wip

Co-authored-by: MisterMLiL <eugenelazurenko@gmail.com>

.idea/misc.xml

@@ -1,4 +1,7 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Poetry (statapp)" />
+  </component>
   <component name="ProjectRootManager" version="2" project-jdk-name="Poetry (statapp)" project-jdk-type="Python SDK" />
 </project>

poetry.lock

@@ -74,6 +74,17 @@ files = [
     {file = "distlib-0.3.7.tar.gz", hash = "sha256:9dafe54b34a028eafd95039d5e5d4851a13734540f1331060d31c9916e7147a8"},
 ]
 
+[[package]]
+name = "et-xmlfile"
+version = "1.1.0"
+description = "An implementation of lxml.xmlfile for the standard library"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "et_xmlfile-1.1.0-py3-none-any.whl", hash = "sha256:a2ba85d1d6a74ef63837eed693bcb89c3f752169b0e3e7ae5b16ca5e1b3deada"},
+    {file = "et_xmlfile-1.1.0.tar.gz", hash = "sha256:8eb9e2bc2f8c97e37a2dc85a09ecdcdec9d8a396530a6d5a33b30b9a92da0c5c"},
+]
+
 [[package]]
 name = "filelock"
 version = "3.12.4"
@@ -261,6 +272,20 @@ files = [
     {file = "numpy-1.24.4.tar.gz", hash = "sha256:80f5e3a4e498641401868df4208b74581206afbee7cf7b8329daae82676d9463"},
 ]
 
+[[package]]
+name = "openpyxl"
+version = "3.1.2"
+description = "A Python library to read/write Excel 2010 xlsx/xlsm files"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "openpyxl-3.1.2-py2.py3-none-any.whl", hash = "sha256:f91456ead12ab3c6c2e9491cf33ba6d08357d802192379bb482f1033ade496f5"},
+    {file = "openpyxl-3.1.2.tar.gz", hash = "sha256:a6f5977418eff3b2d5500d54d9db50c8277a368436f4e4f8ddb1be3422870184"},
+]
+
+[package.dependencies]
+et-xmlfile = "*"
+
 [[package]]
 name = "packaging"
 version = "23.2"
@@ -563,6 +588,44 @@ files = [
     {file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
 ]
 
+[[package]]
+name = "scipy"
+version = "1.10.1"
+description = "Fundamental algorithms for scientific computing in Python"
+optional = false
+python-versions = "<3.12,>=3.8"
+files = [
+    {file = "scipy-1.10.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e7354fd7527a4b0377ce55f286805b34e8c54b91be865bac273f527e1b839019"},
+    {file = "scipy-1.10.1-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:4b3f429188c66603a1a5c549fb414e4d3bdc2a24792e061ffbd607d3d75fd84e"},
+    {file = "scipy-1.10.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1553b5dcddd64ba9a0d95355e63fe6c3fc303a8fd77c7bc91e77d61363f7433f"},
+    {file = "scipy-1.10.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c0ff64b06b10e35215abce517252b375e580a6125fd5fdf6421b98efbefb2d2"},
+    {file = "scipy-1.10.1-cp310-cp310-win_amd64.whl", hash = "sha256:fae8a7b898c42dffe3f7361c40d5952b6bf32d10c4569098d276b4c547905ee1"},
+    {file = "scipy-1.10.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:0f1564ea217e82c1bbe75ddf7285ba0709ecd503f048cb1236ae9995f64217bd"},
+    {file = "scipy-1.10.1-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:d925fa1c81b772882aa55bcc10bf88324dadb66ff85d548c71515f6689c6dac5"},
+    {file = "scipy-1.10.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:aaea0a6be54462ec027de54fca511540980d1e9eea68b2d5c1dbfe084797be35"},
+    {file = "scipy-1.10.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:15a35c4242ec5f292c3dd364a7c71a61be87a3d4ddcc693372813c0b73c9af1d"},
+    {file = "scipy-1.10.1-cp311-cp311-win_amd64.whl", hash = "sha256:43b8e0bcb877faf0abfb613d51026cd5cc78918e9530e375727bf0625c82788f"},
+    {file = "scipy-1.10.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:5678f88c68ea866ed9ebe3a989091088553ba12c6090244fdae3e467b1139c35"},
+    {file = "scipy-1.10.1-cp38-cp38-macosx_12_0_arm64.whl", hash = "sha256:39becb03541f9e58243f4197584286e339029e8908c46f7221abeea4b749fa88"},
+    {file = "scipy-1.10.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bce5869c8d68cf383ce240e44c1d9ae7c06078a9396df68ce88a1230f93a30c1"},
+    {file = "scipy-1.10.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:07c3457ce0b3ad5124f98a86533106b643dd811dd61b548e78cf4c8786652f6f"},
+    {file = "scipy-1.10.1-cp38-cp38-win_amd64.whl", hash = "sha256:049a8bbf0ad95277ffba9b3b7d23e5369cc39e66406d60422c8cfef40ccc8415"},
+    {file = "scipy-1.10.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:cd9f1027ff30d90618914a64ca9b1a77a431159df0e2a195d8a9e8a04c78abf9"},
+    {file = "scipy-1.10.1-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:79c8e5a6c6ffaf3a2262ef1be1e108a035cf4f05c14df56057b64acc5bebffb6"},
+    {file = "scipy-1.10.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:51af417a000d2dbe1ec6c372dfe688e041a7084da4fdd350aeb139bd3fb55353"},
+    {file = "scipy-1.10.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1b4735d6c28aad3cdcf52117e0e91d6b39acd4272f3f5cd9907c24ee931ad601"},
+    {file = "scipy-1.10.1-cp39-cp39-win_amd64.whl", hash = "sha256:7ff7f37b1bf4417baca958d254e8e2875d0cc23aaadbe65b3d5b3077b0eb23ea"},
+    {file = "scipy-1.10.1.tar.gz", hash = "sha256:2cf9dfb80a7b4589ba4c40ce7588986d6d5cebc5457cad2c2880f6bc2d42f3a5"},
+]
+
+[package.dependencies]
+numpy = ">=1.19.5,<1.27.0"
+
+[package.extras]
+dev = ["click", "doit (>=0.36.0)", "flake8", "mypy", "pycodestyle", "pydevtool", "rich-click", "typing_extensions"]
+doc = ["matplotlib (>2)", "numpydoc", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-design (>=0.2.0)"]
+test = ["asv", "gmpy2", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
+
 [[package]]
 name = "setuptools"
 version = "68.2.2"
@@ -771,4 +834,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8,<3.9"
-content-hash = "a652dcb9e1a8a200480197c5618b7ddb4cb33fbf1a89278058eeda745ea7293f"
+content-hash = "2e9cc565e3a28c9d9f4e8d7010f97a7736550c8f64a86c59199ba279915da28b"

pyproject.toml

@@ -12,9 +12,11 @@ readme = "README.md"
 python = ">=3.8,<3.9"
 pre-commit = "^3.4.0"
 pyinstaller = "^6.0.0"
-pandas = "^2.0"
 pyside2 = "^5.15.2.1"
-pylint = "^2"
+pandas = { version = "^2", markers = "python_version < '3.9'" }
+pylint = { version = "^2", markers = "python_version < '3.9'" }
+scipy = { version = "^1", markers = "python_version < '3.9'" }
+openpyxl = "^3.1.2"
 
 
 [build-system]

statapp/__main__.py

@@ -19,9 +19,12 @@
 #
 import sys
 
+import numpy as np
+import pandas as pd
 from PySide2 import QtCore
 from PySide2.QtWidgets import QApplication
 
+from statapp.calculations import linearPolynom
 from statapp.main_window import MainWindow
 
 
@@ -38,6 +41,51 @@ def main():
     window.show()
     return app.exec_()
 
+data = [
+    [6014.700000,  2995.067340,  2982.474660],
+    [6031.200000,  2971.594560,  2993.546160],
+    [6145.800000,  3017.328000,  2970.497280],
+    [6133.200000,  2977.476480,  2970.796320],
+    [6063.600000,  3006.012960,  2982.839040],
+    [5934.900000,  2979.831420,  2992.026240],
+    [6016.800000,  2997.121680,  2984.065920],
+    [6070.200000,  2996.335920,  2975.729640],
+    [5935.800000,  2982.114960,  2976.811560],
+    [6108.300000,  2987.822700,  2974.378500]
+]
+
+data = pd.DataFrame(data).to_numpy()
 
 if __name__ == "__main__":
-    sys.exit(main())
+    n = len(data)
+
+    # y = generateYValues(100, 5, n)
+    # x1 = generateXValues(20, 2, 0, y)
+    # x2 = generateXValues(10, 1, 0, y)
+    # x3 = generateXValues(5, 0, 0, y)
+    # y = np.array([18, 19, 22, 20, 24, 23])
+    # x1 = np.array([13, 14, 15, 17, 16, 15])
+    # x2 = np.array([18, 19, 22, 20, 24, 23])
+
+    # data = np.concatenate([y, x1, x2, x3], axis=1)
+
+    res = linearPolynom(data)
+
+    solution = res[0]
+    residues = res[1]
+    rank = res[2]
+
+    SSE = np.sum(residues)
+
+    print(SSE)
+
+    df = n - rank
+
+    MSE = SSE / df
+
+    # MSE = np.mean(residues)
+    SSE = np.sum(residues)
+
+    print("Остаточная дисперсия (MSE = S^2):", MSE)
+
+    # sys.exit(main())

statapp/calculations.py

@@ -24,6 +24,10 @@ DIRECT_LINK = 0
 INDIRECT_LINK = 1
 
 
+def generateYValues(mean, std, count):
+    return np.random.normal(mean, std, size=(count, 1))
+
+
 def generateXValues(mean, std, typeConnection, yColumn):
     yMean = np.mean(yColumn)
     values = []
@@ -38,7 +42,9 @@ def generateXValues(mean, std, typeConnection, yColumn):
         else:
             x = mean
         values.append(x)
-    return np.array(values)
+
+    res = np.array(values)
+    return res.reshape(len(res), 1)
 
 
 def varianceAnalysis(data):
@@ -49,3 +55,15 @@ def varianceAnalysis(data):
 
 def correlationAnalysis(data):
     return pd.DataFrame(data).corr().to_numpy()
+
+
+def linearPolynom(data):
+    x = data[:, 1:]
+    y = data[:, [0]]
+
+    df = pd.DataFrame(x)
+    df.insert(0, 'const', 1)
+
+    x = df.to_numpy()
+
+    return np.linalg.lstsq(x, y, rcond=None)

statapp/main_window.py

@@ -21,7 +21,7 @@ import numpy as np
 from PySide2.QtCore import Slot
 from PySide2.QtWidgets import QMainWindow, QMessageBox
 
-from statapp.calculations import generateXValues
+from statapp.calculations import generateXValues, generateYValues
 from statapp.generate_factor_window import GenerateFactorWindow
 from statapp.models.input_values_model import InputValuesModel
 from statapp.generate_window import GenerateWindow
@@ -112,7 +112,7 @@ class MainWindow(QMainWindow):
         gw = GenerateWindow()
 
         if gw.exec():
-            y = np.random.normal(gw.mat, gw.deviation, size=(gw.count, 1))
+            y = generateYValues(gw.mat, gw.deviation, gw.count)
             self.model.updateAllData(y.round(2))
             self.isDataChanged = True
             self.ui.generateXaction.setEnabled(True)
@@ -125,8 +125,7 @@ class MainWindow(QMainWindow):
             data = self.model.getData()
             y = self.model.getY()
             xValues = generateXValues(gfw.mat, gfw.deviation, gfw.typeConnection, y)
-            xValues = xValues.reshape(len(xValues), 1).round(2)
+            data = np.concatenate((data, xValues.round(2)), axis=1)
-            data = np.concatenate((data, xValues), axis=1)
             self.model.updateAllData(data)
             self.ui.varianceAnalysisAction.setEnabled(True)
             self.ui.correlationAnalisisAction.setEnabled(True)