583 lines
1.0 MiB
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583 lines
1.0 MiB
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"colab_type": "text",
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"id": "view-in-github"
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},
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"source": [
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"<a href=\"https://colab.research.google.com/github/PYFTS/notebooks/blob/master/Partitioners.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"colab_type": "text",
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"id": "ZlQnXBu9ctrW"
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},
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"source": [
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"# Exploring the Universe of Discourse Partitioners"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"colab_type": "text",
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"id": "thnWEpjBctrb"
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},
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"source": [
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"## Environment Setup"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"colab_type": "text",
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"id": "tUF7TEtictre"
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},
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"source": [
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"### Library install/update"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 211
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},
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"colab_type": "code",
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"id": "8tGJbEpactrh",
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"outputId": "40a187e4-1030-4a2e-9d0d-d3e755ce595c"
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},
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"outputs": [],
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"source": [
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"# !pip install -U --force-reinstall --no-deps -e git+https://git.athene.tech/sam/pyFTS.git#egg=pyFTS"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"colab_type": "text",
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"id": "Q3BI8Ztzctrq"
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},
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"source": [
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"### External libraries import"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 34
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},
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"colab_type": "code",
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"id": "fVffyFL2ctrs",
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"outputId": "e3cd497a-3845-4db9-eadb-2677897309e7"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
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"Populating the interactive namespace from numpy and matplotlib\n"
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]
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}
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],
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"source": [
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"import warnings\n",
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"warnings.filterwarnings('ignore')\n",
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"\n",
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"\n",
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"import matplotlib.pylab as plt\n",
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"\n",
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"%pylab inline\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"colab_type": "text",
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"id": "LCFqX2ZIctr0"
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},
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"source": [
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"### Common pyFTS imports "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"colab": {},
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"colab_type": "code",
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"id": "eb5APQxcctr1"
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},
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"outputs": [
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{
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"name": "stderr",
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|
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"output_type": "stream",
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"text": [
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"2024-08-08 12:33:54.147886: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
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"2024-08-08 12:33:54.168752: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
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"2024-08-08 12:33:54.175031: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
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"2024-08-08 12:33:54.191648: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
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"To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
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"2024-08-08 12:33:55.150180: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
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]
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}
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],
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"source": [
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"from pyFTS.partitioners import KMeans, Grid, FCM, Huarng, Entropy, Util as pUtil\n",
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"from pyFTS.common import Membership as mf\n",
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"from pyFTS.benchmarks import benchmarks as bchmk\n",
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"from pyFTS.data import Enrollments"
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]
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},
|
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{
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"cell_type": "markdown",
|
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|
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"metadata": {
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|
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"colab_type": "text",
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|
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"id": "LFAd9ZEcctr5"
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},
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"source": [
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"### Common data transformations"
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]
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},
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{
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"cell_type": "code",
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|
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"execution_count": 4,
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|
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"metadata": {
|
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|
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"colab": {},
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|
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"colab_type": "code",
|
||
|
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"id": "RB-lOHCYctr8"
|
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|
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},
|
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"outputs": [],
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"source": [
|
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|
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"from pyFTS.common import Transformations\n",
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"\n",
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"tdiff = Transformations.Differential(1)"
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]
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},
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{
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"cell_type": "markdown",
|
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|
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"metadata": {
|
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|
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"colab_type": "text",
|
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|
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"id": "04AsyGJ3ctsB"
|
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|
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},
|
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|
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"source": [
|
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|
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"## Dataset"
|
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|
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]
|
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},
|
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{
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"cell_type": "markdown",
|
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|
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"metadata": {
|
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"colab_type": "text",
|
||
|
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"id": "PYqZTrClctsE"
|
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|
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},
|
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|
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"source": [
|
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|
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"### Data Loading"
|
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|
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]
|
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|
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},
|
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|
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{
|
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|
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"cell_type": "code",
|
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|
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"execution_count": 5,
|
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|
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"metadata": {
|
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|
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"colab": {},
|
||
|
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"colab_type": "code",
|
||
|
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"id": "zlhRQcYZctsG"
|
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|
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},
|
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|
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"outputs": [],
|
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|
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"source": [
|
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|
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"from pyFTS.data import TAIEX\n",
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"\n",
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"dataset = TAIEX.get_data()\n",
|
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|
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"dataset_diff = tdiff.apply(dataset)"
|
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|
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]
|
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|
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},
|
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|
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{
|
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|
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"cell_type": "markdown",
|
||
|
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"metadata": {
|
||
|
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"colab_type": "text",
|
||
|
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"id": "5hLqGdOactsM"
|
||
|
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},
|
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|
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"source": [
|
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|
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"### Visualization"
|
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|
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]
|
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|
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},
|
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|
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{
|
||
|
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"cell_type": "code",
|
||
|
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"execution_count": 6,
|
||
|
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"metadata": {
|
||
|
|
"colab": {
|
||
|
|
"base_uri": "https://localhost:8080/",
|
||
|
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"height": 340
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|
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},
|
||
|
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"colab_type": "code",
|
||
|
|
"id": "zTU74CmlctsM",
|
||
|
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"outputId": "3e1b62fc-95d5-48e4-a85c-50e5c1f32ea7"
|
||
|
|
},
|
||
|
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"outputs": [
|
||
|
|
{
|
||
|
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"data": {
|
||
|
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"text/plain": [
|
||
|
|
"[<matplotlib.lines.Line2D at 0x7048949da350>]"
|
||
|
|
]
|
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|
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},
|
||
|
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"execution_count": 6,
|
||
|
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"metadata": {},
|
||
|
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"output_type": "execute_result"
|
||
|
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},
|
||
|
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{
|
||
|
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"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1000x500 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"fig, ax = plt.subplots(nrows=2, ncols=1, figsize=[10,5])\n",
|
||
|
|
"ax[0].plot(dataset)\n",
|
||
|
|
"ax[1].plot(dataset_diff)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {
|
||
|
|
"colab_type": "text",
|
||
|
|
"id": "sFSoNXc0ctsS"
|
||
|
|
},
|
||
|
|
"source": [
|
||
|
|
"## Exploring partitioning schemes"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {
|
||
|
|
"colab_type": "text",
|
||
|
|
"id": "G6JfThwEctsU"
|
||
|
|
},
|
||
|
|
"source": [
|
||
|
|
"### Same method with different membership functions"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 7,
|
||
|
|
"metadata": {
|
||
|
|
"colab": {
|
||
|
|
"base_uri": "https://localhost:8080/",
|
||
|
|
"height": 729
|
||
|
|
},
|
||
|
|
"colab_type": "code",
|
||
|
|
"id": "cQjZXjuHctsV",
|
||
|
|
"outputId": "615f3d24-7e7b-4dae-8a67-eda8e5a0f493"
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAABKUAAAPdCAYAAABba9tpAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOz9eZAk+Vnfj78ys+6r73O6557ZnXtmF7why/ZXRMiWgcCY+OHgtIxsbCODMcg/ExI2wqdkY2QcQQiEBUL62iaALyH7qy/oC9ZPZk1gBIjd6Z1z5776qL67rq4zM39/ZH2yqmf6qCMrM2v384rY2NmuquxP73TV8+Tzfp73o5imaSKRSCQSiUQikUgkEolEIpG4iOr1ASQSiUQikUgkEolEIpFIJO8+ZFFKIpFIJBKJRCKRSCQSiUTiOrIoJZFIJBKJRCKRSCQSiUQicR1ZlJJIJBKJRCKRSCQSiUQikbiOLEpJJBKJRCKRSCQSiUQikUhcRxalJBKJRCKRSCQSiUQikUgkriOLUhKJRCKRSCQSiUQikUgkEteRRSmJRCKRSCQSiUQikUgkEonryKKURCKRSCQSiUQikUgkEonEdWRRSiKRSCQSiWQPfuAHfoCjR48e+LzHjx+jKAqf//zne36mg3jf+97H+973PkevWavV+Imf+AlmZ2dRVZW//tf/uqPXl0gkEolE8u5EFqUkEolEIpG843j06BE/8iM/wunTp4nFYsRiMc6ePcsP//APc+3aNa+P1xKLi4v883/+z5mbm/P6KHzuc5/j3//7f893fud38oUvfIEf//Ef9/pIEolEIpFI3gEEvD6ARCKRSCQSiZP89m//Nt/1Xd9FIBDg+77v+7h06RKqqvL222/zxS9+kV/8xV/k0aNHHDly5MBrffazn8UwDBdO/SKLi4v8i3/xLzh69CiXL19u+XX/43/8D8fP8j//5//k0KFD/NzP/Zzj15ZIJBKJRPLuRRalJBKJRCKRvGN48OAB3/3d382RI0f46le/ytTU1I7H/92/+3f8wi/8Aqq6f7N4oVAgHo8TDAZ7eVxH2d7eJhaLEQqFHL/2ysoKg4ODjl9XIpFIJBLJuxs5vieRSCQSieQdw8/8zM9QKBT41V/91RcKUgCBQIAf/dEfZXZ21v7aD/zAD5BIJHjw4AHf8i3fQjKZ5Pu+7/vsx573lNra2uIHfuAHGBgYYHBwkL/1t/4WW1tbjv4cr7/+Ot/4jd8IwIc+9CEURdnhWfW+972P8+fP88Ybb/CX/tJfIhaL8ZM/+ZP2Y82eUq+//jqKovCbv/mb/It/8S84dOgQyWSS7/zO7ySTyVAul/mxH/sxxsfHSSQSfOhDH6JcLgMNr6zf//3f5+bNm/Y5Xn/9dUd/XolEIpFIJO9OZKeURCKRSCSSdwy//du/zcmTJ3nttdfael2tVuMDH/gAf+Ev/AV+9md/llgstuvzTNPk27/92/nDP/xDfuiHfogzZ87w3/7bf+Nv/a2/5cTxbc6cOcO//Jf/ko9//OP8vb/39/iLf/EvAvDn//yft5+zvr7ON3/zN/Pd3/3dfP/3fz8TExP7XvOTn/wk0WiUj370o9y/f5+f//mfJxgMoqoqm5ub/PN//s/54z/+Yz7/+c9z7NgxPv7xjzM2NsZ//s//mX/zb/4N+XyeT37yk/b5JBKJRCKRSLpFFqUkEolEIpG8I8hmsywuLu66GW5ra4tarWb/dzweJxqN2v9dLpf5G3/jb9hFl7340pe+xB/8wR/wMz/zM/yTf/JPAPjwhz/MN33TNznzQ9SZmJjgm7/5m/n4xz/Oe97zHr7/+7//heek02k+85nP8Pf//t9v6Zq1Wo3/9b/+lz2SuLq6yq//+q/zV//qX+XLX/4yAP/gH/wD7t+/z+c+9zk+/vGPE4/H+f7v/35++Zd/GU3Tdj2HRCKRSCQSSafI8T2JRCKRSCTvCLLZLACJROKFx973vvcxNjZm//PpT3/6hed8+MMfPvB7fPnLXyYQCOx4rqZp/MN/+A+7OHlnhMNhPvShD7X8/A9+8IM7PLJee+01TNPkb//tv73jea+99hrPnj3bUcSTSCQSiUQi6QWyU0oikUgkEsk7gmQyCUA+n3/hsV/6pV8il8uxvLy8a7dPIBBgZmbmwO/x5MkTpqamXih8vfTSSwe+Vtd1VldXd3xteHi4Y2PyQ4cOtfXaw4cP7/jvgYEBgB3+WuLrhmGQyWQYGRnp6GwSiUQikUgkrSCLUhKJRCKRSN4RDAwMMDU1xY0bN154THhMPX78eNfXhsPhAzfydcuzZ884duzYjq/9/u///g5T8nZoHj9sBU3T2vq6aZptn0kikUgkEomkHWRRSiKRSCQSyTuGb/3Wb+WXf/mX+dM//VP+3J/7c45f/8iRI3z1q18ln8/v6Ja6c+fOga+dnJzkK1/5yo6vXbp0ac/nK4rS+UElEolEIpFI+gDpKSWRSCQSieQdw0/8xE8Qi8X423/7b7O8vPzC4912/3zLt3wLtVqNX/zFX7S/pus6P//zP3/gayORCO9///t3/DM0NLTn8+PxOGCZtEskEolEIpG8E5GdUhKJRCKRSN4xnDp1il/7tV/je77ne3jppZf4vu/7Pi5duoRpmjx69Ihf+7VfQ1XVlvyjduPbvu3beO9738tHP/pRHj9+zNmzZ/niF79IJpNx+CeBEydOMDg4yGc+8xmSySTxeJzXXnvthRFAiUQikUgkkn5FFqUkEolEIpG8o/j2b/92rl+/zqc+9Sn+x//4H3zuc59DURSOHDnCt37rt/JDP/RD+47N7YeqqnzpS1/ix37sx/gv/+W/oCgKf+2v/TU+9alPceXKFUd/jmAwyBe+8AU+9rGP8UM/9EPUajV+9Vd/VRalJBKJRCKRvGNQTOliKZFIJBKJRCKRSCQSiUQicRnpKSWRSCQSiUQikUgkEolEInEdWZSSSCQSiUQikUgkEolEIpG4jixKSSQSiUQikUgkEolEIpFIXEcWpSQSiUQikUgkEolEIpFIJK4ji1ISiUQikUgkEolEIpFIJBLXCXh9gFYwDIPFxUWSySSKonh9HIlEIpFIJBKJRCKRSCQSyR6Ypkkul2N6ehpV3bsfqi+KUouLi8zOznp9DIlEIpFIJBKJRCKRSCQSSYs8e/aMmZmZPR/vi6JUMpkErB8mlUp5fBqJRCKRSCQSiUQikUgkEsleZLNZZmdn7XrOXvRFUUqM7KVSKVmUkkgkEolEIpFIJBKJRCLpAw6yYJJG5xKJRCKRSCQSiUQikUgkEteRRSmJRCKRSCQSiUQikUgkEonryKKURCKRSCQSiUQikUgkEonEdWRRSiKRSCQSiUQikUgkEolE4jqyKCWRSCQSiUQikUgkEolEInEdWZSSSCQSiUQikUgkEolEIpG4jixKSSQSiUQikUgkEolEIpFIXEcWpSQSiUQikUgkEolEIpFIJK4ji1ISiUQikUgkEolEIpFIJBLXkUUpiUQikUgkEolEIpFIJBKJ68iilEQikUgkEolEIpFIJBKJxHVkUUoikUgkEolEIpFIJBKJROI6siglkUgkEolEIpFIJBKJRCJxHVmUkkgkEolEIpFIJBKJRCKRuI4sSkkkEolEIpFIJBKJRCKRSFxHFqUkEolEIpFIJBKJRCKRSCSuI4tSEolEIpFIJBKJRCKRSCQS12m7KPUHf/AHfNu3fRvT09MoisJ//+///cDXvP7667zyyiuEw2FOnjzJ5z//+Q6OKpFIJBKJRCKRSCQSiUQieafQdlGqUChw6dIlPv3pT7f0/EePHvGt3/qtfNM3fRNzc3P82I/9GD/4gz/I7/3e77V9WIlEIpFIJBKJRCKRSCQSyTuDtotS3/zN38y//tf/mu/4ju9o6fmf+cxnOHbsGJ/61Kc4c+YMP/IjP8J3fud38nM/93N7vqZcLpPNZnf8I/EPW9sVvv+X/4Rf/9OnXh+lc0wTfucfw5d+1Ppzn/KlB1/iB3/vB9kobXh9lI4pP3jA4+/+Hgp//MdeH6VjahWdL//iNd743cdeH6Ur/uj/+q/8Pz/3b9FrV
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1200x1000 with 3 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"part = pUtil.explore_partitioners(dataset, 20, methods=[Grid.GridPartitioner], \n",
|
||
|
|
" mf=[mf.trimf, mf.trapmf, mf.gaussmf])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 8,
|
||
|
|
"metadata": {
|
||
|
|
"colab": {},
|
||
|
|
"colab_type": "code",
|
||
|
|
"id": "1maVmSL5ctsa",
|
||
|
|
"outputId": "54a65ef8-897b-4f99-b9a1-79e8facb0363"
|
||
|
|
},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"# for p in part:\n",
|
||
|
|
"# print(p)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {
|
||
|
|
"colab_type": "text",
|
||
|
|
"id": "mtuhZt-yctsh"
|
||
|
|
},
|
||
|
|
"source": [
|
||
|
|
"### Same mathod with different membership functions and transformation"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {
|
||
|
|
"colab": {
|
||
|
|
"base_uri": "https://localhost:8080/",
|
||
|
|
"height": 729
|
||
|
|
},
|
||
|
|
"colab_type": "code",
|
||
|
|
"id": "UNv9tWewctsi",
|
||
|
|
"outputId": "3582cd29-4286-4dff-a494-dd3772d6cd9f"
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAABKUAAAPdCAYAAABba9tpAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOz9d3Ac953n/z97MmYQBjky5whGMYjKJJWzmCRZwfberW/3u7frq+/+1vu99V606+7svava8q73bGsli5JIisqZFCWSCgxgJpgzQOQcBpOnf380ekCCCWFmGhi8H1UsQsBM95tT0KDx6ff79VFUVVURQgghhBBCCCGEECKBTEYXIIQQQgghhBBCCCFGHlmUEkIIIYQQQgghhBAJJ4tSQgghhBBCCCGEECLhZFFKCCGEEEIIIYQQQiScLEoJIYQQQgghhBBCiISTRSkhhBBCCCGEEEIIkXCyKCWEEEIIIYQQQgghEk4WpYQQQgghhBBCCCFEwsmilBBCCCGEEEIIIYRIOFmUEkIIIYS4gZdeeomxY8fe8nEXL15EURReffXVuNd0K3fffTd33313TI8ZCoX467/+a0aNGoXJZOKJJ56I6fGFEEIIMTLJopQQQgghks6FCxf48z//cyZPnozT6cTpdDJ9+nT+7M/+jCNHjhhdXp9UV1fzn/7Tf+LQoUNGl8Irr7zC//pf/4tnnnmG1157jb/6q78yuiQhhBBCJAGL0QUIIYQQQsTSxx9/zJo1a7BYLDz33HOUlpZiMpk4efIk7777Lv/8z//MhQsXGDNmzC2P9bvf/Y5IJJKAqq9VXV3Nf/7P/5mxY8cyZ86cPj9vy5YtMa/lq6++ori4mP/9v/93zI8thBBCiJFLFqWEEEIIkTTOnTvH2rVrGTNmDNu2baOwsPCqr/+P//E/+Kd/+idMpps3i3s8HlwuF1arNZ7lxlRXVxdOpxObzRbzY9fX1+N2u2N+XCGEEEKMbDK+J4QQQoik8T//5//E4/Hwr//6r9csSAFYLBb+4i/+glGjRkU/99JLL5Gamsq5c+d46KGHSEtL47nnnot+rXemVGtrKy+99BIZGRm43W5efPFFWltbY/rv2L59OwsXLgTg5ZdfRlGUqzKr7r77bmbOnMn+/fu58847cTqd/O3f/m30a1dmSm3fvh1FUdi0aRP/+T//Z4qLi0lLS+OZZ56hra0Nv9/PX/7lX5KXl0dqaiovv/wyfr8f6MnK+vrrrzl27Fi0ju3bt8f03yuEEEKIkUk6pYQQQgiRND7++GMmTpzIokWL+vW8UCjE/fffz7Jly/jVr36F0+m87uNUVeXxxx/n22+/5U//9E+ZNm0a7733Hi+++GIsyo+aNm0a/+W//Bd+/vOf82/+zb/hjjvuAGDp0qXRxzQ1NfHggw+ydu1ann/+efLz8296zF/+8pekpKTwN3/zN5w9e5Z//Md/xGq1YjKZaGlp4T/9p//E7t27efXVVxk3bhw///nPyc3N5fXXX+e///f/TmdnJ7/85S+j9QkhhBBCDJYsSgkhhBAiKbS3t1NdXX3dneFaW1sJhULR/3a5XKSkpET/2+/3s2rVquiiy418+OGH7Ny5k//5P/8n/+//+/8C8JOf/IR77rknNv+Ibvn5+Tz44IP8/Oc/Z8mSJTz//PPXPKa2tpbf/va3/Nt/+2/7dMxQKMSOHTuiI4kNDQ1s2LCBBx54gE8//RSAf/fv/h1nz57llVde4ec//zkul4vnn3+e3//+95jN5uvWIYQQQggxUDK+J4QQQoik0N7eDkBqauo1X7v77rvJzc2N/vnNb35zzWN+8pOf3PIcn376KRaL5arHms1m/p//5/8ZROUDY7fbefnll/v8+BdeeOGqjKxFixahqio//OEPr3rcokWLqKysvGoRTwghhBAiHqRTSgghhBBJIS0tDYDOzs5rvvYv//IvdHR0UFdXd91uH4vFQklJyS3PcenSJQoLC69Z+JoyZcotnxsOh2loaLjqc1lZWQMOJi8uLu7Xc0ePHn3Vf2dkZABcla+lfz4SidDW1kZ2dvaAahNCCCGE6AtZlBJCCCFEUsjIyKCwsJDy8vJrvqZnTF28ePG6z7Xb7bfckW+wKisrGTdu3FWf+/rrr68KJe+PK8cP+8JsNvfr86qq9rsmIYQQQoj+kEUpIYQQQiSNhx9+mN///vfs3buX2267LebHHzNmDNu2baOzs/OqbqlTp07d8rkFBQVs3br1qs+Vlpbe8PGKogy8UCGEEEKIYUAypYQQQgiRNP76r/8ap9PJD3/4Q+rq6q75+mC7fx566CFCoRD//M//HP1cOBzmH//xH2/5XIfDwfLly6/6k5mZecPHu1wuQAtpF0IIIYRIRtIpJYQQQoikMWnSJN58803WrVvHlClTeO655ygtLUVVVS5cuMCbb76JyWTqU37U9Tz66KPcfvvt/M3f/A0XL15k+vTpvPvuu7S1tcX4XwITJkzA7Xbz29/+lrS0NFwuF4sWLbpmBFAIIYQQYriSRSkhhBBCJJXHH3+co0eP8utf/5otW7bwyiuvoCgKY8aM4eGHH+ZP//RPbzo2dzMmk4kPP/yQv/zLv2T9+vUoisJjjz3Gr3/9a+bOnRvTf4fVauW1117jZz/7GX/6p39KKBTiX//1X2VRSgghhBBJQ1ElxVIIIYQQQgghhBBCJJhkSgkhhBBCCCGEEEKIhJNFKSGEEEIIIYQQQgiRcLIoJYQQQgghhBBCCCESThalhBBCCCGEEEIIIUTCyaKUEEIIIYQQQgghhEg4i9EF9EUkEqG6upq0tDQURTG6HCGEEEIIIYQQQghxA6qq0tHRQVFRESbTjfuhhsWiVHV1NaNGjTK6DCGEEEIIIYQQQgjRR5WVlZSUlNzw68NiUSotLQ3Q/jHp6ekGVyOEEEIIIYQQQgghbqS9vZ1Ro0ZF13NuZFgsSukje+np6bIoJYQQQgghhBBCCDEM3CqCSYLOhRBCCCGEEEIIIUTCyaKUEEIIIYQQQgghhEg4WZQSQgghhBBCCCGEEAkni1JCCCGEEEIIIYQQIuFkUUoIIYQQQgghhBBCJJwsSgkhhBBCCCGEEEKIhJNFKSGEEEIIIYQQQgiRcLIoJYQQQgghhBBCCCESThalhBBCCCGEEEIIIUTCyaKUEEIIIYQQQgghhEg4WZQSQgghhBBCCCGEEAkni1JCCCGEEEIIIYQQIuFkUUoIIYQQQgghhBBCJJwsSgkhhBBCCCGEEEKIhJNFKSGEEEIIIYQQQgiRcLIoJYQQQgghhBBCCCESThalhBBCCCGEEEIIIUTC9XtRaufOnTz66KMUFRWhKArvv//+LZ+zfft25s2bh91uZ+LEibz66qsDKFUIIYQQQgghhBBCJIt+L0p5PB5KS0v5zW9+06fHX7hwgYcffph77rmHQ4cO8Zd/+Zf8+Mc/5osvvuh3sUIIIYQQQgghhBAiOfR7UerBBx/kv/23/8aTTz7Zp8f/9re/Zdy4cfz6179m2rRp/Pmf/znPPPMM//t//+8bPsfv99Pe3n7VHyEG43BlK4/+47d8f67R6FJGlvqT8Lt74cTHRlcyolR3VvPCZy/wwdkPjC5lRAk1NXHphRdp/uPrRpcyogS8IT76x0OUfXLB6FJGlFAgwAe/+u9sf/0PRpcyoqgRlaYNJ2l59wyqqhpdzoihqiofffQRmzdvJhwOG13OiHL27P/g8JF/SzjsM7qUEeX/XKxl7aFztAVDRpciRoC4Z0rt2rWL5cuXX/W5+++/n127dt3wOb/85S/JyMiI/hk1alS8yxRJ7n98fpKjVW384tMTchGXSNt/CVX74Yu/hUjE6GpGjN8f/T0H6w/yq32/wh/2G13OiNH8x9fp2ruX+n/4B8JyMyVhjn9XTcWxZso+vkBni/zSkignv9/J2bJd7P/4PRorLxldzojhO9mM91ADnr21BC7K+0yiVFZWsn//fsrLyzlz5ozR5YwYHs9ZLlX8Xxobv6Su7iOjyxkxavwB/tfFWra3dLC+ptnocsQIEPdFqdraWvLz86/6XH5+Pu3t7Xi93us+52c/+
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1200x1000 with 3 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"part = pUtil.explore_partitioners(dataset, 10, methods=[Grid.GridPartitioner], \n",
|
||
|
|
" mf=[mf.trimf, mf.trapmf, mf.gaussmf], transformation=tdiff)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {
|
||
|
|
"colab": {},
|
||
|
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"colab_type": "code",
|
||
|
|
"id": "ypeXTdoDctsm",
|
||
|
|
"outputId": "db0a471c-3c4c-4ccb-e50b-55ba08029fd4"
|
||
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},
|
||
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"outputs": [],
|
||
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"source": [
|
||
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"# for p in part:\n",
|
||
|
|
"# print(p)"
|
||
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|
]
|
||
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|
},
|
||
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|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
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"metadata": {
|
||
|
|
"colab_type": "text",
|
||
|
|
"id": "vu8a87vlctsr"
|
||
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|
},
|
||
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|
"source": [
|
||
|
|
"### Several different mathods"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 13,
|
||
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"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"ename": "KeyboardInterrupt",
|
||
|
|
"evalue": "",
|
||
|
|
"output_type": "error",
|
||
|
|
"traceback": [
|
||
|
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||
|
|
"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
|
||
|
|
"Cell \u001b[0;32mIn[13], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m part \u001b[38;5;241m=\u001b[39m \u001b[43mpUtil\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexplore_partitioners\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdataset\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m10\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethods\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43mHuarng\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mHuarngPartitioner\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 2\u001b[0m \u001b[43m \u001b[49m\u001b[43mmf\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43mmf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrimf\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtransformation\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtdiff\u001b[49m\u001b[43m)\u001b[49m\n",
|
||
|
|
"File \u001b[0;32m~/Projects/Disser/pyFTSex/.venv/src/pyfts/pyFTS/partitioners/Util.py:88\u001b[0m, in \u001b[0;36mexplore_partitioners\u001b[0;34m(data, npart, methods, mf, transformation, size, save, file)\u001b[0m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m p \u001b[38;5;129;01min\u001b[39;00m methods:\n\u001b[1;32m 87\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m m \u001b[38;5;129;01min\u001b[39;00m mf:\n\u001b[0;32m---> 88\u001b[0m obj \u001b[38;5;241m=\u001b[39m \u001b[43mp\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnpart\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnpart\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mm\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtransformation\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtransformation\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 89\u001b[0m obj\u001b[38;5;241m.\u001b[39mname \u001b[38;5;241m=\u001b[39m obj\u001b[38;5;241m.\u001b[39mname \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m - \u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m obj\u001b[38;5;241m.\u001b[39mmembership_function\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\n\u001b[1;32m 90\u001b[0m objs\u001b[38;5;241m.\u001b[39mappend(obj)\n",
|
||
|
|
"File \u001b[0;32m~/Projects/Disser/pyFTSex/.venv/src/pyfts/pyFTS/partitioners/Huarng.py:17\u001b[0m, in \u001b[0;36mHuarngPartitioner.__init__\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m---> 17\u001b[0m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mHuarngPartitioner\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__init__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mHuarng\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
|
||
|
|
"File \u001b[0;32m~/Projects/Disser/pyFTSex/.venv/src/pyfts/pyFTS/partitioners/partitioner.py:76\u001b[0m, in \u001b[0;36mPartitioner.__init__\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 73\u001b[0m _max \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mnanmax(ndata)\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmax \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mfloat\u001b[39m(_max \u001b[38;5;241m*\u001b[39m (\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mupper_margin) \u001b[38;5;28;01mif\u001b[39;00m _max \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m _max \u001b[38;5;241m*\u001b[39m (\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m-\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mupper_margin))\n\u001b[0;32m---> 76\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msets \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuild\u001b[49m\u001b[43m(\u001b[49m\u001b[43mndata\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 78\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpartitions \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msets)\n\u001b[1;32m 80\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mordered_sets \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msetnames \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
|
||
|
|
"File \u001b[0;32m~/Projects/Disser/pyFTSex/.venv/src/pyfts/pyFTS/partitioners/Huarng.py:40\u001b[0m, in \u001b[0;36mHuarngPartitioner.build\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m 38\u001b[0m npart \u001b[38;5;241m=\u001b[39m math\u001b[38;5;241m.\u001b[39mceil(dlen \u001b[38;5;241m/\u001b[39m base)\n\u001b[1;32m 39\u001b[0m partition \u001b[38;5;241m=\u001b[39m math\u001b[38;5;241m.\u001b[39mceil(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmin)\n\u001b[0;32m---> 40\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m c \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28;43mrange\u001b[39;49m(npart):\n\u001b[1;32m 41\u001b[0m _name \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_name(c)\n\u001b[1;32m 42\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmembership_function \u001b[38;5;241m==\u001b[39m Membership\u001b[38;5;241m.\u001b[39mtrimf:\n",
|
||
|
|
"File \u001b[0;32m~/Projects/Disser/pyFTSex/.venv/src/pyfts/pyFTS/partitioners/Huarng.py:40\u001b[0m, in \u001b[0;36mHuarngPartitioner.build\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m 38\u001b[0m npart \u001b[38;5;241m=\u001b[39m math\u001b[38;5;241m.\u001b[39mceil(dlen \u001b[38;5;241m/\u001b[39m base)\n\u001b[1;32m 39\u001b[0m partition \u001b[38;5;241m=\u001b[39m math\u001b[38;5;241m.\u001b[39mceil(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmin)\n\u001b[0;32m---> 40\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m c \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28;43mrange\u001b[39;49m(npart):\n\u001b[1;32m 41\u001b[0m _name \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_name(c)\n\u001b[1;32m 42\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmembership_function \u001b[38;5;241m==\u001b[39m Membership\u001b[38;5;241m.\u001b[39mtrimf:\n",
|
||
|
|
"File \u001b[0;32m_pydevd_bundle/pydevd_cython.pyx:1457\u001b[0m, in \u001b[0;36m_pydevd_bundle.pydevd_cython.SafeCallWrapper.__call__\u001b[0;34m()\u001b[0m\n",
|
||
|
|
"File \u001b[0;32m_pydevd_bundle/pydevd_cython.pyx:701\u001b[0m, in \u001b[0;36m_pydevd_bundle.pydevd_cython.PyDBFrame.trace_dispatch\u001b[0;34m()\u001b[0m\n",
|
||
|
|
"File \u001b[0;32m_pydevd_bundle/pydevd_cython.pyx:1395\u001b[0m, in \u001b[0;36m_pydevd_bundle.pydevd_cython.PyDBFrame.trace_dispatch\u001b[0;34m()\u001b[0m\n",
|
||
|
|
"File \u001b[0;32m_pydevd_bundle/pydevd_cython.pyx:1344\u001b[0m, in \u001b[0;36m_pydevd_bundle.pydevd_cython.PyDBFrame.trace_dispatch\u001b[0;34m()\u001b[0m\n",
|
||
|
|
"File \u001b[0;32m_pydevd_bundle/pydevd_cython.pyx:312\u001b[0m, in \u001b[0;36m_pydevd_bundle.pydevd_cython.PyDBFrame.do_wait_suspend\u001b[0;34m()\u001b[0m\n",
|
||
|
|
"File \u001b[0;32m~/Projects/Disser/pyFTSex/.venv/lib/python3.11/site-packages/debugpy/_vendored/pydevd/pydevd.py:2070\u001b[0m, in \u001b[0;36mPyDB.do_wait_suspend\u001b[0;34m(self, thread, frame, event, arg, exception_type)\u001b[0m\n\u001b[1;32m 2067\u001b[0m from_this_thread\u001b[38;5;241m.\u001b[39mappend(frame_custom_thread_id)\n\u001b[1;32m 2069\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_threads_suspended_single_notification\u001b[38;5;241m.\u001b[39mnotify_thread_suspended(thread_id, thread, stop_reason):\n\u001b[0;32m-> 2070\u001b[0m keep_suspended \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_do_wait_suspend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mthread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mframe\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevent\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43marg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msuspend_type\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfrom_this_thread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mframes_tracker\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2072\u001b[0m frames_list \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 2074\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m keep_suspended:\n\u001b[1;32m 2075\u001b[0m \u001b[38;5;66;03m# This means that we should pause again after a set next statement.\u001b[39;00m\n",
|
||
|
|
"File \u001b[0;32m~/Projects/Disser/pyFTSex/.venv/lib/python3.11/site-packages/debugpy/_vendored/pydevd/pydevd.py:2106\u001b[0m, in \u001b[0;36mPyDB._do_wait_suspend\u001b[0;34m(self, thread, frame, event, arg, suspend_type, from_this_thread, frames_tracker)\u001b[0m\n\u001b[1;32m 2103\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_call_input_hook()\n\u001b[1;32m 2105\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprocess_internal_commands()\n\u001b[0;32m-> 2106\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(\u001b[38;5;241m0.01\u001b[39m)\n\u001b[1;32m 2108\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcancel_async_evaluation(get_current_thread_id(thread), \u001b[38;5;28mstr\u001b[39m(\u001b[38;5;28mid\u001b[39m(frame)))\n\u001b[1;32m 2110\u001b[0m \u001b[38;5;66;03m# process any stepping instructions\u001b[39;00m\n",
|
||
|
|
"\u001b[0;31mKeyboardInterrupt\u001b[0m: "
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# part = pUtil.explore_partitioners(dataset, 10, methods=[Huarng.HuarngPartitioner], \n",
|
||
|
|
"# mf=[mf.trimf], transformation=tdiff)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 14,
|
||
|
|
"metadata": {
|
||
|
|
"colab": {
|
||
|
|
"base_uri": "https://localhost:8080/",
|
||
|
|
"height": 729
|
||
|
|
},
|
||
|
|
"colab_type": "code",
|
||
|
|
"id": "w8xYTWCsctst",
|
||
|
|
"outputId": "2f12ca83-02b1-405a-eb1f-a8f464a8db0d"
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1200x1000 with 4 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"part = pUtil.explore_partitioners(dataset, 10, methods=[Grid.GridPartitioner, \n",
|
||
|
|
" KMeans.KMeansPartitioner, \n",
|
||
|
|
" FCM.FCMPartitioner,\n",
|
||
|
|
" Entropy.EntropyPartitioner], \n",
|
||
|
|
" mf=[mf.trimf])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 15,
|
||
|
|
"metadata": {
|
||
|
|
"colab": {},
|
||
|
|
"colab_type": "code",
|
||
|
|
"id": "ivkYqSlzctsz",
|
||
|
|
"outputId": "1a9161cd-ced0-4c8b-e879-b4a1134e3128"
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"Grid - trimf:\n",
|
||
|
|
"A0: trimf([2223.737111111111, 3126.4335, 4029.129888888889])\n",
|
||
|
|
"A1: trimf([3126.4335, 4029.129888888889, 4931.826277777778])\n",
|
||
|
|
"A2: trimf([4029.129888888889, 4931.826277777778, 5834.522666666668])\n",
|
||
|
|
"A3: trimf([4931.826277777778, 5834.522666666668, 6737.219055555557])\n",
|
||
|
|
"A4: trimf([5834.522666666668, 6737.219055555556, 7639.915444444445])\n",
|
||
|
|
"A5: trimf([6737.219055555557, 7639.915444444446, 8542.611833333334])\n",
|
||
|
|
"A6: trimf([7639.915444444445, 8542.611833333334, 9445.308222222224])\n",
|
||
|
|
"A7: trimf([8542.611833333332, 9445.308222222222, 10348.004611111111])\n",
|
||
|
|
"A8: trimf([9445.308222222222, 10348.004611111111, 11250.701000000001])\n",
|
||
|
|
"A9: trimf([10348.004611111111, 11250.701000000001, 12153.39738888889])\n",
|
||
|
|
"\n",
|
||
|
|
"KMeans - trimf:\n",
|
||
|
|
"A1: trimf([3126.434, 4446.984, 5115.59])\n",
|
||
|
|
"A2: trimf([4446.984, 5115.59, 5866.252])\n",
|
||
|
|
"A3: trimf([5115.59, 5866.252, 6468.86])\n",
|
||
|
|
"A4: trimf([5866.252, 6468.86, 7071.561])\n",
|
||
|
|
"A5: trimf([6468.86, 7071.561, 7622.299])\n",
|
||
|
|
"A6: trimf([7071.561, 7622.299, 8067.048])\n",
|
||
|
|
"A7: trimf([7622.299, 8067.048, 8537.641])\n",
|
||
|
|
"A8: trimf([8067.048, 8537.641, 9032.461])\n",
|
||
|
|
"A9: trimf([8537.641, 9032.461, 9632.606])\n",
|
||
|
|
"A10: trimf([9032.461, 9632.606, 11250.701])\n",
|
||
|
|
"\n",
|
||
|
|
"FCM - trimf:\n",
|
||
|
|
"A1: trimf([3126.434, 4889.001, 6010.956])\n",
|
||
|
|
"A2: trimf([4889.001, 6010.956, 6169.123])\n",
|
||
|
|
"A3: trimf([6010.956, 6169.123, 6397.746])\n",
|
||
|
|
"A4: trimf([6169.123, 6397.746, 6990.173])\n",
|
||
|
|
"A5: trimf([6397.746, 6990.173, 7181.347])\n",
|
||
|
|
"A6: trimf([6990.173, 7181.347, 7567.393])\n",
|
||
|
|
"A7: trimf([7181.347, 7567.393, 7818.631])\n",
|
||
|
|
"A8: trimf([7567.393, 7818.631, 8336.612])\n",
|
||
|
|
"A9: trimf([7818.631, 8336.612, 9318.522])\n",
|
||
|
|
"A10: trimf([8336.612, 9318.522, 11250.701])\n",
|
||
|
|
"\n",
|
||
|
|
"Entropy - trimf:\n",
|
||
|
|
"A0: trimf([3126.4335, 5107.275, 5918.92])\n",
|
||
|
|
"A1: trimf([5107.275, 5918.92, 6495.625])\n",
|
||
|
|
"A2: trimf([5918.92, 6495.625, 7199.905])\n",
|
||
|
|
"A3: trimf([6495.625, 7199.905, 7754.915])\n",
|
||
|
|
"A4: trimf([7199.905, 7754.915, 8233.685])\n",
|
||
|
|
"A5: trimf([7754.915, 8233.685, 8852.515])\n",
|
||
|
|
"A6: trimf([8233.685, 8852.515, 11250.701000000001])\n",
|
||
|
|
"\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"for p in part:\n",
|
||
|
|
" print(p)"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"colab": {
|
||
|
|
"include_colab_link": true,
|
||
|
|
"name": "Partitioners.ipynb",
|
||
|
|
"provenance": []
|
||
|
|
},
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "Python 3",
|
||
|
|
"language": "python",
|
||
|
|
"name": "python3"
|
||
|
|
},
|
||
|
|
"language_info": {
|
||
|
|
"codemirror_mode": {
|
||
|
|
"name": "ipython",
|
||
|
|
"version": 3
|
||
|
|
},
|
||
|
|
"file_extension": ".py",
|
||
|
|
"mimetype": "text/x-python",
|
||
|
|
"name": "python",
|
||
|
|
"nbconvert_exporter": "python",
|
||
|
|
"pygments_lexer": "ipython3",
|
||
|
|
"version": "3.11.9"
|
||
|
|
},
|
||
|
|
"toc": {
|
||
|
|
"base_numbering": 1,
|
||
|
|
"nav_menu": {},
|
||
|
|
"number_sections": true,
|
||
|
|
"sideBar": true,
|
||
|
|
"skip_h1_title": false,
|
||
|
|
"title_cell": "Table of Contents",
|
||
|
|
"title_sidebar": "Contents",
|
||
|
|
"toc_cell": false,
|
||
|
|
"toc_position": {},
|
||
|
|
"toc_section_display": true,
|
||
|
|
"toc_window_display": true
|
||
|
|
},
|
||
|
|
"varInspector": {
|
||
|
|
"cols": {
|
||
|
|
"lenName": 16,
|
||
|
|
"lenType": 16,
|
||
|
|
"lenVar": 40
|
||
|
|
},
|
||
|
|
"kernels_config": {
|
||
|
|
"python": {
|
||
|
|
"delete_cmd_postfix": "",
|
||
|
|
"delete_cmd_prefix": "del ",
|
||
|
|
"library": "var_list.py",
|
||
|
|
"varRefreshCmd": "print(var_dic_list())"
|
||
|
|
},
|
||
|
|
"r": {
|
||
|
|
"delete_cmd_postfix": ") ",
|
||
|
|
"delete_cmd_prefix": "rm(",
|
||
|
|
"library": "var_list.r",
|
||
|
|
"varRefreshCmd": "cat(var_dic_list()) "
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"types_to_exclude": [
|
||
|
|
"module",
|
||
|
|
"function",
|
||
|
|
"builtin_function_or_method",
|
||
|
|
"instance",
|
||
|
|
"_Feature"
|
||
|
|
],
|
||
|
|
"window_display": false
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 0
|
||
|
|
}
|