diff --git a/PV-tool_TD.ipynb b/PV-tool_TD.ipynb
index 6e0fe42..86412c6 100644
--- a/PV-tool_TD.ipynb
+++ b/PV-tool_TD.ipynb
@@ -1,78 +1,36 @@
{
"cells": [
{
+ "metadata": {},
"cell_type": "markdown",
- "id": "355a22bc-f5fd-45f5-b2bf-8b6221b21c63",
- "metadata": {
- "scrolled": true
- },
- "source": [
- "STOWA Proevenverzameling tool v5.0
"
- ]
+ "source": "STOWA Proevenverzameling tool v5.0
",
+ "id": "8c8bf0ad27b190bc"
},
{
- "cell_type": "markdown",
- "id": "bbfe3f86-f070-4a0b-8358-b1c47d3255f2",
"metadata": {},
- "source": [
- "## Benodigde installaties"
- ]
+ "cell_type": "markdown",
+ "source": "## Benodigde installaties",
+ "id": "3ca0ca1c587006e3"
},
{
+ "metadata": {},
"cell_type": "code",
- "execution_count": 1,
- "id": "a45004c0-6ab8-41ed-87ad-f41c41573c06",
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Defaulting to user installation because normal site-packages is not writeable\n",
- "Processing c:\\users\\deenekat7271\\documents\\github\\pv-tool\\dist\\pv_tool-0.2.7-py3-none-any.whl\n",
- "Requirement already satisfied: pandas in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from pv-tool==0.2.7) (2.2.3)\n",
- "Requirement already satisfied: numpy in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from pv-tool==0.2.7) (1.26.4)\n",
- "Requirement already satisfied: scipy in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from pv-tool==0.2.7) (1.14.1)\n",
- "Requirement already satisfied: matplotlib in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from pv-tool==0.2.7) (3.9.4)\n",
- "Requirement already satisfied: plotly in c:\\users\\deenekat7271\\appdata\\roaming\\python\\python311\\site-packages (from pv-tool==0.2.7) (6.5.0)\n",
- "Requirement already satisfied: openpyxl in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from pv-tool==0.2.7) (3.1.5)\n",
- "Requirement already satisfied: gitpython in c:\\users\\deenekat7271\\appdata\\roaming\\python\\python311\\site-packages (from pv-tool==0.2.7) (3.1.45)\n",
- "Requirement already satisfied: pandas_schema in c:\\users\\deenekat7271\\appdata\\roaming\\python\\python311\\site-packages (from pv-tool==0.2.7) (0.3.6)\n",
- "Requirement already satisfied: xlsxwriter in c:\\users\\deenekat7271\\appdata\\roaming\\python\\python311\\site-packages (from pv-tool==0.2.7) (3.2.9)\n",
- "Requirement already satisfied: gitdb<5,>=4.0.1 in c:\\users\\deenekat7271\\appdata\\roaming\\python\\python311\\site-packages (from gitpython->pv-tool==0.2.7) (4.0.12)\n",
- "Requirement already satisfied: smmap<6,>=3.0.1 in c:\\users\\deenekat7271\\appdata\\roaming\\python\\python311\\site-packages (from gitdb<5,>=4.0.1->gitpython->pv-tool==0.2.7) (5.0.2)\n",
- "Requirement already satisfied: contourpy>=1.0.1 in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from matplotlib->pv-tool==0.2.7) (1.3.1)\n",
- "Requirement already satisfied: cycler>=0.10 in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from matplotlib->pv-tool==0.2.7) (0.11.0)\n",
- "Requirement already satisfied: fonttools>=4.22.0 in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from matplotlib->pv-tool==0.2.7) (4.55.3)\n",
- "Requirement already satisfied: kiwisolver>=1.3.1 in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from matplotlib->pv-tool==0.2.7) (1.4.8)\n",
- "Requirement already satisfied: packaging>=20.0 in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from matplotlib->pv-tool==0.2.7) (24.2)\n",
- "Requirement already satisfied: pillow>=8 in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from matplotlib->pv-tool==0.2.7) (11.1.0)\n",
- "Requirement already satisfied: pyparsing>=2.3.1 in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from matplotlib->pv-tool==0.2.7) (3.2.0)\n",
- "Requirement already satisfied: python-dateutil>=2.7 in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from matplotlib->pv-tool==0.2.7) (2.9.0.post0)\n",
- "Requirement already satisfied: six>=1.5 in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from python-dateutil>=2.7->matplotlib->pv-tool==0.2.7) (1.16.0)\n",
- "Requirement already satisfied: et-xmlfile in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages (from openpyxl->pv-tool==0.2.7) (1.1.0)\n",
- "Requirement already satisfied: pytz>=2020.1 in c:\\program files\\arcgis\\pro\\bin\\python\\envs\\arcgispro-py3\\lib\\site-packages\\pytz-2025.1-py3.11.egg (from pandas->pv-tool==0.2.7) (2025.1)\n",
- "Requirement already satisfied: narwhals>=1.15.1 in c:\\users\\deenekat7271\\appdata\\roaming\\python\\python311\\site-packages (from plotly->pv-tool==0.2.7) (2.14.0)\n",
- "pv-tool is already installed with the same version as the provided wheel. Use --force-reinstall to force an installation of the wheel.\n"
- ]
- }
- ],
+ "outputs": [],
+ "execution_count": null,
"source": [
"# Importeren van benodigde package\n",
"# Na het eerte keer installeren van de benodigde packages de kernel handmatig opnieuw optarten via het menu Kernel → Restart\n",
"\n",
"path_to_wheel = r\"C:\\Users\\deenekat7271\\Documents\\GitHub\\pv-tool\\dist\\pv_tool-0.2.7-py3-none-any.whl\"\n",
"!pip install \"{path_to_wheel}\""
- ]
+ ],
+ "id": "7bad0b21367b416"
},
{
- "cell_type": "code",
- "execution_count": 2,
- "id": "6517fdb7-5b7b-4000-a6f3-8a7ea54c99bd",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
+ "execution_count": null,
"source": [
"# all imports\n",
"import importlib.util\n",
@@ -88,173 +46,33 @@
"\n",
"# widgetfuncties nog verder aanvullen!\n",
"from widgetfunctie_cphi import *"
- ]
+ ],
+ "id": "5066816e6d9e1a9b"
},
{
- "cell_type": "code",
- "execution_count": 3,
- "id": "4c6852e8-6e01-4581-bd3d-359226eb99bd",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/markdown": [
- "**openpyxl is al geïnstalleerd.**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "**ipyfilechooser is al geïnstalleerd.**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "**pandas_schema is al geïnstalleerd.**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "**xlsxwriter is al geïnstalleerd.**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "**ipywidgets is al geïnstalleerd.**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "**reportlab is al geïnstalleerd.**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "**reportlab is al geïnstalleerd.**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "**kaleido is al geïnstalleerd.**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "cell_type": "code",
+ "outputs": [],
+ "execution_count": null,
"source": [
"# Controleert en installeer indien nodig\n",
"packages = ['openpyxl', 'ipyfilechooser', 'pandas_schema', 'xlsxwriter', 'ipywidgets', 'reportlab', 'reportlab', 'kaleido']\n",
"for package in packages:\n",
" check_package_install(package)"
- ]
+ ],
+ "id": "3b7a0598137e9eec"
},
{
- "cell_type": "markdown",
- "id": "f9b527ad-cc7a-498e-913d-9f844424e65d",
"metadata": {},
- "source": [
- "## Stap 1: Inladen van benodigde data"
- ]
+ "cell_type": "markdown",
+ "source": "## Stap 1: Inladen van benodigde data",
+ "id": "d73df0039f30c1ca"
},
{
- "cell_type": "code",
- "execution_count": 4,
- "id": "41801c0a-b9d1-4e8e-a8ea-1756708ef521",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/markdown": [
- "**Stap 1: Kies Excel template voor uploaden data:**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "8cf05cde02e54976af352669667d236c",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Dropdown(description='Template:', index=2, layout=Layout(width='400px'), options=('Proevenverzamelingtool 4.2n…"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "51e9c74422244a14bc74ea954778fc77",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "FileChooser(path='C:\\', filename='', title='Selecteer een bestand om te uploaden', show_hidden=False, select_d…"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "cell_type": "code",
+ "outputs": [],
+ "execution_count": null,
"source": [
"# Data inladen\n",
"dropdown_template = create_import_dropdown()\n",
@@ -262,118 +80,42 @@
"display(Markdown(\"**Stap 1: Kies Excel template voor uploaden data:**\"))\n",
"display(dropdown_template)\n",
"display(file_chooser_import)"
- ]
+ ],
+ "id": "5243805f175c8832"
},
{
- "cell_type": "markdown",
- "id": "ad2775ae-9478-4cdb-b519-2780ea5176e3",
"metadata": {},
- "source": [
- "## Selecteer export locatie"
- ]
+ "cell_type": "markdown",
+ "source": "## Selecteer export locatie",
+ "id": "ea73d9b45eb5db8a"
},
{
- "cell_type": "code",
- "execution_count": 5,
- "id": "88abfcf3-3302-48e4-9ce9-cf9ad76cab74",
"metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "1e3a602f8e4543a4bcf375cc15f24a84",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "VBox(children=(FileChooser(path='C:\\Users\\deenekat7271\\Documents\\GitHub\\pv-tool', filename='', title='Kies …"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "dir_chooser, name_box = select_export_location_and_name()"
- ]
+ "cell_type": "code",
+ "outputs": [],
+ "execution_count": null,
+ "source": "dir_chooser, name_box = select_export_location_and_name()",
+ "id": "4528ba8cca317ae2"
},
{
- "cell_type": "markdown",
- "id": "d64f66fe-4f95-43d8-af88-0e3c09b3e842",
"metadata": {},
- "source": [
- "## Stap 2a: Importeren en valideren data (inclusief toevoegen/herberekenen analyse kolommen)"
- ]
+ "cell_type": "markdown",
+ "source": "## Stap 2a: Importeren en valideren data (inclusief toevoegen/herberekenen analyse kolommen)",
+ "id": "b0edad325fac3349"
},
{
- "cell_type": "code",
- "execution_count": 6,
- "id": "fbaa5d07-14a9-4243-b374-06a1e94dcef5",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
- "source": [
- "import time"
- ]
+ "execution_count": null,
+ "source": "import time",
+ "id": "46604a82193afed0"
},
{
- "cell_type": "code",
- "execution_count": 9,
- "id": "c7abe32c-8afb-4224-b7e0-7c0b05238c8a",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/markdown": [
- "**Template-code:** PV-tool"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "number of critical_errors in validate_kenmerken_boring = 0\n",
- "number of critical_errors in validate_clas = 0\n",
- "number of critical_errors in validate_crs = 4\n",
- "number of critical_errors in validate_samendrukking = 0\n",
- "number of critical_errors in validate_monster = 0\n",
- "number of critical_errors in validate_triaxiaal = 28\n",
- "number of critical_errors in validate_dss = 17\n",
- "number of warnings in validate_alg = 0\n",
- "number of warnings in validate_kenmerken_boring = 353\n",
- "number of warnings in validate_clas = 1843\n",
- "number of warnings in validate_crs = 76\n",
- "number of warnings in validate_samendrukking = 246\n",
- "number of warnings in validate_monster = 0\n",
- "number of warnings in validate_triaxiaal = 96\n",
- "number of warnings in validate_dss = 33\n"
- ]
- },
- {
- "data": {
- "text/markdown": [
- "**Validatierapporten geëxporteerd naar:** C:\\Users\\deenekat7271\\Documents\\GitHub\\pv-tool"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Duur: 44.46 seconden\n"
- ]
- }
- ],
+ "cell_type": "code",
+ "outputs": [],
+ "execution_count": null,
"source": [
"timestart = time.time()\n",
"dbase = Dbase()\n",
@@ -393,49 +135,20 @@
" export_dir=Path(dir_chooser.selected_path)\n",
" )\n",
"print(f\"Duur: {time.time() - timestart:.2f} seconden\")"
- ]
+ ],
+ "id": "151a99807e912390"
},
{
- "cell_type": "markdown",
- "id": "0cab0c9b-782c-4c73-b743-902aecfac478",
"metadata": {},
- "source": [
- "## Stap 2b: Als errors zijn opgelost exporteer naar Template"
- ]
+ "cell_type": "markdown",
+ "source": "## Stap 2b: Als errors zijn opgelost exporteer naar Template",
+ "id": "1af5e1ec6812df3e"
},
{
- "cell_type": "code",
- "execution_count": 10,
- "id": "74326cfd-d35b-4c15-9924-84f8bce0a98f",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "DataFrame naar template geëxporteerd\n"
- ]
- },
- {
- "data": {
- "text/markdown": [
- "**DataFrame geëxporteerd naar:** `C:\\Users\\deenekat7271\\Documents\\GitHub\\pv-tool\\test4.xlsx`"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Duur: 21.76 seconden\n"
- ]
- }
- ],
+ "cell_type": "code",
+ "outputs": [],
+ "execution_count": null,
"source": [
"# Export dbase-template\n",
"timestart = time.time()\n",
@@ -445,141 +158,20 @@
" filename=name_box.value if name_box.value else None\n",
")\n",
"print(f\"Duur: {time.time() - timestart:.2f} seconden\")"
- ]
+ ],
+ "id": "c6fd102848be3ce2"
},
{
- "cell_type": "markdown",
- "id": "c38059cf-e12b-4bc5-8a7f-6377d0e43e65",
"metadata": {},
- "source": [
- "## Bepalen gedraineerde parameters triaxiaalproeven en DSS-proeven op basis van fit (C en Phi)"
- ]
+ "cell_type": "markdown",
+ "source": "## Bepalen gedraineerde parameters triaxiaalproeven en DSS-proeven op basis van fit (C en Phi)",
+ "id": "198ebb822ebedb9d"
},
{
- "cell_type": "code",
- "execution_count": 11,
- "id": "7ea3d24c-93cf-4b9a-b297-c8db288dc9f6",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/markdown": [
- "**Kies type proef:**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "68ddfc19b5b74662a8c99be900acfa85",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Dropdown(description='Type proef:', layout=Layout(width='400px'), options=('TXT_CPhi', 'DSS_CPhi'), value='TXT…"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "**Kies verzameling voor statistische analyse:**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "6a4ab4354c2e4ca185072b47016c41c9",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Dropdown(description='Verzameling:', layout=Layout(width='400px'), options=('geen', 'TXT_testset_klei', 'TXT_W…"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "**Kies rekpercentage s'en t:**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "eedccbeab22e411bacd2b114f0141d8f",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Output()"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "ab73c799d691415e895d195f9e94b4b1",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Output()"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "**Kies één of meerdere verzamelingen om naast de gekozen verzameling voor de statistische analyse te tonen:**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "b7e291bdd2254f359205ec512fa47192",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "SelectMultiple(description='Vergelijk met:', index=(0,), layout=Layout(height='150px', width='400px'), options…"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "cell_type": "code",
+ "outputs": [],
+ "execution_count": null,
"source": [
"# Dataframe met proefdata\n",
"dbase_df = dbase.dbase_df\n",
@@ -605,126 +197,14 @@
"toon_widgets(\n",
" dropdown_type_proef, dropdown_verzameling, container_rekpercentage, output_rekpercentage, multi_select_verzameling\n",
")"
- ]
+ ],
+ "id": "7837268cdf716824"
},
{
- "cell_type": "code",
- "execution_count": 13,
- "id": "a072c003-04fb-4365-8055-0039cbb6d220",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "C:\\Users\\deenekat7271\\Documents\\GitHub\\pv-tool\\test4.xlsx\n",
- "Er zijn geen eerdere resultaten gevonden voor de opgegeven parameters.\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "C:\\Users\\deenekat7271\\Documents\\GitHub\\pv-tool\\pv_tool\\cphi_analysis\\calc_parameters.py:214: UserWarning:\n",
- "\n",
- "Om berekening standaarddeviatie voor D-stability te kunnen doen moet rekenwaarde van de cohesie waarde positief zijn, gevonden waarde: -1.276. Rekenwaarde cohesie wordt aangepast naar 0.01 om berekening standaarddeviatie voor D-stability te kunnen doen\n",
- "\n"
- ]
- },
- {
- "data": {
- "text/markdown": [
- "**Stel de raaklijnen voor de gemiddelde en karakteristieke waarden van de cohesie en hoek van inwendige wrijving vast:**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "Op basis van regressie wordt een eerste benadering gegeven voor het snijpunt met de y-as (a1) en de helling (a2) voor de gemiddelde en karakteristieke waarde."
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "Toets in de volgende stap bij het genereren van de grafieken of de raaklijnen juist zijn gekozen en pas deze aan naar eigen inzicht"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "De invoer wordt automatisch opgehaald uit het template_PVtool5_0.xlsx [resultaten] indien er eerder resultaten zijn opgeslagen voor de betreffende verzameling."
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\n"
- ]
- },
- {
- "data": {
- "text/markdown": [
- "**Verzameling en rekpercentage: TXT_SAFE_klei_licht_16_175, s'-t bij: ['eindsterkte']**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "**Opgeven invoer effectieve schuifsterkteparameters (fit):**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "18d98458de8f43068612a3cb7b1c7385",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "GridspecLayout(children=(Label(value='Beschrijving', layout=Layout(grid_area='widget001')), Label(value='Benad…"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "cell_type": "code",
+ "outputs": [],
+ "execution_count": null,
"source": [
"analyse, coh_gem, phi_kar, coh_kar, partphi, partcoh, typeverzameling = voer_cphi_analyse_uit(\n",
" dbase,\n",
@@ -737,23 +217,24 @@
" gekozen_rekpercentage,\n",
" toon_cphi_tabel\n",
")"
- ]
+ ],
+ "id": "16a0a51791977efb"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "e9602fbb-27ff-465d-b545-b0ff2b25c36c",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
- "source": []
+ "execution_count": null,
+ "source": "",
+ "id": "f1c8a8521c1e8e45"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "b765ef68-d2df-4e1e-8fd9-2d956efacacd",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
- "source": []
+ "execution_count": null,
+ "source": "\n",
+ "id": "d91ddcaf27fa2e3"
}
],
"metadata": {
diff --git a/PV_tool0.4.ipynb b/PV_tool0.4.ipynb
index 5c1c830..48daf88 100644
--- a/PV_tool0.4.ipynb
+++ b/PV_tool0.4.ipynb
@@ -1,44 +1,29 @@
{
"cells": [
{
- "cell_type": "markdown",
- "id": "5b519e9d-47fb-4aaf-88e6-ea99037b66ce",
"metadata": {},
+ "cell_type": "markdown",
"source": [
"STOWA Proevenverzameling tool v5.0
\n",
"\n",
"Deze Jupyter notebook bevat functies opgenomen in de python package PV-tooling ### voor het opstellen van lokale of regionale proevenverzamelingen voor het bepalen van geotechnische parameters. De methode is ontwikkeld voor het uitvoeren van analyses in relatie tot de geotechnische stabiliteit van dijken, maar kan ook breder worden toegepast. De notebook dient tevens als handleiding om de gebruiker stapsgewijs te ondersteunen bij het opstellen van een proevenverzameling.\n",
"\n",
- "Met de beschikbare functies kunnen zowel gedraineerde als ongedraineerde sterkteparameters worden berekend alsmede enkele samendrukkingsparameters. Van deze parameters worden verwachtingswaarde, karakteristieke waarde en rekenwaarde bepaald. \n",
+ "Met de beschikbare functies kunnen zowel gedraineerde als ongedraineerde sterkteparameters worden berekend alsmede enkele samendrukkingsparameters. Van deze parameters worden verwachtingswaarde, karakteristieke waarde en rekenwaarde bepaald.\n",
"\n",
"De functies zijn opgesteld conform de werkwijze beschreven in [Statistische methoden t.b.v. proevenverzamelingen, DIV, v1.0], zie tevens: https://publicwiki.deltares.nl/spaces/HWBPMacro/pages/217120830/Sterkte+van+grond#Sterktevangrond-150.\n",
- "De tool bevat tevens hulpmiddelen voor het onderscheiden of samenvoegen van groepen in een verzameling op basis van verschillende kenmerken. \n",
+ "De tool bevat tevens hulpmiddelen voor het onderscheiden of samenvoegen van groepen in een verzameling op basis van verschillende kenmerken.\n",
"\n",
"De onderliggende data om een proevenverzameling samen te stellen is beschreven in een vaste structuur. Deze structuur is vastgelegd in een uitwisselformat. Het uitwisselformat-database-proevenverzameling_versie_4_2x.xlsx. De geotechnische laboratoria kennen deze database en kunnen deze database vullen met resultaten van grond- en laboratoriumonderzoek. Op deze wijze ontstaat er uniformering op het gebied van data-uitwisseling en –opslag van proefresultaten.\n",
"\n",
"NB. De verantwoordelijkheid voor het gebruik van deze tools ligt bij de gebruiker."
- ]
+ ],
+ "id": "bee1f1422905e9aa"
},
{
- "cell_type": "code",
- "execution_count": 1,
- "id": "6763641d-41d8-4046-a14f-745ff77b26d3",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "openpyxl is al geïnstalleerd.\n",
- "ipyfilechooser is al geïnstalleerd.\n",
- "pandas_schema is al geïnstalleerd.\n",
- "xlsxwriter is al geïnstalleerd.\n",
- "ipywidgets is al geïnstalleerd.\n",
- "reportlab is al geïnstalleerd.\n",
- "kaleido is al geïnstalleerd.\n"
- ]
- }
- ],
+ "cell_type": "code",
+ "outputs": [],
+ "execution_count": null,
"source": [
"# Importeren van benodigde packages\n",
"# Na het eerte keer installeren van de benodigde packages de kernel handmatig opnieuw optarten via het menu Kernel → Restart\n",
@@ -67,407 +52,48 @@
"#!pip install --force-reinstall C:\\python_cursus\\PVtool2025_github\\dist\\pv_tool-0.1.3-py3-none-any.whl\n",
"\n",
"#!pip install C:\\python_cursus\\PVtool2025_github\\dist\\pv_tool-0.2.0-py3-none-any.whl\n"
- ]
+ ],
+ "id": "9fca9550118698a9"
},
{
+ "metadata": {},
"cell_type": "code",
- "execution_count": 2,
- "id": "4c7a71ff-256e-4c3d-b8d4-49a826f3cca6",
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Defaulting to user installation because normal site-packages is not writeable\n",
- "Collecting ipywidgets\n",
- " Using cached ipywidgets-8.1.8-py3-none-any.whl.metadata (2.4 kB)\n",
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- "Installing collected packages: pure-eval, widgetsnbextension, wcwidth, typing_extensions, traitlets, pygments, parso, jupyterlab_widgets, executing, decorator, comm, colorama, asttokens, stack_data, prompt_toolkit, matplotlib-inline, jedi, ipython-pygments-lexers, ipython, ipywidgets\n",
- "\n",
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- " Uninstalling ipython_pygments_lexers-1.1.1:\n",
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- " ---------------------------------- ----- 17/20 [ipython-pygments-lexers]\n",
- " Successfully uninstalled ipython_pygments_lexers-1.1.1\n",
- " ---------------------------------- ----- 17/20 [ipython-pygments-lexers]\n",
- " Attempting uninstall: ipython\n",
- " ---------------------------------- ----- 17/20 [ipython-pygments-lexers]\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " Found existing installation: ipython 9.8.0\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " Uninstalling ipython-9.8.0:\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " Successfully uninstalled ipython-9.8.0\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " Attempting uninstall: ipywidgets\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " Found existing installation: ipywidgets 8.1.8\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " Uninstalling ipywidgets-8.1.8:\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " Successfully uninstalled ipywidgets-8.1.8\n",
- " ------------------------------------ --- 18/20 [ipython]\n",
- " -------------------------------------- - 19/20 [ipywidgets]\n",
- " -------------------------------------- - 19/20 [ipywidgets]\n",
- " ---------------------------------------- 20/20 [ipywidgets]\n",
- "\n",
- "Successfully installed asttokens-3.0.1 colorama-0.4.6 comm-0.2.3 decorator-5.2.1 executing-2.2.1 ipython-9.8.0 ipython-pygments-lexers-1.1.1 ipywidgets-8.1.8 jedi-0.19.2 jupyterlab_widgets-3.0.16 matplotlib-inline-0.2.1 parso-0.8.5 prompt_toolkit-3.0.52 pure-eval-0.2.3 pygments-2.19.2 stack_data-0.6.3 traitlets-5.14.3 typing_extensions-4.15.0 wcwidth-0.2.14 widgetsnbextension-4.0.15\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- " WARNING: The script pygmentize.exe is installed in 'C:\\Users\\deenekat7271\\AppData\\Roaming\\Python\\Python311\\Scripts' which is not on PATH.\n",
- " Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.\n",
- " WARNING: The scripts ipython.exe and ipython3.exe are installed in 'C:\\Users\\deenekat7271\\AppData\\Roaming\\Python\\Python311\\Scripts' which is not on PATH.\n",
- " Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.\n"
- ]
- }
- ],
- "source": [
- "!pip install --force-reinstall ipywidgets"
- ]
+ "outputs": [],
+ "execution_count": null,
+ "source": "!pip install --force-reinstall ipywidgets",
+ "id": "30cf1c2aaee08295"
},
{
- "cell_type": "code",
- "execution_count": 3,
- "id": "6231896f-1143-4c22-ae72-9b6dd4d4a014",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Defaulting to user installation because normal site-packages is not writeable\n",
- "Requirement already satisfied: pyarrow in c:\\users\\deenekat7271\\appdata\\roaming\\python\\python311\\site-packages (22.0.0)\n"
- ]
- }
- ],
- "source": [
- "!pip install pyarrow"
- ]
+ "cell_type": "code",
+ "outputs": [],
+ "execution_count": null,
+ "source": "!pip install pyarrow",
+ "id": "878410f93e074377"
},
{
- "cell_type": "markdown",
- "id": "6ddea397-c025-4f29-93ff-936bc26ff4b7",
"metadata": {},
+ "cell_type": "markdown",
"source": [
"## Stap 1: Inladen van benodigde data\n",
"\n",
"De benodigde data voor het bepalen van geotechnische parameters kan op 3 manieren worden ingeladen in deze notebook.\n",
- "- Op basis van de data in de excel versie van de proevenverzamelingtool (vanaf versie 4.2n of hoger) waarin zowel reeds proevenverzamelingen zijn onderscheiden als geotechnische parameters zijn vastgesteld. NB. de onderscheiden verzamelingen worden als uitgangspunt worden ingeladen, de sterkteparameters worden opnieuw berekend. Onderliggende keuzes zoals het gewenste rekpercentage en de gekozen raaklijnen worden niet ingelezen uit de Excelversie. \n",
+ "- Op basis van de data in de excel versie van de proevenverzamelingtool (vanaf versie 4.2n of hoger) waarin zowel reeds proevenverzamelingen zijn onderscheiden als geotechnische parameters zijn vastgesteld. NB. de onderscheiden verzamelingen worden als uitgangspunt worden ingeladen, de sterkteparameters worden opnieuw berekend. Onderliggende keuzes zoals het gewenste rekpercentage en de gekozen raaklijnen worden niet ingelezen uit de Excelversie.\n",
"- Op basis van het Excel Uitwisselformat-database-proevenverzameling_versie_4_2x.xlsx waarin nog geen verzamelingen onderscheiden zijn.\n",
"\n",
"Zie tevens: https://github.com/kkpdata/Proevenverzamelingentool/\n",
"\n",
- "De proevenverzamelingtool of het uitwisselformat worden omgezet naar het template proevenverzamelingtool 5.0 \n",
+ "De proevenverzamelingtool of het uitwisselformat worden omgezet naar het template proevenverzamelingtool 5.0\n",
"\n",
"- Op basis van het Excel template voor de Proevenverzameling 5.0. Deze bestaat uit de data conform het uitwisselformat 4.2 aangevuld met de benodigde in en uitvoerdata van voorliggende tooling."
- ]
+ ],
+ "id": "4062aa452d2f9e29"
},
{
- "cell_type": "code",
- "execution_count": 4,
- "id": "229ba24b-906d-49ac-b5a8-213bd644d22b",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/markdown": [
- "**Stap 1: Kies Excel template voor uploaden data:**"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "c3f3390e98c34aa68058fdc9de33b8ad",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Dropdown(description='Template:', index=2, layout=Layout(width='400px'), options=('Proevenverzamelingtool 4.2n…"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "6492a9a343c64aa0b43a82fc83de917c",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "FileChooser(path='C:\\', filename='', title='Selecteer een bestand om te uploaden', show_hidden=False, select_d…"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\n"
- ]
- }
- ],
+ "cell_type": "code",
+ "outputs": [],
+ "execution_count": null,
"source": [
"# Laden van widgets voor uploaden bestanden\n",
"import ipywidgets as widgets\n",
@@ -477,14 +103,14 @@
"# Dropdown widget voor keuze template\n",
"dropdown_template = widgets.Dropdown(\n",
" options=[\n",
- " 'Proevenverzamelingtool 4.2n of hoger', \n",
- " 'STOWA uitwisselingsformat 4.2x', \n",
+ " 'Proevenverzamelingtool 4.2n of hoger',\n",
+ " 'STOWA uitwisselingsformat 4.2x',\n",
" 'Proevenverzamelingtool 5.0'\n",
" ], # De opties in het menu\n",
" value='Proevenverzamelingtool 5.0', # Standaard geselecteerde waarde\n",
" description='Template:',\n",
- " disabled=False, \n",
- " layout=widgets.Layout(width='400px') \n",
+ " disabled=False,\n",
+ " layout=widgets.Layout(width='400px')\n",
")\n",
"\n",
"# Maak een FileChooser-widget\n",
@@ -504,91 +130,50 @@
"display(file_chooser_import)\n",
"\n",
"print()"
- ]
+ ],
+ "id": "2041d8dede6a6e5a"
},
{
- "attachments": {},
+ "metadata": {},
"cell_type": "markdown",
- "id": "49c409f6-3e78-478e-8d55-e1d1a47cb7eb",
- "metadata": {
- "jp-MarkdownHeadingCollapsed": true
- },
"source": [
"## Stap 2a: Importeren inclusief toevoegen/herberekenen analyse kolommen\n",
- "De importfunctie laadt de data in. Daarnaast worden analyse kolommen (ANA) toegevoegd die benodigd zijn voor de functies in \"shansep_analysis\" en \"sutabel_analysis\". \n",
+ "De importfunctie laadt de data in. Daarnaast worden analyse kolommen (ANA) toegevoegd die benodigd zijn voor de functies in \"shansep_analysis\" en \"sutabel_analysis\".\n",
"\n",
- "Hiervoor worden verschillende kolommen aangemaakt: \n",
+ "Hiervoor worden verschillende kolommen aangemaakt:\n",
"ANA_TERREINSPANNING, ANA_TXT_MAX_VERTICALE_CONSOLIDATIE_SPANNING, ANA_DSS_MAX_CONSOLIDATIE_SPANNING, ANA_TXT_CONSOLIDATIE_TYPE_VOORSTEL, ANA_TXT_CONSOLIDATIE_TYPE_HANDMATIG, ANA_TXT_CONSOLIDATIE_TYPE_REKEN, ANA_DSS_CONSOLIDATIE_TYPE_VOORSTEL, ANA_DSS_CONSOLIDATIE_TYPE_HANDMATIG\n",
"ANA_DSS_CONSOLIDATIE_TYPE_REKEN, ANA_GRENSSPANNING_PROEF, ANA_POP_VELD, ANA_POP_VELD_GEMIDDELD, ANA_GRENSSPANNING_VOORSTEL, ANA_GRENSSPANNING_HANDMATIG\n",
"ANA_GRENSSPANNING_REKEN, OCR_TXT, OCR_DSS.\n",
"\n",
"Er moet worden vastgesteld of een proef is uitgevoerd op een normaal geconsolideerd monster (NC) ruim boven de grensspanning of overconsolideerd (OC) bij de geschatte dagelijkse effectieve terreinspanning (OCR>1). De tooling doet hier een voorstel voor door de consolidatiespanning (sigma'vc) te vergelijken met de terreinspanning (sigma'vi). Indien deze niet meer dan +30% afwijkt wordt aangenomen dat het een OC-proef betreft en bij grotere afwijkingen een NC-proef. Het is noodzakelijk om dit voorstel te controleren. In de regel is een OC-proef vrijwel altijd dicht bij de terreinspanning gekozen en ligt een NC-proef er ruim boven, maar hier zijn altijd uitzonderingen op mogelijk.\n",
"\n",
- "Daarnaast is een schatting van de OCR benodigd. Om deze te berekenen is een schatting van de grensspanning benodigd. Indien er op dezelfde regel een resultaat beschikbaar is uit een samendrukkingsproef of CRS-proef wordt deze gebruikt. Indien deze ontbreekt wordt een voorstel gedaan op basis van de gemiddelde POP (POP = grensspanning - effectieve terreinspanning o.b.v. de monsters waar wel een proef is uitgevoerd ) per boring. Indien er bij de betreffende boring geen grensspanning beschikbaar is wordt geen waarde ingevuld. Het is dan niet mogelijk om geautomatiseerd een OCR te schatten. \n",
+ "Daarnaast is een schatting van de OCR benodigd. Om deze te berekenen is een schatting van de grensspanning benodigd. Indien er op dezelfde regel een resultaat beschikbaar is uit een samendrukkingsproef of CRS-proef wordt deze gebruikt. Indien deze ontbreekt wordt een voorstel gedaan op basis van de gemiddelde POP (POP = grensspanning - effectieve terreinspanning o.b.v. de monsters waar wel een proef is uitgevoerd ) per boring. Indien er bij de betreffende boring geen grensspanning beschikbaar is wordt geen waarde ingevuld. Het is dan niet mogelijk om geautomatiseerd een OCR te schatten.\n",
"De data wordt weggeschreven in de velden (ANA_GRENSSPANNING_VOORSTEL). Het is noodzakelijk om de voorgestelde waarden te controleren. Als gebruiker kan je het voorstel overrulen in de kolom (ANA_GRENSSPANNING_HANDMATIG).\n",
"\n",
"NB. Bij gebruik van de bestaande Excel versie van de proevenverzamelingtool zijn de cellen ANA_GRENSSPANNING_HANDMATIG veelal reeds ingevuld. In dat geval worden deze waarden overgenomen.\n"
- ]
+ ],
+ "id": "19b567b87c6ee36"
},
{
- "cell_type": "markdown",
- "id": "ae6f0418-c80a-4bef-b7d6-e30530e4ac3d",
"metadata": {},
+ "cell_type": "markdown",
"source": [
- "## Stap 2a: Valideren data \n",
+ "## Stap 2a: Valideren data\n",
"De validatie bestaat uit de volgende controles: voor de verschillende typen proeven – classificatie, CRS-proef, samendrukkingsproef, DSS-proef en triaxiaalproef – wordt per regel gecontroleerd of er een proef is uitgevoerd (data ingevuld) en zo ja, of de velden die in de PV-tool benodigd zijn volledig en correct zijn ingevuld.\n",
"\n",
- "Het resultaat van de validatie wordt opgeslagen in een twee Excel-bestanden Validation_log_##_critical_errors.xlsx en Validation_log_##_warnings.xlsx, waarin per gevalideerde kolom en regel het resultaat wordt weergegeven. Ir is per kolom aangegeven hoeveel fouten zijn aangetroffen. Er is onderscheid gemaakt tussen 'critical errors' en 'warnings'. De critical errors leiden tot fouten wanneer deze data wordt gebruikt bij het bepalen van de parameters. Deze dienen te worden gecorrigeerd of aangevuld. De warnings betreffen aanbevelingen. De resultaten worden weggeschreven in dezelfde directory als de importmap. \n",
+ "Het resultaat van de validatie wordt opgeslagen in een twee Excel-bestanden Validation_log_##_critical_errors.xlsx en Validation_log_##_warnings.xlsx, waarin per gevalideerde kolom en regel het resultaat wordt weergegeven. Ir is per kolom aangegeven hoeveel fouten zijn aangetroffen. Er is onderscheid gemaakt tussen 'critical errors' en 'warnings'. De critical errors leiden tot fouten wanneer deze data wordt gebruikt bij het bepalen van de parameters. Deze dienen te worden gecorrigeerd of aangevuld. De warnings betreffen aanbevelingen. De resultaten worden weggeschreven in dezelfde directory als de importmap.\n",
"\n",
- "Indien de validatie goed is doorlopen worden proevenverzamelingtool (vanaf versie 4.2n of hoger) of Uitwisselformat-database-proevenverzameling_versie_4_2x.xlsx weggeschreven naar het Template_PVtool5_0.xlsx. Indien reeds gebruik is gemaakt van het nieuwe template worden de analyse kolommen opnieuw berekend. Dit is noodzakelijk indien er data gewijzigd is. \n",
+ "Indien de validatie goed is doorlopen worden proevenverzamelingtool (vanaf versie 4.2n of hoger) of Uitwisselformat-database-proevenverzameling_versie_4_2x.xlsx weggeschreven naar het Template_PVtool5_0.xlsx. Indien reeds gebruik is gemaakt van het nieuwe template worden de analyse kolommen opnieuw berekend. Dit is noodzakelijk indien er data gewijzigd is.\n",
"\n",
"Indien er reeds een gevalideerde dataset beschikbaar is conform het Template_PVtool5_0 laadt de data dan in via stap 2b. Dit kost aanzienlijk minder rekentijd bij een grote dataset."
- ]
+ ],
+ "id": "f1f88d13ff53cdf"
},
{
- "cell_type": "code",
- "execution_count": 6,
- "id": "0afe3ee1-a4bd-4935-8c80-de311f3f0d47",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Je hebt gekozen: Proevenverzamelingtool 4.2n of hoger\n",
- "Code in script: PV-tool\n",
- "Geselecteerd bestand: SAFE 2022 Proevenverzameling_tool_v4.2n_test_zonder_functies.xlsm\n",
- "Geselecteerde directory: C:\\Users\\deenekat7271\\Documents\\GitHub\\pv-tool\\import_files\n",
- "Volledig pad: C:\\Users\\deenekat7271\\Documents\\GitHub\\pv-tool\\import_files\\SAFE 2022 Proevenverzameling_tool_v4.2n_test_zonder_functies.xlsm\n",
- "number of critical_errors in validate_kenmerken_boring = 0\n",
- "number of critical_errors in validate_clas = 0\n",
- "number of critical_errors in validate_crs = 4\n",
- "number of critical_errors in validate_samendrukking = 0\n",
- "number of critical_errors in validate_monster = 0\n",
- "number of critical_errors in validate_triaxiaal = 28\n",
- "number of critical_errors in validate_dss = 17\n",
- "number of warnings in validate_alg = 0\n",
- "number of warnings in validate_kenmerken_boring = 353\n",
- "number of warnings in validate_clas = 1843\n",
- "number of warnings in validate_crs = 76\n",
- "number of warnings in validate_samendrukking = 246\n",
- "number of warnings in validate_monster = 0\n",
- "number of warnings in validate_triaxiaal = 96\n",
- "number of warnings in validate_dss = 33\n"
- ]
- },
- {
- "ename": "AttributeError",
- "evalue": "'Dbase' object has no attribute 'export_dbase_to_excel'",
- "output_type": "error",
- "traceback": [
- "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
- "\u001b[31mAttributeError\u001b[39m Traceback (most recent call last)",
- "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[6]\u001b[39m\u001b[32m, line 52\u001b[39m\n\u001b[32m 49\u001b[39m filename_export = file_chooser_import.selected_filename\n\u001b[32m 51\u001b[39m \u001b[38;5;66;03m#Export naar Template_PVtool5_0.xlsx \u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m52\u001b[39m \u001b[43mdbase\u001b[49m\u001b[43m.\u001b[49m\u001b[43mexport_dbase_to_excel\u001b[49m(export_dir=dir2, filename=filename_export)\n",
- "\u001b[31mAttributeError\u001b[39m: 'Dbase' object has no attribute 'export_dbase_to_excel'"
- ]
- }
- ],
+ "cell_type": "code",
+ "outputs": [],
+ "execution_count": null,
"source": [
"from pv_tool.imports.import_data import Dbase\n",
"from pathlib import Path\n",
@@ -628,10 +213,10 @@
"dir_in = (file_chooser_import.selected)\n",
"dir2 = Path(file_chooser_import.selected_path)\n",
"\n",
- "#starten importeren \n",
+ "#starten importeren\n",
"dbase.import_data(source = template_code, source_dir=dir_in)\n",
"\n",
- "#starten validatie \n",
+ "#starten validatie\n",
"dbase.validate_data(export_path=dir2)\n",
"\n",
"# Bepaal bestandsnaam voor de export van de data, bij PV4.2 of 4.2 uitwisselformat standaard export naar Template_PVtool5_0.xlsx\n",
@@ -640,26 +225,26 @@
"elif dropdown_template.value == 'Proevenverzamelingtool 5.0':\n",
" filename_export = file_chooser_import.selected_filename\n",
"\n",
- "#Export naar Template_PVtool5_0.xlsx \n",
+ "#Export naar Template_PVtool5_0.xlsx\n",
"dbase.export_dbase_to_excel(export_dir=dir2, filename=filename_export)"
- ]
+ ],
+ "id": "f0836be7c7db1a3e"
},
{
- "cell_type": "markdown",
- "id": "b72b6fa4-5e92-4b90-a335-099a8058cfdd",
"metadata": {},
+ "cell_type": "markdown",
"source": [
"## Stap 2b: Importeren data zonder validatie of herberekening analysekolommen\n",
"\n",
- "De importfunctie laadt de data conform het Template_PVtool5_0. Deze functie mag alleen gebruikt worden indien er reeds een gevalideerde dataset beschikbaar is conform het Template_PVtool5_0. Na het aanbrengen van wijzigingen in de data altijd stap 2a toepassen voor het importeren. Dit is noodzakelijk omdat de analsyekolommen benodigd voor onderstaande functies opnieuw berekend moeten worden bij aanpassingen aan de data. "
- ]
+ "De importfunctie laadt de data conform het Template_PVtool5_0. Deze functie mag alleen gebruikt worden indien er reeds een gevalideerde dataset beschikbaar is conform het Template_PVtool5_0. Na het aanbrengen van wijzigingen in de data altijd stap 2a toepassen voor het importeren. Dit is noodzakelijk omdat de analsyekolommen benodigd voor onderstaande functies opnieuw berekend moeten worden bij aanpassingen aan de data."
+ ],
+ "id": "7b9ab9203867511f"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "cfab8ba1-c3c7-4711-85f3-11f26d3db623",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
+ "execution_count": null,
"source": [
"from pv_tool.imports.import_data import Dbase\n",
"from pathlib import Path\n",
@@ -695,32 +280,32 @@
"\n",
"# Start importeren zonder validatie\n",
"dbase.import_dbase_short(source=template_code, source_dir=full_path)"
- ]
+ ],
+ "id": "f32dbbcee31ac05b"
},
{
- "cell_type": "markdown",
- "id": "5c3a7976-c5b9-479d-8947-5553e7e40b9a",
"metadata": {},
+ "cell_type": "markdown",
"source": [
"## Stap 4a: Bepalen gedraineerde parameters triaxiaalproeven en DSS-proeven op basis van fit (C en Phi)\n",
"\n",
- "In deze stap worden op basis van de data vastgelegd in het template PV-tool 5.0. gedraineerde parameters bepaald. Maak een keuze uit de verzameling waarop de statistische analyse moet plaatsvinden. Als er nog geen aparte verzamelingen onderscheiden zijn in het veld (PV_NAAM) worden alle triaxaalproeven in één verzameling opgenomen. \n",
+ "In deze stap worden op basis van de data vastgelegd in het template PV-tool 5.0. gedraineerde parameters bepaald. Maak een keuze uit de verzameling waarop de statistische analyse moet plaatsvinden. Als er nog geen aparte verzamelingen onderscheiden zijn in het veld (PV_NAAM) worden alle triaxaalproeven in één verzameling opgenomen.\n",
"\n",
"Als gebruiker kunnen handmatig verzamelingen worden opgegeven in de Excel template in het veld PV_NAAM of er kan gebruik worden gemaakt van de functie:\n",
"Definiëren en aanpassen van verzamelingen (stap #). Met behulp van de functie ## kunnen in de grafiek met behulp van de selectietool (should have) ook één of meer proefresultaten worden geselecteerd en worden toegekend aan een andere groep.\n",
"\n",
- "Geef het te hanteren rekpercentage op waarbij de s' en t zijn bepaald: 2%, 5%, 15%, eindrek of bij pieksterkte. \n",
+ "Geef het te hanteren rekpercentage op waarbij de s' en t zijn bepaald: 2%, 5%, 15%, eindrek of bij pieksterkte.\n",
"Indien er eerder parameters zijn vastgesteld worden de gemaakte keuzes voor het % en de raaklijnen ingeladen.\n",
"\n",
"Ook kunnen meerdere verzamelingen getoond worden. NB. Deze extra verzamelingen worden niet meegenomen in de statistische analyse."
- ]
+ ],
+ "id": "6b3e28750d15bed9"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "844c1507-d97a-4bf5-b162-0c8c395845a4",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
+ "execution_count": null,
"source": [
"import ipywidgets as widgets\n",
"from IPython.display import display, Markdown, clear_output\n",
@@ -745,9 +330,9 @@
"output_rekpercentage = widgets.Output()\n",
"\n",
"# Lijsten rekpercentage en verzamelingen aanpassen bij wijziging van proeftype txt/dss\n",
- "def update_verzamelings_dropdowns(change): \n",
- " with container_rekpercentage: \n",
- " clear_output(); \n",
+ "def update_verzamelings_dropdowns(change):\n",
+ " with container_rekpercentage:\n",
+ " clear_output();\n",
" (dropdown_verzameling.options, dropdown_verzameling.value, multi_select_verzameling.options, multi_select_verzameling.value, _d) = \\\n",
" (PV_txt_lijst, PV_txt_lijst[0], PV_txt_lijst, [PV_txt_lijst[0]], display(dropdown_rekpercentage_txt)) if dropdown_type_proef.value == 'TXT_CPhi' \\\n",
" else (PV_dss_lijst, PV_dss_lijst[0], PV_dss_lijst, [PV_dss_lijst[0]], display(dropdown_rekpercentage_dss))\n",
@@ -783,14 +368,14 @@
"display(output_rekpercentage)\n",
"display(Markdown(\"**Kies één of meerdere verzamelingen om naast de gekozen verzameling voor de statistische analyse te tonen:**\"))\n",
"display(multi_select_verzameling)"
- ]
+ ],
+ "id": "510521965ad86c5e"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "add5e012-d3cd-4e3c-a5d0-8bf1e091bebf",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
+ "execution_count": null,
"source": [
"#widget inladen voor opgeven parameters bepalen cohesie en hoek van inwendige wrijving\n",
"\n",
@@ -829,8 +414,8 @@
"#laatste_resultaten = analyse.get_previous_results(path=str(dir2), file_name=filename_export )\n",
"laatste_resultaten = analyse.get_previous_results(path=str(dir2) )\n",
"\n",
- "if (laatste_resultaten is not None and \n",
- " not laatste_resultaten.empty and \n",
+ "if (laatste_resultaten is not None and\n",
+ " not laatste_resultaten.empty and\n",
" 'PV_A1_COH_GEM [kPa]' in laatste_resultaten):\n",
" PV_A1_COH_GEM_handmatig = [laatste_resultaten['PV_A1_COH_GEM [kPa]']]\n",
" PV_A2_PHI_KAR_handmatig = [laatste_resultaten['PV_A2_TAN_PHI_KAR [-]']]\n",
@@ -868,24 +453,22 @@
" dropdown_verzameling,\n",
" gekozen_rekpercentage\n",
")"
- ]
+ ],
+ "id": "4739039b5805463"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "aa6474ce-ff88-4f15-b0b1-3650f9140927",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
- "source": [
- "print (dir2)"
- ]
+ "execution_count": null,
+ "source": "print (dir2)",
+ "id": "e07888b336325a67"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "98d76aef-5480-47fa-921c-e643799a1b77",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
+ "execution_count": null,
"source": [
"#voer C-phi analyse uit met invoer en toon grafieken\n",
"if dropdown_type_proef.value.startswith('TXT'):\n",
@@ -903,14 +486,14 @@
"analyse.show_figure(plot_spanningspaden=True)\n",
"\n",
"analyse.print_short_results()"
- ]
+ ],
+ "id": "52e61c68f0c07459"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "e9b57eef-764e-4a4f-84d3-c185663e395f",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
+ "execution_count": null,
"source": [
"# Resultaten opslaan naar: ##_PVtool5_0.xlsx, pdf en exporteer tussenstappen naar excel\n",
"import os\n",
@@ -920,7 +503,7 @@
"os.makedirs(output_path1, exist_ok=True)\n",
"\n",
"# Sla resultaten op als PDF\n",
- "analyse.save_to_pdf(path=output_path1) \n",
+ "analyse.save_to_pdf(path=output_path1)\n",
"\n",
"# schrijf invoer en resultaten naar PV_template, tabblad resultaten c-phi.\n",
"analyse.add_results_to_dbase(path=dir2, file_name=filename_export)\n",
@@ -929,52 +512,52 @@
"bestand_naam = os.path.join(output_path1, \"c_phi_data_geforceerd.xlsx\")\n",
"analyse.cphi_analyses_data_df.to_excel(bestand_naam, index=False)\n",
"\n",
- "#Plotly bestand maken \n",
+ "#Plotly bestand maken\n",
"fig_s_t = analyse.figure # of analyse.fig als die bestaat\n",
"bestandsnaam = dropdown_verzameling.value.replace(' ', '_') + '.html'\n",
"output_path = os.path.join(output_path1, bestandsnaam)\n",
"fig_s_t.write_html(output_path)\n",
"print(f\"Figuur opgeslagen als {output_path}\")\n"
- ]
+ ],
+ "id": "b7f1de4bfeb6f4c0"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "931d2008-a079-4586-ba22-e2a034e40375",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
- "source": []
+ "execution_count": null,
+ "source": "",
+ "id": "e9f78b1a21eb73b4"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "bf00389b-3e9c-4c04-880c-31b281915c72",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
- "source": []
+ "execution_count": null,
+ "source": "",
+ "id": "1fdc22653874abf8"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "aefecf81-4b57-40f9-b26b-a736db27cae2",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
- "source": []
+ "execution_count": null,
+ "source": "",
+ "id": "7a27665ca3c54823"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "12800281-f317-42ed-85e0-5069bfa16c35",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
- "source": []
+ "execution_count": null,
+ "source": "",
+ "id": "ceabef6342602f20"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "6c17d7b6-68c4-4c44-bc9b-a4b54b962c33",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
+ "execution_count": null,
"source": [
"# work in progress widget voor Shansep\n",
"\n",
@@ -1070,22 +653,22 @@
"# Toon de tabelwidget\n",
"display(Markdown(\"**Opgeven gemiddelde waarden (fit):**\"))\n",
"display(grid)"
- ]
+ ],
+ "id": "66ee44bf82d6c3b8"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "b270d822-cd07-480f-a21c-0eb91ab783be",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
- "source": []
+ "execution_count": null,
+ "source": "",
+ "id": "a0eb979d47102481"
},
{
- "cell_type": "code",
- "execution_count": null,
- "id": "63a7463c-b81d-415b-aec3-d329f2a51945",
"metadata": {},
+ "cell_type": "code",
"outputs": [],
+ "execution_count": null,
"source": [
"# Laden van widgets voor keuzes afleiden gedraineerde parameters\n",
"import ipywidgets as widgets\n",
@@ -1098,7 +681,7 @@
"PV_txt_lijst = ['geen'] + dbase_df.loc[dbase_df['ALG__TRIAXIAAL'], 'PV_NAAM'].dropna().unique().tolist()\n",
"PV_dss_lijst = ['geen'] + dbase_df.loc[dbase_df['ALG__DSS'], 'PV_NAAM'].dropna().unique().tolist()\n",
"\n",
- "#### Widgets \n",
+ "#### Widgets\n",
"# # Dropdown widget voor rek%\n",
"dropdown_rekpercentage = widgets.Dropdown(options=['2% rek', '5% rek', '15% rek', 'eindsterkte', 'pieksterkte'], value='eindsterkte', layout=widgets.Layout(width='400px'))\n",
"\n",
@@ -1118,8 +701,9 @@
"display(Markdown(\"**Kies één of meerdere verzamelingen om naast de gekozen verzameling voor de statistische analyse te tonen:**\"))\n",
"display(multi_select_verzameling)\n",
"\n",
- "print()"
- ]
+ "print()\n"
+ ],
+ "id": "37a0b53deefd214a"
}
],
"metadata": {
diff --git a/main_nathan.py b/main_nathan.py
index b2a24d5..9e97ac5 100644
--- a/main_nathan.py
+++ b/main_nathan.py
@@ -96,8 +96,8 @@ def database_import_test(source: Literal['Stowa', 'PV-tool', 'Dbase'],
return None
if export:
- print(f"Exporting database to {save_test / file_name_export}")
- dbase.export_dbase_to_excel(export_dir=save_test, filename=file_name_export)
+ print(f"Exporting database to {save_test / file_name_export} is no longer part of the test.")
+ # dbase.export_dbase_to_excel(export_dir=save_test, filename=file_name_export)
return dbase
@@ -141,8 +141,8 @@ def cphi_analysis_txt_test(dbase: Dbase, export_path: Path, export_file: str, pl
# Print en exporteer resultaten
print('\nResultaten TXT C-phi analyse:')
- print(analyse.print_short_results())
- analyse.add_results_to_dbase(path=str(export_path), file_name=export_file)
+ print(analyse.get_short_results())
+ analyse.add_results_to_template(path=str(export_path), export_name=export_file)
# Visualisatie
analyse.show_figure(plot_extra_dataset = plot_extra_dataset, plot_spanningspaden=plot_spanningspaden)
@@ -175,8 +175,8 @@ def cphi_analysis_dss_test(dbase: Dbase, export_path: Path, export_file: str, pl
# Print en exporteer resultaten
print('\nResultaten DSS C-phi analyse:')
- print(analyse.print_short_results())
- analyse.add_results_to_dbase(path=str(export_path), file_name=export_file)
+ print(analyse.get_short_results())
+ analyse.add_results_to_template(path=str(export_path), export_name=export_file)
# Visualisatie
analyse.show_figure(plot_extra_dataset = plot_extra_dataset, plot_spanningspaden=plot_spanningspaden)
@@ -243,8 +243,8 @@ def cphi_analysis_dss_sh_test(dbase: Dbase, export_path: Path, export_file: str,
# Print en exporteer resultaten
print('\nResultaten DSS C-phi analyse (schematiseringshandleiding):')
- print(analyse.print_short_results())
- analyse.add_results_to_dbase(path=str(export_path), file_name=export_file)
+ print(analyse.get_short_results())
+ analyse.add_results_to_template(path=str(export_path), export_name=export_file)
# Visualisatie
analyse.show_figure(plot_extra_dataset = plot_extra_dataset, plot_spanningspaden=plot_spanningspaden)
@@ -282,7 +282,7 @@ def shansep_analysis_test(dbase: Dbase, export_path: Path, export_file: str, plo
# Print en exporteer resultaten
print('\nResultaten SHANSEP analyse:')
- analyse.add_results_to_dbase(path=str(export_path), file_name=export_file)
+ analyse.add_results_to_template(path=str(export_path), export_name=export_file)
analyse.set_parameters_handmatig(snijpunt_gem=11, s_gem=0.31, m_gem=0.9, snijpunt_kar=7, s_kar=0.28, m_kar=0.9)
@@ -330,7 +330,7 @@ def sutabel_analysis_test(dbase: Dbase, export_path: Path, export_file: str, plo
sutabel.show_figure_sv_su_sutabel(plot_extra_dataset=plot_extra_dataset)
# Export (analysis runs automatically if needed)
- sutabel.add_results_to_dbase(str(export_path), export_file)
+ sutabel.add_results_to_template(str(export_path), export_file)
sutabel.save_to_pdf(str(export_path))
@@ -369,25 +369,25 @@ def sutabel_analysis_test(dbase: Dbase, export_path: Path, export_file: str, plo
# Test verschillende analyses
print("\nUitvoeren van verschillende test cases...")
- #
- # print("\nTXT C-phi analyse test")
- # cphi_analysis_txt_test(dbase, export_dir, export_name, plot_extra_dataset=plot_extra_dataset, plot_spanningspaden=plot_spanningspaden)
- #
- # print("\nDSS C-phi analyse test")
- # cphi_analysis_dss_test(dbase, export_dir, export_name, plot_extra_dataset=plot_extra_dataset, plot_spanningspaden=plot_spanningspaden)
+
+ print("\nTXT C-phi analyse test")
+ cphi_analysis_txt_test(dbase, export_dir, export_name, plot_extra_dataset=plot_extra_dataset, plot_spanningspaden=plot_spanningspaden)
+
+ print("\nDSS C-phi analyse test")
+ cphi_analysis_dss_test(dbase, export_dir, export_name, plot_extra_dataset=plot_extra_dataset, plot_spanningspaden=plot_spanningspaden)
print("\nTXT C-phi analyse (schematiseringshandleiding) test")
cphi_analysis_txt_sh_test(dbase, export_dir, export_name, plot_extra_dataset=plot_extra_dataset, plot_spanningspaden=plot_spanningspaden)
- # print("\nDSS C-phi analyse (schematiseringshandleiding) test")
- # cphi_analysis_dss_sh_test(dbase, export_dir, export_name, plot_extra_dataset=plot_extra_dataset, plot_spanningspaden=plot_spanningspaden)
- #
- # plot_extra_dataset = ['TXT_SAFE_klei_zwaar']
- #
- # print("\nTXT SHANSEP analyse test")
- # shansep_analysis_test(dbase, export_dir, export_name, plot_extra_dataset=plot_extra_dataset)
- #
- # print("\nSUTABEL analyse test")
- # sutabel_analysis_test(dbase, export_dir, export_name, plot_extra_dataset=plot_extra_dataset)
+ print("\nDSS C-phi analyse (schematiseringshandleiding) test")
+ cphi_analysis_dss_sh_test(dbase, export_dir, export_name, plot_extra_dataset=plot_extra_dataset, plot_spanningspaden=plot_spanningspaden)
+
+ plot_extra_dataset = ['TXT_SAFE_klei_zwaar']
+
+ print("\nTXT SHANSEP analyse test")
+ shansep_analysis_test(dbase, export_dir, export_name, plot_extra_dataset=plot_extra_dataset)
+
+ print("\nSUTABEL analyse test")
+ sutabel_analysis_test(dbase, export_dir, export_name, plot_extra_dataset=plot_extra_dataset)
print("\nAlle tests zijn voltooid!")
diff --git a/pv_tool/cphi_analysis/c_phi_analysis.py b/pv_tool/cphi_analysis/c_phi_analysis.py
index 61778f1..c16eea1 100644
--- a/pv_tool/cphi_analysis/c_phi_analysis.py
+++ b/pv_tool/cphi_analysis/c_phi_analysis.py
@@ -3,7 +3,7 @@
from openpyxl.utils import get_column_letter
from pathlib import Path
from datetime import datetime
-from utils import get_repo_root, make_temp_folder
+from pv_tool.utilities.utils import get_repo_root, make_temp_folder
from pandas import DataFrame, ExcelWriter, concat, read_excel, isna
from pv_tool.cphi_analysis.globals import (TEXTUAL_NAMES, ALL_TEXTUAL_NAMES,
NEW_COLUMN_NAMES, TEXTUAL_NAMES_DSS, ALL_TEXTUAL_NAMES_DSS)
@@ -570,6 +570,25 @@ def show_figure(self, plot_extra_dataset: Optional[List] = None, plot_spanningsp
self.set_figure(plot_extra_dataset, plot_spanningspaden=plot_spanningspaden)
self.figure.show()
+ def save_fig_html(self, path: str, export_name: Optional[str] = None):
+ """
+ Slaat de visualisatie van de analyseresultaten op als een HTML-bestand.
+
+ NB: als de figuur leeg is, roep dan eerst show_figure() aan om de figuur te genereren.
+
+ Parameters
+ ----------
+ path : str
+ Pad naar de map waar het bestand opgeslagen moet worden
+ export_name : str, optioneel
+ Naam van het HTML-bestand
+ """
+ if export_name is None:
+ export_name = f"c-phi_analyse_{self.investigation_groups[0].value.replace(' ', '_')}.html"
+ file_path = Path(path) / export_name
+ self.figure.write_html(file_path)
+ print(f"figuur opgeslagen als HTML: {file_path}")
+
def get_short_results(self):
"""
Genereert een samenvattend overzicht van de analyseresultaten.
diff --git a/pv_tool/cphi_analysis/test_c_phi_analysis.py b/pv_tool/cphi_analysis/test_c_phi_analysis.py
index 3e0e6c4..43c8f4c 100644
--- a/pv_tool/cphi_analysis/test_c_phi_analysis.py
+++ b/pv_tool/cphi_analysis/test_c_phi_analysis.py
@@ -1,7 +1,7 @@
import os.path
import unittest
from pv_tool.imports.import_data import Dbase
-from utils import get_repo_root, make_temp_folder
+from pv_tool.utilities.utils import get_repo_root, make_temp_folder
from pathlib import Path
from pv_tool.cphi_analysis.c_phi_analysis import CPhiAnalyse
import shutil
@@ -36,7 +36,7 @@ def test_cphi_analyse():
# apply parameters
analyse.apply_parameters(cohesie_gem=8.0, phi_kar=0.53, cohesie_kar=6.72)
# print results
- analyse.print_short_results()
+ analyse.get_short_results()
# exports
analyse.add_results_to_template(path=export_dir, export_name=export_name)
analyse.save_to_pdf(path=export_dir)
@@ -51,3 +51,71 @@ class TestImportAndValidate(unittest.TestCase):
def test_cphi_analyse(self):
self.assertTrue(test_cphi_analyse())
+
+ def test_creating_figures(self):
+ """Test het aanmaken van figuren en save_fig_html functionaliteit voor CPhiAnalyse."""
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+
+ analyse = CPhiAnalyse(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='15% rek',
+ analysis_type='TXT_CPhi'
+ )
+
+ # Apply settings and parameters
+ analyse.apply_settings(alpha=0.75)
+ analyse.apply_parameters(cohesie_gem=8.0, phi_kar=0.53, cohesie_kar=6.72)
+ analyse._run()
+
+ # Test dat we een figure kunnen aanmaken en opslaan
+ figure_created = False
+ html_saved = False
+
+ # Test figure creation
+ try:
+ analyse.show_figure()
+ # Controleer dat figure object is aangemaakt
+ self.assertIsNotNone(analyse.figure)
+ figure_created = True
+
+ # Test save_fig_html functionaliteit
+ analyse.save_fig_html(path=str(export_dir), export_name="test_cphi_figure.html")
+ # Controleer dat het HTML bestand bestaat
+ html_file = export_dir / "test_cphi_figure.html"
+ self.assertTrue(html_file.exists(), "HTML file should be created")
+ html_saved = True
+
+ except Exception as e:
+ print(f"C-Phi figure creation failed: {e}")
+
+ # Test figure with spanningspaden
+ try:
+ analyse.show_figure(plot_spanningspaden=True)
+ # Test save_fig_html functionaliteit met spanningspaden
+ analyse.save_fig_html(path=str(export_dir), export_name="test_cphi_spanningspaden.html")
+ html_file = export_dir / "test_cphi_spanningspaden.html"
+ self.assertTrue(html_file.exists(), "HTML file with spanningspaden should be created")
+ html_saved = True
+
+ except Exception as e:
+ print(f"C-Phi figure with spanningspaden creation failed: {e}")
+
+ # Test dat minstens één van de figure tests is gelukt
+ if not figure_created:
+ self.skipTest("Figure creation failed - may require specific data conditions")
+
+ # Test dat save_fig_html functionaliteit werkt
+ self.assertTrue(html_saved, "save_fig_html should successfully create HTML files")
+
+ # Test default export name functionality
+ try:
+ analyse.show_figure()
+ analyse.save_fig_html(path=str(export_dir)) # No export_name specified
+ # Check that a file with default name pattern was created
+ html_files = list(export_dir.glob("c-phi_analyse_*.html"))
+ self.assertTrue(len(html_files) > 0, "Default export name should create a file")
+ except Exception as e:
+ print(f"Default export name test failed: {e}")
diff --git a/pv_tool/imports/test_imports.py b/pv_tool/imports/test_imports.py
index 20ed913..6675168 100644
--- a/pv_tool/imports/test_imports.py
+++ b/pv_tool/imports/test_imports.py
@@ -1,7 +1,7 @@
import os.path
import unittest
from pv_tool.imports.import_data import Dbase
-from utils import get_repo_root, make_temp_folder
+from pv_tool.utilities.utils import get_repo_root, make_temp_folder
from pathlib import Path
import shutil
diff --git a/pv_tool/shansep_analysis/save_and_export.py b/pv_tool/shansep_analysis/save_and_export.py
index 7931b08..d5ecc24 100644
--- a/pv_tool/shansep_analysis/save_and_export.py
+++ b/pv_tool/shansep_analysis/save_and_export.py
@@ -1,7 +1,7 @@
from typing import TYPE_CHECKING, List
from pandas import ExcelWriter, concat, DataFrame, read_excel
from datetime import datetime
-from utils import get_repo_root, make_temp_folder
+from pv_tool.utilities.utils import get_repo_root, make_temp_folder
from openpyxl import load_workbook
from reportlab.lib.pagesizes import A4, landscape
from reportlab.lib import colors
diff --git a/pv_tool/shansep_analysis/shansep_analysis.py b/pv_tool/shansep_analysis/shansep_analysis.py
index 00182cf..962ef19 100644
--- a/pv_tool/shansep_analysis/shansep_analysis.py
+++ b/pv_tool/shansep_analysis/shansep_analysis.py
@@ -4,6 +4,7 @@
from pv_tool.shansep_analysis.globals import (TEXTUAL_NAMES, NEW_COLUMN_NAMES, TEXTUAL_NAMES_DSS)
from pandas import DataFrame, ExcelWriter, read_excel
import plotly.graph_objects as go
+from pathlib import Path
from pv_tool.shansep_analysis.calc_parameters import (
calc_watergehalte_gem_txt, calc_watergehalte_gem_dss,
calc_watergehalte_sd_txt, calc_watergehalte_sd_dss,
@@ -50,7 +51,7 @@
calculate_sv_eff_nc_oc, calculate_5pr_bovengrens_oc, calculate_5pr_bovengrens_nc_oc)
from pv_tool.shansep_analysis.save_and_export import (
- add_results_to_dbase as _add_results_to_dbase,
+ add_results_to_template as _add_results_to_template,
save_total_to_excel as _save_total_to_excel,
save_to_pdf as _save_to_pdf
)
@@ -124,6 +125,28 @@ def __init__(self, dbase: Dbase,
self.st_dev_pop_handmatig: Optional[float] = None
self.st_dev_m_handmatig: Optional[float] = None
+ # Inschatting (estimation) parameters
+ self.inschatting_snijpunt_gem: Optional[float] = None
+ self.inschatting_s_gem: Optional[float] = None
+ self.inschatting_m_gem: Optional[float] = None
+ self.inschatting_pop_gem: Optional[float] = None
+
+ self.inschatting_snijpunt_kar: Optional[float] = None
+ self.inschatting_s_kar: Optional[float] = None
+ self.inschatting_m_kar: Optional[float] = None
+ self.inschatting_pop_kar: Optional[float] = None
+
+ # NC (Normal Consolidated) inschatting parameters
+ self.inschatting_snijpunt_gem_nc: Optional[float] = None
+ self.inschatting_s_gem_nc: Optional[float] = None
+ self.inschatting_m_gem_nc: Optional[float] = None
+ self.inschatting_pop_gem_nc: Optional[float] = None
+
+ self.inschatting_snijpunt_kar_nc: Optional[float] = None
+ self.inschatting_s_kar_nc: Optional[float] = None
+ self.inschatting_m_kar_nc: Optional[float] = None
+ self.inschatting_pop_kar_nc: Optional[float] = None
+
# dataframes
self.shansep_data_df: Optional[DataFrame] = None
self.total_shansep_data_df: Optional[DataFrame] = None
@@ -353,6 +376,58 @@ def get_short_results(self):
return analyse_output_df
+ def get_estimated_parameters(self):
+ """
+ Haalt de geschatte parameters op voor gebruik als eerste benadering.
+ Deze methode moet worden aangeroepen nadat get_result_values_shansep() is uitgevoerd.
+
+ Returns
+ -------
+ dict
+ Dictionary met geschatte parameters voor gemiddelde en karakteristieke waarden
+ """
+ # Zorg dat resultaten zijn berekend
+ self.get_result_values_shansep()
+
+ estimated_params = {
+ 'snijpunt_gem': self.inschatting_snijpunt_gem,
+ 's_gem': self.inschatting_s_gem,
+ 'm_gem': self.inschatting_m_gem,
+ 'pop_gem': self.inschatting_pop_gem,
+ 'snijpunt_kar': self.inschatting_snijpunt_kar,
+ 's_kar': self.inschatting_s_kar,
+ 'm_kar': self.inschatting_m_kar,
+ 'pop_kar': self.inschatting_pop_kar
+ }
+
+ return estimated_params
+
+ def get_estimated_parameters_nc(self):
+ """
+ Haalt de geschatte NC (Normal Consolidated) parameters op.
+ Deze methode moet worden aangeroepen nadat get_result_values_nc() is uitgevoerd.
+
+ Returns
+ -------
+ dict
+ Dictionary met geschatte NC parameters voor gemiddelde en karakteristieke waarden
+ """
+ # Zorg dat NC resultaten zijn berekend
+ self.get_result_values_nc()
+
+ estimated_params_nc = {
+ 'snijpunt_gem_nc': self.inschatting_snijpunt_gem_nc,
+ 's_gem_nc': self.inschatting_s_gem_nc,
+ 'm_gem_nc': self.inschatting_m_gem_nc,
+ 'pop_gem_nc': self.inschatting_pop_gem_nc,
+ 'snijpunt_kar_nc': self.inschatting_snijpunt_kar_nc,
+ 's_kar_nc': self.inschatting_s_kar_nc,
+ 'm_kar_nc': self.inschatting_m_kar_nc,
+ 'pop_kar_nc': self.inschatting_pop_kar_nc
+ }
+
+ return estimated_params_nc
+
def _run_shansep(self):
"""
Voert de volledige shansep analyse uit in de juiste volgorde:
@@ -395,6 +470,25 @@ def get_result_values_shansep(self):
pop_bepaald = self.a1_kar_oc/self.a2_kar_oc/self.a2_kar_nc_oc
self.df_results_shansep_kar['POP [kPa]'] = [pop_bepaald, pop_bepaald, self.pop_kar_oc, None, self.pop_kar_handmatig]
+ self.inschatting_snijpunt_gem = self.e_a1_oc
+ self.inschatting_s_gem = self.e_a2_oc
+ self.inschatting_m_gem = self.e_a2_nc_oc
+ self.inschatting_pop_gem = pop_bepaald
+
+ self.inschatting_snijpunt_kar = self.a1_kar_oc
+ self.inschatting_s_kar = self.a2_kar_oc
+ self.inschatting_m_kar = self.a2_kar_nc_oc
+ self.inschatting_pop_kar = pop_bepaald
+
+ # write a warning that if any of the values of m are larger than 1, the user should change this
+ for m_value in [self.m_gem_handmatig, self.m_kar_handmatig]:
+ if m_value is not None and m_value > 1:
+ print("Waarschuwing: De handmatige waarde van m is groter dan 1. Dit is fysiek niet mogelijk. Overweeg om deze waarde aan te passen.")
+ for m_value in [self.e_a2_nc_oc, self.a2_kar_nc_oc]:
+ if m_value is not None and m_value > 1:
+ print("Waarschuwing: De inschatting van de waarde van m is groter dan 1. Dit is fysiek niet mogelijk. Overweeg om deze waarde aan te passen.")
+
+
# write these dataframes to excel
return self.df_results_shansep_gem, self.df_results_shansep_kar
@@ -435,6 +529,16 @@ def get_result_values_nc(self):
df_results_nc_kar['sterkte toename exponent = m [-]'] = [None, 0, None, None, 0]
df_results_nc_kar['POP [kPa]'] = [0, 0, 0, None, 0]
+ self.inschatting_snijpunt_gem_nc = 0
+ self.inschatting_s_gem_nc = self.e_a2_oc
+ self.inschatting_m_gem_nc = 0
+ self.inschatting_pop_gem_nc = 0
+
+ self.inschatting_snijpunt_kar_nc = 0
+ self.inschatting_s_kar_nc = self.a2_kar_oc
+ self.inschatting_m_kar_nc = 0
+ self.inschatting_pop_kar_nc = 0
+
return df_results_nc_gem, df_results_nc_kar
def calculate_sutabel(self):
@@ -666,17 +770,37 @@ def show_figure_sv_su_nc(self, plot_extra_dataset: Optional[List] = None):
self.set_figure_sv_su_nc(plot_extra_dataset)
self.figure.show()
+ def save_fig_html(self, path: str, export_name: Optional[str] = None):
+ """
+ Slaat de visualisatie van de analyseresultaten op als een HTML-bestand.
+
+ NB: als de figuur leeg is, roep dan eerst show_figure_...() aan om de figuur te genereren.
+ Kies uit show_figure_sv_su, show_figure_ln_ocr_ln_s of show_figure_sv_su_nc.
+
+ Parameters
+ ----------
+ path: str
+ Pad naar de map waar het bestand opgeslagen moet worden
+ export_name : str, optioneel
+ Naam van het HTML-bestand
+ """
+ if export_name is None:
+ export_name = f"shansep_analyse_{self.investigation_groups[0].value.replace(' ', '_')}.html"
+ file_path = Path(path) / export_name
+ self.figure.write_html(file_path)
+ print(f"figuur opgeslagen als HTML: {file_path}")
+
# ========== Export Methodes ==========
- def add_results_to_dbase(self, path: str, file_name: str = 'Template_PVtool5_0.xlsx'):
+ def add_results_to_template(self, path: str, export_name: str = 'Template_PVtool5_0.xlsx'):
"""
- Voegt de SHANSEP analyseresultaten toe aan de database Excel-bestand.
+ Voegt de SHANSEP analyseresultaten toe aan het template Excel-bestand.
Parameters
----------
path : str
Pad naar de map waar het Excel-bestand staat
- file_name : str, optioneel
+ export_name : str, optioneel
Naam van het Excel-bestand (default: 'Template_PVtool5_0.xlsx')
Returns
@@ -684,7 +808,7 @@ def add_results_to_dbase(self, path: str, file_name: str = 'Template_PVtool5_0.x
DataFrame
Bijgewerkte DataFrame met alle resultaten
"""
- return _add_results_to_dbase(self, path, file_name)
+ return _add_results_to_template(self, path, export_name)
def save_total_to_excel(self, path: str):
"""
diff --git a/pv_tool/shansep_analysis/test_shansep_analysis.py b/pv_tool/shansep_analysis/test_shansep_analysis.py
index e69de29..5099f93 100644
--- a/pv_tool/shansep_analysis/test_shansep_analysis.py
+++ b/pv_tool/shansep_analysis/test_shansep_analysis.py
@@ -0,0 +1,372 @@
+import os.path
+import unittest
+from pv_tool.imports.import_data import Dbase
+from pv_tool.utilities.utils import get_repo_root, make_temp_folder
+from pathlib import Path
+from pv_tool.shansep_analysis.shansep_analysis import SHANSEP
+import shutil
+
+FILE_PATH = os.path.join(get_repo_root(), "test_files")
+repo_root = get_repo_root()
+export_dir = make_temp_folder(
+ parent_folder=os.path.join(repo_root, "temp_exports"), add_microseconds=True
+)
+export_dir = Path(export_dir)
+
+
+def test_shansep_analyse():
+ """
+ Test voor SHANSEP analyse. Voert een volledige SHANSEP analyse uit met verschillende analyse types.
+ Test geïmplementeerd. Verander de invoer niet.
+ """
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+ export_name = 'Template_PVtool5_0.xlsx'
+ dbase.export_dbase_to_template(export_dir=export_dir)
+
+ # Initialize analysis types voor SHANSEP
+ analysis_types = ['TXT_S_POP', 'DSS_S_POP']
+ effective_stresses = {
+ 'TXT_S_POP': ['2% rek', '5% rek', '15% rek', 'pieksterkte', 'eindsterkte'],
+ 'DSS_S_POP': ['2% rek', '5% rek', '10% rek', '15% rek', '20% rek', 'pieksterkte', 'eindsterkte']
+ }
+
+ for analysis_type in analysis_types:
+ # Test met een representatieve effective stress voor elk analysis type
+ effective_stress = '15% rek' # Deze werkt voor beide types
+
+ analyse = SHANSEP(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress=effective_stress,
+ analysis_type=analysis_type
+ )
+
+ # Apply settings
+ analyse.apply_settings(alpha=0.75)
+
+ # Run de shansep analyse
+ analyse._run_shansep()
+
+ # Test het ophalen van data
+ analyse.get_shansep_data()
+
+ # Test parameters ophalen
+ analyse.get_shansep_parameters()
+
+ # Test korte resultaten
+ analyse.get_short_results()
+
+ # Test geschatte parameters ophalen voor eerste benadering
+ try:
+ estimated_params = analyse.get_estimated_parameters()
+ # Controleer dat de geschatte parameters zijn opgehaald
+ if estimated_params is None:
+ raise AssertionError("Geschatte parameters zijn None")
+ if 'snijpunt_gem' not in estimated_params:
+ raise AssertionError("snijpunt_gem ontbreekt in geschatte parameters")
+ print(f"Geschatte parameters: {estimated_params}")
+ except Exception as e:
+ print(f"Ophalen geschatte parameters mislukt: {e}")
+ estimated_params = None
+
+ # Test NC geschatte parameters
+ try:
+ estimated_params_nc = analyse.get_estimated_parameters_nc()
+ # Controleer dat de NC geschatte parameters zijn opgehaald
+ if estimated_params_nc is None:
+ raise AssertionError("NC geschatte parameters zijn None")
+ if 'snijpunt_gem_nc' not in estimated_params_nc:
+ raise AssertionError("snijpunt_gem_nc ontbreekt in NC geschatte parameters")
+ print(f"Geschatte NC parameters: {estimated_params_nc}")
+ except Exception as e:
+ print(f"Ophalen NC geschatte parameters mislukt: {e}")
+
+ # Test handmatige parameters (gebruik geschatte waardes als eerste benadering)
+ try:
+ if estimated_params and all(v is not None for v in [
+ estimated_params['snijpunt_gem'], estimated_params['s_gem'], estimated_params['m_gem'],
+ estimated_params['snijpunt_kar'], estimated_params['s_kar'], estimated_params['m_kar']
+ ]):
+ analyse.set_parameters_handmatig(
+ snijpunt_gem=estimated_params['snijpunt_gem'],
+ s_gem=estimated_params['s_gem'],
+ m_gem=estimated_params['m_gem'],
+ snijpunt_kar=estimated_params['snijpunt_kar'],
+ s_kar=estimated_params['s_kar'],
+ m_kar=estimated_params['m_kar']
+ )
+ print("Handmatige parameters ingesteld met geschatte waardes")
+ else:
+ # Fallback naar default waardes als geschatte parameters niet beschikbaar zijn
+ analyse.set_parameters_handmatig(
+ snijpunt_gem=0.25, s_gem=0.8, m_gem=0.9,
+ snijpunt_kar=0.20, s_kar=0.7, m_kar=0.8
+ )
+ print("Handmatige parameters ingesteld met default waardes")
+ except Exception as e:
+ print(f"Instellen handmatige parameters mislukt: {e}")
+ # Parameters kunnen afhangen van specifieke data
+ pass
+
+ # Test sutabel berekeningen (na het instellen van parameters)
+ try:
+ analyse.calculate_sutabel()
+ analyse.calculate_sutabel_nc()
+ except Exception:
+ # Sutabel berekeningen kunnen falen zonder juiste parameters
+ pass
+
+ # Test figure generatie
+ analyse.set_figure_sv_su()
+ analyse.set_figure_sv_su_nc()
+ analyse.set_figure_ln_ocr_ln_s()
+
+ # Test show figures (deze kunnen visualisatie genereren)
+ try:
+ analyse.show_figure_sv_su()
+ analyse.show_figure_sv_su_nc()
+ analyse.show_figure_ln_ocr_ln_s()
+ except Exception:
+ # Figures kunnen falen in test environment zonder display
+ pass
+
+ # Test exports
+ analyse.export_shansep_results_excel(str(export_dir / f"shansep_results_{analysis_type}.xlsx"))
+ analyse.write_analysis_to_excel(str(export_dir / f"shansep_analysis_{analysis_type}.xlsx"))
+ analyse.save_to_pdf(path=str(export_dir))
+
+
+ # Test effective stress validatie
+ try:
+ # Dit zou een ValueError moeten geven
+ invalid_analyse = SHANSEP(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='10% rek', # Niet toegestaan voor TXT_S_POP
+ analysis_type='TXT_S_POP'
+ )
+ assert False, "Verwachtte ValueError voor ongeldige effective stress combinatie"
+ except ValueError:
+ # Verwacht gedrag
+ pass
+
+ # Remove temp_folder (optioneel uitcommentariëren voor debugging)
+ # shutil.rmtree(export_dir)
+ return True
+
+
+class TestShansepAnalyse(unittest.TestCase):
+ """Unit test klasse voor SHANSEP analyse methoden."""
+
+ def test_shansep_analyse(self):
+ """Test de volledige SHANSEP analyse workflow."""
+ self.assertTrue(test_shansep_analyse())
+
+ def test_shansep_initialization(self):
+ """Test de initialisatie van SHANSEP klasse met verschillende parameters."""
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+
+ # Test geldige initialisatie
+ analyse = SHANSEP(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='15% rek',
+ analysis_type='TXT_S_POP'
+ )
+ self.assertEqual(analyse.analysis_type, 'TXT_S_POP')
+ self.assertEqual(analyse.effective_stress, '15% rek')
+ self.assertEqual(analyse.investigation_groups, ['TXT_SAFE_klei_licht_16_175'])
+ self.assertEqual(analyse.alpha, 0.75) # Default waarde
+
+ def test_invalid_effective_stress_combination(self):
+ """Test dat ongeldige combinaties van analysis_type en effective_stress een error geven."""
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+
+ # Test ongeldige combinatie: TXT_S_POP met 10% rek
+ with self.assertRaises(ValueError):
+ SHANSEP(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='10% rek',
+ analysis_type='TXT_S_POP'
+ )
+
+ # Test ongeldige combinatie: TXT_S_POP met 20% rek
+ with self.assertRaises(ValueError):
+ SHANSEP(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='20% rek',
+ analysis_type='TXT_S_POP'
+ )
+
+ def test_settings_application(self):
+ """Test het toepassen van instellingen."""
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+
+ analyse = SHANSEP(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='15% rek',
+ analysis_type='TXT_S_POP'
+ )
+
+ # Test apply_settings
+ analyse.apply_settings(alpha=0.9)
+ self.assertEqual(analyse.alpha, 0.9)
+
+ def test_estimated_parameters(self):
+ """Test het ophalen van geschatte parameters voor eerste benadering."""
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+
+ analyse = SHANSEP(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='15% rek',
+ analysis_type='TXT_S_POP'
+ )
+
+ # Apply settings and run analysis
+ analyse.apply_settings(alpha=0.75)
+ analyse._run_shansep()
+
+ # Test geschatte parameters ophalen
+ estimated_params = analyse.get_estimated_parameters()
+
+ # Controleer dat de geschatte parameters zijn opgehaald
+ self.assertIsNotNone(estimated_params)
+ self.assertIsInstance(estimated_params, dict)
+
+ # Controleer dat alle verwachte keys aanwezig zijn
+ expected_keys = ['snijpunt_gem', 's_gem', 'm_gem', 'pop_gem',
+ 'snijpunt_kar', 's_kar', 'm_kar', 'pop_kar']
+ for key in expected_keys:
+ self.assertIn(key, estimated_params)
+
+ # Controleer dat de waardes numeriek zijn (None of float)
+ for key, value in estimated_params.items():
+ self.assertTrue(value is None or isinstance(value, (int, float)),
+ f"Parameter {key} heeft ongeldige waarde: {value}")
+
+ # Test NC geschatte parameters
+ estimated_params_nc = analyse.get_estimated_parameters_nc()
+
+ self.assertIsNotNone(estimated_params_nc)
+ self.assertIsInstance(estimated_params_nc, dict)
+
+ # Controleer dat alle verwachte NC keys aanwezig zijn
+ expected_nc_keys = ['snijpunt_gem_nc', 's_gem_nc', 'm_gem_nc', 'pop_gem_nc',
+ 'snijpunt_kar_nc', 's_kar_nc', 'm_kar_nc', 'pop_kar_nc']
+ for key in expected_nc_keys:
+ self.assertIn(key, estimated_params_nc)
+
+ def test_creating_figures(self):
+ """Test het aanmaken van figuren en save_fig_html functionaliteit voor SHANSEP."""
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+
+ analyse = SHANSEP(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='15% rek',
+ analysis_type='TXT_S_POP'
+ )
+
+ # Apply settings and run analysis
+ analyse.apply_settings(alpha=0.75)
+ analyse._run_shansep()
+
+ # Test handmatige parameters (vereist voor de analyses)
+ try:
+ analyse.set_parameters_handmatig(
+ snijpunt_gem=0.25, s_gem=0.8, m_gem=0.9,
+ snijpunt_kar=0.20, s_kar=0.7, m_kar=0.8
+ )
+ except Exception:
+ # Parameters kunnen afhangen van specifieke data
+ pass
+
+ # Test dat we figuren kunnen aanmaken en opslaan
+ figure_created = False
+ html_saved = False
+
+ # Test sv-su figure
+ try:
+ analyse.show_figure_sv_su()
+ # Controleer dat figure object is aangemaakt
+ self.assertIsNotNone(analyse.figure)
+ figure_created = True
+
+ # Test save_fig_html functionaliteit
+ analyse.save_fig_html(path=str(export_dir), export_name="test_shansep_sv_su.html")
+ # Controleer dat het HTML bestand bestaat
+ html_file = export_dir / "test_shansep_sv_su.html"
+ self.assertTrue(html_file.exists(), "HTML file should be created")
+ html_saved = True
+
+ except Exception as e:
+ print(f"SHANSEP sv-su figure creation failed: {e}")
+
+ # Test ln(OCR)-ln(s) figure
+ try:
+ analyse.show_figure_ln_ocr_ln_s()
+ # Controleer dat figure object is aangemaakt
+ self.assertIsNotNone(analyse.figure)
+ figure_created = True
+
+ # Test save_fig_html functionaliteit
+ analyse.save_fig_html(path=str(export_dir), export_name="test_shansep_ln_ocr.html")
+ html_file = export_dir / "test_shansep_ln_ocr.html"
+ self.assertTrue(html_file.exists(), "HTML file should be created")
+ html_saved = True
+
+ except Exception as e:
+ print(f"SHANSEP ln(OCR)-ln(s) figure creation failed: {e}")
+
+ # Test sv-su NC figure
+ try:
+ analyse.show_figure_sv_su_nc()
+ # Controleer dat figure object is aangemaakt
+ self.assertIsNotNone(analyse.figure)
+ figure_created = True
+
+ # Test save_fig_html functionaliteit
+ analyse.save_fig_html(path=str(export_dir), export_name="test_shansep_sv_su_nc.html")
+ html_file = export_dir / "test_shansep_sv_su_nc.html"
+ self.assertTrue(html_file.exists(), "HTML file should be created")
+ html_saved = True
+
+ except Exception as e:
+ print(f"SHANSEP sv-su NC figure creation failed: {e}")
+
+ # Test dat minstens één van de figure tests is gelukt
+ if not figure_created:
+ self.skipTest("Figure creation failed for all figure types - may require specific data conditions")
+
+ # Test dat save_fig_html functionaliteit werkt
+ self.assertTrue(html_saved, "save_fig_html should successfully create HTML files")
+
+ # Test default export name functionality
+ try:
+ analyse.show_figure_sv_su()
+ analyse.save_fig_html(path=str(export_dir)) # No export_name specified
+ # Check that a file with default name pattern was created
+ html_files = list(export_dir.glob("shansep_analyse_*.html"))
+ self.assertTrue(len(html_files) > 0, "Default export name should create a file")
+ except Exception as e:
+ print(f"Default export name test failed: {e}")
+
+
+if __name__ == '__main__':
+ unittest.main()
diff --git a/pv_tool/sutabel_analysis/save_and_export.py b/pv_tool/sutabel_analysis/save_and_export.py
index 9d1d70d..0da416e 100644
--- a/pv_tool/sutabel_analysis/save_and_export.py
+++ b/pv_tool/sutabel_analysis/save_and_export.py
@@ -8,7 +8,7 @@
from typing import TYPE_CHECKING, List
from pandas import ExcelWriter, concat, DataFrame, read_excel
from datetime import datetime
-from utils import get_repo_root, make_temp_folder
+from pv_tool.utilities.utils import get_repo_root, make_temp_folder
from openpyxl import load_workbook
from reportlab.lib.pagesizes import A4, landscape
from reportlab.lib import colors
diff --git a/pv_tool/sutabel_analysis/sutabel_analysis.py b/pv_tool/sutabel_analysis/sutabel_analysis.py
index b3da24c..2ca37d6 100644
--- a/pv_tool/sutabel_analysis/sutabel_analysis.py
+++ b/pv_tool/sutabel_analysis/sutabel_analysis.py
@@ -12,6 +12,7 @@
from pv_tool.shansep_analysis.globals import (TEXTUAL_NAMES, NEW_COLUMN_NAMES, TEXTUAL_NAMES_DSS)
from pandas import DataFrame, ExcelWriter
import plotly.graph_objects as go
+from pathlib import Path
from pv_tool.shansep_analysis.calc_parameters import (
calc_watergehalte_gem_txt, calc_watergehalte_gem_dss,
calc_watergehalte_sd_txt, calc_watergehalte_sd_dss,
@@ -611,11 +612,31 @@ def show_figure_sv_su_sutabel(self, plot_extra_dataset: Optional[List] = None):
self.set_figure_sv_su_sutabel(plot_extra_dataset)
self.figure.show()
+ def save_fig_html(self, path: str, export_name: Optional[str] = None):
+ """
+ Slaat de visualisatie van de analyseresultaten op als een HTML-bestand.
+
+ NB: als de figuur leeg is, roep dan eerst show_figure_...() aan om de figuur te genereren.
+ Kies uit show_figure_ln_sv_ln_su_sutabel() of show_figure_sv_su_sutabel().
+
+ Parameters
+ ----------
+ path: str
+ Pad naar de map waar het bestand opgeslagen moet worden
+ export_name : str, optioneel
+ Naam van het HTML-bestand
+ """
+ if export_name is None:
+ export_name = f"sutabel_analyse_{self.investigation_groups[0].value.replace(' ', '_')}.html"
+ file_path = Path(path) / export_name
+ self.figure.write_html(file_path)
+ print(f"figuur opgeslagen als HTML: {file_path}")
+
# ========== Export Methodes ==========
- def add_results_to_dbase(self, path: str, file_name: str = 'Template_PVtool5_0.xlsx'):
+ def add_results_to_template(self, path: str, export_name: str = 'Template_PVtool5_0.xlsx'):
"""
- Voegt de sutabel-m analyseresultaten toe aan de database Excel-bestand.
+ Voegt de sutabel-m analyseresultaten toe aan het template Excel-bestand.
De analyse wordt automatisch uitgevoerd als deze nog niet is gedaan.
@@ -623,7 +644,7 @@ def add_results_to_dbase(self, path: str, file_name: str = 'Template_PVtool5_0.x
----------
path : str
Pad naar de map waar het Excel-bestand staat
- file_name : str
+ export_name : str
Naam van het Excel-bestand
Returns
@@ -638,8 +659,10 @@ def add_results_to_dbase(self, path: str, file_name: str = 'Template_PVtool5_0.x
if self.e_a1_sutabel is None:
self.get_sutabel_parameters()
- from pv_tool.sutabel_analysis.save_and_export import add_sutabel_results_to_dbase
- return add_sutabel_results_to_dbase(self, path, file_name)
+ from pv_tool.sutabel_analysis.save_and_export import add_results_to_template
+ return add_results_to_template(self, path, export_name)
+
+
def save_to_pdf(self, path: str, vc_fit_kar: float = None) -> str:
"""
diff --git a/pv_tool/sutabel_analysis/test_sutabel_analysis.py b/pv_tool/sutabel_analysis/test_sutabel_analysis.py
new file mode 100644
index 0000000..fb179e7
--- /dev/null
+++ b/pv_tool/sutabel_analysis/test_sutabel_analysis.py
@@ -0,0 +1,337 @@
+import os.path
+import unittest
+from pv_tool.imports.import_data import Dbase
+from pv_tool.utilities.utils import get_repo_root, make_temp_folder
+from pathlib import Path
+from pv_tool.sutabel_analysis.sutabel_analysis import SUTABEL
+import shutil
+
+FILE_PATH = os.path.join(get_repo_root(), "test_files")
+repo_root = get_repo_root()
+export_dir = make_temp_folder(
+ parent_folder=os.path.join(repo_root, "temp_exports"), add_microseconds=True
+)
+export_dir = Path(export_dir)
+
+
+def test_sutabel_analyse():
+ """
+ Test voor SUTABEL analyse. Voert een volledige SUTABEL analyse uit met verschillende analyse types.
+ Test geïmplementeerd. Verander de invoer niet.
+ """
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+ export_name = 'Template_PVtool5_0.xlsx'
+ dbase.export_dbase_to_template(export_dir=export_dir)
+
+ # Initialize analysis types voor SUTABEL
+ analysis_types = ['TXT_su_tabel', 'DSS_su_tabel']
+ effective_stresses = ['2% rek', '5% rek', '10% rek', '15% rek', '20% rek', 'pieksterkte', 'eindsterkte']
+
+ for analysis_type in analysis_types:
+ # Test met een representatieve effective stress
+ effective_stress = '15% rek'
+
+ analyse = SUTABEL(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress=effective_stress,
+ analysis_type=analysis_type
+ )
+
+ # Apply settings
+ analyse.apply_settings(alpha=0.75)
+
+ # Run de sutabel analyse
+ analyse._run_sutabel()
+
+ # Test het ophalen van data
+ analyse.get_sutabel_data()
+
+ # Test expand analysis (creates required columns)
+ try:
+ analyse.expand_analysis_df_sutabel()
+ except Exception:
+ # Expand analysis kan falen als er geen OC proeven zijn
+ pass
+
+ # Test parameters ophalen (after expand analysis)
+ try:
+ analyse.get_sutabel_parameters()
+ except Exception:
+ # Parameters kunnen afhangen van data kwaliteit
+ pass
+
+ # Test korte resultaten
+ analyse.get_short_results()
+
+ # Test manual parameters (met voorbeeldwaardes)
+ try:
+ analyse.set_manual_parameters(
+ a1_kar=0.2,
+ a2_kar=0.7,
+ vc_fit_kar=0.25
+ )
+ # Update parameters na manual input
+ analyse._update_parameters_from_manual()
+ except Exception:
+ # Manual parameters kunnen afhangen van specifieke data
+ pass
+
+ # Test sutabel grafiek berekening
+ try:
+ analyse.calculate_sutabel_grafiek()
+ except Exception:
+ # Grafiek berekening kan falen zonder juiste parameters
+ pass
+
+ # Test figure generatie
+ try:
+ analyse.set_figure_ln_sv_ln_su_sutabel()
+ analyse.set_figure_sv_su_sutabel()
+ except Exception:
+ # Figure generatie kan falen in test environment
+ pass
+
+ # Test show figures (deze kunnen visualisatie genereren)
+ try:
+ analyse.show_figure_ln_sv_ln_su_sutabel()
+ analyse.show_figure_sv_su_sutabel()
+ except Exception:
+ # Figures kunnen falen in test environment zonder display
+ pass
+
+ # Test exports
+ try:
+ analyse.write_analysis_to_excel(str(export_dir / f"sutabel_analysis_{analysis_type}.xlsx"))
+ analyse.save_to_pdf(path=str(export_dir))
+ except Exception:
+ # Export kan falen als parameters niet volledig zijn
+ pass
+
+ # Test results to template
+ try:
+ analyse.add_results_to_template(path=str(export_dir), export_name=export_name)
+ except Exception:
+ # Results to template kan falen als parameters ontbreken
+ pass
+
+ # Remove temp_folder (optioneel uitcommentariëren voor debugging)
+ # shutil.rmtree(export_dir)
+ return True
+
+
+class TestSutabelAnalyse(unittest.TestCase):
+ """Unit test klasse voor SUTABEL analyse methoden."""
+
+ def test_sutabel_analyse(self):
+ """Test de volledige SUTABEL analyse workflow."""
+ self.assertTrue(test_sutabel_analyse())
+
+ def test_sutabel_initialization(self):
+ """Test de initialisatie van SUTABEL klasse met verschillende parameters."""
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+
+ # Test geldige initialisatie voor TXT
+ analyse_txt = SUTABEL(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='15% rek',
+ analysis_type='TXT_su_tabel'
+ )
+ self.assertEqual(analyse_txt.analysis_type, 'TXT_su_tabel')
+ self.assertEqual(analyse_txt.effective_stress, '15% rek')
+ self.assertEqual(analyse_txt.investigation_groups, ['TXT_SAFE_klei_licht_16_175'])
+ self.assertEqual(analyse_txt.alpha, 0.75) # Default waarde
+
+ # Test geldige initialisatie voor DSS
+ analyse_dss = SUTABEL(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='10% rek',
+ analysis_type='DSS_su_tabel'
+ )
+ self.assertEqual(analyse_dss.analysis_type, 'DSS_su_tabel')
+ self.assertEqual(analyse_dss.effective_stress, '10% rek')
+
+ def test_settings_application(self):
+ """Test het toepassen van instellingen."""
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+
+ analyse = SUTABEL(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='15% rek',
+ analysis_type='TXT_su_tabel'
+ )
+
+ # Test apply_settings
+ analyse.apply_settings(alpha=0.9)
+ self.assertEqual(analyse.alpha, 0.9)
+
+ # Test terug naar default
+ analyse.apply_settings(alpha=1.0)
+ self.assertEqual(analyse.alpha, 1.0)
+
+ def test_data_retrieval_methods(self):
+ """Test de data ophaal methoden."""
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+
+ analyse = SUTABEL(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='15% rek',
+ analysis_type='TXT_su_tabel'
+ )
+
+ # Test get_sutabel_data (sets instance variables)
+ analyse.get_sutabel_data()
+ # Controleer of data is opgehaald
+ self.assertIsNotNone(analyse.sutabel_data_df)
+ self.assertIsNotNone(analyse.total_sutabel_data_df)
+
+ # Test _run_sutabel
+ analyse._run_sutabel()
+ self.assertIsNotNone(analyse.sutabel_data_df)
+
+ def test_manual_parameters_setting(self):
+ """Test het handmatig instellen van parameters."""
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+
+ analyse = SUTABEL(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='15% rek',
+ analysis_type='TXT_su_tabel'
+ )
+
+ # Run analyse eerst
+ analyse._run_sutabel()
+
+ # Test manual parameters instellen
+ try:
+ analyse.set_manual_parameters(
+ a1_kar=0.2,
+ a2_kar=0.7,
+ vc_fit_kar=0.25
+ )
+
+ # Controleer of parameters zijn ingesteld
+ self.assertEqual(analyse.a1_kar_handmatig, 0.2)
+ self.assertEqual(analyse.a2_kar_handmatig, 0.7)
+ self.assertEqual(analyse.vc_fit_kar_handmatig, 0.25)
+ self.assertTrue(analyse.parameters_handmatig)
+
+ except AttributeError:
+ # Sommige attributen kunnen afhangen van specifieke data
+ self.skipTest("Manual parameters require specific data structure")
+
+ def test_parameter_calculation(self):
+ """Test parameter berekening methoden."""
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+
+ analyse = SUTABEL(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='15% rek',
+ analysis_type='TXT_su_tabel'
+ )
+
+ # Run analyse eerst
+ analyse._run_sutabel()
+
+ # Test parameter berekening
+ try:
+ analyse.get_sutabel_parameters()
+ # Controleer of basis parameters zijn berekend
+ self.assertIsNotNone(analyse.watergehalte_gem)
+ self.assertIsNotNone(analyse.watergehalte_sd)
+ except Exception:
+ # Parameter berekening kan afhangen van data kwaliteit
+ self.skipTest("Parameter calculation requires valid data")
+
+ def test_creating_figures(self):
+ """Test het aanmaken van figuren en save_fig_html functionaliteit."""
+ dbase = Dbase()
+ source_dir = Path(os.path.join(FILE_PATH, "Dbase.xlsx"))
+ dbase.import_data(source="Dbase", source_dir=source_dir)
+
+ analyse = SUTABEL(
+ dbase=dbase,
+ investigation_groups=['TXT_SAFE_klei_licht_16_175'],
+ effective_stress='15% rek',
+ analysis_type='TXT_su_tabel'
+ )
+
+ # Run analyse eerst
+ analyse._run_sutabel()
+
+ # Test dat we een figure kunnen aanmaken en opslaan
+ figure_created = False
+ html_saved = False
+
+ # Test ln(sv) vs ln(su) figure
+ try:
+ analyse.show_figure_ln_sv_ln_su_sutabel()
+ # Controleer dat figure object is aangemaakt
+ self.assertIsNotNone(analyse.figure)
+ figure_created = True
+
+ # Test save_fig_html functionaliteit
+ analyse.save_fig_html(path=str(export_dir), export_name="test_sutabel_ln_figure.html")
+ # Controleer dat het HTML bestand bestaat
+ html_file = export_dir / "test_sutabel_ln_figure.html"
+ self.assertTrue(html_file.exists(), "HTML file should be created")
+ html_saved = True
+
+ except Exception as e:
+ print(f"ln(sv) vs ln(su) figure creation failed: {e}")
+
+ # Test sv vs su figure
+ try:
+ analyse.show_figure_sv_su_sutabel()
+ # Controleer dat figure object is aangemaakt
+ self.assertIsNotNone(analyse.figure)
+ figure_created = True
+
+ # Test save_fig_html functionaliteit
+ analyse.save_fig_html(path=str(export_dir), export_name="test_sutabel_sv_figure.html")
+ # Controleer dat het HTML bestand bestaat
+ html_file = export_dir / "test_sutabel_sv_figure.html"
+ self.assertTrue(html_file.exists(), "HTML file should be created")
+ html_saved = True
+
+ except Exception as e:
+ print(f"sv vs su figure creation failed: {e}")
+
+ # Test dat minstens één van de figure tests is gelukt
+ if not figure_created:
+ self.skipTest("Figure creation failed for both figure types - may require specific data conditions")
+
+ # Test dat save_fig_html functionaliteit werkt
+ self.assertTrue(html_saved, "save_fig_html should successfully create HTML files")
+
+ # Test default export name functionality
+ try:
+ analyse.show_figure_sv_su_sutabel()
+ analyse.save_fig_html(path=str(export_dir)) # No export_name specified
+ # Check that a file with default name pattern was created
+ html_files = list(export_dir.glob("sutabel_analyse_*.html"))
+ self.assertTrue(len(html_files) > 0, "Default export name should create a file")
+ except Exception as e:
+ print(f"Default export name test failed: {e}")
+
+
+if __name__ == '__main__':
+ unittest.main()
diff --git a/pv_tool/utilities/__init__.py b/pv_tool/utilities/__init__.py
new file mode 100644
index 0000000..ae09443
--- /dev/null
+++ b/pv_tool/utilities/__init__.py
@@ -0,0 +1,20 @@
+"""
+Utilities Module
+
+Deze module bevat algemene utility functies en widget functionaliteit
+voor de PV-tool applicatie.
+
+Modules:
+ utils: Algemene utility functies voor bestandsbeheer en git operaties
+ widget_functions: Widget functies voor interactieve Jupyter notebook gebruik
+"""
+
+from pv_tool.utilities.utils import get_repo_root, make_temp_folder
+
+# Note: widget_functions imports are available but not exposed here to avoid circular imports
+# Import directly from pv_tool.utilities.widget_functions when needed
+
+__all__ = [
+ 'get_repo_root',
+ 'make_temp_folder',
+]
diff --git a/utils.py b/pv_tool/utilities/utils.py
similarity index 100%
rename from utils.py
rename to pv_tool/utilities/utils.py
diff --git a/widgetfunctie_cphi.py b/pv_tool/utilities/widget_functions.py
similarity index 100%
rename from widgetfunctie_cphi.py
rename to pv_tool/utilities/widget_functions.py
diff --git a/requirements.txt b/requirements.txt
index 62e2f47..8a9c796 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -23,5 +23,3 @@ ipywidgets
ipython
ipyfilechooser
-#TODO moet jupyter notebook zelf ook in de requirements? Dan wordt die met een wheel meteen mee geinstalleerd
-