x_test.astype('float32') / 255.0\r\n\r\nx_train = x_train.reshape(x_train.shape[0], 28, 28, 1)\r\nx_test = x_test.reshape(x_test.shape[0], 28, 28, 1)\r\n\r\nprint('train:', x_train.shape, '|test:', x_test.shape)\r\n", + "stdout": "train: (60000, 28, 28, 1) |test: (10000, 28, 28, 1)\n" }, { "id": 2443479017656, "title": "Build Keras CNN", "block_type": "OCBCodeBlock", - "source": "import tensorflow as tf\r\nfrom tensorflow.keras.layers import (Dense, Flatten,\r\nConv2D, MaxPooling2D, Dropout)\r\nfrom tensorflow.keras.models import Sequential\r\n\r\nmodel = Sequential()\r\nmodel.add(Conv2D(28, kernel_size=(3,3), input_shape=x_train.shape[1:]))\r\nmodel.add(MaxPooling2D(pool_size=(2, 2)))\r\nmodel.add(Flatten())\r\nmodel.add(Dense(128, activation=tf.nn.relu))\r\nmodel.add(Dropout(0.2))\r\nmodel.add(Dense(10,activation=tf.nn.softmax))\r\n\r\nmodel.compile(optimizer='adam', \r\n loss='sparse_categorical_crossentropy', \r\n metrics=['accuracy'])\r\n", - "stdout": "", "splitter_pos": [ - 418, + 420, 0 ], "position": [ @@ -254,8 +247,7 @@ "title_metadata": { "color": "white", "font": "Ubuntu", - "size": 10, - "padding": 4.0 + "size": 10 } }, "sockets": [ @@ -264,26 +256,26 @@ "type": "output", "position": [ 1002.0, - 42.0 + 44.0 ], "metadata": { "color": "#FF55FFF0", "linecolor": "#FF000000", "linewidth": 1.0, - "radius": 6.0 + "radius": 10.0 } } - ] + ], + "source": "import tensorflow as tf\r\nfrom tensorflow.keras.layers import (Dense, Flatten,\r\nConv2D, MaxPooling2D, Dropout)\r\nfrom tensorflow.keras.models import Sequential\r\n\r\nmodel = Sequential()\r\nmodel.add(Conv2D(28, kernel_size=(3,3), input_shape=x_train.shape[1:]))\r\nmodel.add(MaxPooling2D(pool_size=(2, 2)))\r\nmodel.add(Flatten())\r\nmodel.add(Dense(128, activation=tf.nn.relu))\r\nmodel.add(Dropout(0.2))\r\nmodel.add(Dense(10,activation=tf.nn.softmax))\r\n\r\nmodel.compile(optimizer='adam', \r\n loss='sparse_categorical_crossentropy', \r\n metrics=['accuracy'])\r\n", + "stdout": "" }, { "id": 2828158533848, "title": "Plot Image Dataset Example", "block_type": "OCBCodeBlock", - "source": "import matplotlib.pyplot as plt\r\nimport numpy as np\r\n\r\n# Display an example from the dataset\r\nrd_index = np.random.randint(len(x_train))\r\nplt.imshow(x_train[rd_index], cmap='gray')\r\nplt.title('Class '+ str(y_train[rd_index]))\r\n", - "stdout": "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\n", "splitter_pos": [ 0, - 274 + 276 ], "position": [ 103.60937500000011, @@ -295,8 +287,7 @@ "title_metadata": { "color": "white", "font": "Ubuntu", - "size": 10, - "padding": 4.0 + "size": 10 } }, "sockets": [ @@ -305,16 +296,18 @@ "type": "input", "position": [ 0.0, - 42.0 + 44.0 ], "metadata": { "color": "#FF55FFF0", "linecolor": "#FF000000", "linewidth": 1.0, - "radius": 6.0 + "radius": 10.0 } } - ] + ], + "source": "import matplotlib.pyplot as plt\r\nimport numpy as np\r\n\r\n# Display an example from the dataset\r\nrd_index = np.random.randint(len(x_train))\r\nplt.imshow(x_train[rd_index], cmap='gray')\r\nplt.title('Class '+ str(y_train[rd_index]))\r\n", + "stdout": "iVBORw0KGgoAAAANSUhEUgAAAPsAAAEICAYAAACZA4KlAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAAQyklEQVR4nO3dfaxUdX7H8fdHquIqoogSfGBZtvQP1scNMd1IUBQ3SqRA1viwmw0qFjUS61PRsPUhbWh0q1tXg0ZWzaK1WlqlqHGzojWrTawBkUVUVlmCCkHR1Sq01UX59o85mCve+c29M2fmDPf3eSU3d+Z858z5MuFzz5nz9FNEYGYD3x5VN2BmneGwm2XCYTfLhMNulgmH3SwTDrtZJhz2jEi6UdI/Vd2HVcNhH2Ak/VDSCknbJG2W9CtJEyrqZbSkZyX9r6S1kiZX0YfVOOwDiKQrgduAvwdGAKOAO4FpFbX0EPAycBDwE+DfJB1cUS/Zc9gHCElDgb8FLo2IRyPifyJie0Q8HhF/XWeef5X0rqSPJT0n6Ts9alMkvSZpq6RNkq4upg+X9ISk/5b0oaTnJX3t/5GkPwO+C9wQEf8XEY8ArwA/aMe/3xpz2AeO7wGDgSX9mOdXwFjgEGAl8GCP2r3ARRExBDgS+I9i+lXARuBgalsP84Dezrn+DrA+Irb2mPbbYrpVwGEfOA4CPoiIz/s6Q0TcFxFbI+Iz4EbgmGILAWA7ME7S/hHxUUSs7DF9JPDNYsvh+ej9Aov9gI93mfYxMKQf/yYrkcM+cPwBGC7pT/ryYkmDJN0k6feSPgE2FKXhxe8fAFOAtyT9RtL3iun/AKwDnpK0XtK1dRaxDdh/l2n7A1t7ea11gMM+cLwAfAZM7+Prf0htx91kYCgwupgugIhYHhHTqG3i/zuwuJi+NSKuiogxwF8AV0o6pZf3fxUYI6nnmvyYYrpVwGEfICLiY+B6YIGk6ZK+IWlPSadL+mkvswyh9sfhD8A3qO3BB0DSXpJ+JGloRGwHPgF2FLUzJP2pJFHbLP9iZ22Xft4AVgE3SBosaQZwNPBIif9s6weHfQCJiFuBK4G/Ad4H3gHmUFsz7+p+4C1gE/Aa8F+71H8MbCg28S8GflRMHws8TW0z/QXgzoh4tk5L5wDjgY+Am4AzI+L9Zv5t1jr55hVmefCa3SwTDrtZJhx2s0w47GaZ6NMJGGWR5L2BZm0WEeptektrdkmnSfqdpHWJM6nMrAs0fehN0iDgDeBUahdGLAfOjYjXEvN4zW7WZu1Ysx8PrIuI9RHxR+Bhqrtu2swaaCXsh1E7Q2unjcW0r5A0u7hzyooWlmVmLWr7DrqIWAgsBG/Gm1WplTX7JuCIHs8PL6aZWRdqJezLgbGSviVpL2oXPTxWTltmVramN+Mj4nNJc4BfA4OA+yLC1yqbdamOXvXm7+xm7deWk2rMbPfhsJtlwmE3y4TDbpYJh90sEw67WSYcdrNMOOxmmXDYzTLhsJtlwmE3y4TDbpYJh90sEw67WSYcdrNMOOxmmXDYzTLhsJtlwmE3y4TDbpYJh90sEw67WSYcdrNMOOxmmXDYzTLhsJtlwmE3y4TDbpYJh90sE00P2WwDw+DBg5P1E044IVmfO3dusn7qqaf2u6edpF4HI/1SoxGIU/PPmzcvOe/NN9+crO/YsSNZ70YthV3SBmAr8AXweUSML6MpMytfGWv2SRHxQQnvY2Zt5O/sZploNewBPCXpJUmze3uBpNmSVkha0eKyzKwFrW7GT4iITZIOAZZJWhsRz/V8QUQsBBYCSErvUTGztmlpzR4Rm4rfW4AlwPFlNGVm5Ws67JL2lTRk52Pg+8Cashozs3Kp0bHKujNKY6itzaH2deCfI2J+g3m8Gd9h06ZNS9ZPPvnkZH3OnDlltrPbuOyyy5L1BQsWdKiT/ouIXk8waPo7e0SsB45puiMz6ygfejPLhMNulgmH3SwTDrtZJhx2s0w0feitqYX50FtTGl3quc8++9St3Xbbbcl5Z82a1UxLA96LL76YrJ944onJ+vbt28tsp1/qHXrzmt0sEw67WSYcdrNMOOxmmXDYzTLhsJtlwmE3y4SPs+8GzjjjjGR96dKlHerk61atWpWsb9y4sW3L3n///ZP1iRMntm3Z8+cnr+bm+uuvb9uyG/FxdrPMOexmmXDYzTLhsJtlwmE3y4TDbpYJh90sEx6yuQtMnz49Wb/77rs700gvli9fnqyfd955yfratWtL7OarDj744GQ99bk1usX2QOQ1u1kmHHazTDjsZplw2M0y4bCbZcJhN8uEw26WCR9nL8HgwYOT9RdeeCFZP/TQQ5P14cOH97unnbZt25asn3POOcn6mjVrkvV33nmn3z2V5f3330/Wly1bVrd2+umnJ+fda6+9muqpmzVcs0u6T9IWSWt6TBsmaZmkN4vfB7a3TTNrVV82438JnLbLtGuBZyJiLPBM8dzMuljDsEfEc8CHu0yeBiwqHi8CppfblpmVrdnv7CMiYnPx+F1gRL0XSpoNzG5yOWZWkpZ30EVEpG4kGRELgYXgG06aVanZQ2/vSRoJUPzeUl5LZtYOzYb9MWBm8XgmUN29jM2sTxpuxkt6CDgJGC5pI3ADcBOwWNIs4C3grHY22e322CP9N/Poo49u6/JTx7ovvPDC5LxPP/102e10jbvuuqtubcqUKcl5G9V3Rw3DHhHn1imdUnIvZtZGPl3WLBMOu1kmHHazTDjsZplw2M0y4UtcS3DFFVe09f0bXaaaOrw2kA+tNTJ58uS6tSOPPLKDnXQHr9nNMuGwm2XCYTfLhMNulgmH3SwTDrtZJhx2s0z4OHsfDR06tG5txowZbV12o9s953osvdHtnidMmFC3NmrUqLLb6Xpes5tlwmE3y4TDbpYJh90sEw67WSYcdrNMOOxmmfBx9j66+uqr69aOO+64lt57+fLlyXqjYZNzdfnllyfr1113XdPvvWVLetyTl19+uen3rorX7GaZcNjNMuGwm2XCYTfLhMNulgmH3SwTDrtZJnycvTBu3LhkferUqW1b9sMPP5ysp4ZkztncuXPb9t7r1q1L1pcsWdK2ZbdLwzW7pPskbZG0pse0GyVtkrSq+Bl4g1mbDTB92Yz/JXBaL9P/MSKOLX6eLLctMytbw7BHxHPAhx3oxczaqJUddHMkrS428w+s9yJJsyWtkLSihWWZWYuaDftdwLeBY4HNwK31XhgRCyNifESMb3JZZlaCpsIeEe9FxBcRsQP4BXB8uW2ZWdmaCrukkT2ezgB8DaZZl2t4nF3SQ8BJwHBJG4EbgJMkHQsEsAG4qH0tdsbIkSOT9aOOOqpubceOHcl5H3jggWT9nnvuSdYHqgMOOCBZv+OOO5L11L38G9m0aVOy3uhe/bujhmGPiHN7mXxvG3oxszby6bJmmXDYzTLhsJtlwmE3y4TDbpYJX+Jagk8//TRZv+CCCzrUSfdJHV5bsGBBct52Hv666KL00eJGh+Z2R16zm2XCYTfLhMNulgmH3SwTDrtZJhx2s0w47GaZ8HF2a6tDDjmkbq3V4+gbNmxI1q+55pq6tVWrVrW07N2R1+xmmXDYzTLhsJtlwmE3y4TDbpYJh90sEw67WSZ8nL0Ee+yR/ps5ZsyYZH39+vVltlOqYcOGJeujRo1K1hcvXlxmO18xadKkZP3tt99u27J3R16zm2XCYTfLhMNulgmH3SwTDrtZJhx2s0w47GaZ6MuQzUcA9wMjqA3RvDAifi5pGPAvwGhqwzafFREfta/V7jV48OBkfenSpcn6zJkzk/WVK1f2u6e+Ov/885P1yZMnJ+tVDm28devWypa9O+rLmv1z4KqIGAf8OXCppHHAtcAzETEWeKZ4bmZdqmHYI2JzRKwsHm8FXgcOA6YBi4qXLQKmt6lHMytBv76zSxoNHAe8CIyIiM1F6V1qm/lm1qX6fG68pP2AR4DLI+ITSV/WIiIkRZ35ZgOzW23UzFrTpzW7pD2pBf3BiHi0mPyepJFFfSSwpbd5I2JhRIyPiPFlNGxmzWkYdtVW4fcCr0fEz3qUHgN27kaeCaR3OZtZpfqyGX8C8GPgFUmrimnzgJuAxZJmAW8BZ7WlwwFg3LhxyfqiRYuS9alTpybrhx9+eN1a6nbKACeeeGKyvu+++ybrrXjyySeT9TvvvDNZ37ZtW5ntDHgNwx4R/wmoTvmUctsxs3bxGXRmmXDYzTLhsJtlwmE3y4TDbpYJh90sE4ro9SzX9iyszim13aDR7aAvueSSurX58+cn5x0yZEhTPe302WefJeup3vfcc8+Wlt2q1OW9Z599dnLe7du3l91OFiKi10PlXrObZcJhN8uEw26WCYfdLBMOu1kmHHazTDjsZpnwkM2FHTt2JOsLFixo+r1vv/32pucF2HvvvVuavxWrV69O1h9//PFk/ZZbbqlb83H0zvKa3SwTDrtZJhx2s0w47GaZcNjNMuGwm2XCYTfLhK9nL8GgQYOS9YkTJybrF198cbJ+5pln9runvtqypdeBfL40adKkZH3t2rVltmMl8PXsZplz2M0y4bCbZcJhN8uEw26WCYfdLBMOu1kmGh5nl3QEcD8wAghgYUT8XNKNwF8C7xcvnRcRyQG3B+pxdrNuUu84e1/CPhIYGRErJQ0BXgKmA2cB2yKi/t0Jvv5eDrtZm9ULe8M71UTEZmBz8XirpNeBw8ptz8zarV/f2SWNBo4DXiwmzZG0WtJ9kg6sM89sSSskrWitVTNrRZ/PjZe0H/AbYH5EPCppBPABte/xf0dtU/+CBu/hzXizNmv6OzuApD2BJ4BfR8TPeqmPBp6IiCMbvI/DbtZmTV8II0nAvcDrPYNe7LjbaQawptUmzax9+rI3fgLwPPAKsPN+y/OAc4FjqW3GbwAuKnbmpd7La3azNmtpM74sDrtZ+/l6drPMOexmmXDYzTLhsJtlwmE3y4TDbpYJh90sEw67WSYcdrNMOOxmmXDYzTLhsJtlwmE3y4TDbpaJhjecLNkHwFs9ng8vpnWjbu2tW/sC99asMnv7Zr1CR69n/9rCpRURMb6yBhK6tbdu7QvcW7M61Zs3480y4bCbZaLqsC+sePkp3dpbt/YF7q1ZHemt0u/sZtY5Va/ZzaxDHHazTFQSdkmnSfqdpHWSrq2ih3okbZD0iqRVVY9PV4yht0XSmh7ThklaJunN4nevY+xV1NuNkjYVn90qSVMq6u0ISc9Kek3Sq5L+qphe6WeX6Ksjn1vHv7NLGgS8AZwKbASWA+dGxGsdbaQOSRuA8RFR+QkYkiYC24D7dw6tJemnwIcRcVPxh/LAiLimS3q7kX4O492m3uoNM34eFX52ZQ5/3owq1uzHA+siYn1E/BF4GJhWQR9dLyKeAz7cZfI0YFHxeBG1/ywdV6e3rhARmyNiZfF4K7BzmPFKP7tEXx1RRdgPA97p8Xwj3TXeewBPSXpJ0uyqm+nFiB7DbL0LjKiymV40HMa7k3YZZrxrPrtmhj9vlXfQfd2EiPgucDpwabG52pWi9h2sm46d3gV8m9oYgJuBW6tsphhm/BHg8oj4pGetys+ul7468rlVEfZNwBE9nh9eTOsKEbGp+L0FWELta0c3eW/nCLrF7y0V9/OliHgvIr6IiB3AL6jwsyuGGX8EeDAiHi0mV/7Z9dZXpz63KsK+HBgr6VuS9gLOAR6roI+vkbRvseMESfsC36f7hqJ+DJhZPJ4JLK2wl6/olmG86w0zTsWfXeXDn0dEx3+AKdT2yP8e+EkVPdTpawzw2+Ln1ap7Ax6itlm3ndq+jVnAQcAzwJvA08CwLurtAWpDe6+mFqyRFfU2gdom+mpgVfEzperPLtFXRz43ny5rlgnvoDPLhMNulgmH3SwTDrtZJhx2s0w47GaZcNjNMvH/q8Ie6tP1LgoAAAAASUVORK5CYII=\n" } ], "edges": [ diff --git a/opencodeblocks/__main__.py b/opencodeblocks/__main__.py index d763abba..957d8365 100644 --- a/opencodeblocks/__main__.py +++ b/opencodeblocks/__main__.py @@ -1,15 +1,17 @@ # OpenCodeBlock an open-source tool for modular visual programing in python # Copyright (C) 2021 Mathïs FEDERICO +# pylint:disable=wrong-import-position import os import sys import asyncio +if os.name == "nt": # If on windows + asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy()) + from qtpy.QtWidgets import QApplication from opencodeblocks.graphics.window import OCBWindow -if os.name == "nt": # If on windows - asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy()) sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "..")) diff --git a/opencodeblocks/blocks/block.py b/opencodeblocks/blocks/block.py index 2d9a02a4..754c330d 100644 --- a/opencodeblocks/blocks/block.py +++ b/opencodeblocks/blocks/block.py @@ -196,7 +196,7 @@ def remove(self): scene.removeItem(self) def update_splitter(self): - """ Change the geometry of the splitter to match the block """ + """Change the geometry of the splitter to match the block""" # We make the resizing of splitter only affect # the last element of the split view sizes = self.splitter.sizes() @@ -213,7 +213,7 @@ def update_splitter(self): self.splitter.setSizes(sizes) def update_title(self): - """ Change the geometry of the title to match the block """ + """Change the geometry of the title to match the block""" self.title_widget.setGeometry( int(self.edge_size), int(self.edge_size / 2), @@ -222,7 +222,7 @@ def update_title(self): ) def update_size_grip(self): - """ Change the geometry of the size grip to match the block""" + """Change the geometry of the size grip to match the block""" self.size_grip.setGeometry( int(self.width - self.edge_size * 2), int(self.height - self.edge_size * 2), @@ -231,7 +231,7 @@ def update_size_grip(self): ) def update_all(self): - """ Update sockets and title.""" + """Update sockets and title.""" self.update_sockets() self.update_splitter() self.update_title() @@ -266,7 +266,7 @@ def height(self, value: float): self.root.setGeometry(0, 0, self.root.width(), int(value)) def serialize(self) -> OrderedDict: - """ Return a serialized version of this widget """ + """Return a serialized version of this widget""" self.metadata.update({"title_metadata": self.title_widget.serialize()}) metadata = OrderedDict(sorted(self.metadata.items())) return OrderedDict( @@ -290,7 +290,7 @@ def serialize(self) -> OrderedDict: ) def deserialize(self, data: dict, hashmap: dict = None, restore_id=True) -> None: - """ Restore the block from serialized data """ + """Restore the block from serialized data""" if restore_id: self.id = data["id"] for dataname in ("title", "block_type", "width", "height"): @@ -305,11 +305,17 @@ def deserialize(self, data: dict, hashmap: dict = None, restore_id=True) -> None if "splitter_pos" in data: self.splitter.setSizes(data["splitter_pos"]) - for socket_data in data["sockets"]: - socket = OCBSocket(block=self) - socket.deserialize(socket_data, hashmap, restore_id) - self.add_socket(socket) - if hashmap is not None: - hashmap.update({socket_data["id"]: socket}) + if len(data["sockets"]) > 0: + # Remove old sockets + for socket in self.sockets_in + self.sockets_out: + self.remove_socket(socket) + + # Deserialize new sockets + for socket_data in data["sockets"]: + socket = OCBSocket(block=self) + socket.deserialize(socket_data, hashmap, restore_id) + self.add_socket(socket) + if hashmap is not None: + hashmap.update({socket_data["id"]: socket}) self.update_all() diff --git a/opencodeblocks/blocks/codeblock.py b/opencodeblocks/blocks/codeblock.py index 3b45ce81..fec56fce 100644 --- a/opencodeblocks/blocks/codeblock.py +++ b/opencodeblocks/blocks/codeblock.py @@ -9,6 +9,7 @@ from ansi2html import Ansi2HTMLConverter from opencodeblocks.blocks.block import OCBBlock +from opencodeblocks.graphics.socket import OCBSocket from opencodeblocks.graphics.pyeditor import PythonEditor from opencodeblocks.graphics.worker import Worker @@ -44,14 +45,25 @@ def __init__(self, **kwargs): self._splitter_size = [0, 0] self._cached_stdout = "" + # Add exectution flow sockets + exe_sockets = ( + OCBSocket(self, socket_type="input", flow_type="exe"), + OCBSocket(self, socket_type="output", flow_type="exe"), + ) + for socket in exe_sockets: + self.add_socket(socket) + + # Add output pannel self.output_panel = self.init_output_panel() self.run_button = self.init_run_button() + # Add splitter between source_editor and panel self.splitter.addWidget(self.source_editor) self.splitter.addWidget(self.output_panel) self.title_left_offset = 3 * self.edge_size + # Build root widget into holder self.holder.setWidget(self.root) self.update_all() # Set the geometry of display and source_editor @@ -67,8 +79,7 @@ def init_run_button(self): """Initialize the run button""" run_button = QPushButton(">", self.root) run_button.move(int(self.edge_size), int(self.edge_size / 2)) - run_button.setFixedSize(int(3 * self.edge_size), - int(3 * self.edge_size)) + run_button.setFixedSize(int(3 * self.edge_size), int(3 * self.edge_size)) run_button.clicked.connect(self.run_code) return run_button @@ -85,7 +96,7 @@ def run_code(self): self.source_editor.threadpool.start(worker) def update_title(self): - """ Change the geometry of the title widget """ + """Change the geometry of the title widget""" self.title_widget.setGeometry( int(self.edge_size) + self.run_button.width(), int(self.edge_size / 2), @@ -94,7 +105,7 @@ def update_title(self): ) def update_output_panel(self): - """ Change the geometry of the output panel """ + """Change the geometry of the output panel""" # Close output panel if no output if self.stdout == "": self.previous_splitter_size = self.splitter.sizes() @@ -102,13 +113,13 @@ def update_output_panel(self): self.splitter.setSizes([1, 0]) def update_all(self): - """ Update the code block parts """ + """Update the code block parts""" super().update_all() self.update_output_panel() @property def source(self) -> str: - """ Source code """ + """Source code""" return self.source_editor.text() @source.setter @@ -117,7 +128,7 @@ def source(self, value: str): @property def stdout(self) -> str: - """ Access the content of the output panel of the block """ + """Access the content of the output panel of the block""" return self._stdout @stdout.setter @@ -141,7 +152,7 @@ def stdout(self, value: str): @staticmethod def str_to_html(text: str): - """ Format text so that it's properly displayed by the code block """ + """Format text so that it's properly displayed by the code block""" # Remove carriage returns and backspaces text = text.replace("\x08", "") text = text.replace("\r", "") @@ -154,7 +165,7 @@ def str_to_html(text: str): return text def handle_stdout(self, value: str): - """ Handle the stdout signal """ + """Handle the stdout signal""" # If there is a new line # Save every line but the last one @@ -168,12 +179,12 @@ def handle_stdout(self, value: str): @staticmethod def b64_to_html(image: str): - """ Transform a base64 encoded image into a html image""" + """Transform a base64 encoded image into a html image""" return f'' def handle_image(self, image: str): - """ Handle the image signal """ - self.stdout = '' + image + """Handle the image signal""" + self.stdout = "" + image def serialize(self): base_dict = super().serialize() @@ -181,10 +192,12 @@ def serialize(self): base_dict["stdout"] = self.stdout return base_dict - def deserialize(self, data: OrderedDict, - hashmap: dict = None, restore_id: bool = True): - """ Restore a codeblock from it's serialized state """ - for dataname in ('source', 'stdout'): + + def deserialize( + self, data: OrderedDict, hashmap: dict = None, restore_id: bool = True + ): + """Restore a codeblock from it's serialized state""" + for dataname in ("source", "stdout"): if dataname in data: setattr(self, dataname, data[dataname]) super().deserialize(data, hashmap, restore_id) diff --git a/opencodeblocks/graphics/socket.py b/opencodeblocks/graphics/socket.py index d4fbd152..d567c54f 100644 --- a/opencodeblocks/graphics/socket.py +++ b/opencodeblocks/graphics/socket.py @@ -20,13 +20,19 @@ class OCBSocket(QGraphicsItem, Serializable): - """ Base class for sockets in OpenCodeBlocks. """ - - def __init__(self, block: 'OCBBlock', - socket_type: str = 'undefined', flow_type: str = 'exe', - radius: float = 6.0, color: str = '#FF55FFF0', - linewidth: float = 1.0, linecolor: str = '#FF000000'): - """ Base class for sockets in OpenCodeBlocks. + """Base class for sockets in OpenCodeBlocks.""" + + def __init__( + self, + block: "OCBBlock", + socket_type: str = "undefined", + flow_type: str = "exe", + radius: float = 10.0, + color: str = "#FF55FFF0", + linewidth: float = 1.0, + linecolor: str = "#FF000000", + ): + """Base class for sockets in OpenCodeBlocks. Args: block: Block containing the socket. @@ -42,7 +48,7 @@ def __init__(self, block: 'OCBBlock', self.block = block QGraphicsItem.__init__(self, parent=self.block) - self.edges: List['OCBEdge'] = [] + self.edges: List["OCBEdge"] = [] self.socket_type = socket_type self.flow_type = flow_type @@ -52,80 +58,88 @@ def __init__(self, block: 'OCBBlock', self._brush = QBrush(QColor(color)) self.metadata = { - 'radius': radius, - 'color': color, - 'linewidth': linewidth, - 'linecolor': linecolor, + "radius": radius, + "color": color, + "linewidth": linewidth, + "linecolor": linecolor, } - def add_edge(self, edge: 'OCBEdge', is_destination: bool): - """ Add a given edge to the socket edges. """ + def add_edge(self, edge: "OCBEdge", is_destination: bool): + """Add a given edge to the socket edges.""" if not self._allow_multiple_edges: for prev_edge in self.edges: prev_edge.remove() - if self.flow_type == 'exe': - if ((is_destination and self.socket_type != 'input') or - (not is_destination and self.socket_type != 'output')): + if self.flow_type == "exe": + if (is_destination and self.socket_type != "input") or ( + not is_destination and self.socket_type != "output" + ): edge.remove() return self.edges.append(edge) - def remove_edge(self, edge: 'OCBEdge'): - """ Remove a given edge from the socket edges. """ + def remove_edge(self, edge: "OCBEdge"): + """Remove a given edge from the socket edges.""" self.edges.remove(edge) def remove(self): - """ Remove the socket and all its edges from the scene it is in. """ + """Remove the socket and all its edges from the scene it is in.""" for edge in self.edges: edge.remove() scene = self.scene() if scene is not None: scene.removeItem(self) + self.setParentItem(None) @property def _allow_multiple_edges(self): - if self.flow_type == 'exe': + if self.flow_type == "exe": return True raise NotImplementedError - def paint(self, painter: QPainter, - option: QStyleOptionGraphicsItem, # pylint:disable=unused-argument - widget: Optional[QWidget] = None): # pylint:disable=unused-argument - """ Paint the socket. """ + def paint( + self, + painter: QPainter, + option: QStyleOptionGraphicsItem, # pylint:disable=unused-argument + widget: Optional[QWidget] = None, + ): # pylint:disable=unused-argument + """Paint the socket.""" painter.setBrush(self._brush) painter.setPen(self._pen) r = self.radius - if self.flow_type == 'exe': - angles = [0, 2*math.pi/3, -2*math.pi/3] + if self.flow_type == "exe": + angles = [0, 2 * math.pi / 3, -2 * math.pi / 3] right_triangle_points = [ - QPoint(int(r*math.cos(angle)), int(r*math.sin(angle))) + QPoint(int(r * math.cos(angle)), int(r * math.sin(angle))) for angle in angles ] painter.drawPolygon(QPolygon(right_triangle_points)) else: - painter.drawEllipse(int(-r), int(-r), int(2*r), int(2*r)) + painter.drawEllipse(int(-r), int(-r), int(2 * r), int(2 * r)) def boundingRect(self) -> QRectF: - """ Get the socket bounding box. """ + """Get the socket bounding box.""" r = self.radius - return QRectF(-r, -r, 2*r, 2*r) + return QRectF(-r, -r, 2 * r, 2 * r) def serialize(self) -> OrderedDict: metadata = OrderedDict(sorted(self.metadata.items())) - return OrderedDict([ - ('id', self.id), - ('type', self.socket_type), - ('position', [self.pos().x(), self.pos().y()]), - ('metadata', metadata) - ]) + return OrderedDict( + [ + ("id", self.id), + ("type", self.socket_type), + ("position", [self.pos().x(), self.pos().y()]), + ("metadata", metadata), + ] + ) def deserialize(self, data: OrderedDict, hashmap: dict = None, restore_id=True): if restore_id: - self.id = data['id'] - self.socket_type = data['type'] - self.setPos(QPointF(*data['position'])) - - self.metadata = dict(data['metadata']) - self._pen.setColor(QColor(self.metadata['linecolor'])) - self._pen.setWidth(int(self.metadata['linewidth'])) - self._brush.setColor(QColor(self.metadata['color'])) + self.id = data["id"] + self.socket_type = data["type"] + self.setPos(QPointF(*data["position"])) + + self.metadata = dict(data["metadata"]) + self.radius = self.metadata["radius"] + self._pen.setColor(QColor(self.metadata["linecolor"])) + self._pen.setWidth(int(self.metadata["linewidth"])) + self._brush.setColor(QColor(self.metadata["color"]))