818 lines
27 KiB
Plaintext
818 lines
27 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"id": "initial_id",
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"metadata": {
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"collapsed": true,
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"ExecuteTime": {
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"end_time": "2025-12-22T15:35:00.039338Z",
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"start_time": "2025-12-22T15:34:58.697001Z"
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}
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},
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"source": [
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"# Hier werden alle verwendeten Pythonmodule importiert\n",
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"import Datenbank\n",
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"import Import\n",
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"import importlib\n",
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"import Koordinatentransformationen\n",
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"import sqlite3\n",
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"import Funktionales_Modell\n",
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"import Berechnungen\n",
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"import Parameterschaetzung\n",
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"import Stochastisches_Modell\n",
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"from Stochastisches_Modell import StochastischesModell\n",
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"import Export\n",
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"import Netzqualität_Genauigkeit"
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],
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"outputs": [],
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"execution_count": 1
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-22T15:35:00.823775Z",
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"start_time": "2025-12-22T15:35:00.741818Z"
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}
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},
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"cell_type": "code",
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"source": [
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"importlib.reload(Datenbank)\n",
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"importlib.reload(Import)\n",
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"# Anlegen der Datenbank, wenn nicht vorhanden\n",
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"pfad_datenbank = r\"Campusnetz.db\"\n",
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"Datenbank.Datenbank_anlegen(pfad_datenbank)\n",
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"\n",
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"# Import vervollständigen\n",
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"imp = Import.Import(pfad_datenbank)\n",
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"db_zugriff = Datenbank.Datenbankzugriff(pfad_datenbank)"
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],
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"id": "82d514cd426db78b",
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"outputs": [],
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"execution_count": 2
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-22T15:35:02.430245Z",
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"start_time": "2025-12-22T15:35:02.406780Z"
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}
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},
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"cell_type": "code",
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"source": [
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"# Import der Koordinatendatei(en) vom Tachymeter\n",
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"pfad_datei = r\"Daten\\campsnetz_koordinaten_bereinigt.csv\"\n",
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"imp.import_koordinaten_lh_tachymeter(pfad_datei)"
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],
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"id": "d3bce3991a8962dc",
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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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"Der Import der Näherungskoordinaten wurde erfolgreich abgeschlossen\n"
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]
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}
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],
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"execution_count": 3
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-22T15:35:04.334700Z",
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"start_time": "2025-12-22T15:35:04.320176Z"
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}
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},
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"cell_type": "code",
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"source": [
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"importlib.reload(Datenbank)\n",
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"db_zugriff = Datenbank.Datenbankzugriff(pfad_datenbank)\n",
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"# Transformationen in ETRS89 / DREF91 Realisierung 2025\n",
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"print(db_zugriff.get_koordinaten(\"naeherung_lh\"))"
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],
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"id": "196ff0c8f8b5aea1",
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"outputs": [
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{
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],
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"execution_count": 4
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-22T15:35:08.088450Z",
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"start_time": "2025-12-22T15:35:08.082894Z"
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}
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},
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"cell_type": "code",
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"source": [
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"importlib.reload(Datenbank)\n",
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"db_zugriff = Datenbank.Datenbankzugriff(pfad_datenbank)\n",
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"# Transformationen in ETRS89 / DREF91 Realisierung 2025\n",
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"print(db_zugriff.get_koordinaten(\"naeherung_us\"))"
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],
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"id": "3989b7b41874c16a",
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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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"{}\n"
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]
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}
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],
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"execution_count": 5
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-22T16:19:10.888607Z",
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"start_time": "2025-12-22T16:19:10.864125Z"
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}
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},
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"cell_type": "code",
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"source": [
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"importlib.reload(Import)\n",
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"imp = Import.Import(pfad_datenbank)\n",
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"\n",
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"pfad_koordinaten_gnss = r\"Daten\\Koordinaten_OL_umliegend_bereinigt.csv\"\n",
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"# X, Y, Z der SAPOS-Stationen\n",
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"genauigkeit_sapos_referenzstationen = [0.05, 0.04, 0.09]\n",
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"\n",
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"imp.import_koordinaten_gnss(pfad_koordinaten_gnss, genauigkeit_sapos_referenzstationen)\n"
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],
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"id": "7b6a359712fe858e",
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'Import der Koordinaten aus stationärem GNSS abgeschlossen.'"
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]
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},
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"execution_count": 28,
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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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"execution_count": 28
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-22T16:19:38.227496Z",
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"start_time": "2025-12-22T16:19:38.223777Z"
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}
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},
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"cell_type": "code",
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"source": [
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"# ToDo: Sobald GNSS vorliegend Koordinaten im ETRS89 / DREF 91 (2025) daraus berechnen!\n",
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"#liste_koordinaten_naeherung_us = {\n",
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"# 10001: (3794874.984, 546741.752, 5080029.990),\n",
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"# 10002: (3794842.533, 546726.907, 5080071.133),\n",
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"# 10037: (3794774.148, 546955.423, 5080040.520),\n",
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"# 10044: (3794725.786, 546954.557, 5080084.411),\n",
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"#}\n",
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"\n",
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"\n",
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"#con = sqlite3.connect(pfad_datenbank)\n",
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"#cursor = con.cursor()\n",
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"#sql = \"\"\"\n",
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"#UPDATE Netzpunkte\n",
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"#SET naeherungx_us = ?, naeherungy_us = ?, naeherungz_us = ?\n",
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"#WHERE punktnummer = ?\n",
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"#\"\"\"\n",
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"#for punktnummer, (x, y, z) in #liste_koordinaten_naeherung_us.items():\n",
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"# cursor.execute(sql, (x, y, z, punktnummer))\n",
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"#con.commit()\n",
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"#cursor.close()\n",
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"#con.close()"
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],
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"id": "f64d9c01318b40f1",
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"outputs": [],
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"execution_count": 29
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-22T16:19:45.126506Z",
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"start_time": "2025-12-22T16:19:42.245751Z"
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}
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},
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"cell_type": "code",
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"source": [
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"# ToDo: Sobald GNSS-Daten vorliegen und die Berechnungen richtig sind, aufräumen!!!\n",
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"\n",
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"importlib.reload(Koordinatentransformationen)\n",
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"trafos = Koordinatentransformationen.Transformationen(pfad_datenbank)\n",
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"\n",
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"\n",
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"import numpy as np\n",
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"\n",
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"import itertools\n",
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"import numpy as np\n",
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"import sympy as sp\n",
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"\n",
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"db = Datenbank.Datenbankzugriff(pfad_datenbank)\n",
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"dict_ausgangssystem = db.get_koordinaten(\"naeherung_lh\", \"Dict\")\n",
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"dict_zielsystem = db.get_koordinaten(\"naeherung_us\", \"Dict\")\n",
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"\n",
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"gemeinsame_punktnummern = sorted(set(dict_ausgangssystem.keys()) & set(dict_zielsystem.keys()))\n",
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"anzahl_gemeinsame_punkte = len(gemeinsame_punktnummern)\n",
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"\n",
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"liste_punkte_ausgangssystem = [dict_ausgangssystem[i] for i in gemeinsame_punktnummern]\n",
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"liste_punkte_zielsystem = [dict_zielsystem[i] for i in gemeinsame_punktnummern]\n",
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"\n",
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"def dist(a, b):\n",
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" return float((a - b).norm())\n",
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"\n",
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"print(\"d(p2,p1)=\", dist(liste_punkte_ausgangssystem[1], liste_punkte_ausgangssystem[0]))\n",
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"print(\"d(P2,P1)=\", dist(liste_punkte_zielsystem[1], liste_punkte_zielsystem[0]))\n",
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"print(\"m0 ~\", dist(liste_punkte_zielsystem[1], liste_punkte_zielsystem[0]) /\n",
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" dist(liste_punkte_ausgangssystem[1], liste_punkte_ausgangssystem[0]))\n",
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"\n",
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"\n",
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"def dist(a, b):\n",
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" return float((a - b).norm())\n",
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"\n",
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"ratios = []\n",
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"pairs = list(itertools.combinations(range(len(liste_punkte_ausgangssystem)), 2))\n",
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"\n",
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"for i, j in pairs:\n",
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" d_loc = dist(liste_punkte_ausgangssystem[i], liste_punkte_ausgangssystem[j])\n",
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" d_ecef = dist(liste_punkte_zielsystem[i], liste_punkte_zielsystem[j])\n",
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" if d_loc > 1e-6:\n",
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" ratios.append(d_ecef / d_loc)\n",
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"\n",
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"print(\"Anzahl Ratios:\", len(ratios))\n",
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"print(\"min/mean/max:\", min(ratios), sum(ratios)/len(ratios), max(ratios))\n",
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"print(\"std:\", float(np.std(ratios)))\n",
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"\n",
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"S_loc = sum(liste_punkte_ausgangssystem, sp.Matrix([0,0,0])) / anzahl_gemeinsame_punkte\n",
|
|
"S_ecef = sum(liste_punkte_zielsystem, sp.Matrix([0,0,0])) / anzahl_gemeinsame_punkte\n",
|
|
"\n",
|
|
"print(\"S_loc:\", S_loc)\n",
|
|
"print(\"S_ecef:\", S_ecef)\n",
|
|
"print(\"Delta:\", (S_ecef - S_loc).evalf(6))\n",
|
|
"\n",
|
|
"\n",
|
|
"def dist(a, b):\n",
|
|
" return float((a - b).norm())\n",
|
|
"\n",
|
|
"n = len(liste_punkte_ausgangssystem)\n",
|
|
"\n",
|
|
"scores = []\n",
|
|
"for i in range(n):\n",
|
|
" d_loc = []\n",
|
|
" d_ecef = []\n",
|
|
" for j in range(n):\n",
|
|
" if i == j:\n",
|
|
" continue\n",
|
|
" d_loc.append(dist(liste_punkte_ausgangssystem[i], liste_punkte_ausgangssystem[j]))\n",
|
|
" d_ecef.append(dist(liste_punkte_zielsystem[i], liste_punkte_zielsystem[j]))\n",
|
|
"\n",
|
|
" d_loc = np.array(d_loc)\n",
|
|
" d_ecef = np.array(d_ecef)\n",
|
|
"\n",
|
|
" # Verhältnisvektor; robust gegen Nullschutz\n",
|
|
" r = d_ecef / np.where(d_loc == 0, np.nan, d_loc)\n",
|
|
"\n",
|
|
" # Streuung der Ratios für Punkt i\n",
|
|
" score = np.nanstd(r)\n",
|
|
" scores.append(score)\n",
|
|
"\n",
|
|
"for pn, sc in sorted(zip(gemeinsame_punktnummern, scores), key=lambda x: -x[1]):\n",
|
|
" print(pn, round(sc, 4))\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"transformationsparameter = trafos.Helmerttransformation_Euler_Transformationsparameter_berechne()"
|
|
],
|
|
"id": "21d60465e432c649",
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"d(p2,p1)= 46.60388451996242\n",
|
|
"d(P2,P1)= 46.59145296840883\n",
|
|
"m0 ~ 0.999733250743331\n",
|
|
"Anzahl Ratios: 45\n",
|
|
"min/mean/max: 0.9986498495467658 0.9999468893556359 1.0004164038548047\n",
|
|
"std: 0.00025301851725699595\n",
|
|
"S_loc: Matrix([[937.945990000000], [1847.25831000000], [99.9451600000000]])\n",
|
|
"S_ecef: Matrix([[3794821.39483000], [546885.587320000], [5080110.27740000]])\n",
|
|
"Delta: Matrix([[3.79388e+6], [545038.], [5.08001e+6]])\n",
|
|
"10054 0.0004\n",
|
|
"10059 0.0004\n",
|
|
"10037 0.0002\n",
|
|
"10028 0.0002\n",
|
|
"10044 0.0001\n",
|
|
"10001 0.0001\n",
|
|
"10014 0.0001\n",
|
|
"10002 0.0001\n",
|
|
"10026 0.0001\n",
|
|
"10008 0.0001\n",
|
|
"Anzahl gemeinsame Punkte: 10\n",
|
|
"\n",
|
|
"Erste Zielpunkte:\n",
|
|
"10001 [3794901.5252, 546745.559, 5080065.7672]\n",
|
|
"10002 [3794866.9711, 546729.5958, 5080092.6364]\n",
|
|
"10008 [3794783.8581, 546746.6347, 5080152.7404]\n",
|
|
"10014 [3794838.7464, 546812.3658, 5080105.2]\n",
|
|
"10026 [3794753.8595, 546827.4296, 5080167.0938]\n",
|
|
"\n",
|
|
"Erste Ausgangspunkte:\n",
|
|
"10001 [833.9439, 1978.3737, 99.8946]\n",
|
|
"10002 [875.9684, 1998.5174, 99.5867]\n",
|
|
"10008 [979.7022, 1991.401, 99.732]\n",
|
|
"10014 [913.9706, 1918.7731, 99.8872]\n",
|
|
"10026 [1020.0059, 1913.8703, 100.3059]\n",
|
|
"min/mean/max: 0.9986498495467658 0.9999468893556359 1.0004164038548047\n",
|
|
"R ist Orthonormal!\n",
|
|
"Iteration Nr.1 abgeschlossen\n",
|
|
"Matrix([[-11.6], [6.17], [1.24], [-0.0287], [-0.303], [0.0131], [0.234]])\n",
|
|
"Iteration Nr.2 abgeschlossen\n",
|
|
"Matrix([[6.69], [-7.21], [-7.49], [0.0287], [-0.00526], [-0.0136], [0.00423]])\n",
|
|
"Iteration Nr.3 abgeschlossen\n",
|
|
"Matrix([[-0.0296], [0.0719], [0.0282], [4.06e-5], [0.000189], [0.000386], [-0.000202]])\n",
|
|
"Iteration Nr.4 abgeschlossen\n",
|
|
"Matrix([[-0.000141], [3.72e-5], [-0.000110], [4.57e-8], [-8.87e-9], [9.87e-8], [-5.50e-8]])\n",
|
|
"Iteration Nr.5 abgeschlossen\n",
|
|
"Matrix([[-2.01e-8], [-2.70e-9], [-2.25e-8], [-4.34e-14], [-5.16e-12], [2.79e-11], [5.62e-12]])\n",
|
|
"Iteration Nr.6 abgeschlossen\n",
|
|
"Matrix([[5.49e-10], [-9.92e-10], [-2.05e-9], [1.18e-13], [-8.18e-13], [1.23e-12], [1.45e-12]])\n",
|
|
"Matrix([[3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6]])\n",
|
|
"Matrix([[3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6], [3.79e+6], [5.47e+5], [5.08e+6]])\n",
|
|
"x = Matrix([[3.80e+6], [5.49e+5], [5.08e+6], [1.00], [-0.156], [0.627], [3.26]])\n",
|
|
"\n",
|
|
"l_berechnet_final:\n",
|
|
"10001: 3794901.510, 546745.579, 5080065.739\n",
|
|
"10002: 3794867.000, 546729.613, 5080092.680\n",
|
|
"10008: 3794783.863, 546746.642, 5080152.749\n",
|
|
"10014: 3794838.739, 546812.364, 5080105.171\n",
|
|
"10026: 3794753.855, 546827.443, 5080167.088\n",
|
|
"10028: 3794889.666, 546908.762, 5080056.912\n",
|
|
"10037: 3794800.626, 546960.749, 5080117.708\n",
|
|
"10044: 3794752.687, 546958.324, 5080154.240\n",
|
|
"10054: 3794889.165, 547086.950, 5080038.116\n",
|
|
"10059: 3794736.836, 547079.449, 5080152.372\n",
|
|
"Streckendifferenzen:\n",
|
|
"[0.037854, 0.054708, 0.012057, 0.029525, 0.015332, 0.073156, 0.071369, 0.025069, 0.127425, 0.139397]\n",
|
|
"\n",
|
|
"Differenz Schwerpunkt (Vektor):\n",
|
|
"Matrix([[7.45e-10], [-1.16e-11], [8.38e-10]])\n",
|
|
"Betrag der Schwerpunkt-Differenz:\n",
|
|
"0.000m\n"
|
|
]
|
|
}
|
|
],
|
|
"execution_count": 30
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"importlib.reload(Koordinatentransformationen)\n",
|
|
"trafos = Koordinatentransformationen.Transformationen(pfad_datenbank)\n",
|
|
"\n",
|
|
"koordinaten_transformiert = trafos.Helmerttransformation(transformationsparameter)\n",
|
|
"print(koordinaten_transformiert)"
|
|
],
|
|
"id": "df0dcccb73299fcf",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"importlib.reload(Datenbank)\n",
|
|
"db_zugriff = Datenbank.Datenbankzugriff(pfad_datenbank)\n",
|
|
"\n",
|
|
"db_zugriff.set_koordinaten(koordinaten_transformiert, \"naeherung_us\")"
|
|
],
|
|
"id": "f6993d81c8a145dd",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"# Importieren der tachymetrischen Beobachtungen\n",
|
|
"importlib.reload(Datenbank)\n",
|
|
"db_zugriff = Datenbank.Datenbankzugriff(pfad_datenbank)\n",
|
|
"\n",
|
|
"db_zugriff.get_instrument_liste(\"Tachymeter\")\n",
|
|
"db_zugriff.set_instrument(\"Tachymeter\", \"Trimble S9\")\n",
|
|
"db_zugriff.get_instrument_liste(\"Tachymeter\")"
|
|
],
|
|
"id": "e376b4534297016c",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"#Importieren der apriori Genauigkeitsinformationen\n",
|
|
"#Zulässige Beobachtungsarten = \"Tachymeter_Richtung\", \"Tachymeter_Strecke\"\n",
|
|
"# Wenn Beobachtungsart = \"Tachymeter_Richtung\" --> Übergabe in Milligon und nur Stabw_apriori_konst\n",
|
|
"# Wenn Beobachtungsart = \"Tachymeter_Strecke\" --> Übergabe Stabw_apriori_konst in Millimeter und Stabw_apriori_streckenprop in ppm\n",
|
|
"\n",
|
|
"importlib.reload(Datenbank)\n",
|
|
"db_zugriff = Datenbank.Datenbankzugriff(pfad_datenbank)\n",
|
|
"importlib.reload(Berechnungen)\n",
|
|
"\n",
|
|
"db_zugriff.set_genauigkeiten(1, \"Tachymeter_Richtung\", 0.15)\n",
|
|
"db_zugriff.set_genauigkeiten(1, \"Tachymeter_Strecke\", 0.8, 1)\n",
|
|
"db_zugriff.set_genauigkeiten(1, \"Tachymeter_Zenitwinkel\", 0.15)"
|
|
],
|
|
"id": "97e24245ce3398a2",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"# Importieren der tachymetrischen Beobachtungen\n",
|
|
"importlib.reload(Import)\n",
|
|
"imp = Import.Import(pfad_datenbank)\n",
|
|
"\n",
|
|
"pfad_datei_tachymeterbeobachtungen = r\"Daten\\campsnetz_beobachtungen_bereinigt.csv\"\n",
|
|
"\n",
|
|
"imp.import_beobachtungen_tachymeter(pfad_datei_tachymeterbeobachtungen, 1)"
|
|
],
|
|
"id": "509e462917e98145",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"# Jacobimatrix aufstellen\n",
|
|
"importlib.reload(Datenbank)\n",
|
|
"db_zugriff = Datenbank.Datenbankzugriff(pfad_datenbank)\n",
|
|
"\n",
|
|
"# Parameter des GRS80-ellipsoids (Bezugsellipsoid des ETRS89 / DREF 91 (2025)\n",
|
|
"# ToDo: Quelle mit möglichst genauen Parametern heraussuchen!\n",
|
|
"a = 6378137.0 #m\n",
|
|
"b = 63567552.314 #m\n",
|
|
"\n",
|
|
"importlib.reload(Funktionales_Modell)\n",
|
|
"fm = Funktionales_Modell.FunktionalesModell(pfad_datenbank, a, b)\n",
|
|
"\n",
|
|
"#db_zugriff.get_beobachtungen_id_standpunkt_zielpunkt(\"tachymeter_distanz\")\n",
|
|
"Jacobimatrix_symbolisch = fm.jacobi_matrix_symbolisch()[0]\n",
|
|
"Jacobimatrix_symbolisch_liste_unbekannte = fm.jacobi_matrix_symbolisch()[1]\n",
|
|
"Jacobimatrix_symbolisch_liste_beobachtungsvektor = fm.jacobi_matrix_symbolisch()[2]"
|
|
],
|
|
"id": "d38939f7108e1788",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"importlib.reload(Datenbank)\n",
|
|
"db_zugriff = Datenbank.Datenbankzugriff(pfad_datenbank)\n",
|
|
"importlib.reload(Funktionales_Modell)\n",
|
|
"fm = Funktionales_Modell.FunktionalesModell(pfad_datenbank, a, b)\n",
|
|
"\n",
|
|
"A_matrix_numerisch_iteration0 = fm.jacobi_matrix_zahlen_iteration_0(Jacobimatrix_symbolisch, \"naeherung_us\", Jacobimatrix_symbolisch_liste_unbekannte, Jacobimatrix_symbolisch_liste_beobachtungsvektor)"
|
|
],
|
|
"id": "4a0b1790c65d59ee",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"importlib.reload(Funktionales_Modell)\n",
|
|
"fm = Funktionales_Modell.FunktionalesModell(pfad_datenbank, a, b)\n",
|
|
"\n",
|
|
"beobachtungsvektor_numerisch = fm.beobachtungsvektor_numerisch(Jacobimatrix_symbolisch_liste_beobachtungsvektor)"
|
|
],
|
|
"id": "38f698b6694bebe7",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"importlib.reload(Funktionales_Modell)\n",
|
|
"fm = Funktionales_Modell.FunktionalesModell(pfad_datenbank, a, b)\n",
|
|
"\n",
|
|
"beobachtungsvektor_naeherung_symbolisch = fm.beobachtungsvektor_naeherung_symbolisch(Jacobimatrix_symbolisch_liste_beobachtungsvektor)"
|
|
],
|
|
"id": "e5cca13bbb6b95c5",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"importlib.reload(Funktionales_Modell)\n",
|
|
"fm = Funktionales_Modell.FunktionalesModell(pfad_datenbank, a, b)\n",
|
|
"\n",
|
|
"beobachtungsvektor_naeherung_numerisch_iteration0 = fm.beobachtungsvektor_naeherung_numerisch_iteration0(Jacobimatrix_symbolisch_liste_beobachtungsvektor, beobachtungsvektor_naeherung_symbolisch)"
|
|
],
|
|
"id": "eb0452c52e7afa6b",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"# Auftstellen der Qll-Matrix\n",
|
|
"importlib.reload(Stochastisches_Modell)\n",
|
|
"stoch_modell = Stochastisches_Modell.StochastischesModell(A_matrix_numerisch_iteration0.rows)\n",
|
|
"\n",
|
|
"Qll_matrix_symbolisch = stoch_modell.Qll_symbolisch(pfad_datenbank, Jacobimatrix_symbolisch_liste_beobachtungsvektor)\n",
|
|
"Qll_matrix_numerisch = stoch_modell.Qll_numerisch(pfad_datenbank, Qll_matrix_symbolisch,Jacobimatrix_symbolisch_liste_beobachtungsvektor)"
|
|
],
|
|
"id": "40a3df8fe549c81",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": "",
|
|
"id": "8e2aa544249c9d29",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": "",
|
|
"id": "b479d3a946400ff6",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": "",
|
|
"id": "5d47e0771b22eb0b",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"importlib.reload(Funktionales_Modell)\n",
|
|
"fm = Funktionales_Modell.FunktionalesModell(pfad_datenbank, a, b)\n",
|
|
"\n",
|
|
"importlib.reload(Parameterschaetzung)\n",
|
|
"importlib.reload(Stochastisches_Modell)\n",
|
|
"\n",
|
|
"importlib.reload(Netzqualität_Genauigkeit)\n",
|
|
"importlib.reload(Export)\n",
|
|
"\n",
|
|
"\n",
|
|
"stoch_modell = Stochastisches_Modell.StochastischesModell(A_matrix_numerisch_iteration0.rows)\n",
|
|
"\n",
|
|
"dx = Parameterschaetzung.ausgleichung_global(A_matrix_numerisch_iteration0, fm.berechnung_dl(beobachtungsvektor_numerisch, beobachtungsvektor_naeherung_numerisch_iteration0), stoch_modell)[1]"
|
|
],
|
|
"id": "f53849ee4757d5e8",
|
|
"outputs": [],
|
|
"execution_count": null
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"cell_type": "code",
|
|
"source": [
|
|
"# Von Fabian\n",
|
|
"\n",
|
|
"importlib.reload(Funktionales_Modell)\n",
|
|
"fm = Funktionales_Modell.FunktionalesModell(pfad_datenbank, a, b)\n",
|
|
"importlib.reload(Export)\n",
|
|
"importlib.reload(Datenbank)\n",
|
|
"\n",
|
|
"unbekanntenvektor_symbolisch = (fm.unbekanntenvektor_symbolisch(Jacobimatrix_symbolisch_liste_unbekannte))\n",
|
|
"unbekanntenvektor_numerisch_iteration0 = fm.unbekanntenvektor_numerisch(Jacobimatrix_symbolisch_liste_unbekannte, unbekanntenvektor_symbolisch)\n",
|
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"print(unbekanntenvektor_numerisch_iteration0)\n",
|
|
"print(\"-----\")\n",
|
|
"unbekanntenvektor_numerisch = fm.unbekanntenvektor_numerisch(Jacobimatrix_symbolisch_liste_unbekannte, unbekanntenvektor_symbolisch, dx, unbekanntenvektor_numerisch_iteration0)\n",
|
|
"print(unbekanntenvektor_numerisch)"
|
|
],
|
|
"id": "122dca077d1d267c",
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"outputs": [],
|
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"execution_count": null
|
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}
|
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],
|
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
|
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"language": "python",
|
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"name": "python3"
|
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},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
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"version": 2
|
|
},
|
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"file_extension": ".py",
|
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"mimetype": "text/x-python",
|
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"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython2",
|
|
"version": "2.7.6"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|