From 4ade029d2d1d0039ae8f24ecc1f165c912869358 Mon Sep 17 00:00:00 2001 From: tangchao0503 <735056338@qq.com> Date: Mon, 4 Jul 2022 12:44:13 +0800 Subject: [PATCH] =?UTF-8?q?=E7=AC=AC=E4=B8=80=E6=AC=A1=E6=8F=90=E4=BA=A4?= =?UTF-8?q?=20=E5=AE=9E=E7=8E=B0=E4=BA=86=E7=BA=BF=E6=80=A7=E5=9B=9E?= =?UTF-8?q?=E5=BD=92=EF=BC=9A=E5=B0=86=E5=BA=B7=E5=AE=81=E7=BB=99=E7=9A=84?= =?UTF-8?q?=E6=9C=89=E6=95=88=E7=AA=97=E5=8F=A3=E5=92=8C=E6=B3=A2=E9=95=BF?= =?UTF-8?q?=E6=96=87=E4=BB=B6=20=E2=86=92(=E8=BD=AC=E5=8C=96)=20=E4=B8=BAy?= =?UTF-8?q?=3Dax+b=20=E7=9A=84=E5=8F=82=E6=95=B0a=E3=80=81b=EF=BC=9B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .gitignore | 243 +++++++++++++++++++++++++++++++++++++++++++++++++++++ main.py | 88 +++++++++++++++++++ 2 files changed, 331 insertions(+) create mode 100644 .gitignore create mode 100644 main.py diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..a648c2f --- /dev/null +++ b/.gitignore @@ -0,0 +1,243 @@ +# tc +/.idea +*.xlsx +*.cal + +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/#use-with-ide +.pdm.toml + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ + +# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio, WebStorm and Rider +# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839 + +# User-specific stuff +.idea/**/workspace.xml +.idea/**/tasks.xml +.idea/**/usage.statistics.xml +.idea/**/dictionaries +.idea/**/shelf + +# AWS User-specific +.idea/**/aws.xml + +# Generated files +.idea/**/contentModel.xml + +# Sensitive or high-churn files +.idea/**/dataSources/ +.idea/**/dataSources.ids +.idea/**/dataSources.local.xml +.idea/**/sqlDataSources.xml +.idea/**/dynamic.xml +.idea/**/uiDesigner.xml +.idea/**/dbnavigator.xml + +# Gradle +.idea/**/gradle.xml +.idea/**/libraries + +# Gradle and Maven with auto-import +# When using Gradle or Maven with auto-import, you should exclude module files, +# since they will be recreated, and may cause churn. Uncomment if using +# auto-import. +# .idea/artifacts +# .idea/compiler.xml +# .idea/jarRepositories.xml +# .idea/modules.xml +# .idea/*.iml +# .idea/modules +# *.iml +# *.ipr + +# CMake +cmake-build-*/ + +# Mongo Explorer plugin +.idea/**/mongoSettings.xml + +# File-based project format +*.iws + +# IntelliJ +out/ + +# mpeltonen/sbt-idea plugin +.idea_modules/ + +# JIRA plugin +atlassian-ide-plugin.xml + +# Cursive Clojure plugin +.idea/replstate.xml + +# SonarLint plugin +.idea/sonarlint/ + +# Crashlytics plugin (for Android Studio and IntelliJ) +com_crashlytics_export_strings.xml +crashlytics.properties +crashlytics-build.properties +fabric.properties + +# Editor-based Rest Client +.idea/httpRequests + +# Android studio 3.1+ serialized cache file +.idea/caches/build_file_checksums.ser diff --git a/main.py b/main.py new file mode 100644 index 0000000..7ed6a0a --- /dev/null +++ b/main.py @@ -0,0 +1,88 @@ +# https://www.cnblogs.com/vachester/p/7202793.html +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +from sklearn import datasets, linear_model + + +def get_data(file_name): + # data = pd.read_csv(file_name, header = None) + # data = pd.read_excel(file_name) + # X_parameter = [] + # Y_parameter = [] + # for single_square_feet, single_price_value in zip(data['square_feet'], data['price']): + # X_parameter.append([float(single_square_feet)]) + # Y_parameter.append(float(single_price_value)) + + row = list(range(340, 340 + 300)) + wave = [399.959, 401.958, 403.958, 405.957, 407.957, 409.957, 411.956, 413.956, 415.955, 417.955, 419.954, 421.954, + 423.954, 425.953, 427.953, 429.952, 431.952, 433.951, 435.951, 437.951, 439.95, 441.95, 443.949, 445.949, + 447.948, 449.948, 451.947, 453.947, 455.947, 457.946, 459.946, 461.945, 463.945, 465.944, 467.944, 469.944, + 471.943, 473.943, 475.942, 477.942, 479.941, 481.941, 483.94, 485.94, 487.94, 489.939, 491.939, 493.938, + 495.938, 497.937, 499.937, 501.937, 503.936, 505.936, 507.935, 509.935, 511.934, 513.934, 515.933, 517.933, + 519.933, 521.932, 523.932, 525.931, 527.931, 529.93, 531.93, 533.93, 535.929, 537.929, 539.928, 541.928, + 543.927, 545.927, 547.927, 549.926, 551.926, 553.925, 555.925, 557.924, 559.924, 561.923, 563.923, 565.923, + 567.922, 569.922, 571.921, 573.921, 575.92, 577.92, 579.92, 581.919, 583.919, 585.918, 587.918, 589.917, + 591.917, 593.917, 595.916, 597.916, 599.915, 601.915, 603.914, 605.914, 607.913, 609.913, 611.913, 613.912, + 615.912, 617.911, 619.911, 621.91, 623.91, 625.909, 627.909, 629.909, 631.908, 633.908, 635.907, 637.907, + 639.906, 641.906, 643.906, 645.905, 647.905, 649.904, 651.904, 653.903, 655.903, 657.903, 659.902, 661.902, + 663.901, 665.901, 667.9, 669.9, 671.899, 673.899, 675.899, 677.898, 679.898, 681.897, 683.897, 685.896, + 687.896, 689.896, 691.895, 693.895, 695.894, 697.894, 699.893, 701.893, 703.893, 705.892, 707.892, 709.891, + 711.891, 713.89, 715.89, 717.889, 719.889, 721.889, 723.888, 725.888, 727.887, 729.887, 731.886, 733.886, + 735.886, 737.885, 739.885, 741.884, 743.884, 745.883, 747.883, 749.883, 751.882, 753.882, 755.881, 757.881, + 759.88, 761.88, 763.879, 765.879, 767.879, 769.878, 771.878, 773.877, 775.877, 777.876, 779.876, 781.876, + 783.875, 785.875, 787.874, 789.874, 791.873, 793.873, 795.872, 797.872, 799.872, 801.871, 803.871, 805.87, + 807.87, 809.869, 811.869, 813.869, 815.868, 817.868, 819.867, 821.867, 823.866, 825.866, 827.866, 829.865, + 831.865, 833.864, 835.864, 837.863, 839.863, 841.862, 843.862, 845.862, 847.861, 849.861, 851.86, 853.86, + 855.859, 857.859, 859.858, 861.858, 863.858, 865.857, 867.857, 869.856, 871.856, 873.855, 875.855, 877.855, + 879.854, 881.854, 883.853, 885.853, 887.852, 889.852, 891.852, 893.851, 895.851, 897.85, 899.85, 901.849, + 903.849, 905.848, 907.848, 909.848, 911.847, 913.847, 915.846, 917.846, 919.845, 921.845, 923.845, 925.844, + 927.844, 929.843, 931.843, 933.842, 935.842, 937.841, 939.841, 941.841, 943.84, 945.84, 947.839, 949.839, + 951.838, 953.838, 955.838, 957.837, 959.837, 961.836, 963.836, 965.835, 967.835, 969.835, 971.834, 973.834, + 975.833, 977.833, 979.832, 981.832, 983.831, 985.831, 987.831, 989.83, 991.83, 993.829, 995.829, 997.828] + + row_bin2 = list(range(170, 170 + 150)) + wave_bin2 = [] + for i in range(0, len(wave), 2): + # print(i) + # print(wave[i:i + 2]) + wave_bin2.append((wave[i] + wave[i+1])/2) + + X_parameter = [] + Y_parameter = [] + for single_square_feet, single_price_value in zip(row_bin2, wave_bin2): + X_parameter.append([float(single_square_feet)]) + Y_parameter.append(float(single_price_value)) + + return X_parameter, Y_parameter + + +def plot(x, y, regre): + plt.scatter(x, y, color='blue') + plt.plot(x, regre.predict(x), color='red', linewidth=4) + # plt.xticks(()) + # plt.yticks(()) + plt.show() + + +def linearRegression(X_parameters, Y_parameters):# + regr = linear_model.LinearRegression() + regr.fit(X_parameters, Y_parameters) + + # 绘图 + plot(X_parameters, Y_parameters, regr) + + return regr + + +if __name__ == "__main__": + x, y = get_data(r'D:\PycharmProjects\linear_regression\123.xlsx') + regr = linearRegression(x, y) + + yPredicted = [] + for i in x: + xxxx = regr.predict(i[0]) + yPredicted.append(xxxx[0]) + + print("Intercept value ", regr.intercept_) + print("coefficient", regr.coef_)