diff --git a/scHPL/evaluate.py b/scHPL/evaluate.py index 5c75301..e729edc 100644 --- a/scHPL/evaluate.py +++ b/scHPL/evaluate.py @@ -11,6 +11,7 @@ import seaborn as sns from .utils import TreeNode +# from utils import TreeNode def hierarchical_F1(true_labels, pred_labels, diff --git a/scHPL/learn.py b/scHPL/learn.py index 2c95992..1bef064 100644 --- a/scHPL/learn.py +++ b/scHPL/learn.py @@ -12,6 +12,10 @@ from .utils import TreeNode, create_tree, print_tree from .predict import predict_labels from .update import update_tree +# from train import train_tree +# from utils import TreeNode, create_tree, print_tree +# from predict import predict_labels +# from update import update_tree try: from typing import Literal @@ -142,8 +146,8 @@ def learn_tree(data: AnnData, distkNN) # Predict labels other dataset - labels_2_pred = predict_labels(data_2, tree, threshold=rej_threshold) - labels_1_pred = predict_labels(data_1, tree_2, threshold=rej_threshold) + labels_2_pred,_ = predict_labels(data_2, tree, threshold=rej_threshold) + labels_1_pred,_ = predict_labels(data_1, tree_2, threshold=rej_threshold) # Update first tree and labels second dataset tree, mis_pop = update_tree(tree, labels_1.reshape(-1,1), diff --git a/scHPL/predict.py b/scHPL/predict.py index 55d11dc..590f7ec 100644 --- a/scHPL/predict.py +++ b/scHPL/predict.py @@ -7,6 +7,7 @@ import numpy as np from numpy import linalg as LA from .utils import TreeNode +# from utils import TreeNode def predict_labels(testdata, tree: TreeNode, @@ -26,6 +27,8 @@ def predict_labels(testdata, Returns ------ Predicted labels + Probability of the predicted labels (only works for kNN, since SVM + doesn't return probabilities) ''' useRE = False @@ -50,8 +53,8 @@ def predict_labels(testdata, dimred = True labels_all = [] + prob_all = np.zeros((np.shape(testdata)[0],1)) for idx, testpoint in enumerate(testdata): - # print(idx) if useRE: if rej_RE[idx]: labels_all.append('Rejected (RE)') @@ -71,7 +74,7 @@ def predict_labels(testdata, ### Reject cells based on distance predict=True - dist,idx = parentnode.classifier.kneighbors(testpoint, return_distance=True) + dist,_ = parentnode.classifier.kneighbors(testpoint, return_distance=True) if(np.mean(dist) > parentnode.get_maxDist()): labels.append('Rejection (dist)') predict=False @@ -83,6 +86,7 @@ def predict_labels(testdata, #If score higher than threshold -> iterate further over tree if score > threshold: labels.append(label[0]) + prob_all[idx] = score oldparent = parentnode for n in parentnode.descendants: if n.name[0] == label: @@ -122,7 +126,8 @@ def predict_labels(testdata, # Label cell with last predicted label labels_all.append(labels[-1]) - return np.asarray(labels_all) + + return np.asarray(labels_all), prob_all def _predict_node(testpoint, n, dimred): '''Use the local classifier of a node to predict the label of a cell. diff --git a/scHPL/train.py b/scHPL/train.py index b779e4c..40ef7ff 100644 --- a/scHPL/train.py +++ b/scHPL/train.py @@ -15,6 +15,7 @@ from sklearn.model_selection import StratifiedKFold from scipy.stats import ttest_ind from .utils import TreeNode +# from utils import TreeNode import copy as cp try: @@ -350,3 +351,11 @@ def _find_negativesamples(labels, group, n): return group + + + + + + + + diff --git a/scHPL/update.py b/scHPL/update.py index 9d171c2..50fd454 100644 --- a/scHPL/update.py +++ b/scHPL/update.py @@ -9,6 +9,8 @@ import pandas as pd from .utils import TreeNode from .evaluate import confusion_matrix +# from utils import TreeNode +# from evaluate import confusion_matrix def update_tree(tree: TreeNode, y_true1, diff --git a/vignettes/tutorial.ipynb b/vignettes/tutorial.ipynb index 94cdca0..de37778 100644 --- a/vignettes/tutorial.ipynb +++ b/vignettes/tutorial.ipynb @@ -54,7 +54,10 @@ "name": "stderr", "output_type": "stream", "text": [ - "Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n" + "/tmp/ipykernel_1627501/3653877580.py:4: FutureWarning: X.dtype being converted to np.float32 from int64. In the next version of anndata (0.9) conversion will not be automatic. Pass dtype explicitly to avoid this warning. Pass `AnnData(X, dtype=X.dtype, ...)` to get the future behavour.\n", + " adata = anndata.AnnData(data.values, row, col)\n", + "/exports/humgen/lmichielsen/miniconda3_v2/envs/scarches2/lib/python3.8/site-packages/anndata/_core/anndata.py:1830: UserWarning: Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n", + " utils.warn_names_duplicates(\"var\")\n" ] } ], @@ -103,7 +106,7 @@ "outputs": [ { "data": { - "image/png": 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Wlg8zIiLSp043/a7k2ca+lLkfQHNaeFpaGhYuXAiHw9GcPtVRrOGiRYu8Yg23b98OoP1Yw1GjRjXHGkopceLECQwaNAhSSrzzzju45pprfJ0SEZEuqXJ7YlOs4fz587FixQrExsbCarVi+fLlcDqdLfbNzc1FVlYWbDYbLBZLi1jD9evXw263IyUlpc1YwwceeABXXXUV5syZAyklMjIyUFlZCSklkpOTW2TpEhF1B6rdk65GrOGHH37oe8FEREFAkQu5Ukq3HnJkXS4XhBCejvckItInRZp+fX398a+++kqJoXyONQQu3EoaGhp6xs8lERFphiJNv7q6es3SpUurtm7d2ubdOFpw9OhRTJkyxVlVVbVY7VqIiAJFkTV9KWWBECLt3nvv/bfb7Y40m82NSozbWQ0NDSEul0u63e45Lpdrg9r1EBEFimIXcqWUhwDECiEi6+vrrR3+grIaAZQyx5aIgp3id+9IKc8DuPhXaomIKCAUbfpCiDEAkgBo7UzfFzUACqSU+R3uSUSkEYo1fYvF8nSfPn0eSU9PN0RFRfVQatxAKS8vb9y+fbs0m83LnE7n02rXQ0TUGYo0faPRmNWvX7/5H330kaVPnz5KDKkE4+nTp3HDDTc8LoQ4KaXcqHZBREQdUeSWzZ49e6Y/+eSTwdTwAQCXX345Fi5caImMjLxV7VqIiDpDkaYfEhISGxMT02KbGnGJTebNm4fw8PDmn/fu3YvIyEjY7XbY7XYsWbKk+bWKigpMmTIF11xzDRITE3Hw4MEWx4qNjYXRaAyudzMiClqKLO8IIVo83rgpLjEjIwMbN15YFfn222/x9ttvt/g9l8sFo9G/JR46dAgVFRVe20ePHt381M5f++Mf/4jx48fjjTfeQENDg9fTQJm+RUR60q3iEt1uNx577DGsWLGiU3VWVlZi//79mDlzJgDAZDIhKirKT38FIiLldau4xDVr1uC2225DXFxcm2MmJydjwoQJOHr0KADg5MmTiI2NRVZWFoYNG4ZZs2ahpqbGx1kTEamv28Qlnj59Gq+//nqbubjDhw/Ht99+i4KCAsybNw+TJ08GcGF56ciRI5gzZw4+++wzWK1WPPPMM/6aNhGR4rpNXOJnn32G48ePY9CgQQAuJHUNGjQIx48fR0RERPO+t956K+bOnYvS0lLEx8cjPj4eN9xwAwBgypQpbPpEpGudavpdiUoEtBGXOHHiRPz888/N+4SHh+P48eMAgJ9//hl9+vSBEAKffPIJPB4PYmJiIIRAv379cOzYMVx99dV47733cO2113blT0FEpKpuE5d4MW+88QYcDgeMRiPMZjPy8vKaPy08//zzmDZtGhoaGnDllVfilVde8fNfg4hIOUKJB0vGxsbuf/nll0dPmjQp4GMVFxcjPT3d5yCVS7VlyxY88MADu0tLS29RZEAioi7QxIVcIiJShiJN3+12l5eXlysxVJfiEn1RVlYGl8tVptiARERdoEjTr6qq2r1y5crajm611Jvy8nI899xztZWVle+pXQsRUWcosqYvhBBWq3VtXFzctKlTp5ojIiJ0v6x0/vx5z6ZNm5xnz559uaam5o9M3SIiPVCk6QMXGj+AOw0Gg81kMvUEAPOwifOdn+1YpUgBftbQ0FDp8XgKALzFhk9EeqFY02/LwJwdsqvfASAios5T5T79QBBCGAFo7Q3ExU8BRKQlum/6ZrP5TwaDYZHBYIgAoKkGGxIS4oqKijp8/vz5SVJK3uFDRKrT9QVVs9n855iYmCWHDh2KbGxsFG6326ClfyUlJaasrKzrwsPDDwgheqn99yIi0m3TF0IY3G73UwcOHLAkJibCYNDeVCIjI/Hcc8+ZbrrppngAd6ldDxGR9jpl58WGhoZ6+vfvr3YdFyWEwMiRI80Gg2Gg2rUQEem56YcYjUZP641ayt5tYjKZREhIiO6vnxCR/um56Xtpyt5NTU3FyZMncfjwYeTl5eGHH35osZ/L5fL72O1l7xIRaUlQNX29ZO8SEaklqJq+FrN3iYi0RPV1Zl9jGK+Yuw41/3zsovtkZ2cjPz8fJpMJ2dnZXtm7TZGNvmbvrl69Gvfccw9ef/117N2715dpEBEpSvWm7+tjGIQQl0dFRX0DwNK0TWvZu0REWhNUyztpaWmoq6uDw+Fo3tZR9i4Ar+zdI0eOAGg/exeAV/Zu07q/xWJhwycizQqqpt+Uvbtv3z4kJCRgxIgRyMjIwPLly732zc3NxaFDh2Cz2ZCTk9Mie7e8vBx2ux0Oh6PN7F2bzYby8vIOs3eJiLRG9eUdf4uLi0NeXl6br2VmZjb/Pzo6Gtu2bfPax2w2Y+fOnV7bi4uLYTAYsHbt2ouOX11dfWkFExEpSM9n+q7GxkZd1F9fXy/dbnej2nUQEemiabajpKGhwXDixAlFBvM1e1dKifz8fKfH4znV8d5ERIGl2+UdKaUMDQ199MYbb1yxY8cOy5AhQ2A0amc6UkqUlZUhNze3/tNPPz0B4A21ayIi0k6X9EF9ff0LYWFhnrS0tMW1tbW9pZSaClExmUzO0NDQj6qqqu6SUlaqXQ8Rka6bPgDU1dU5ADg63JGIiHS9pk9ERJdI92f6Qoj+AKaGh4cPEkKEqF1PZ7hcrjqn01kEYJ2Uskrteoio+9B10xdCXGmxWD6aOnVqlM1m66GlC7kXU1dXh927dzsPHDgwQwgxho2fiJSijy7ZjvDw8D3PPPNMTHZ2tu6WqR599FFzVlZW4rZt214FoxSJSCG6a5ZNhBDhDQ0Nl8+ZM0eXczAYDPjzn/8cJqUcqXYtRNR96LJh/iLCYrE0tg5EVyMuMTMzEwkJCbDb7bDb7fj888+bX9u7dy/sdjuGDBmCMWPGtPi9Xr16weVyWUFEpBBdL++01hSXmJGRgY0bNwIAvv32W7z99tst9nO5XH7/Itezzz6LKVOmtNhWUVGBuXPn4j//+Q/69++Ps2fP+nVMIqJLpeczfS9qxSW2Z+PGjbjzzjvRv39/AMBll10WgFkTEXVeUDV9teISAeCJJ56AzWbD/PnzUV9fDwD4+uuvce7cOdx888247rrrsH79+q5PkoioC4Kq6beWnZ2N5ORkpKSkAIBXXOL06dMB+B6XmJ+fDwBYtmwZioqK8Omnn6K8vLz5+f0ulwuHDx/Gjh078O677+Kpp57C119/HZC5EhF1hupr+v7MyFUjLhFAcyB6aGgosrKympeH4uPj0bt3b1itVlitVqSmpqKgoKBFMAsRkZJUbfq+5uMCbWfkpqWlYeHChXA4HM2pVh3FJS5atMgrLnH79u0A2o9LHDVqVHNcIgD89NNPiIuLg5QSb731FpKSkgAAt99+Ox566CG4XC40NDTg448/xvz5832dMhFRl6l+pu9PTXGJ8+fPx4oVKxAbGwur1Yrly5fD6XS22Dc3NxdZWVmw2WywWCwt4hLXr18Pu92OlJSUNuMSH3jgAVx11VXNbyzTpk1DSUkJpJSw2+3N6VqJiYkYP348bDYbDAYDZs2a1fyGQESkBtHWMoceNJ3pnzt3ztLx3l1XXFyM9PR0n4JU2nP69GlcddVV52tqaqL8dlAioovQ9YVcvb5hNdF7/USkP3pu+uU1NTWhLpdLkcF8jUu8mLNnz8JkMlX49aBERBeh26YvpayzWCyfPfLIIw16PGN2Op14+OGHaz0ezw61ayGi7kO3a/oAIISI6tmz54eDBw/uZ7PZjD169BAA4IYhLASeuo5+Xy21tbWeDz/80FNaWrqzqqrqv6SUbrVrIqLuQddNH7jwtE0ANwPoj18+ufT63QPPn9v9j3lq1tWBBgDHAexjwyciJem+6bdlYM4O2ZXvABARBauguk/fn8SFr9vGAIhSuZTWPABOSyk1u3xFRNrFpt8GIUQ/q9X6gcfjiYuIiGho/fgFNbndbnHu3LmwiIiIV6uqqmZLKT0d/xYR0QVs+q0IIfpYrdaPc3NzY//0pz8ZhRAmtWtqrbKyEjfffPN/Hz9+HABmqV0PEemHbm/ZDKD0cePGRS5YsMCopTP8X4uIiMDevXuttbW1mVp8UyIi7WLT9xY/dOhQs9pFdCQiIgKRkZF1AOLUroWI9INN35swGo0tTvG1lrvb5Jd8YG1+HCEiTeKafge0lrtLRNQVPNPvgNZyd4mIuoJNvwNay90lIuqKoF3e8TWGMfKmuy/6enZ2NvLz82EymZCdne2Vu9sU1+hr7u7q1auxYMECLFu2DH379kVDQwNmz56N5cuX48knn/RlSkREzYK26fv6GAYh0nPxu8WLm37WWu4uEVFXcHmnA2lpaairq4PD4Wje1lHuLgCv3N0jR44AaD93F4BX7i4Ar9xdIqKuYNPvQFPu7r59+5CQkIARI0YgIyMDy5cv99o3NzcXhw4dgs1mQ05OTovc3fLyctjtdjgcjjZzd202G8rLy1vk7g4dOhRDhw5FaWkp/vKXvygzYSIKakG7vONPcXFxyMvLa/O1zMzM5v9HR0dj27ZtXvuYzWbs3LnTa3txcTEMBkNzkPqv7dmzx/eCiYjawTN9bw01NTW6eMZ9Q0ODAReezU9E1Cls+t6O79y5s06JWyS7krtbUFAAp9NpAPCzf6siomDG5R1vW0+dOpWVnp6eumTJEkvv3r297rBRk8vlQlFRETIyMpwulyuLj1YmokvBpt+KlLJRCHHbJ598snrixInj3G53hNo1tSJ79OjxY3V19f/2eDyBfQAQEQUdNv02SCkbAcxRuw4iIn/jmj4RUTfCM/02CCGEwWCYHRkZ+b9CQkJ6q13Pr0kp3fX19Seqq6sdUsrDatdDRPrCpt+KEEJYLJbn4uPj73/88cet0dHRmrqQ63a7UVRUdPNTTz01VQhxi5TyI7VrIiL9YNP3NiEmJub+AwcOWGNiYtSupV1Dhw4NnzJlyn+EEL1kWw/9ISJqA9f0vSXdeeedJi03fACYOHEiQkJCQgHEql0LEekHm743S1RUVI9fb1AjLlFKiSeeeAKDBw9GYmIiVq9e7bWP2Wx2A7AEtBAiCipc3umAWnGJr776Kr7//nsUFRXBYDDg7Nmzfjs2EXVfPNPvgFpxiQ6HA08++WRT+Dkuu+wyBWdNRMGKTb8DasUlnjhxAps3b8b111+PCRMm4JtvvvHbnIio+2LTv0TZ2dlITk5GSkoKAHjFJU6fPh2A73GJ+fn5AID6+nqEhYXh0KFDuP/++zFjxoxATYmIupGgXdP3V0auWnGJ8fHxuOuuuwAAd9xxB7KysnyZDhFRC0HZ9H3NxwW8M3LT0tKwcOFCOByO5lSrjuISFy1a5BWXuH37dgDtxyWOGjWqRVzi5MmTsWfPHsyYMQP79u1rkbZFROQrLu90QK24xJycHGzZsgVDhw7F448/jhdffFGZCRNRUBP8MmdLQojcxYsXL87NzQ34WMXFxUhPT/c5SCU2NramtLQ0SUpZ7N/KiChY8Uy/DXp5I9RLnUSkHWz63s6cPHnSqcRAXYlLbGxsxPnz58MA8FtbRNRpbPredr355puubdu2qV1Hu1wuF+6++26nxWLZL6Vs+6oyEVEbuKbfBiHE9WFhYXt+85vfeGJjYzX1aGWXy4Xjx48bq6urP6+qqrpFSqnIpxIiCg5s+u0QQvQCkAQgSuVSWvMA+B7AV1JKl9rFEJG+sOkTEXUjXNMnIupG2PSJiLqR/w8lQBTMYFINygAAAABJRU5ErkJggg==\n", + "image/png": 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zZ7b+RIiI/Fyrm3578myj30j/CEB9WrjFYsHixYuRm5tbnz7VUqzhkiVL3GINd+7cCaD5WMNhw4bVxxpKKfHdd9+hX79+kFJix44duOUWPp1JRB2LKs/O18UaLliwAKtWrUJ0dDRMJhNWrlwJm83WYN/s7GxkZGTAbDbDaDQ2iDXcsGED4uPjcfvttzcZa5iRkYGBAwdizpw5kFIiLS0NV69ehZQSSUlJDbJ0iYg6AtW+MKVGrOHHH3/scb1ERIFAkRu5UkqnP+TI/lSjq6X9iIj8lSJN3263n/n666+VGMrjWEPg2qOkQojvvVwSEZFmKNL0Kyoq1i5fvrx827Zt0GKAlJQSeXl5mD9/flVJScn/qV0PEZGvKDKnL6U8LoSwPPzww/9wOp1dQkJCapUYt7XsdrteSmmvrq6+X0p5QO16iIh8RbEbuVLKIwCihRBd7HZ7yw/iK6saQClzbIko0Cn+9I6U8gqAK0qPS0RECjd9IcRIAAkAtHal74krAA5LKY+pXQgRUWsp1vSNRuOL3bp1ezI1NVUXERHh92vWFxQU1OzYsQN6vf4xh8Ph/qUAIiINUqTp6/X6mT179lzw6aefGrt166bEkErQnzx5EnfdddfrQojvpZQH1S6IiKglijyyGRYWlrp06dJAavgAri0cN2vWrGAhxAi1ayEiag1Fmn5QUFB0VFRUg21qxCXWmT9/PkJDQ+t/Xr9+PaKjo5GcnIzk5GSsW7eu/rXz58/j17/+NeLi4jBw4EBYrdYGx+rWrZveYDAE1qcZEQUsRaZ3hBANljeui0tMS0vDpk2bAADff/89duzY0eB9DocDer13Szxy5AhKS0vdtk+dOrXJ+MQZM2bgueeew5gxY1BRUQGdruHnZONzIyLSsg4Vl+h0OrFo0SKsWrWqVXV+/fXXcDgcGDNmDAAgNDQURqPRW78GIiLFdai4xLVr12LixImIiYlxe8/WrVthNpsxZcoUXLhwAQBw+vRpREREYPLkyRg0aBAWLVoEp9Pp4VkTEamvw8QlXrp0Ce+9916TubgTJkyA1WrFiRMnMGbMGKSlpQG4Nr108OBBrF69GocPH8bZs2exfv16b502EZHiOkxc4ueff44zZ86gX79+AK4ldfXr1w9nzpzBz28yz5o1C8888wwAoEePHkhOTkbfvn0BAJMmTcKnn36KRx55pFXnTUSkNa1q+u2JSgS0EZc4fvx4/Pe//63fJzQ0FGfOnAEA/Pjjj/VTPjt27EBcXBwAICUlBWVlZSgsLER0dDT2799f/8FEROSPOkxc4vXk5OTgp2/XIjIysn4KJygoCKtXr8bo0aMhpcTgwYMxe/Zs7/4yiIgUJJRYWDI6OvqjN998c/iECRN8PpbVakVqaqrHQSpt9fvf/x5Lly59pbKycr4iAxIRtYMmbuQSEZEyFGn6TqezpKSkRImh2hWX6InCwkJndXV1sWIDEhG1gyJNv7y8fN/q1aurrlwJrGX0rVYr3nzzTbvL5Tqkdi1ERK2hyJy+EEKYTKbXYmJipk2dOjUkPDzc76eVioqKHOvXr6+5cuXKYrvd/ke16yEiag1Fmj5wrfEDmKzT6czBwcFhABAyaPwC2+e71ihSgJfZ7fZiKeVnUsp9atdCRNRaijX9pvTJ2iXb+x0AIiJqPVWe0/cFIYQegNY+QBwMWyciLfH7ph8SEvK0TqdbotPpwgFoqcEKvV5vj4iI2HflypXfSCltLb+FiMi3/PqGakhIyDNRUVHLjhw50qW2tlY4nU6dhv6JS5cuGUaPHj06LCxsjxAiWO3fFxGR3zZ9IYTO6XS+cOjQIWNcXJxbuIkWREVFYcuWLSExMTHJABipSESq016nbL3ozp07u3r16qV2Hdel1+sxePBgAaC32rUQEflz0w/S6/Wuxhu1lL1bJzg4WAAIUqQIIqLr8Oem76Yue3fEiBE4e/Ysjh49is2bN+OHH35osJ/D4fD62M1l7xIRaUlANX1/yd4lIlJLQDV9LWbvEhFpierP6Xsaw3jz3LdQ+ZdF190nMzMT+fn5CA4ORmZmplv2bl1ko6fZuzk5OXjooYfw3nvv4cCBA56cBhGRolRv+p4uwyCEuCkiIuJbAMa6bVrL3iUi0pqAmt6xWCyorq5Gbm5u/baWsncBuGXvHjt2DEDz2bsA3LJ36+b9jUYjGz4RaVZANf267N28vDzExsZiyJAhSEtLw8qVK932zc7OxtGjR2E2m5GVldUge7ekpATx8fFYu3Ztk9m7cXFxKC0tbTF7l4hIa1Sf3vG2mJgYbN68ucnX0tPT6/8fGRmJ7du3u+0TEhKCPXv2uG23Wq3Q6/V45513rjt+RUVFm+olIlKSP1/pO2pra/2ifrvdLgF4/8sBRERt5BdNsxmFNTU1uu+++06RwTzN3q2pqcGRI0ckAKvXiyIiaiO/nd6RUsrOnTs/dccdd6zatWuXMT4+Hnq9dk5HSomCggI89thjVQUFBZ8AOKh2TURE2umSHrDb7a8aDAaXxWJ5vqqq6gYppaZCVAwGQ3mnTp12l5eXT5dS1qpdDxGRXzd9AKiurs4FkNvijkRE5Ndz+kRE1EZ+f6UvhOgFYGpoaGg/IYRfLF/scDiqbTbbKQBvSSnL1a6HiDoOv276Qoi+RqPx06lTp0aYzeZOWrqRez3V1dXYt2+f7dChQxlCiJFs/ESkFP/oks0IDQ3d/9JLL0VlZmb63TTVU089FTJz5sy4Dz74YD2A+9Wuh4g6Br9rlnWEEKE1NTU3zZkzxy/PQafT4ZlnnjFIKYeqXQsRdRx+2TB/Em40GmsbB6KrEZeYnp6O2NhYJCcnIzk5GV988UX9awcOHEBycjLi4+MxcuTIBu/r2rUrHA5Hy0t/EhF5iV9P7zRWF5eYlpaGTZs2AQC+//577Nixo8F+DofD61/kevnllzFlypQG28rKyjB37lz885//RK9evXD58mWvjklE1Fb+fKXvRq24xOZs2rQJkydPRq9evQAAN954ow/Omoio9QKq6asVlwgAzz33HMxmMxYsWAC73Q4AOH36NEpLS3H33Xdj8ODB2LBhQ/tPkoioHQKq6TeWmZmJpKQkpKSkAIBbXOL06dMBeB6XmJ+fDwBYsWIFTp06hcOHD6OkpKR+/X6Hw4GjR49i165d2L17N1544QWcPn3aJ+dKRNQaqs/pezMjV424RAD1geidO3fGzJkz66eHevTogaioKJhMJphMJowYMQLHjx9vEMxCRKQkVZu+p/m4QNMZuRaLBYsXL0Zubm59qlVLcYlLlixxi0vcuXMngObjEocNG1YflwgAP/74I2JiYiClxPbt25GQkAAAuPfee/HEE0/A4XCgpqYGn332GRYsWODpKRMRtZvqV/reVBeXuGDBAqxatQrR0dEwmUxYuXIlbDZbg32zs7ORkZEBs9kMo9HYIC5xw4YNiI+Px+23395kXGJGRgYGDhxY/8Eybdo0FBYWQkqJ5ORkvPbaawCAuLg4jB07FmazGTqdDrNmzar/QCAiUoOQ0qPZFdXVXemXlpYaW967/axWK1JTUz0KUmnOpUuX8Mtf/vJKZWVlhNcOSkR0HX59I9dfP7Dq+Hv9ROR//Lnpl1RWVnZ2OJSJnvU0LvF6Ll++jODg4DKvHpSI6Dr8tulLKauNRuPnTz75ZI0/XjHbbDbMnz+/yuVy7VK7FiLqOPx2Th8AhBARYWFhH/fv37+n2WzWd+rUSQCAEzpDEFzVLb1fLVVVVa6PP/7YVVRUtKe8vPw3Ukqn2jURUcfg100fuLbaJoC7AfTCT3+5dP3VY6+U7nt9npp1taAGwBkAeWz4RKQkv2/6TemTtUu25zsARESBKqCe0/cmce3rtlEAIlQupTEXgEtSSs1OXxGRdrHpN0EI0dNkMh10uVwx4eHhNY2XX1CT0+kUpaWlhvDw8PXl5eWPSildLb+LiOgaNv1GhBDdTCbTZ9nZ2dFPP/20XggRrHZNjV29ehV33333A2fOnAGAWWrXQ0T+w28f2fSh1NGjR3dZuHChXktX+D8XHh6OAwcOmKqqqtK1+KFERNrFpu+uR2JiYojaRbQkPDwcXbp0qQYQo3YtROQ/2PTdCb1e3+ASX2u5u3V+ygfW5p8jRKRJnNNvgdZyd4mI2oNX+i3QWu4uEVF7sOm3QGu5u0RE7RGw0zuexjB2ufPB676emZmJ/Px8BAcHIzMz0y13ty6u0dPc3ZycHCxcuBArVqxA9+7dUVNTg0cffRQrV67E0qVLPTklIqJ6Adv0PV2GQYjUbPzq+efrftZa7i4RUXtweqcFFosF1dXVyM3Nrd/WUu4uALfc3WPHjgFoPncXgFvuLgC33F0iovZg029BXe5uXl4eYmNjMWTIEKSlpWHlypVu+2ZnZ+Po0aMwm83IyspqkLtbUlKC+Ph4rF27tsnc3bi4OJSWljbI3U1MTERiYiKKiorw29/+VpkTJqKAFrDTO94UExODzZs3N/laenp6/f8jIyOxfft2t31CQkKwZ88et+1WqxV6vR7vvPOO22v79+/3uF4ioubwSt9dTWVlpV+scV9TU6PDtbX5iYhahU3f3Zk9e/ZUK/GIZHtyd48fPw6bzaYD8F/vVkVEgYzTO+62nTt3bmZqauqIZcuWGW+44Qa3J2zU5HA4cOrUKaSlpdkcDsdMLq1MRG3Bpt+IlLJWCDHx3//+d8748eNHO53OcLVrakR26tTpYkVFxf+5XC7fLgBERAGHTb8JUspaAHPUroOIyNs4p09E1IHwSr8JQgih0+ke7dKly/8EBQXdoHY9PyeldNrt9u8qKipypZRH1a6HiPwLm34jQghhNBr/0KNHj9nPPvusKTIyUlM3cp1OJ06dOnX3Cy+8MFUIMUZK+anaNRGR/2DTdzcuKipq9qFDh0xRUVFq19KsxMTE0ClTpvxTCNFVSunR4nJE1PFwTt9dwuTJk4O13PABYPz48QgKCuoMIFrtWojIf7DpuzNGRER0+vkGNeISpZR47rnn0L9/f8TFxSEnJ8dtn5CQECcAo08LIaKAwumdFqgVl7h+/XpcuHABp06dgk6nw+XLl712bCLquHil3wK14hJzc3OxdOnSuvBz3HjjjQqeNREFKjb9FqgVl/jdd99hy5YtuO222zBu3Dh8++23XjsnIuq42PTbKDMzE0lJSUhJSQEAt7jE6dOnA/A8LjE/Px8AYLfbYTAYcOTIEcyePRsZGRm+OiUi6kACdk7fWxm5asUl9ujRA5MnTwYA3HfffZg5c2Ybz4SIyF1ANn1P83EB94xci8WCxYsXIzc3tz7VqqW4xCVLlrjFJe7cuRNA83GJw4YNaxCXOGnSJHz44YeIjY1FXl5eg7QtIiJPcXqnBWrFJWZlZWHr1q1ITEzEs88+i3Xr1ilzwkQU0AS/zNmQECL7+eeffz47O9vnY1mtVqSmpnocpBIdHV1ZVFSUIKW0ercyIgpUvNJvgr98EPpLnUSkHWz67grOnj1rU2Kg9sQl1tbW4sqVKwYA/NYWEbUam767ve+//77jgw8+ULuOZjkcDjz44IM2o9H4kZSy6bvKRERN4Jx+E4QQtxkMhv2/+MUvXNHR0ZpaWtnhcODMmTP6ioqKL8rLy8dIKRX5q4SIAgObfjOEEF0BJACIULmUxlwALgD4WkrpULsYIvIvbPpERB0I5/SJiDoQNn0iog7k/wG5Luo5p60fXgAAAABJRU5ErkJggg==\n", 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" ] @@ -115,8 +118,9 @@ } ], "source": [ - "tree1 = utils.create_tree('((Group1, Group2)Group12, Group3,(Group4, (Group5, Group6)Group56)Group456)root')\n", - "utils.print_tree(tree1)" + "tree1_oc = utils.create_tree('((Group1, Group2)Group12, Group3,(Group4, (Group5, Group6)Group56)Group456)root')\n", + "tree1_knn = utils.create_tree('((Group1, Group2)Group12, Group3,(Group4, (Group5, Group6)Group56)Group456)root')\n", + "utils.print_tree(tree1_oc)" ] }, { @@ -142,7 +146,9 @@ "metadata": {}, "outputs": [], "source": [ - "tree1 = train.train_tree(x_train, y_train, tree1, classifier = 'svm_occ', dimred = True, useRE = True, FN = 0.5)" + "# We train one tree with the oneclass SVM and one with the kNN classifier\n", + "tree1_oc = train.train_tree(x_train, y_train, tree1_oc, classifier = 'svm_occ', dimred = True, useRE = True, FN = 0.5)\n", + "tree1_knn = train.train_tree(x_train, y_train, tree1_knn, classifier = 'knn', dimred = True, useRE = True, FN = 0.5)" ] }, { @@ -171,12 +177,18 @@ "name": "stderr", "output_type": "stream", "text": [ - "AnnData expects .obs.index to contain strings, but your first indices are: Int64Index([4607, 2233], dtype='int64'), …\n", - "C:\\Users\\lcmmichielsen\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:1732: SettingWithCopyWarning: \n", + "/exports/humgen/lmichielsen/miniconda3_v2/envs/scarches2/lib/python3.8/site-packages/anndata/_core/anndata.py:798: UserWarning: \n", + "AnnData expects .obs.index to contain strings, but got values like:\n", + " [4607, 2233, 6328, 5815, 4333]\n", + "\n", + " Inferred to be: integer\n", + "\n", + " value_idx = self._prep_dim_index(value.index, attr)\n", + "/tmp/ipykernel_1627501/1670240449.py:13: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " self._setitem_single_block(indexer, value, name)\n" + " adata_progressive.obs['batch'].iloc[testindex] = count\n" ] } ], @@ -259,7 +271,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", "text/plain": [ "
" ] @@ -329,7 +341,7 @@ "source": [ "### Predict labels\n", "\n", - "A trained tree (with or without progressive learning) can be used to predict the labels of another dataset" + "A trained tree (with or without progressive learning) can be used to predict the labels of another dataset. When using the one-class SVM or linear SVM, this function only returns the predicted labels. For the kNN, the probabilities are also returned." ] }, { @@ -338,8 +350,38 @@ "metadata": {}, "outputs": [], "source": [ - "y_pred1 = predict.predict_labels(x_test, tree1) # tree constructed without progressive learning\n", - "y_pred2 = predict.predict_labels(x_test, tree2) # tree constructed with progressive" + "y_pred1_oc, _ = predict.predict_labels(x_test, tree1_oc) # tree constructed without progressive learning\n", + "y_pred1_knn, y_prob1_knn = predict.predict_labels(x_test, tree1_knn) # tree constructed without progressive learning\n", + "y_pred2, _ = predict.predict_labels(x_test, tree2) # tree constructed with progressive" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['Group4' 'Group6' 'Group4' 'Group3' 'Group1' 'Group1' 'Group4' 'Group6'\n", + " 'Group1' 'Group5']\n", + "[[1. ]\n", + " [0.98]\n", + " [1. ]\n", + " [0.92]\n", + " [0.92]\n", + " [0.84]\n", + " [1. ]\n", + " [0.96]\n", + " [0.86]\n", + " [1. ]]\n" + ] + } + ], + "source": [ + "print(y_pred1_knn[:10])\n", + "print(y_prob1_knn[:10])" ] }, { @@ -355,7 +397,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -367,7 +409,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", "text/plain": [ "
" ] @@ -391,12 +433,12 @@ } ], "source": [ - "HF1_score1 = evaluate.hierarchical_F1(y_test.values, y_pred1, tree1)\n", + "HF1_score1 = evaluate.hierarchical_F1(y_test.values, y_pred1_oc, tree1_oc)\n", "\n", "print('Hierarchical F1-score without progressive learning: ', \n", " np.round(HF1_score1,2))\n", "\n", - "confmatrix1 = evaluate.heatmap(y_test, y_pred1, shape=(6,4))\n", + "confmatrix1 = evaluate.heatmap(y_test, y_pred1_oc, shape=(6,4))\n", "confmatrix2 = evaluate.heatmap(y_test, y_pred2, shape=(6,4))" ] }, @@ -411,7 +453,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -423,7 +465,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -443,7 +485,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -455,7 +497,7 @@ }, { "data": { - "image/png": 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\n", 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R0dE4evQoYmNj8Y9//AMAMHv2bCQmJuLYsWNISEjAnDlzAAD//d//jRkzZuCHH35ASEhI9XHS0tJw9uxZfPvttzhy5AgyMzOxd+9eJ7xzROSKPPaWzabGMAYMfbTG46+//hqZmZkYOHAgAKC0tBTt2rUDACxatAgDBw6Et7c3Vq1aVe8xfx/TKKXEggULsHfvXqhUKly5cgVZWVno0KFDjdd4eXkhPj4eANC/f398+eWXAICDBw9i27ZtAICJEydi/vz5AID9+/dXp4ZNnDgRzzzzDIAbTT8tLQ19+/YFABQXF+Ps2bOIjY1tyttDRG7OI5t+82IY41Pwp/+bA5FSIjExES+//LLNvrm5uSguLkZlZSXKysrqjWP8/fZNmzYhOzsbmZmZ0Gq1CA0NrRHJWEWr1VZ/yKpWqxv1eUBdH8pKKfHss89i+vTpDb6eiDwfp3caMHz4cHz88ce4du0aACAvLw8XL14EAEyfPh0vvvgiEhISqq+s/fz8UFRUVO/xCgsL0a5dO2i1Wuzevbv6WI01ZMiQ6pCYTZs2VYewDx06tMb2Kvfeey/ee+89VOUOXLlypfpciKjl8cgrfXvq3bs3XnrpJdxzzz2wWq3QarVYs2YN0tPTodVqMX78eFgsFgwZMgS7du1CTEwM1Go1+vTpg6SkJLRu3brG8RISEjBy5EhERkZiwIAB6NWr1y3V8/e//x2TJ0/GihUrEBwcjPfffx8A8MYbb2D8+PFYtmwZHnzwwer977nnHpw6dQqDBw8GcOMD4o0bN1ZPURFRCyOlbPCn6zOfysbs5wk/AFIWL14sW4rFixdLACnSBd57/vCHP47/4fSOrZL8/PxKpYtwlry8vAoAJUrXQUTOwaZv6+hHH31UUXVfvCfLysrCxx9/XAngiNK1EJFzcE6/Fillmk6n+5/o6Oi58+bN07Vt29bjliqQUiInJwevvvqqqaCg4H+klF8qXRMROQebfh1MJtNzQojTCxYsGOHl5RWsdD2OUFFRkV1UVPSllHKj0rUQkfOw6dfjt2bIhkhEHoVz+kRELYjTrvSFECGBgYEbLBZLpMVi8XbWuI2hVqsr1Gr1mYKCgslSyrNK10NE5ChOafpCiA56vf6bJ5544rakpCSNn5+fM4ZtNJPJhB07dgQtWrTooBAiWkp5TumaiIgcwSlN39vbO3nSpEm3vfzyyy77GcK8efNUJpOp9WuvvbYCwENK10NE5AhOmdPX6/URw4YNc9mGXyUuLk6lUqlubV0EIiI34pSmL4Tw8vauOY2flZWF8ePH4/bbb0f//v0xePBgbN++3aF1PPbYY+jTpw8MBgPGjh1bvQhZFW9vb0gptQ4tgohIQYrcvSOlxOjRoxEbG4vz588jMzMTW7ZsweXLl2vsZ+94wddffx1Hjx7FsWPH0KVLF6xevdquxycicnWKNP1du3bBy8sLTzzxRPW2rl27Yvbs2Tbxgnl5eRg9ejQMBgOio6Nx7NgxAEBKSgpWrlxZ/fqIiAgYjUYYjUb06tULCQkJCAsLw9ixY2EymQAA/v7+AG780iktLfW4b9oSETVEkaZ/4sQJ9OvXr97nfx8vuHjxYvTt2xfHjh3D0qVLMWnSpAaP/+OPP2LmzJk4deoU/P398eabb1Y/N3nyZHTo0AGnT5/G7Nmz7XI+RETuwiW+nDVr1iz06dOnOpLw9/GCGRkZmDhxIgAgLi4Oubm5uH79+k2P17lzZwwdOhQAMGHCBGRkZFQ/9/777+Pq1asICwvD1q1bHXE6REQuq9F31DQ1cxYAVO171HgcHh5enecKAGvWrEFOTg4GDBgAAPXGDv6eRqOB1Wqtfvz7yMHa0za1H6vVavzlL3/B8uXLMXny5MafCBGRm2t0029O7mzwu0l7AcRUPY6Li8OCBQuwdu1azJgxAwCq591ri4mJwaZNm/D8889jz549aNu2Lfz9/REaGopPP/0UwI3poAsXLlS/5tKlSzh48CAGDx6MzZs3484774SUEj/99BO6d+8OKSV27tx5y6lVRETuTpF754UQSE1Nxdy5c7F8+XIEBwdDr9dj2bJlKC0trbFvSkoKpkyZAoPBAJ1Oh/Xr1wMAHn74YWzYsAHh4eG444470KPH//010bNnT6xZswZTpkxB7969MWPGDEh5I+D8+vXrkFKiT58+WLt2rVPPm4hIaYp9YSokJKQ6yLu2pKSk6n+3adMGqampNvv4+PggLS3NZrvRaIRGo8HGjbYLZO7fv7/J9RIReQKnfJArpbTY+557R/itRmtD+xERuSunNP3y8vJzJ0+edMZQCA0NxfHjx5v02hMnTkAIcdHOJRERuQynNP3i4uLVS5cuLdq+fTukbPJNQA4jpUR6ejrmzJljysvL+5vS9RAROYpT5vSllEeFEHETJkz43GKxBPj4+FQ6Y9zGKi8v10gpy8vKyh6WUu5Ruh4iIkdx2ge5UspDAIKFEAHl5eUN34jvXGUA8qUr/hlCRGRHTr97R0pZCKDQ2eMSEZGTm74Q4i4AEQBc7Uq/KQoBfCelPKx0IUREjeW0pq/T6V5q3779k/Hx8arAwEC3X7M+KyurYufOndBoNNPNZrPtlwKIiFyQU5q+RqOZ3Llz57nffPONrn379s4Y0hk0J06cwJ133vm2EOKilHKf0gURETXEKbds+vn5xS9atMiTGj6AGwvHTZ061UsIEat0LUREjeGUpq9Wq4ODgoKcMZTTtW/fXuPt7e1Zv82IyGM5KyPXZnljJTJyq8yZMwe+vr7Vj9etW4fg4GBERUUhKioK77zzTvVzly5dwj333IOwsDD07t0bRqOxxrHqOjciIlelyIJrVRm5iYmJ2Lx5MwDg4sWL2LlzZ439zGYzNBr7lnjo0CHk5+fbbB83blydmbmTJk3CwoULMWLECBQXF0OlconcGSKiJmlRGbkWiwVPP/00li9f3qg6T548CbPZjBEjRgAAfH19odPp7PU2EBE5XYvKyF29ejVGjRqFkJAQm9d88sknMBgMGDt2LH7++WcAwJkzZxAYGIgxY8agb9++ePrpp2GxWJp41kREylMkLrG2WbNmISMjA15eXpg1a5ZNRm5VtGJTM3JXrVqF8ePH46OPPsKePXts9h85ciQeffRRtGrVCm+//TYSExOxa9cumM1m7Nu3D99//z26dOmCcePGYd26dXjsscea8C4QESmvUU2/OVGJgG1cohIZud9//z3OnTuH7t27A7gRz9i9e3ecO3cOv7+zaOrUqZg/fz4AoFOnToiKisLtt98OABg9ejS++eYbNn0icluKTO/ExcWhrKysRlxhQxm5AGwycg8fvrECQn0ZuQCqM3IfeOAB/Prrr9Xz/jqdDufOnQMA/PLLL9Wv3blzJ8LCwgAAAwcOREFBAbKzswHc+Cyid+/e9nobiIicrsVk5N7MqlWr8NuSCmjTpg3WrVsHAFCr1Vi5ciWGDx8OKSX69++Pxx9/3L5vBhGREwlnrCYcHBy897333osZOXKkw8cyGo2Ij49vcnrWrXr11VexaNGiv5eUlMxxyoBERM3glOkdi8WSl5eX54yhnC47O9tSVlaWq3QdRESN4ZQrfa1W+/969eq1LCMjQxcQEODw8ZzFaDRi0KBBpuzs7NFSyi+VroeIqCFOafpCCKHX698KCQlJGDdunI+/v7/bf601JyfHvG7duorCwsIF5eXlbyhdDxFRYzil6QM3Gj+AMSqVyuDl5eUHAD59H5hb+v1nrzulADsrLy/PlVL+R0r5ldK1EBE1ltOafl1Ckz+Tzf0OABERNZ4it2w6ghBCA8DVfoGYGbZORK7E7Zu+j4/PPJVK9bxKpfIH4EoNVmg0mvLAwMCvCgsL/0tKWdrwS4iIHMutP1D18fGZHxQUtOTQoUMBlZWVwmKxqFzoR1y9etV7+PDhw/38/NKEEF5Kv19ERG7b9IUQKovF8uKBAwd0YWFhLrnOfVBQELZu3eoTEhISBYCRikSkONfrlI0X3KpVK2uXLl2UruOmNBoN+vfvLwB0VboWIiJ3bvpqjUZjrb3RlWIYq3h5eQkAaqcUQUR0E+7c9G1UxTDGxsbi/PnzyMzMxJYtW3D58uUa+5nNZruPXV8MIxGRK/Gopu8uMYxERErxqKbvijGMRESuRPH79Jsaw9hx5nqUfPj0TfdROoaRiMjVKN70m7oMgxDitsDAwLMAdFXbXC2GkYjI1XjU9I6rxTASEbkaj2r6VTGM6enp6NatGwYNGoTExEQsW7bMZt+UlBRkZmbCYDAgOTm5RgxjXl4ewsPDsXr16jpjGMPCwpCfn99gDCMRkatRfHrH3kJCQrBly5Y6n0tKSqr+d5s2bZCammqzj4+PD9LS0my2G41GaDQabNy48abjFxcX31K9RETO5M5X+ubKykq3qL+8vFwCsP+XA4iIbpFbNM16ZFdUVKh++uknpwwWGhrapLD1iooKHDp0SAIw2r0oIqJb5LbTO1JK2apVq78OGTJk+WeffaYLDw+HRuM6pyOlRFZWFqZPn27Kyso6CGCf0jUREblOl2yC8vLyNd7e3ta4uLjFJpOprZTSpUJUvL29i7Ra7RdFRUUTpZSVStdDROTWTR8AysrK1gJY2+CORETk1nP6RER0i9z+Sl8I0QXAOF9f3+5CCLdYvthsNpeVlpaeBrBeSlmkdD1E1HK4ddMXQtyu0+m+GTduXKDBYNC60ge5N1NWVoavvvqq9MCBA1OEEHex8RORs7hHl6yHr6/vrldeeSVo1qxZbjdN9de//tVn8uTJYTt27FgH4GGl6yGilsHtmmUVIYRvRUXFbTNmzHDLc1CpVJg/f763lDJa6VqIqOVwy4b5G3+dTlfpioHojdW6dWuYzeaGl/4kIrIT9+2Y9VAiIzcpKQndunVDVFQUoqKicOTIkern9uzZg6ioKISHh+Ouu+5yaB1ERA1x6zn92qoychMTE7F582YAwMWLF7Fz584a+5nNZrt/e3fFihUYO3ZsjW0FBQWYOXMm/v3vf6NLly64du2aXcckIrpVHnWlr1RGbn02b96MMWPGoEuXLgCAdu3aOeCsiYgaz6OavlIZuQCwcOFCGAwGzJ07F+Xl5QCAM2fOID8/H3fffTf69++PDRs2NP8kiYiaQfHpHXfPyH3qqafw8ssvo0OHDqioqMC0adOwbNkyLFq0CGazGZmZmfj6669RWlqKwYMHIzo6ukYwCxGRMyna9Juajwu4TkYucCO4BQBatWqFyZMnV08PderUCUFBQdDr9dDr9YiNjcXRo0fZ9IlIMR41vaNERi4A/PLLLwBufJCcmpqKiIgIAMCDDz6IjIwMmM1mmEwm/Oc//0FYWJidz5qIqPEUn96xp6qM3Llz52L58uUIDg6GXq/HsmXLUFpaWmPflJQUTJkyBQaDATqdrkZG7oYNGxAeHo477rijzozcKVOmoHfv3tUZuQkJCcjOzoaUElFRUXjrrbcAAGFhYbjvvvtgMBigUqkwderU6l8IRERKEFI2aUpdcUKI2wICAs4WFBToGt67+YxGI+Lj45uUnlWfK1euoEePHoUlJSWBdjsoEdFNuPP0Tl5JSUkrs9l9o2evXbsGLy+vAqXrIKKWw22bvpSyTKfTff/kk09WOOOvlaZm5NantLQUc+bMMVmt1s/sdlAioga47fQOAAghAv38/Pb36NGjs8Fg0Gi1WgEAFqi81bCWNfR6pZhMJuv+/futOTk5aUVFRf8lpbQoXRMRtQxu3fSBG6ttArgbQBf89pdL6z9N/3v+V2/PVrKuBlQAOAcgnQ2fiJzJ7Zt+XUKTP5PN+Q4AEZGn8qhbNu1J3PjmVRCAQIVLqc0K4KqU0mWnr4jIdbHp10EI0Vmv1++zWq0h/v7+FbW/iaski8Ui8vPzvf39/dcVFRVNk1JaG34VEdENbPq1CCHa6/X6/6SkpATPmzdPI4TwUrqm2q5fv4677777L+fOnQOAqUrXQ0Tuw21v2XSg+OHDhwc89dRTGle6wv89f39/7NmzR28ymZJc8ZcSEbkuNn1bnSIjI32ULqIh/v7+CAgIKAMQonQtROQ+2PRtCY1GU+MS39UiGKv8lg/smn+OEJFL4px+A1wtgpGIqDl4pd8AV4tgJCJqDjb9BrhaBCMRUXN47PROU2MYA4Y+etPnlY5gJCJqDo9t+k1dhkGI+BT8afHiqseuFsFIRNQcnN5pgKtFMBIRNQebfgOqIhjT09PRrVs3DBo0CImJiVi2bJnNvikpKcjMzITBYEBycnKNCMa8vDyEh4dj9erVdUYwhoWFIT8/v0YEY2RkJCIjI5GTk4PnnnvOOSdMRB7NY6d37CkkJARbtmyp87mkpKTqf7dp0wapqak2+/j4+CAtLc1mu9FohEajwcaNG22e27VrV5PrJSKqD6/0bVWUlJS4xRr3FRUVKtxYm5+IqFHY9G2dS0tLK3PGLZLNiWA8evQoSktLVQB+tW9VROTJOL1ja/uFCxcmx8fHxy5ZskTXtm1bmztslGQ2m3H69GkkJiaWms3myVxamYhuBZt+LVLKSiHEqG+//XbVAw88MNxisfgrXVMtUqvVXikuLv6b1Wp17AJARORx2PTrIKWsBDBD6TqIiOyNc/pERC0Ir/TrIIQQKpVqWkBAwL1qtbqt0vX8npTSUl5e/lNxcfFaKWWm0vUQkXth069FCCF0Ot1rnTp1evzZZ5/Vt2nTxqU+yLVYLDh9+vTdL7744jghxAgp5TdK10RE7oNN39b9QUFBjx84cEAfFBSkdC31ioyM9B07duy/hRCtpZRNWlyOiFoezunbihgzZoyXKzd8AHjggQegVqtbAQhWuhYich9s+rZ0gYGBWqWLaAwfHx8LAJ3SdRCR+2DTbwQlMnKllFi4cCF69OiBsLAwrFq1yqHjEVHLwDn9BiiVkbtu3Tr8/PPPOH36NFQqFa5du2a3YxNRy8Ur/QYolZG7du1aLFq0CCrVjf+idu3aOfGsichTsek3QKmM3J9++glbt27FgAEDcP/99+Ps2bN2Oyciark8dnrH3TNyy8vL4e3tjUOHDmHbtm2YMmUK9u3b15RTIiKq5pFNv6n5uIDrZOR26tQJY8aMAQA89NBDmDx5clNOh4ioBk7vNECpjNzRo0dj9+7dAID09PQaEYtERE3Fpt8ApTJyk5OT8cknnyAyMhLPPvss3nnnHeecMBF5NMFv8NckhEhZtGjR4hdeeMHhYxmNRsTHxzc5Patt27Ylubm5EVJKo30rIyJPxSt9W1nnz58vVbqIhlRWVqKwsNAbAG/gJ6JGY9O39eW2bdvMO3bscPhATc3INZvNePTRR0t1Ot1eKWXdHzAQEdWB0zt1EEIM8Pb23vWHP/zBGhwc7FJLK5vNZpw7d05TXFx8pKioaISU0uX/KiEi18GmXw8hRGsAEQACFS6lNiuAnwGclFKalS6GiNwLmz4RUQvCOX0iohaETZ+IqAX5X5dFVbIrjyusAAAAAElFTkSuQmCC\n", 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" ] @@ -475,7 +517,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -487,7 +529,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -508,7 +550,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -520,7 +562,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -538,6 +580,13 @@ "utils.print_tree(tree)" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": null, @@ -562,7 +611,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.3" + "version": "3.8.13" } }, "nbformat": 4,