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{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"authorship_tag":"ABX9TyNNn+xhXVbN7MyzlTixT4fX"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","execution_count":null,"metadata":{"id":"CaBZOlQOIbXS"},"outputs":[],"source":["import tensorflow as tf\n","import pandas as pd"]},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"_dwkKj_8Ir-L","executionInfo":{"status":"ok","timestamp":1684363750774,"user_tz":-60,"elapsed":1290,"user":{"displayName":"Bailey Barber-Scargill","userId":"06508271859993528557"}},"outputId":"edbd29ac-735e-43d9-cc60-eabbb34a5a4a"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"]}]},{"cell_type":"code","source":["# Load our models\n","model25 = tf.keras.models.load_model(\"/content/drive/MyDrive/CSGO MODELS/NEWMODEL25\")\n","model10 = tf.keras.models.load_model(\"/content/drive/MyDrive/CSGO MODELS/NEWMODEL10\")\n","model5 = tf.keras.models.load_model(\"/content/drive/MyDrive/CSGO MODELS/NEWMODEL5\")"],"metadata":{"id":"lFMgq3HSIfZe"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["#Test Data\n","testMatch = allData = pd.read_csv('/content/drive/MyDrive/CSGO DEMOS/ApeksVTL.csv')\n","\n","testMatch"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":424},"id":"AL17JzAnJtbl","executionInfo":{"status":"ok","timestamp":1684364757448,"user_tz":-60,"elapsed":652,"user":{"displayName":"Bailey Barber-Scargill","userId":"06508271859993528557"}},"outputId":"14cae6b6-942e-4ff3-fd06-8a14b693bea2"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":[" roundNum tick seconds side teamName steamID name \\\n","0 1 10289 0.265625 CT Apeks 76561198153651861 nawwk \n","1 1 10289 0.265625 CT Apeks 76561198016194159 STYKO \n","2 1 10289 0.265625 CT Apeks 76561198002708642 jkaem \n","3 1 10289 0.265625 CT Apeks 76561198176878303 jL \n","4 1 10289 0.265625 CT Apeks 76561198057282432 kyxsan \n","... ... ... ... ... ... ... ... \n","26525 28 480615 7.421875 T Apeks 76561198002708642 jkaem \n","26526 28 480615 7.421875 T Apeks 76561198057282432 kyxsan \n","26527 28 480615 7.421875 T Apeks 76561198016194159 STYKO \n","26528 28 480615 7.421875 T Apeks 76561198176878303 jL \n","26529 28 480615 7.421875 T Apeks 76561198153651861 nawwk \n","\n"," team x y ... cash cashSpendThisRound \\\n","0 Apeks -463.347961 1717.978149 ... 0 800 \n","1 Apeks -317.601898 1751.550293 ... 150 650 \n","2 Apeks -254.765594 1738.578735 ... 150 650 \n","3 Apeks -343.482361 1649.797607 ... 150 650 \n","4 Apeks -345.950134 1713.207764 ... 150 650 \n","... ... ... ... ... ... ... \n","26525 Apeks -97.416710 729.962646 ... 2450 3400 \n","26526 Apeks 734.583984 619.332764 ... 1550 4800 \n","26527 Apeks -511.782990 -833.808228 ... 0 4600 \n","26528 Apeks -459.914429 846.747253 ... 2900 2100 \n","26529 Apeks 602.775879 761.842163 ... 5400 1000 \n","\n"," cashSpendTotal hasHelmet hasDefuse hasBomb ping zoomLevel \\\n","0 800 False False False 5 0 \n","1 650 False False False 2 0 \n","2 650 False False False 5 0 \n","3 650 False False False 5 0 \n","4 650 False False False 5 0 \n","... ... ... ... ... ... ... \n","26525 80700 False False False 5 0 \n","26526 82700 False False False 5 0 \n","26527 80800 False False False 3 0 \n","26528 79100 False False False 5 0 \n","26529 72250 True False False 5 0 \n","\n"," matchID mapName \n","0 apeks-vs-liquid-ancient de_ancient \n","1 apeks-vs-liquid-ancient de_ancient \n","2 apeks-vs-liquid-ancient de_ancient \n","3 apeks-vs-liquid-ancient de_ancient \n","4 apeks-vs-liquid-ancient de_ancient \n","... ... ... \n","26525 apeks-vs-liquid-ancient de_ancient \n","26526 apeks-vs-liquid-ancient de_ancient \n","26527 apeks-vs-liquid-ancient de_ancient \n","26528 apeks-vs-liquid-ancient de_ancient \n","26529 apeks-vs-liquid-ancient de_ancient \n","\n","[26530 rows x 58 columns]"],"text/html":["\n"," <div id=\"df-60dc92ea-8bb1-4a86-9eac-cecb2c5461a4\">\n"," <div class=\"colab-df-container\">\n"," <div>\n","<style scoped>\n"," .dataframe tbody tr th:only-of-type {\n"," vertical-align: middle;\n"," }\n","\n"," .dataframe tbody tr th {\n"," vertical-align: top;\n"," }\n","\n"," .dataframe thead th {\n"," text-align: right;\n"," }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n"," <thead>\n"," <tr style=\"text-align: right;\">\n"," <th></th>\n"," <th>roundNum</th>\n"," <th>tick</th>\n"," <th>seconds</th>\n"," <th>side</th>\n"," <th>teamName</th>\n"," <th>steamID</th>\n"," <th>name</th>\n"," <th>team</th>\n"," <th>x</th>\n"," <th>y</th>\n"," <th>...</th>\n"," <th>cash</th>\n"," <th>cashSpendThisRound</th>\n"," 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<td>apeks-vs-liquid-ancient</td>\n"," <td>de_ancient</td>\n"," </tr>\n"," <tr>\n"," <th>26527</th>\n"," <td>28</td>\n"," <td>480615</td>\n"," <td>7.421875</td>\n"," <td>T</td>\n"," <td>Apeks</td>\n"," <td>76561198016194159</td>\n"," <td>STYKO</td>\n"," <td>Apeks</td>\n"," <td>-511.782990</td>\n"," <td>-833.808228</td>\n"," <td>...</td>\n"," <td>0</td>\n"," <td>4600</td>\n"," <td>80800</td>\n"," <td>False</td>\n"," <td>False</td>\n"," <td>False</td>\n"," <td>3</td>\n"," <td>0</td>\n"," <td>apeks-vs-liquid-ancient</td>\n"," <td>de_ancient</td>\n"," </tr>\n"," <tr>\n"," <th>26528</th>\n"," <td>28</td>\n"," <td>480615</td>\n"," <td>7.421875</td>\n"," <td>T</td>\n"," <td>Apeks</td>\n"," <td>76561198176878303</td>\n"," <td>jL</td>\n"," <td>Apeks</td>\n"," <td>-459.914429</td>\n"," <td>846.747253</td>\n"," <td>...</td>\n"," <td>2900</td>\n"," <td>2100</td>\n"," <td>79100</td>\n"," <td>False</td>\n"," <td>False</td>\n"," <td>False</td>\n"," <td>5</td>\n"," <td>0</td>\n"," <td>apeks-vs-liquid-ancient</td>\n"," <td>de_ancient</td>\n"," </tr>\n"," <tr>\n"," <th>26529</th>\n"," <td>28</td>\n"," <td>480615</td>\n"," <td>7.421875</td>\n"," <td>T</td>\n"," <td>Apeks</td>\n"," <td>76561198153651861</td>\n"," <td>nawwk</td>\n"," <td>Apeks</td>\n"," <td>602.775879</td>\n"," <td>761.842163</td>\n"," <td>...</td>\n"," <td>5400</td>\n"," <td>1000</td>\n"," <td>72250</td>\n"," <td>True</td>\n"," <td>False</td>\n"," <td>False</td>\n"," <td>5</td>\n"," <td>0</td>\n"," <td>apeks-vs-liquid-ancient</td>\n"," <td>de_ancient</td>\n"," </tr>\n"," </tbody>\n","</table>\n","<p>26530 rows × 58 columns</p>\n","</div>\n"," <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-60dc92ea-8bb1-4a86-9eac-cecb2c5461a4')\"\n"," title=\"Convert this dataframe to an interactive table.\"\n"," style=\"display:none;\">\n"," \n"," <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n"," width=\"24px\">\n"," <path d=\"M0 0h24v24H0V0z\" 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'block' : 'none';\n","\n"," async function convertToInteractive(key) {\n"," const element = document.querySelector('#df-60dc92ea-8bb1-4a86-9eac-cecb2c5461a4');\n"," const dataTable =\n"," await google.colab.kernel.invokeFunction('convertToInteractive',\n"," [key], {});\n"," if (!dataTable) return;\n","\n"," const docLinkHtml = 'Like what you see? Visit the ' +\n"," '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n"," + ' to learn more about interactive tables.';\n"," element.innerHTML = '';\n"," dataTable['output_type'] = 'display_data';\n"," await google.colab.output.renderOutput(dataTable, element);\n"," const docLink = document.createElement('div');\n"," docLink.innerHTML = docLinkHtml;\n"," element.appendChild(docLink);\n"," }\n"," </script>\n"," </div>\n"," </div>\n"," "]},"metadata":{},"execution_count":226}]},{"cell_type":"code","source":["round_num = 22\n","player_name = \"NAF-FLY\"\n","deathPoint = 84\n","\n","# Filter based on roundNum and playerName\n","testRound = testMatch[(testMatch['roundNum'] == round_num) & (testMatch['name'] == player_name)]\n","\n","testRound['isAlive']"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"kFJhY0yRJ0tX","executionInfo":{"status":"ok","timestamp":1684372008225,"user_tz":-60,"elapsed":220,"user":{"displayName":"Bailey Barber-Scargill","userId":"06508271859993528557"}},"outputId":"e978b0f5-8ede-4284-c4cd-383815ccf8d2"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["20494 True\n","20502 True\n","20513 True\n","20521 True\n","20534 True\n"," ... \n","21392 True\n","21402 True\n","21412 True\n","21422 True\n","21430 True\n","Name: isAlive, Length: 95, dtype: bool"]},"metadata":{},"execution_count":465}]},{"cell_type":"code","source":["def processInput(dataframe):\n"," features = ['tick', 'eyeX', 'eyeY', 'eyeZ', 'viewX', 'viewY', 'isPlanting', 'isDefusing', 'x', 'y', 'z', 'seconds', 'hp', 'hasBomb',\n"," 'isScoped', 'roundNum', 'isBlinded', 'isDucking', 'armor', 'equipmentValue', 'flashGrenades', 'smokeGrenades',\n"," 'heGrenades', 'isWalking', 'side']\n","\n","\n"," # Set our input and output\n"," X = dataframe[features]\n","\n"," # Encode our categorical features\n"," # Select the categorical columns to be one-hot encoded\n"," categorical_cols = ['side', 'isPlanting', 'isDefusing', 'hasBomb', 'isScoped', 'isBlinded', 'isDucking', 'isWalking']\n","\n"," # Perform one-hot encoding using pandas get_dummies function\n"," X = pd.get_dummies(X, columns=categorical_cols)\n","\n"," # Add the missing columns from the test data to get the same shape\n"," inputCol = ['tick', 'eyeX', 'eyeY', 'eyeZ', 'viewX', 'viewY', 'x', 'y', 'z',\n"," 'seconds', 'hp', 'roundNum', 'armor', 'equipmentValue', 'flashGrenades',\n"," 'smokeGrenades', 'heGrenades', 'side_CT', 'side_T', 'isPlanting_False',\n"," 'isPlanting_True', 'isDefusing_False', 'isDefusing_True',\n"," 'hasBomb_False', 'hasBomb_True', 'isScoped_False', 'isScoped_True',\n"," 'isBlinded_False', 'isBlinded_True', 'isDucking_False',\n"," 'isDucking_True', 'isWalking_False', 'isWalking_True']\n"," testMatchCol = dataframe.columns\n","\n"," # Find missing columns\n"," missing_columns = set(inputCol) - set(testMatchCol)\n","\n"," # Copy missing columns\n"," dataframe = dataframe.reindex(columns=testMatchCol.union(missing_columns))\n","\n"," # Replace NaN values with 0\n"," dataframe = dataframe.fillna(0)\n","\n"," # Cast the columns back to uint8\n"," for column in missing_columns:\n"," dataframe[column] = dataframe[column].astype('uint8')\n","\n"," return X"],"metadata":{"id":"Sr4RdbRgKPTg"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["testMatchInput = processInput(testRound)"],"metadata":{"id":"qs_X1PsFsT3C"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# Check the updated DataFrame\n","testMatchInput.columns"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"FBD2mCUg2qWH","executionInfo":{"status":"ok","timestamp":1684371566978,"user_tz":-60,"elapsed":2,"user":{"displayName":"Bailey Barber-Scargill","userId":"06508271859993528557"}},"outputId":"e0da6a5c-62b2-4cc2-e866-affbf8998efb"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index(['tick', 'eyeX', 'eyeY', 'eyeZ', 'viewX', 'viewY', 'x', 'y', 'z',\n"," 'seconds', 'hp', 'roundNum', 'armor', 'equipmentValue', 'flashGrenades',\n"," 'smokeGrenades', 'heGrenades', 'side_CT', 'isPlanting_False',\n"," 'isDefusing_False', 'hasBomb_False', 'isScoped_False',\n"," 'isBlinded_False', 'isBlinded_True', 'isDucking_False',\n"," 'isDucking_True', 'isWalking_False', 'isWalking_True'],\n"," dtype='object')"]},"metadata":{},"execution_count":453}]},{"cell_type":"code","source":["pred5 = model5.predict(testMatchInput)\n","pred10 = model10.predict(testMatchInput)\n","pred25 = model25.predict(testMatchInput)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"RKaxAF-0tF6E","executionInfo":{"status":"ok","timestamp":1684366903882,"user_tz":-60,"elapsed":490,"user":{"displayName":"Bailey Barber-Scargill","userId":"06508271859993528557"}},"outputId":"8c14aa13-d155-4c40-e8d6-9e008ebbdf29"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["3/3 [==============================] - 0s 7ms/step\n","3/3 [==============================] - 0s 7ms/step\n","3/3 [==============================] - 0s 10ms/step\n"]}]},{"cell_type":"code","source":["import matplotlib.pyplot as plt\n","\n","# Assuming pred5, pred10, pred25 are lists of probabilities and testMatchInput is a list of seconds\n","\n","seconds = testMatchInput['seconds']\n","\n","plt.figure(figsize=(15, 1.5))\n","\n","plt.plot(seconds, pred5, color='blue', label='5 Matches')\n","plt.plot(seconds, pred10, color='green', label='10 Matches')\n","plt.plot(seconds, pred25, color='red', label='25 Matches')\n","\n","plt.axhline(y=0.25, linestyle='-', color='lightgray')\n","plt.axhline(y=0.5, linestyle='-', color='lightgray')\n","plt.axhline(y=0.75, linestyle='-', color='lightgray')\n","\n","# Add a vertical line at x seconds if a player has a death point\n","#plt.axvline(x=deathPoint, linestyle='--', color='purple')\n","\n","plt.xlabel('Seconds')\n","plt.ylabel('Probability')\n","plt.title('Player: ' + player_name)\n","plt.ylim(0, 1) # Set the y-axis limits to be between 0 and 1\n","plt.grid(color='lightgray', linestyle='--', linewidth=0.5)\n","\n","# Create a custom legend entry for the death point with specified colors\n","legend_lines = [plt.Line2D([0], [0], color='blue'),\n"," plt.Line2D([0], [0], color='green'),\n"," plt.Line2D([0], [0], color='red'),\n"," plt.Line2D([0], [0], linestyle='--', color='purple')]\n","\n","legend_labels = ['5 Matches', '10 Matches', '25 Matches', 'NO DEATH']\n","plt.legend(legend_lines, legend_labels, loc='center left', bbox_to_anchor=(1, 0.5))\n","\n","plt.show()\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":218},"id":"Xc9Ptn6E3EsB","executionInfo":{"status":"ok","timestamp":1684366904380,"user_tz":-60,"elapsed":501,"user":{"displayName":"Bailey Barber-Scargill","userId":"06508271859993528557"}},"outputId":"e35ca8e5-6c01-4478-8708-26191d5da704"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1500x150 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]}]}
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