Tutorial 51: Manual Creation of Element Dataframes

This Example demonstrates the capabilities of the class Dataframes_SIR3S_Model that extends SIR3S_Model be abilities to work directley with pandas dataframes. It is shown how to create dataframes containing information about elements such as Nodes, Pipes, etc. existing in a SIR 3S Model. The methods presented are manual, user-defined and detailed. For creating more general dataframes with less input necessary, see Tutorial 52.

Toolkit Release

#pip install

Imports

SIR 3S Toolkit

Regular Import/Init

SIR3S_SIRGRAF_DIR = r"C:\3S\SIR 3S\SirGraf-90-15-00-24_Quebec-Upd2" #change to local path

from sir3stoolkit.core import wrapper

wrapper

<module 'sir3stoolkit.core.wrapper' from 'C:\\Users\\aUsername\\3S\\sir3stoolkit\\src\\sir3stoolkit\\core\\wrapper.py'>

wrapper.Initialize_Toolkit(SIR3S_SIRGRAF_DIR)

Additional Import/Init for Dataframes class

from sir3stoolkit.mantle.dataframes import SIR3S_Model_Dataframes

s3s = SIR3S_Model_Dataframes()

Initialization complete

Additional

import pandas as pd
from shapely.geometry import Point
import re
import folium
from folium.plugins import HeatMap
import numpy as np
import geopandas as gpd
from shapely import wkt
import matplotlib.pyplot as plt
import contextily as cx

Open Model

s3s.OpenModel(dbName=r"Toolkit_Tutorial51_Model.db3",
              providerType=s3s.ProviderTypes.SQLite,
              Mid="M-1-0-1",
              saveCurrentlyOpenModel=False,
              namedInstance="",
              userID="",
              password="")

Model is open for further operation

Calculate Model

s3s.ExecCalculation(True) # To ensure result data

Model Calculation is complete

Manual Dataframe creation

model_data - Nodes

We can use the generate_element_model_data_dataframe() method to obtain a dataframe for all instances of a specifc component type (Nodes, Pipes, etc.) with user defined model_data properties (all non-result data related to a component) to be added. For this example we will use nodes.

In this case we are interested in Nodes, let’s check what model_data properties are available for this element.

s3s.GetPropertiesofElementType(s3s.ObjectTypes.Node)

['Name',
 'Ktyp',
 'Zkor',
 'QmEin',
 'Lfakt',
 'Fkpzon',
 'Fkfstf',
 'Fkutmp',
 'Fkfqps',
 'Fkcont',
 'Fk2lknot',
 'Beschreibung',
 'Idreferenz',
 'Iplanung',
 'Kvr',
 'Qakt',
 'Xkor',
 'Ykor',
 'NodeNamePosition',
 'ShowNodeName',
 'KvrKlartext',
 'NumberOfVERB',
 'HasBlockConnection',
 'Tk',
 'Pk',
 'InVariant',
 'GeometriesDiffer',
 'SymbolFactor',
 'bz.Drakonz',
 'bz.Fk',
 'bz.Fkpvar',
 'bz.Fkqvar',
 'bz.Fklfkt',
 'bz.PhEin',
 'bz.Tm',
 'bz.Te',
 'bz.PhMin']

In the below subcases differnt choices of parameters for creating the model_data dataframe manually are shown. Note that not all possible combination of paramters are shown here.

Subcase 1: Minimal

Let’s say for now we only want a dataframe with all node tks without any related data.

(s3s.generate_element_model_data_dataframe(element_type=s3s.ObjectTypes.Node
                                        ,properties=[]
                                        )).head(3)

[2026-03-15 23:20:14,271] INFO in sir3stoolkit.mantle.dataframes: [model_data] Generating model_data dataframe for element type: ObjectTypes.Node
[2026-03-15 23:20:14,275] INFO in sir3stoolkit.mantle.dataframes: [model_data] Retrieved 517 element(s) of element type ObjectTypes.Node.
[2026-03-15 23:20:14,290] INFO in sir3stoolkit.mantle.dataframes: [Resolving model_data Properties] Using 0 model_data properties.
[2026-03-15 23:20:14,291] INFO in sir3stoolkit.mantle.dataframes: [model_data] Retrieving ...
[2026-03-15 23:20:14,293] INFO in sir3stoolkit.mantle.dataframes: [model_data] Done. Shape: (517, 1)

	tk
0	5669301360686511351
1	5397948523091900401
2	5239335112004772156

Subcase 2: Specific Properties

Let’s say we now want the minimal dataframe extended with supply/return info (kvr) and height (Zkor) of the nodes.

(s3s.generate_element_model_data_dataframe(element_type=s3s.ObjectTypes.Node
                                        ,properties=["Kvr", "Zkor"]
                                        )).head(3)

[2026-03-15 23:20:14,314] INFO in sir3stoolkit.mantle.dataframes: [model_data] Generating model_data dataframe for element type: ObjectTypes.Node
[2026-03-15 23:20:14,316] INFO in sir3stoolkit.mantle.dataframes: [model_data] Retrieved 517 element(s) of element type ObjectTypes.Node.
[2026-03-15 23:20:14,319] INFO in sir3stoolkit.mantle.dataframes: [Resolving model_data Properties] Using 2 model_data properties.
[2026-03-15 23:20:14,320] INFO in sir3stoolkit.mantle.dataframes: [model_data] Retrieving model_data properties ['Kvr', 'Zkor']...
[2026-03-15 23:20:14,359] INFO in sir3stoolkit.mantle.dataframes: [model_data] Done. Shape: (517, 3)

	tk	Kvr	Zkor
0	5669301360686511351	1	554.04
1	5397948523091900401	1	556.16
2	5239335112004772156	1	561.01

Subcase 3: Maximal

Let’s say now we want basically all available model_data (non-result data) related to nodes.

If geometry=True, the 2D Point geometry will be added for Nodes and it will be attempted to transform the DataFrame into a GeoDataFrame using the SRID (eg. EPSG: 25832) defined in the model. If no SRID is defined, the DataFrame will remain as a DataFrame, but the geometry column with be added nonetheless.

(s3s.generate_element_model_data_dataframe(element_type=s3s.ObjectTypes.Node
                                        ,properties=None # Instead of an empty or filled list, we pass None to indicate we want all available properties
                                        ,geometry=True # geometry data has to be explicitly requested
                                        )).head(3)

[2026-03-15 23:20:14,395] INFO in sir3stoolkit.mantle.dataframes: [model_data] Generating model_data dataframe for element type: ObjectTypes.Node
[2026-03-15 23:20:14,398] INFO in sir3stoolkit.mantle.dataframes: [model_data] Retrieved 517 element(s) of element type ObjectTypes.Node.
[2026-03-15 23:20:14,401] INFO in sir3stoolkit.mantle.dataframes: [Resolving model_data Properties] No properties given → using ALL model_data properties for ObjectTypes.Node.
[2026-03-15 23:20:14,402] INFO in sir3stoolkit.mantle.dataframes: [Resolving model_data Properties] Using 37 model_data properties.
[2026-03-15 23:20:14,403] INFO in sir3stoolkit.mantle.dataframes: [model_data] Retrieving model_data properties ['Name', 'Ktyp', 'Zkor', 'QmEin', 'Lfakt', 'Fkpzon', 'Fkfstf', 'Fkutmp', 'Fkfqps', 'Fkcont', 'Fk2lknot', 'Beschreibung', 'Idreferenz', 'Iplanung', 'Kvr', 'Qakt', 'Xkor', 'Ykor', 'NodeNamePosition', 'ShowNodeName', 'KvrKlartext', 'NumberOfVERB', 'HasBlockConnection', 'Tk', 'Pk', 'InVariant', 'GeometriesDiffer', 'SymbolFactor', 'bz.Drakonz', 'bz.Fk', 'bz.Fkpvar', 'bz.Fkqvar', 'bz.Fklfkt', 'bz.PhEin', 'bz.Tm', 'bz.Te', 'bz.PhMin'], geometry...
[2026-03-15 23:20:15,669] INFO in sir3stoolkit.mantle.dataframes: [model_data] Transforming DataFrame to GeoDataFrame successful with EPSG: 25832
[2026-03-15 23:20:15,670] INFO in sir3stoolkit.mantle.dataframes: [model_data] Done. Shape: (517, 39)

	tk	Name	Ktyp	Zkor	QmEin	Lfakt	Fkpzon	Fkfstf	Fkutmp	Fkfqps	Fkcont	Fk2lknot	Beschreibung	Idreferenz	Iplanung	Kvr	Qakt	Xkor	Ykor	NodeNamePosition	ShowNodeName	KvrKlartext	NumberOfVERB	HasBlockConnection	Tk	Pk	InVariant	GeometriesDiffer	SymbolFactor	bz.Drakonz	bz.Fk	bz.Fkpvar	bz.Fkqvar	bz.Fklfkt	bz.PhEin	bz.Tm	bz.Te	bz.PhMin	geometry
0	5669301360686511351	V-K03S	QKON	554.04	0	1	5520728169779652386	4798673252636751115	5591325053703727727	-1	5029128874972463118	5761544923588724980	Abzw. Am Sonnenbühl	3S3768E2953006F125B34916F6A1681667	1	1	0	713620.267807	5.578828e+06	1	False	Vorlauf	0	False	5669301360686511351	5669301360686511351	False	False	0.2	0	5669301360686511351	-1	-1	-1	0	0	0	0	POINT (713620.268 5578828.419)
1	5397948523091900401	V-K13S	QKON	556.16	0	1	5520728169779652386	4798673252636751115	5591325053703727727	-1	5029128874972463118	4749864932928780363	Anfangsknoten generiert von SirDB	3SC30ED954AA2F1D59B1F92FFEBCCB7B5B	1	1	0	713602.294600	5.578860e+06	1	False	Vorlauf	0	False	5397948523091900401	5397948523091900401	False	False	0.2	0	5397948523091900401	-1	-1	-1	0	0	0	0	POINT (713602.295 5578860.106)
2	5239335112004772156	V-K23S	QKON	561.01	0	1	5520728169779652386	4798673252636751115	5591325053703727727	-1	5029128874972463118	4899862460906451371	Anfangsknoten generiert von SirDB	3SC30ED954AA2F1D59B1F92FFEBCCB7B5B	1	1	0	713574.061627	5.578910e+06	1	False	Vorlauf	0	False	5239335112004772156	5239335112004772156	False	False	0.2	0	5239335112004772156	-1	-1	-1	0	0	0	0	POINT (713574.062 5578909.873)

Subcase 4: Filtering + Element Type Col

Let’s say we only want nodes inside a specific container and we also want to have an element type col adding “Node” to each row (useful when joining with other dataframes later).

for container_id in (s3s.GetTksofElementType(s3s.ObjectTypes.ObjectContainerSymbol)):
    print(f"{container_id}: {s3s.GetValue(container_id, 'Name')[0]}")

5029128874972463118: M-1-0-1
5027846505677995694: Erzeugung
5172832702839270493: TS
5152808213068069018: Laststeuerung
5467315850619588583: Sekundärwerte
5320319133990336755: Netztrennung

all_tks = s3s.GetTksofElementType(s3s.ObjectTypes.Node)

good_tks = []

for tk in all_tks:
    if s3s.GetValue(tk, "FkCont") == "5029128874972463118": # Main container
        if s3s.GetValue(tk, "Kvr")[0] == "1": # Supply/Vorlauf
            good_tks.append(tk)

(s3s.generate_element_model_data_dataframe(element_type=s3s.ObjectTypes.Node
                                        ,properties=[]
                                        ,tks=good_tks
                                        ,geometry=True
                                        ,element_type_col=True
                                        )).head(3)

[2026-03-15 23:20:15,768] INFO in sir3stoolkit.mantle.dataframes: [model_data] Generating model_data dataframe for element type: ObjectTypes.Node
[2026-03-15 23:20:15,770] INFO in sir3stoolkit.mantle.dataframes: [model_data] Retrieved 517 element(s) of element type ObjectTypes.Node.
[2026-03-15 23:20:15,773] INFO in sir3stoolkit.mantle.dataframes: [Resolving model_data Properties] Using 0 model_data properties.
[2026-03-15 23:20:15,774] INFO in sir3stoolkit.mantle.dataframes: [model_data] Retrieving geometry...
[2026-03-15 23:20:15,812] INFO in sir3stoolkit.mantle.dataframes: [model_data] Transforming DataFrame to GeoDataFrame successful with EPSG: 25832
[2026-03-15 23:20:15,814] INFO in sir3stoolkit.mantle.dataframes: [model_data] Done. Shape: (517, 3)

	tk	geometry	element type
0	5669301360686511351	POINT (713620.268 5578828.419)	Node
1	5397948523091900401	POINT (713602.295 5578860.106)	Node
2	5239335112004772156	POINT (713574.062 5578909.873)	Node

Result Data - Pipes

We can use the generate_element_model_data_dataframe() method to obtain a dataframe for all instances of a specifc component type (Nodes, Pipes, etc.) with user defined result values for certain timestamps to be added. For this example we will use pipes.

Let’s check what result properties are available for Pipes.

s3s.GetResultProperties_from_elementType(elementType=s3s.ObjectTypes.Pipe
                                         ,onlySelectedVectors=False
                                         )

['A',
 'ACALC',
 'CPI',
 'CPK',
 'DH',
 'DP',
 'DRAGRED',
 'DRAKONZ',
 'DSI',
 'DSK',
 'DTTR',
 'DWVERL',
 'DWVERLABS',
 'ETAAV',
 'FS',
 'HR',
 'HVEC',
 'IAKTIV',
 'IRTRENN',
 'JV',
 'JV2',
 'LAMBDA',
 'LECKEINAUS',
 'LECKMENGE',
 'LECKORT',
 'LINEPACK',
 'LINEPACKGEOM',
 'LINEPACKRATE',
 'MAINELEMENT',
 'MAV',
 'MI',
 'MK',
 'MKOND',
 'MMAX_INST',
 'MMIN_INST',
 'MVEC',
 'MVECMAX_INST',
 'MVECMIN_INST',
 'PAV',
 'PDAMPF',
 'PHR',
 'PHVEC',
 'PMAX',
 'PMIN',
 'PR',
 'PVEC',
 'PVECMAX_INST',
 'PVECMIN_INST',
 'QI2',
 'QK2',
 'QMAV',
 'QMI',
 'QMK',
 'QMMAX_INST',
 'QMMIN_INST',
 'QMVEC',
 'QSVB',
 'RHOAV',
 'RHOI',
 'RHOK',
 'RHOVEC',
 'SVEC',
 'TAV',
 'TI',
 'TK',
 'TTRVEC',
 'TVEC',
 'TVECMAX_INST',
 'TVECMIN_INST',
 'VAV',
 'VI',
 'VK',
 'VMAX_INST',
 'VMIN_INST',
 'VOLDA',
 'WALTERI',
 'WALTERK',
 'WVL',
 'ZAUS',
 'ZEIN',
 'ZHKNR',
 'ZVEC']

Let’s also check what simulation timestamps are available in the model.

s3s.GetTimeStamps()[0] # list of simulation timestamps

['2023-02-13 00:00:00.000 +01:00',
 '2023-02-13 01:00:00.000 +01:00',
 '2023-02-13 02:00:00.000 +01:00',
 '2023-02-13 03:00:00.000 +01:00',
 '2023-02-13 04:00:00.000 +01:00',
 '2023-02-13 05:00:00.000 +01:00',
 '2023-02-13 06:00:00.000 +01:00',
 '2023-02-13 07:00:00.000 +01:00',
 '2023-02-13 08:00:00.000 +01:00',
 '2023-02-13 09:00:00.000 +01:00',
 '2023-02-13 10:00:00.000 +01:00',
 '2023-02-13 11:00:00.000 +01:00',
 '2023-02-13 12:00:00.000 +01:00',
 '2023-02-13 13:00:00.000 +01:00',
 '2023-02-13 14:00:00.000 +01:00',
 '2023-02-13 15:00:00.000 +01:00',
 '2023-02-13 16:00:00.000 +01:00',
 '2023-02-13 17:00:00.000 +01:00',
 '2023-02-13 18:00:00.000 +01:00',
 '2023-02-13 19:00:00.000 +01:00',
 '2023-02-13 20:00:00.000 +01:00',
 '2023-02-13 21:00:00.000 +01:00',
 '2023-02-13 22:00:00.000 +01:00',
 '2023-02-13 23:00:00.000 +01:00',
 '2023-02-14 00:00:00.000 +01:00']

s3s.GetTimeStamps()[1] # Static

'2023-02-13 00:00:00.000 +01:00'

In the below subcases differnt choices of parameters for creating the result dataframe manually are shown. Note that not all possible combination of paramters are shown here.

Subcase 1: Static + All Result Values

(s3s.generate_element_results_dataframe(element_type=s3s.ObjectTypes.Pipe
                                        ,properties=None # None => All available properties
                                        ,timestamps=[s3s.GetTimeStamps()[1]] # static
                                        )).head(3)

[2026-03-15 23:20:16,103] INFO in sir3stoolkit.mantle.dataframes: [results] Generating results dataframe for element type: ObjectTypes.Pipe
[2026-03-15 23:20:16,170] INFO in sir3stoolkit.mantle.dataframes: [Resolving Timestamps] Only static timestamp 2023-02-13 00:00:00.000 +01:00 is used
[2026-03-15 23:20:16,170] INFO in sir3stoolkit.mantle.dataframes: [Resolving Timestamps] 1 valid timestamp(s) will be used.
[2026-03-15 23:20:16,171] INFO in sir3stoolkit.mantle.dataframes: [Resolving tks] Retrieved 524 element(s) of element type ObjectTypes.Pipe.
[2026-03-15 23:20:16,173] INFO in sir3stoolkit.mantle.dataframes: [results] No properties given → using ALL result properties for ObjectTypes.Pipe.
[2026-03-15 23:20:16,174] INFO in sir3stoolkit.mantle.dataframes: [results] Using 82 result properties.
[2026-03-15 23:20:16,290] INFO in sir3stoolkit.mantle.dataframes: [results] Retrieving result values...
[2026-03-15 23:20:21,317] INFO in sir3stoolkit.mantle.dataframes: [results] 26724 fully NaN columns dropped.
[2026-03-15 23:20:24,156] INFO in sir3stoolkit.mantle.dataframes: [results] Done. Shape: (1, 16244)

tk	5442010239090746007																															4917786378639043296																															4762482310382009633																															4987229536643024523																															5722206630503885118																															5089459212485379804																															5526871502288882655																															4809089329099085219																															5170001087020228683																															5625716875961234775																															5501916898830363065																															5192970129555982907																															5027225217797463802																															5107343838750080243																															4840056338230495043																...	5269134948859572308																5491353045770208506																															5351083508550202918																															5405503540588733856																															5409157591891833907																															5288551187767515760																															5273136311620767333																															5331559348183931626																															5263881428814102490																															5139154449387664728																															4919408196640282331																															4957957828740199285																															5499776682108862751																															5285235772707481262																															5373158549695106826
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timestamp
2023-02-13 00:00:00.000 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086e-26	1.304095	1.34039\t1.32829\t1.316195\t1.304095	1.34039\t1.32829\t1.316195\t1.304095	1.34039\t1.32829\t1.316195\t1.304095	-1.440640e-10	-1.440640e-10	-1.440640e-10	1000.3	1000.3	1000.3\t1000.3\t1000.3\t1000.3	0\t8.404923\t16.80985\t25.21477	9.999994	9.999994	38.70423\t30.2993\t21.89438\t13.48946	10\t10\t10\t10	-5.155371e-14	-5.155371e-14	-5.155371e-14	0.0	0.0	547.89\t548.0134\t548.1367\t548.26	0.0	13.48946	0.0	0.0	1.0	0.0	6.260403e-24	-1.082299E-10\t-1.082299E-10\t-1.082299E-10	0.0123	8.444945e-26	1.288402	1.304095\t1.29625\t1.2884	1.304095\t1.29625\t1.2884	1.304095\t1.29625\t1.2884	-3.896275e-10	-3.896275e-10	-3.896275e-10	1000.3	1000.3	1000.3\t1000.3\t1000.3	0\t6.74473\t13.48946	9.999994	9.999994	13.48946\t6.74473\t0	10\t10\t10	-1.394293e-13	-1.394293e-13	-1.394293e-13	0.0	0.0	548.26\t548.34\t548.42	0.0	8.799599	0.0	0.0	1.0	0.0	0.0	0\t0	0.0123	0.0	1.266818	1.2884\t1.26682	1.2884\t1.26682	1.2884\t1.26682	0.0	0.0	0.0	1000.3	1000.3	1000.3\t1000.3	0\t8.799599	9.999994	9.999994	14.20205\t14.20205	10\t10	0.0	0.0	0.0	0.0	0.0	548.42\t548.64	0.0	11.09779	0.0	0.0	1.0	0.0	7.702934e-24	-1.200533E-10\t-1.200533E-10\t-1.200533E-10	0.0123	8.548555e-26	1.215812	1.26682\t1.241315\t1.21581	1.26682\t1.241315\t1.21581	1.26682\t1.241315\t1.21581	-4.321919e-10	-4.321919e-10	-4.321919e-10	1000.3	1000.3	1000.3\t1000.3\t1000.3	0\t5.548895\t11.09779	9.999994	9.999994	11.09779\t5.548895\t0	10\t10\t10	-1.546611e-13	-1.546611e-13	-1.546611e-13	0.0	0.0	548.64\t548.9\t549.16	0.0	26.07811	0.0	0.0	1.0	0.0	0.0	0\t0\t0\t0	0.0123	0.0	1.107903	1.21581\t1.179845\t1.143875\t1.107905	1.21581\t1.179845\t1.143875\t1.107905	1.21581\t1.179845\t1.143875\t1.107905	0.0	0.0	0.0	1000.3	1000.3	1000.3\t1000.3\t1000.3\t1000.3	0\t8.692703\t17.38541\t26.07811	9.999994	9.999994	80.36217\t80.36217\t80.36217\t80.36217	10\t10\t10\t10	0.0	0.0	0.0	0.0	0.0	549.16\t549.5267\t549.8933\t550.26	0.0	17.34526	0.0	0.0	1.0	0.0	0.0	0\t0\t0	0.0123	0.0	1.383552	1.638605\t1.51108\t1.38355	1.638605\t1.51108\t1.38355	1.638605\t1.51108\t1.38355	0.0	0.0	0.0	1000.3	1000.3	1000.3\t1000.3\t1000.3	0\t8.67263\t17.34526	9.999994	9.999994	2.653971E+07\t2.653971E+07\t2.653971E+07	10\t10\t10	0.0	0.0	0.0	0.0	0.0	544.85\t546.15\t547.45	0.0	20.64109	0.0	0.0	1.0	0.0	1.018570e-24	-4.365575E-11\t-4.365575E-11\t-4.365575E-11\t-...	0.0123	2.102439e-26	1.068668	1.38355\t1.27859\t1.17363\t1.06867	1.38355\t1.27859\t1.17363\t1.06867	1.38355\t1.27859\t1.17363\t1.06867	-1.571607e-10	-1.571607e-10	-1.571607e-10	1000.3	1000.3	1000.3\t1000.3\t1000.3\t1000.3	0\t6.880363\t13.76073\t20.64109	9.999994	9.999994	20.64109\t13.76073\t6.880363\t0	10\t10\t10\t10	-5.624041e-14	-5.624041e-14	-5.624041e-14	0.0	0.0	547.45\t548.52\t549.59\t550.66	0.0	0.002894	22.78418	0.227842	0.0	0.0	0.757062	8.40759\t8.40759	0.473539	0.007571	4.839626	4.839625\t4.8454	4.839625\t4.8454	4.839625\t4.8454	30.26732	30.26732	30.26732	972.2	972.2039	972.2\t972.2039	0\t10	79.99999	79.99355	0\t0.002893685	80\t79.99356	0.959945	0.959947	0.959943	0.0	708.3129	546.23\t546.09	0.0	0.002928	16.21576	0.162158	0.0	0.0	0.765799	-8.407589\t-8.407589	0.198149	0.007658	3.981986	3.981985\t3.997365	3.981985\t3.997365	3.981985\t3.997365	-30.26732	-30.26732	-30.26732	983.7596	983.7573	983.7596\t983.7573	0\t10	59.88087	59.88548	0.04499983\t0.04207175	59.88086\t59.8855	-0.948668	-0.948667	-0.948669	0.0	0.0	546.26\t546.18

1 rows × 16244 columns

Note that a multi index on the columns is created, holding the most important model_data.

• Level 0: tk (device ID)

• Level 1: name (device name)

• Level 2: end_nodes (tuple of connected node IDs as string)

• Level 3: property (result name)

As can be seen a lot of 99999.0 placeholder values are inserted, because we attempt to access many result values that SIR Calc can calculate but are not requested for this model. Therefore using all available result properties(properties=None), is generally not recommended.

Subcase 2: All Timestamps + Specific Values

df_pipes_2 = s3s.generate_element_results_dataframe(element_type=s3s.ObjectTypes.Pipe
                                                    ,properties=["DTTR", "PHR"] # Specify result properties of interest
                                                    ,timestamps=None # None => All available simulation timestamps
                                                    )

[2026-03-15 23:20:24,906] INFO in sir3stoolkit.mantle.dataframes: [results] Generating results dataframe for element type: ObjectTypes.Pipe
[2026-03-15 23:20:24,912] INFO in sir3stoolkit.mantle.dataframes: [Resolving Timestamps] No timestamps were given. Checking available simulation timestamps (SIR3S_Model.GetTimeStamps()[0]).
[2026-03-15 23:20:25,032] INFO in sir3stoolkit.mantle.dataframes: [Resolving Timestamps] 25 simulation timestamp(s) are available.
[2026-03-15 23:20:25,121] INFO in sir3stoolkit.mantle.dataframes: [Resolving Timestamps] 25 valid timestamp(s) will be used.
[2026-03-15 23:20:25,122] INFO in sir3stoolkit.mantle.dataframes: [Resolving tks] Retrieved 524 element(s) of element type ObjectTypes.Pipe.
[2026-03-15 23:20:25,125] INFO in sir3stoolkit.mantle.dataframes: [results] Using 2 result properties.
[2026-03-15 23:20:25,150] INFO in sir3stoolkit.mantle.dataframes: [results] Retrieving result values...
[2026-03-15 23:20:29,331] INFO in sir3stoolkit.mantle.dataframes: [results] 0 fully NaN columns dropped.
[2026-03-15 23:20:29,499] INFO in sir3stoolkit.mantle.dataframes: [results] Done. Shape: (25, 1048)

df_pipes_2.head(3)

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timestamp
2023-02-13 00:00:00.000 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2023-02-13 01:00:00.000 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4	0.011039	0.005319	0.0116	0.005589	0.020583	0.009917	0.016737	0.008065	0.0159	0.007661	35.89539	3.313088e-26	72.46398	3.332966e-25	71.66468	0.0	49.03616	3.333252e-25	54.56744	0.0	92.76953	0.0	0.023111	0.011893	0.019357	0.009632	0.018318	0.009675	0.028447	0.019632	0.005504	0.00211	0.00434	0.001664	0.005004	0.001918	0.006498	0.001853	0.021653	0.018858	0.006376	0.003339	0.002393	0.003292	0.001055	0.001452	0.001503	0.002068	0.007957	0.01258	0.041119	0.012034	0.023626	0.010705	0.005816	0.003685	0.003218	0.002804	0.003273	0.002852	0.00291	0.000911	0.003892	0.001605	0.043215	0.025172	0.042147	0.01164	0.013968	0.002407	0.033753	0.015579	0.084669	0.047416	0.030686	0.007475	0.003897	0.003118	0.002824	0.002259	0.003437	0.001983	0.029106	0.012807	76.11499	0.0	0.046102	0.021898	0.203459	0.005518	0.002682	0.000223	0.00444	0.000369	0.022085	0.001836	0.018817	0.002239	0.004516	0.00075	0.004254	0.000169	0.167143	0.003845	0.001902	0.000929	0.015718	0.015831	0.00178	0.000822	0.001841	0.00085	0.002803	0.000685	0.014642	0.003579	0.027562	0.002526	0.035425	0.007734	0.077527	0.023833	0.027558	0.025218	0.034402	0.005777	0.009633	0.014163	0.012929	0.010933	0.004087	0.01382	0.005108	0.011797	0.005289	0.006377	0.006334	0.006964	0.004437	0.007617	0.004207	0.007222	0.006515	0.005366	0.023215	0.015846	0.010218	0.006975	0.038396	0.006148	22.46283	7.871059e-26	11.13411	3.361424e-25	18.74616	3.296165e-25	27.98768	3.370467e-25	32.47894	8.594241e-26	63.81877	0.0	0.032964	0.015184	0.027192	0.013729	0.007962	0.002383	0.02138	0.008757	0.022239	0.019862	0.036189	0.013256	0.019879	0.008786	0.013771	0.002986	0.004935	0.002378	0.004021	0.001937	10.56986	1.601792e-13	14.57936	2.209403e-13	19.87988	3.012669e-13	24.45074	3.705358e-13	23.61157	3.578183e-13	50.96676	7.723688e-13	21.2934	3.398291e-25	16.31768	0.0	21.15114	8.483442e-26	6.620245	1.161618e-26	5.387928	2.104679e-26	11.07489	0.0	6.690278	0.0	21.84747	0.0	18.86606	7.686560e-26	26.74521	2.125622e-24	17.53896	7.547817e-25	15.2731	7.622792e-25	7.780674	1.373914e-24	35.01923	5.306902e-13	18.98862	2.877589e-13	14.42032	7.631948e-25	16.00222	2.798916e-24	40.99183	7.541643e-25	37.58163	5.383057e-25	3.547835	0.0	34.96974	2.003576e-26	105.8952	0.0	80.62691	3.315878e-22	36.44118	0.0	31.60874	0.0	0.048071	0.00153	0.038926	0.004357	0.01592	0.006248	0.005553	0.002676	0.004345	0.002093	18.81272	7.112188e-23	15.6488	0.0	0.027928	0.011203	45.47781	0.0	0.082113	0.034165	34.57665	0.0	8.426783	2.095524e-26	22.79576	7.565951e-25	33.26721	7.645297e-25	18.7625	1.360533e-24	14.43095	5.837865e-25	0.032542	0.005464	0.021149	0.018736	16.76996	0.0	0.004631	0.002231	0.002014	0.00097	0.002583	0.000796	0.010455	0.005038	0.00451	0.002173	0.00317	0.001528	0.004195	0.004084	0.027372	0.008274	64.70937	0.0	80.91752	0.0	102.0578	7.392213e-25	47.21349	0.0	0.015279	0.007224	0.0169	0.002843	0.028449	0.004785	42.44363	7.013738e-22	12.77701	5.615462e-23	27.49709	2.144340e-26	5.377964	0.0	2.779566	8.363599e-29	2.251996	6.694277e-27	9.412791	1.905699e-25	3.21121	8.308066e-27	2.603956	6.693013e-27	5.753166	1.565872e-25	17.9649	5.368832e-27	0.087385	0.015387	0.017306	0.002236	0.014931	0.001814	26.05582	2.110405e-24	0.008468	0.004144	0.017298	0.008858	25.21477	2.158086e-26	13.48946	8.444945e-26	8.799599	0.0	11.09779	8.548555e-26	26.07811	0.0	17.34526	0.0	20.64109	2.102439e-26	0.002894	0.007571	0.002928	0.007658
2023-02-13 02:00:00.000 +01:00	0.013437	0.010421	0.025371	0.014625	0.017832	0.010872	0.002972	0.001812	0.003259	0.001987	0.00362	0.002207	0.039475	0.018532	0.001627	0.002248	0.002951	0.001065	0.00225	0.000812	0.012035	0.004345	0.015949	0.004761	0.014919	0.009291	0.057364	0.003588	0.057824	0.032887	165.7806	0.0	3.842942	6.508102e-26	64.19534	3.053230e-24	51.01035	7.638580e-24	83.9612	2.910067e-24	64.28724	3.057601e-24	43.0797	1.950208e-24	0.092052	0.003742	0.00784	0.002576	0.017054	0.006804	0.032463	0.015606	0.012821	0.008887	0.001881	0.003044	0.005522	0.008423	0.005497	0.008385	0.009616	0.01367	0.00408	0.005393	0.023947	0.022913	52.3749	3.839639e-21	13.53016	8.613383e-26	12.6086	1.907738e-25	10.49419	3.382087e-25	8.190004	3.051250e-24	13.37522	1.363872e-24	0.032132	0.029687	0.007637	0.003357	0.011384	0.007474	0.009444	0.008443	0.015609	0.008071	0.01357	0.008731	0.023328	0.010592	14.29888	0.0	6.310922	0.0	59.923	0.0	99.99299	0.0	14.00829	3.043193e-24	5.560995	1.187491e-26	17.37406	4.733136e-26	126.116	8.920691e-26	21.51779	0.0	0.028187	0.025678	0.038952	0.004936	0.130386	0.002724	0.016946	0.000045	42.03592	1.073386e-25	23.02995	1.672062e-21	117.7475	8.328753e-24	25.77541	3.081205e-24	18.48974	8.841090e-26	20.08946	2.132400e-24	20.21883	1.330405e-25	71.85966	0.0	24.84862	1.196296e-26	25.31222	1.071969e-25	30.19752	8.543967e-26	36.38173	2.084475e-26	34.99198	1.940497e-25	6.78462	2.116374e-26	33.2108	1.908083e-25	50.19061	8.527610e-26	47.19448	0.0	50.84296	0.0	50.56349	0.0	41.89281	1.290790e-24	9.602071	7.631413e-25	25.53992	0.0	0.010837	0.005245	0.011387	0.005511	0.020205	0.009779	0.01643	0.007952	0.015608	0.007554	35.89539	1.358886e-24	72.46398	1.359455e-24	71.66468	0.0	49.03616	0.0	54.56744	0.0	92.76953	0.0	0.022689	0.01168	0.019005	0.009458	0.018562	0.008927	0.030195	0.016532	0.005952	0.001709	0.004693	0.001348	0.005412	0.001554	0.007105	0.001468	0.02445	0.014112	0.008329	0.001894	0.002318	0.003328	0.001022	0.001468	0.001456	0.002091	0.013377	0.003171	0.039901	0.012031	0.022962	0.010703	0.005711	0.003578	0.003159	0.002729	0.003213	0.002776	0.002857	0.000881	0.003821	0.001556	0.042426	0.02448	0.027605	0.031203	0.013715	0.002306	0.033139	0.015126	0.121582	0.016338	0.030131	0.007245	0.003501	0.003602	0.002537	0.002611	0.003056	0.002328	0.028583	0.012432	76.11499	0.0	0.045279	0.021157	0.201245	0.005192	0.002646	0.000212	0.004381	0.000352	0.02179	0.001748	0.018555	0.002141	0.004451	0.00072	0.002772	0.000448	0.164562	0.00366	0.001868	0.000903	0.015436	0.015433	0.001748	0.000796	0.001808	0.000823	0.002753	0.00066	0.014381	0.00345	0.027072	0.002408	0.034794	0.007449	0.076125	0.022934	0.027069	0.024718	0.033999	0.005591	0.00952	0.013961	0.012777	0.010746	0.00404	0.013655	0.005048	0.011634	0.005227	0.006267	0.00626	0.00684	0.004385	0.007488	0.004158	0.0071	0.006439	0.005254	0.022945	0.015466	0.010101	0.006809	0.037958	0.005952	22.46283	4.149739e-24	11.13411	1.344570e-24	18.74616	3.296165e-25	27.98768	0.0	32.47894	3.361727e-25	63.81877	0.0	0.032378	0.014523	0.026701	0.013308	0.007818	0.002306	0.020992	0.008493	0.028376	0.01179	0.035534	0.012847	0.01952	0.008507	0.013524	0.002875	0.004844	0.002345	0.003947	0.00191	10.56986	1.001119e-14	14.57936	1.380879e-14	19.87988	1.882906e-14	24.45074	2.315853e-14	23.61157	2.236356e-14	50.96676	4.827315e-14	21.2934	2.114998e-24	16.31768	1.346276e-24	21.15114	1.355253e-24	6.620245	2.245649e-25	5.387928	8.463555e-26	11.07489	1.919456e-25	6.690278	0.0	21.84747	8.901269e-26	18.86606	0.0	26.74521	5.467291e-24	17.53896	1.341834e-24	15.2731	2.117442e-24	7.780674	2.114256e-24	35.01923	3.316817e-14	18.98862	1.798501e-14	14.42032	2.672777e-26	16.00222	8.405074e-26	40.99183	8.478477e-24	37.58163	6.890579e-24	3.547835	6.404327e-25	34.96974	0.0	105.8952	7.490393e-26	80.62691	3.468148e-22	36.44118	0.0	31.60874	3.355576e-26	0.047206	0.001445	0.038217	0.004156	0.015629	0.006058	0.005451	0.002638	0.004265	0.002064	18.81272	5.724689e-23	15.6488	1.906363e-25	0.027419	0.010803	45.47781	0.0	0.080638	0.032965	34.57665	0.0	8.426783	4.756933e-26	22.79576	3.411914e-25	33.26721	8.494775e-26	18.7625	0.0	14.43095	2.230933e-25	0.032167	0.00529	0.020764	0.018191	16.76996	0.0	0.004546	0.0022	0.001977	0.000957	0.002536	0.000782	...	13.37522	1.899922e-25	0.03272	0.030558	0.007778	0.003467	0.011594	0.007695	0.009619	0.008671	0.015899	0.008306	0.013823	0.00897	0.023763	0.010876	14.29888	1.929519e-26	6.310922	0.0	59.923	0.0	99.99299	0.0	14.00829	4.687399e-26	5.560995	6.491837e-26	17.37406	1.893444e-25	126.116	0.0	21.51779	2.191737e-26	0.028714	0.025998	0.036726	0.005907	0.115364	0.003698	0.013126	0.000078	42.03592	1.905105e-25	23.02995	4.290247e-23	117.7475	3.331501e-25	25.77541	0.0	18.48974	0.0	20.08946	1.893138e-25	20.21883	5.148573e-27	71.85966	0.0	24.84862	1.196296e-26	25.31222	1.102300e-25	30.19752	8.331703e-26	36.38173	2.084475e-26	34.99198	8.935195e-26	6.78462	2.116374e-26	33.2108	1.908083e-25	50.19061	3.411726e-25	47.19448	0.0	50.84296	3.236694e-25	50.56349	3.218903e-25	41.89281	1.370205e-24	9.602071	1.350304e-24	25.53992	6.869373e-24	0.011039	0.005319	0.0116	0.005589	0.020583	0.009917	0.016737	0.008065	0.0159	0.007661	35.89539	3.313088e-26	72.46398	3.332966e-25	71.66468	0.0	49.03616	3.333252e-25	54.56744	0.0	92.76953	0.0	0.023111	0.011893	0.019357	0.009632	0.018318	0.009675	0.028447	0.019632	0.005504	0.00211	0.00434	0.001664	0.005004	0.001918	0.006498	0.001853	0.021653	0.018858	0.006376	0.003339	0.002393	0.003292	0.001055	0.001452	0.001503	0.002068	0.007957	0.01258	0.041119	0.012034	0.023626	0.010705	0.005816	0.003685	0.003218	0.002804	0.003273	0.002852	0.00291	0.000911	0.003892	0.001605	0.043215	0.025172	0.042147	0.01164	0.013968	0.002407	0.033753	0.015579	0.084669	0.047416	0.030686	0.007475	0.003897	0.003118	0.002824	0.002259	0.003437	0.001983	0.029106	0.012807	76.11499	0.0	0.046102	0.021898	0.203459	0.005518	0.002682	0.000223	0.00444	0.000369	0.022085	0.001836	0.018817	0.002239	0.004516	0.00075	0.004254	0.000169	0.167143	0.003845	0.001902	0.000929	0.015718	0.015831	0.00178	0.000822	0.001841	0.00085	0.002803	0.000685	0.014642	0.003579	0.027562	0.002526	0.035425	0.007734	0.077527	0.023833	0.027558	0.025218	0.034402	0.005777	0.009633	0.014163	0.012929	0.010933	0.004087	0.01382	0.005108	0.011797	0.005289	0.006377	0.006334	0.006964	0.004437	0.007617	0.004207	0.007222	0.006515	0.005366	0.023215	0.015846	0.010218	0.006975	0.038396	0.006148	22.46283	7.871059e-26	11.13411	3.361424e-25	18.74616	3.296165e-25	27.98768	3.370467e-25	32.47894	8.594241e-26	63.81877	0.0	0.032964	0.015184	0.027192	0.013729	0.007962	0.002383	0.02138	0.008757	0.022239	0.019862	0.036189	0.013256	0.019879	0.008786	0.013771	0.002986	0.004935	0.002378	0.004021	0.001937	10.56986	1.601792e-13	14.57936	2.209403e-13	19.87988	3.012669e-13	24.45074	3.705358e-13	23.61157	3.578183e-13	50.96676	7.723688e-13	21.2934	3.398291e-25	16.31768	0.0	21.15114	8.483442e-26	6.620245	1.161618e-26	5.387928	2.104679e-26	11.07489	0.0	6.690278	0.0	21.84747	0.0	18.86606	7.686560e-26	26.74521	2.125622e-24	17.53896	7.547817e-25	15.2731	7.622792e-25	7.780674	1.373914e-24	35.01923	5.306902e-13	18.98862	2.877589e-13	14.42032	7.631948e-25	16.00222	2.798916e-24	40.99183	7.541643e-25	37.58163	5.383057e-25	3.547835	0.0	34.96974	2.003576e-26	105.8952	0.0	80.62691	3.315878e-22	36.44118	0.0	31.60874	0.0	0.048071	0.00153	0.038926	0.004357	0.01592	0.006248	0.005553	0.002676	0.004345	0.002093	18.81272	7.112188e-23	15.6488	0.0	0.027928	0.011203	45.47781	0.0	0.082113	0.034165	34.57665	0.0	8.426783	2.095524e-26	22.79576	7.565951e-25	33.26721	7.645297e-25	18.7625	1.360533e-24	14.43095	5.837865e-25	0.032542	0.005464	0.021149	0.018736	16.76996	0.0	0.004631	0.002231	0.002014	0.00097	0.002583	0.000796	0.010455	0.005038	0.00451	0.002173	0.00317	0.001528	0.004195	0.004084	0.027372	0.008274	64.70937	0.0	80.91752	0.0	102.0578	7.392213e-25	47.21349	0.0	0.015279	0.007224	0.0169	0.002843	0.028449	0.004785	42.44363	7.013738e-22	12.77701	5.615462e-23	27.49709	2.144340e-26	5.377964	0.0	2.779566	8.363599e-29	2.251996	6.694277e-27	9.412791	1.905699e-25	3.21121	8.308066e-27	2.603956	6.693013e-27	5.753166	1.565872e-25	17.9649	5.368832e-27	0.087385	0.015387	0.017306	0.002236	0.014931	0.001814	26.05582	2.110405e-24	0.008468	0.004144	0.017298	0.008858	25.21477	2.158086e-26	13.48946	8.444945e-26	8.799599	0.0	11.09779	8.548555e-26	26.07811	0.0	17.34526	0.0	20.64109	2.102439e-26	0.002894	0.007571	0.002928	0.007658

3 rows × 1048 columns

We can access individual values as follows.

df_pipes_2.loc[
    "2023-02-13 00:00:00.000 +01:00",
    ("5442010239090746007", slice(None), slice(None), "DTTR")
].item()

0.01343678

Subcase 3: Specific Timestamps + Specific Values

We can specify the list of timestamps to include either as a list of str timestamps …

(s3s.generate_element_results_dataframe(element_type=s3s.ObjectTypes.Pipe
                                        ,properties=["DTTR", "PHR"]
                                        ,timestamps=['2023-02-13 00:00:00.000 +01:00', '2023-02-13 05:00:00.000 +01:00', '2023-02-13 23:00:00.000 +01:00']
                                        )).head(3)

[2026-03-15 23:20:30,683] INFO in sir3stoolkit.mantle.dataframes: [results] Generating results dataframe for element type: ObjectTypes.Pipe
[2026-03-15 23:20:30,988] INFO in sir3stoolkit.mantle.dataframes: [Resolving Timestamps] 3 valid timestamp(s) will be used.
[2026-03-15 23:20:30,991] INFO in sir3stoolkit.mantle.dataframes: [Resolving tks] Retrieved 524 element(s) of element type ObjectTypes.Pipe.
[2026-03-15 23:20:30,996] INFO in sir3stoolkit.mantle.dataframes: [results] Using 2 result properties.
[2026-03-15 23:20:31,034] INFO in sir3stoolkit.mantle.dataframes: [results] Retrieving result values...
[2026-03-15 23:20:32,020] INFO in sir3stoolkit.mantle.dataframes: [results] 0 fully NaN columns dropped.
[2026-03-15 23:20:32,323] INFO in sir3stoolkit.mantle.dataframes: [results] Done. Shape: (3, 1048)

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timestamp
2023-02-13 00:00:00.000 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2023-02-13 05:00:00.000 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4	0.011039	0.005319	0.0116	0.005589	0.020583	0.009917	0.016737	0.008065	0.0159	0.007661	35.89539	3.313088e-26	72.46398	3.332966e-25	71.66468	0.0	49.03616	3.333252e-25	54.56744	0.0	92.76953	0.0	0.023111	0.011893	0.019357	0.009632	0.018318	0.009675	0.028447	0.019632	0.005504	0.00211	0.00434	0.001664	0.005004	0.001918	0.006498	0.001853	0.021653	0.018858	0.006376	0.003339	0.002393	0.003292	0.001055	0.001452	0.001503	0.002068	0.007957	0.01258	0.041119	0.012034	0.023626	0.010705	0.005816	0.003685	0.003218	0.002804	0.003273	0.002852	0.00291	0.000911	0.003892	0.001605	0.043215	0.025172	0.042147	0.01164	0.013968	0.002407	0.033753	0.015579	0.084669	0.047416	0.030686	0.007475	0.003897	0.003118	0.002824	0.002259	0.003437	0.001983	0.029106	0.012807	76.11499	0.0	0.046102	0.021898	0.203459	0.005518	0.002682	0.000223	0.00444	0.000369	0.022085	0.001836	0.018817	0.002239	0.004516	0.00075	0.004254	0.000169	0.167143	0.003845	0.001902	0.000929	0.015718	0.015831	0.00178	0.000822	0.001841	0.00085	0.002803	0.000685	0.014642	0.003579	0.027562	0.002526	0.035425	0.007734	0.077527	0.023833	0.027558	0.025218	0.034402	0.005777	0.009633	0.014163	0.012929	0.010933	0.004087	0.01382	0.005108	0.011797	0.005289	0.006377	0.006334	0.006964	0.004437	0.007617	0.004207	0.007222	0.006515	0.005366	0.023215	0.015846	0.010218	0.006975	0.038396	0.006148	22.46283	7.871059e-26	11.13411	3.361424e-25	18.74616	3.296165e-25	27.98768	3.370467e-25	32.47894	8.594241e-26	63.81877	0.0	0.032964	0.015184	0.027192	0.013729	0.007962	0.002383	0.02138	0.008757	0.022239	0.019862	0.036189	0.013256	0.019879	0.008786	0.013771	0.002986	0.004935	0.002378	0.004021	0.001937	10.56986	1.601792e-13	14.57936	2.209403e-13	19.87988	3.012669e-13	24.45074	3.705358e-13	23.61157	3.578183e-13	50.96676	7.723688e-13	21.2934	3.398291e-25	16.31768	0.0	21.15114	8.483442e-26	6.620245	1.161618e-26	5.387928	2.104679e-26	11.07489	0.0	6.690278	0.0	21.84747	0.0	18.86606	7.686560e-26	26.74521	2.125622e-24	17.53896	7.547817e-25	15.2731	7.622792e-25	7.780674	1.373914e-24	35.01923	5.306902e-13	18.98862	2.877589e-13	14.42032	7.631948e-25	16.00222	2.798916e-24	40.99183	7.541643e-25	37.58163	5.383057e-25	3.547835	0.0	34.96974	2.003576e-26	105.8952	0.0	80.62691	3.315878e-22	36.44118	0.0	31.60874	0.0	0.048071	0.00153	0.038926	0.004357	0.01592	0.006248	0.005553	0.002676	0.004345	0.002093	18.81272	7.112188e-23	15.6488	0.0	0.027928	0.011203	45.47781	0.0	0.082113	0.034165	34.57665	0.0	8.426783	2.095524e-26	22.79576	7.565951e-25	33.26721	7.645297e-25	18.7625	1.360533e-24	14.43095	5.837865e-25	0.032542	0.005464	0.021149	0.018736	16.76996	0.0	0.004631	0.002231	0.002014	0.00097	0.002583	0.000796	0.010455	0.005038	0.00451	0.002173	0.00317	0.001528	0.004195	0.004084	0.027372	0.008274	64.70937	0.0	80.91752	0.0	102.0578	7.392213e-25	47.21349	0.0	0.015279	0.007224	0.0169	0.002843	0.028449	0.004785	42.44363	7.013738e-22	12.77701	5.615462e-23	27.49709	2.144340e-26	5.377964	0.0	2.779566	8.363599e-29	2.251996	6.694277e-27	9.412791	1.905699e-25	3.21121	8.308066e-27	2.603956	6.693013e-27	5.753166	1.565872e-25	17.9649	5.368832e-27	0.087385	0.015387	0.017306	0.002236	0.014931	0.001814	26.05582	2.110405e-24	0.008468	0.004144	0.017298	0.008858	25.21477	2.158086e-26	13.48946	8.444945e-26	8.799599	0.0	11.09779	8.548555e-26	26.07811	0.0	17.34526	0.0	20.64109	2.102439e-26	0.002894	0.007571	0.002928	0.007658
2023-02-13 23:00:00.000 +01:00	0.013437	0.010421	0.025371	0.014625	0.017832	0.010872	0.002972	0.001812	0.003259	0.001987	0.00362	0.002207	0.039475	0.018532	0.001627	0.002248	0.002951	0.001065	0.00225	0.000812	0.012035	0.004345	0.015949	0.004761	0.014919	0.009291	0.057364	0.003588	0.057824	0.032887	165.7806	0.0	3.842942	6.508102e-26	64.19534	3.053230e-24	51.01035	7.638580e-24	83.9612	2.910067e-24	64.28724	3.057601e-24	43.0797	1.950208e-24	0.092052	0.003742	0.00784	0.002576	0.017054	0.006804	0.032463	0.015606	0.012821	0.008887	0.001881	0.003044	0.005522	0.008423	0.005497	0.008385	0.009616	0.01367	0.00408	0.005393	0.023947	0.022913	52.3749	3.839639e-21	13.53016	8.613383e-26	12.6086	1.907738e-25	10.49419	3.382087e-25	8.190004	3.051250e-24	13.37522	1.363872e-24	0.032132	0.029687	0.007637	0.003357	0.011384	0.007474	0.009444	0.008443	0.015609	0.008071	0.01357	0.008731	0.023328	0.010592	14.29888	0.0	6.310922	0.0	59.923	0.0	99.99299	0.0	14.00829	3.043193e-24	5.560995	1.187491e-26	17.37406	4.733136e-26	126.116	8.920691e-26	21.51779	0.0	0.028187	0.025678	0.038952	0.004936	0.130386	0.002724	0.016946	0.000045	42.03592	1.073386e-25	23.02995	1.672062e-21	117.7475	8.328753e-24	25.77541	3.081205e-24	18.48974	8.841090e-26	20.08946	2.132400e-24	20.21883	1.330405e-25	71.85966	0.0	24.84862	1.196296e-26	25.31222	1.071969e-25	30.19752	8.543967e-26	36.38173	2.084475e-26	34.99198	1.940497e-25	6.78462	2.116374e-26	33.2108	1.908083e-25	50.19061	8.527610e-26	47.19448	0.0	50.84296	0.0	50.56349	0.0	41.89281	1.290790e-24	9.602071	7.631413e-25	25.53992	0.0	0.010837	0.005245	0.011387	0.005511	0.020205	0.009779	0.01643	0.007952	0.015608	0.007554	35.89539	1.358886e-24	72.46398	1.359455e-24	71.66468	0.0	49.03616	0.0	54.56744	0.0	92.76953	0.0	0.022689	0.01168	0.019005	0.009458	0.018562	0.008927	0.030195	0.016532	0.005952	0.001709	0.004693	0.001348	0.005412	0.001554	0.007105	0.001468	0.02445	0.014112	0.008329	0.001894	0.002318	0.003328	0.001022	0.001468	0.001456	0.002091	0.013377	0.003171	0.039901	0.012031	0.022962	0.010703	0.005711	0.003578	0.003159	0.002729	0.003213	0.002776	0.002857	0.000881	0.003821	0.001556	0.042426	0.02448	0.027605	0.031203	0.013715	0.002306	0.033139	0.015126	0.121582	0.016338	0.030131	0.007245	0.003501	0.003602	0.002537	0.002611	0.003056	0.002328	0.028583	0.012432	76.11499	0.0	0.045279	0.021157	0.201245	0.005192	0.002646	0.000212	0.004381	0.000352	0.02179	0.001748	0.018555	0.002141	0.004451	0.00072	0.002772	0.000448	0.164562	0.00366	0.001868	0.000903	0.015436	0.015433	0.001748	0.000796	0.001808	0.000823	0.002753	0.00066	0.014381	0.00345	0.027072	0.002408	0.034794	0.007449	0.076125	0.022934	0.027069	0.024718	0.033999	0.005591	0.00952	0.013961	0.012777	0.010746	0.00404	0.013655	0.005048	0.011634	0.005227	0.006267	0.00626	0.00684	0.004385	0.007488	0.004158	0.0071	0.006439	0.005254	0.022945	0.015466	0.010101	0.006809	0.037958	0.005952	22.46283	4.149739e-24	11.13411	1.344570e-24	18.74616	3.296165e-25	27.98768	0.0	32.47894	3.361727e-25	63.81877	0.0	0.032378	0.014523	0.026701	0.013308	0.007818	0.002306	0.020992	0.008493	0.028376	0.01179	0.035534	0.012847	0.01952	0.008507	0.013524	0.002875	0.004844	0.002345	0.003947	0.00191	10.56986	1.001119e-14	14.57936	1.380879e-14	19.87988	1.882906e-14	24.45074	2.315853e-14	23.61157	2.236356e-14	50.96676	4.827315e-14	21.2934	2.114998e-24	16.31768	1.346276e-24	21.15114	1.355253e-24	6.620245	2.245649e-25	5.387928	8.463555e-26	11.07489	1.919456e-25	6.690278	0.0	21.84747	8.901269e-26	18.86606	0.0	26.74521	5.467291e-24	17.53896	1.341834e-24	15.2731	2.117442e-24	7.780674	2.114256e-24	35.01923	3.316817e-14	18.98862	1.798501e-14	14.42032	2.672777e-26	16.00222	8.405074e-26	40.99183	8.478477e-24	37.58163	6.890579e-24	3.547835	6.404327e-25	34.96974	0.0	105.8952	7.490393e-26	80.62691	3.468148e-22	36.44118	0.0	31.60874	3.355576e-26	0.047206	0.001445	0.038217	0.004156	0.015629	0.006058	0.005451	0.002638	0.004265	0.002064	18.81272	5.724689e-23	15.6488	1.906363e-25	0.027419	0.010803	45.47781	0.0	0.080638	0.032965	34.57665	0.0	8.426783	4.756933e-26	22.79576	3.411914e-25	33.26721	8.494775e-26	18.7625	0.0	14.43095	2.230933e-25	0.032167	0.00529	0.020764	0.018191	16.76996	0.0	0.004546	0.0022	0.001977	0.000957	0.002536	0.000782	...	13.37522	1.899922e-25	0.03272	0.030558	0.007778	0.003467	0.011594	0.007695	0.009619	0.008671	0.015899	0.008306	0.013823	0.00897	0.023763	0.010876	14.29888	1.929519e-26	6.310922	0.0	59.923	0.0	99.99299	0.0	14.00829	4.687399e-26	5.560995	6.491837e-26	17.37406	1.893444e-25	126.116	0.0	21.51779	2.191737e-26	0.028714	0.025998	0.036726	0.005907	0.115364	0.003698	0.013126	0.000078	42.03592	1.905105e-25	23.02995	4.290247e-23	117.7475	3.331501e-25	25.77541	0.0	18.48974	0.0	20.08946	1.893138e-25	20.21883	5.148573e-27	71.85966	0.0	24.84862	1.196296e-26	25.31222	1.102300e-25	30.19752	8.331703e-26	36.38173	2.084475e-26	34.99198	8.935195e-26	6.78462	2.116374e-26	33.2108	1.908083e-25	50.19061	3.411726e-25	47.19448	0.0	50.84296	3.236694e-25	50.56349	3.218903e-25	41.89281	1.370205e-24	9.602071	1.350304e-24	25.53992	6.869373e-24	0.011039	0.005319	0.0116	0.005589	0.020583	0.009917	0.016737	0.008065	0.0159	0.007661	35.89539	3.313088e-26	72.46398	3.332966e-25	71.66468	0.0	49.03616	3.333252e-25	54.56744	0.0	92.76953	0.0	0.023111	0.011893	0.019357	0.009632	0.018318	0.009675	0.028447	0.019632	0.005504	0.00211	0.00434	0.001664	0.005004	0.001918	0.006498	0.001853	0.021653	0.018858	0.006376	0.003339	0.002393	0.003292	0.001055	0.001452	0.001503	0.002068	0.007957	0.01258	0.041119	0.012034	0.023626	0.010705	0.005816	0.003685	0.003218	0.002804	0.003273	0.002852	0.00291	0.000911	0.003892	0.001605	0.043215	0.025172	0.042147	0.01164	0.013968	0.002407	0.033753	0.015579	0.084669	0.047416	0.030686	0.007475	0.003897	0.003118	0.002824	0.002259	0.003437	0.001983	0.029106	0.012807	76.11499	0.0	0.046102	0.021898	0.203459	0.005518	0.002682	0.000223	0.00444	0.000369	0.022085	0.001836	0.018817	0.002239	0.004516	0.00075	0.004254	0.000169	0.167143	0.003845	0.001902	0.000929	0.015718	0.015831	0.00178	0.000822	0.001841	0.00085	0.002803	0.000685	0.014642	0.003579	0.027562	0.002526	0.035425	0.007734	0.077527	0.023833	0.027558	0.025218	0.034402	0.005777	0.009633	0.014163	0.012929	0.010933	0.004087	0.01382	0.005108	0.011797	0.005289	0.006377	0.006334	0.006964	0.004437	0.007617	0.004207	0.007222	0.006515	0.005366	0.023215	0.015846	0.010218	0.006975	0.038396	0.006148	22.46283	7.871059e-26	11.13411	3.361424e-25	18.74616	3.296165e-25	27.98768	3.370467e-25	32.47894	8.594241e-26	63.81877	0.0	0.032964	0.015184	0.027192	0.013729	0.007962	0.002383	0.02138	0.008757	0.022239	0.019862	0.036189	0.013256	0.019879	0.008786	0.013771	0.002986	0.004935	0.002378	0.004021	0.001937	10.56986	1.601792e-13	14.57936	2.209403e-13	19.87988	3.012669e-13	24.45074	3.705358e-13	23.61157	3.578183e-13	50.96676	7.723688e-13	21.2934	3.398291e-25	16.31768	0.0	21.15114	8.483442e-26	6.620245	1.161618e-26	5.387928	2.104679e-26	11.07489	0.0	6.690278	0.0	21.84747	0.0	18.86606	7.686560e-26	26.74521	2.125622e-24	17.53896	7.547817e-25	15.2731	7.622792e-25	7.780674	1.373914e-24	35.01923	5.306902e-13	18.98862	2.877589e-13	14.42032	7.631948e-25	16.00222	2.798916e-24	40.99183	7.541643e-25	37.58163	5.383057e-25	3.547835	0.0	34.96974	2.003576e-26	105.8952	0.0	80.62691	3.315878e-22	36.44118	0.0	31.60874	0.0	0.048071	0.00153	0.038926	0.004357	0.01592	0.006248	0.005553	0.002676	0.004345	0.002093	18.81272	7.112188e-23	15.6488	0.0	0.027928	0.011203	45.47781	0.0	0.082113	0.034165	34.57665	0.0	8.426783	2.095524e-26	22.79576	7.565951e-25	33.26721	7.645297e-25	18.7625	1.360533e-24	14.43095	5.837865e-25	0.032542	0.005464	0.021149	0.018736	16.76996	0.0	0.004631	0.002231	0.002014	0.00097	0.002583	0.000796	0.010455	0.005038	0.00451	0.002173	0.00317	0.001528	0.004195	0.004084	0.027372	0.008274	64.70937	0.0	80.91752	0.0	102.0578	7.392213e-25	47.21349	0.0	0.015279	0.007224	0.0169	0.002843	0.028449	0.004785	42.44363	7.013738e-22	12.77701	5.615462e-23	27.49709	2.144340e-26	5.377964	0.0	2.779566	8.363599e-29	2.251996	6.694277e-27	9.412791	1.905699e-25	3.21121	8.308066e-27	2.603956	6.693013e-27	5.753166	1.565872e-25	17.9649	5.368832e-27	0.087385	0.015387	0.017306	0.002236	0.014931	0.001814	26.05582	2.110405e-24	0.008468	0.004144	0.017298	0.008858	25.21477	2.158086e-26	13.48946	8.444945e-26	8.799599	0.0	11.09779	8.548555e-26	26.07811	0.0	17.34526	0.0	20.64109	2.102439e-26	0.002894	0.007571	0.002928	0.007658

3 rows × 1048 columns

… or as a list of int indices.

simulation_timestamps=s3s.GetTimeStamps()[0]

for idx, timestamp in enumerate(simulation_timestamps):
    print(idx, timestamp)

0 2023-02-13 00:00:00.000 +01:00
1 2023-02-13 01:00:00.000 +01:00
2 2023-02-13 02:00:00.000 +01:00
3 2023-02-13 03:00:00.000 +01:00
4 2023-02-13 04:00:00.000 +01:00
5 2023-02-13 05:00:00.000 +01:00
6 2023-02-13 06:00:00.000 +01:00
7 2023-02-13 07:00:00.000 +01:00
8 2023-02-13 08:00:00.000 +01:00
9 2023-02-13 09:00:00.000 +01:00
10 2023-02-13 10:00:00.000 +01:00
11 2023-02-13 11:00:00.000 +01:00
12 2023-02-13 12:00:00.000 +01:00
13 2023-02-13 13:00:00.000 +01:00
14 2023-02-13 14:00:00.000 +01:00
15 2023-02-13 15:00:00.000 +01:00
16 2023-02-13 16:00:00.000 +01:00
17 2023-02-13 17:00:00.000 +01:00
18 2023-02-13 18:00:00.000 +01:00
19 2023-02-13 19:00:00.000 +01:00
20 2023-02-13 20:00:00.000 +01:00
21 2023-02-13 21:00:00.000 +01:00
22 2023-02-13 22:00:00.000 +01:00
23 2023-02-13 23:00:00.000 +01:00
24 2023-02-14 00:00:00.000 +01:00

(s3s.generate_element_results_dataframe(element_type=s3s.ObjectTypes.Pipe
                                        ,properties=["DTTR", "PHR"]
                                        ,timestamps=[0, 5, -2]
                                        )).head(3)

[2026-03-15 23:20:34,270] INFO in sir3stoolkit.mantle.dataframes: [results] Generating results dataframe for element type: ObjectTypes.Pipe
[2026-03-15 23:20:34,542] INFO in sir3stoolkit.mantle.dataframes: [Resolving Timestamps] 3 valid timestamp(s) will be used.
[2026-03-15 23:20:34,548] INFO in sir3stoolkit.mantle.dataframes: [Resolving tks] Retrieved 524 element(s) of element type ObjectTypes.Pipe.
[2026-03-15 23:20:34,552] INFO in sir3stoolkit.mantle.dataframes: [results] Using 2 result properties.
[2026-03-15 23:20:34,607] INFO in sir3stoolkit.mantle.dataframes: [results] Retrieving result values...
[2026-03-15 23:20:36,129] INFO in sir3stoolkit.mantle.dataframes: [results] 0 fully NaN columns dropped.
[2026-03-15 23:20:36,683] INFO in sir3stoolkit.mantle.dataframes: [results] Done. Shape: (3, 1048)

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timestamp
2023-02-13 00:00:00.000 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2023-02-13 05:00:00.000 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4	0.011039	0.005319	0.0116	0.005589	0.020583	0.009917	0.016737	0.008065	0.0159	0.007661	35.89539	3.313088e-26	72.46398	3.332966e-25	71.66468	0.0	49.03616	3.333252e-25	54.56744	0.0	92.76953	0.0	0.023111	0.011893	0.019357	0.009632	0.018318	0.009675	0.028447	0.019632	0.005504	0.00211	0.00434	0.001664	0.005004	0.001918	0.006498	0.001853	0.021653	0.018858	0.006376	0.003339	0.002393	0.003292	0.001055	0.001452	0.001503	0.002068	0.007957	0.01258	0.041119	0.012034	0.023626	0.010705	0.005816	0.003685	0.003218	0.002804	0.003273	0.002852	0.00291	0.000911	0.003892	0.001605	0.043215	0.025172	0.042147	0.01164	0.013968	0.002407	0.033753	0.015579	0.084669	0.047416	0.030686	0.007475	0.003897	0.003118	0.002824	0.002259	0.003437	0.001983	0.029106	0.012807	76.11499	0.0	0.046102	0.021898	0.203459	0.005518	0.002682	0.000223	0.00444	0.000369	0.022085	0.001836	0.018817	0.002239	0.004516	0.00075	0.004254	0.000169	0.167143	0.003845	0.001902	0.000929	0.015718	0.015831	0.00178	0.000822	0.001841	0.00085	0.002803	0.000685	0.014642	0.003579	0.027562	0.002526	0.035425	0.007734	0.077527	0.023833	0.027558	0.025218	0.034402	0.005777	0.009633	0.014163	0.012929	0.010933	0.004087	0.01382	0.005108	0.011797	0.005289	0.006377	0.006334	0.006964	0.004437	0.007617	0.004207	0.007222	0.006515	0.005366	0.023215	0.015846	0.010218	0.006975	0.038396	0.006148	22.46283	7.871059e-26	11.13411	3.361424e-25	18.74616	3.296165e-25	27.98768	3.370467e-25	32.47894	8.594241e-26	63.81877	0.0	0.032964	0.015184	0.027192	0.013729	0.007962	0.002383	0.02138	0.008757	0.022239	0.019862	0.036189	0.013256	0.019879	0.008786	0.013771	0.002986	0.004935	0.002378	0.004021	0.001937	10.56986	1.601792e-13	14.57936	2.209403e-13	19.87988	3.012669e-13	24.45074	3.705358e-13	23.61157	3.578183e-13	50.96676	7.723688e-13	21.2934	3.398291e-25	16.31768	0.0	21.15114	8.483442e-26	6.620245	1.161618e-26	5.387928	2.104679e-26	11.07489	0.0	6.690278	0.0	21.84747	0.0	18.86606	7.686560e-26	26.74521	2.125622e-24	17.53896	7.547817e-25	15.2731	7.622792e-25	7.780674	1.373914e-24	35.01923	5.306902e-13	18.98862	2.877589e-13	14.42032	7.631948e-25	16.00222	2.798916e-24	40.99183	7.541643e-25	37.58163	5.383057e-25	3.547835	0.0	34.96974	2.003576e-26	105.8952	0.0	80.62691	3.315878e-22	36.44118	0.0	31.60874	0.0	0.048071	0.00153	0.038926	0.004357	0.01592	0.006248	0.005553	0.002676	0.004345	0.002093	18.81272	7.112188e-23	15.6488	0.0	0.027928	0.011203	45.47781	0.0	0.082113	0.034165	34.57665	0.0	8.426783	2.095524e-26	22.79576	7.565951e-25	33.26721	7.645297e-25	18.7625	1.360533e-24	14.43095	5.837865e-25	0.032542	0.005464	0.021149	0.018736	16.76996	0.0	0.004631	0.002231	0.002014	0.00097	0.002583	0.000796	0.010455	0.005038	0.00451	0.002173	0.00317	0.001528	0.004195	0.004084	0.027372	0.008274	64.70937	0.0	80.91752	0.0	102.0578	7.392213e-25	47.21349	0.0	0.015279	0.007224	0.0169	0.002843	0.028449	0.004785	42.44363	7.013738e-22	12.77701	5.615462e-23	27.49709	2.144340e-26	5.377964	0.0	2.779566	8.363599e-29	2.251996	6.694277e-27	9.412791	1.905699e-25	3.21121	8.308066e-27	2.603956	6.693013e-27	5.753166	1.565872e-25	17.9649	5.368832e-27	0.087385	0.015387	0.017306	0.002236	0.014931	0.001814	26.05582	2.110405e-24	0.008468	0.004144	0.017298	0.008858	25.21477	2.158086e-26	13.48946	8.444945e-26	8.799599	0.0	11.09779	8.548555e-26	26.07811	0.0	17.34526	0.0	20.64109	2.102439e-26	0.002894	0.007571	0.002928	0.007658
2023-02-13 23:00:00.000 +01:00	0.013437	0.010421	0.025371	0.014625	0.017832	0.010872	0.002972	0.001812	0.003259	0.001987	0.00362	0.002207	0.039475	0.018532	0.001627	0.002248	0.002951	0.001065	0.00225	0.000812	0.012035	0.004345	0.015949	0.004761	0.014919	0.009291	0.057364	0.003588	0.057824	0.032887	165.7806	0.0	3.842942	6.508102e-26	64.19534	3.053230e-24	51.01035	7.638580e-24	83.9612	2.910067e-24	64.28724	3.057601e-24	43.0797	1.950208e-24	0.092052	0.003742	0.00784	0.002576	0.017054	0.006804	0.032463	0.015606	0.012821	0.008887	0.001881	0.003044	0.005522	0.008423	0.005497	0.008385	0.009616	0.01367	0.00408	0.005393	0.023947	0.022913	52.3749	3.839639e-21	13.53016	8.613383e-26	12.6086	1.907738e-25	10.49419	3.382087e-25	8.190004	3.051250e-24	13.37522	1.363872e-24	0.032132	0.029687	0.007637	0.003357	0.011384	0.007474	0.009444	0.008443	0.015609	0.008071	0.01357	0.008731	0.023328	0.010592	14.29888	0.0	6.310922	0.0	59.923	0.0	99.99299	0.0	14.00829	3.043193e-24	5.560995	1.187491e-26	17.37406	4.733136e-26	126.116	8.920691e-26	21.51779	0.0	0.028187	0.025678	0.038952	0.004936	0.130386	0.002724	0.016946	0.000045	42.03592	1.073386e-25	23.02995	1.672062e-21	117.7475	8.328753e-24	25.77541	3.081205e-24	18.48974	8.841090e-26	20.08946	2.132400e-24	20.21883	1.330405e-25	71.85966	0.0	24.84862	1.196296e-26	25.31222	1.071969e-25	30.19752	8.543967e-26	36.38173	2.084475e-26	34.99198	1.940497e-25	6.78462	2.116374e-26	33.2108	1.908083e-25	50.19061	8.527610e-26	47.19448	0.0	50.84296	0.0	50.56349	0.0	41.89281	1.290790e-24	9.602071	7.631413e-25	25.53992	0.0	0.010837	0.005245	0.011387	0.005511	0.020205	0.009779	0.01643	0.007952	0.015608	0.007554	35.89539	1.358886e-24	72.46398	1.359455e-24	71.66468	0.0	49.03616	0.0	54.56744	0.0	92.76953	0.0	0.022689	0.01168	0.019005	0.009458	0.018562	0.008927	0.030195	0.016532	0.005952	0.001709	0.004693	0.001348	0.005412	0.001554	0.007105	0.001468	0.02445	0.014112	0.008329	0.001894	0.002318	0.003328	0.001022	0.001468	0.001456	0.002091	0.013377	0.003171	0.039901	0.012031	0.022962	0.010703	0.005711	0.003578	0.003159	0.002729	0.003213	0.002776	0.002857	0.000881	0.003821	0.001556	0.042426	0.02448	0.027605	0.031203	0.013715	0.002306	0.033139	0.015126	0.121582	0.016338	0.030131	0.007245	0.003501	0.003602	0.002537	0.002611	0.003056	0.002328	0.028583	0.012432	76.11499	0.0	0.045279	0.021157	0.201245	0.005192	0.002646	0.000212	0.004381	0.000352	0.02179	0.001748	0.018555	0.002141	0.004451	0.00072	0.002772	0.000448	0.164562	0.00366	0.001868	0.000903	0.015436	0.015433	0.001748	0.000796	0.001808	0.000823	0.002753	0.00066	0.014381	0.00345	0.027072	0.002408	0.034794	0.007449	0.076125	0.022934	0.027069	0.024718	0.033999	0.005591	0.00952	0.013961	0.012777	0.010746	0.00404	0.013655	0.005048	0.011634	0.005227	0.006267	0.00626	0.00684	0.004385	0.007488	0.004158	0.0071	0.006439	0.005254	0.022945	0.015466	0.010101	0.006809	0.037958	0.005952	22.46283	4.149739e-24	11.13411	1.344570e-24	18.74616	3.296165e-25	27.98768	0.0	32.47894	3.361727e-25	63.81877	0.0	0.032378	0.014523	0.026701	0.013308	0.007818	0.002306	0.020992	0.008493	0.028376	0.01179	0.035534	0.012847	0.01952	0.008507	0.013524	0.002875	0.004844	0.002345	0.003947	0.00191	10.56986	1.001119e-14	14.57936	1.380879e-14	19.87988	1.882906e-14	24.45074	2.315853e-14	23.61157	2.236356e-14	50.96676	4.827315e-14	21.2934	2.114998e-24	16.31768	1.346276e-24	21.15114	1.355253e-24	6.620245	2.245649e-25	5.387928	8.463555e-26	11.07489	1.919456e-25	6.690278	0.0	21.84747	8.901269e-26	18.86606	0.0	26.74521	5.467291e-24	17.53896	1.341834e-24	15.2731	2.117442e-24	7.780674	2.114256e-24	35.01923	3.316817e-14	18.98862	1.798501e-14	14.42032	2.672777e-26	16.00222	8.405074e-26	40.99183	8.478477e-24	37.58163	6.890579e-24	3.547835	6.404327e-25	34.96974	0.0	105.8952	7.490393e-26	80.62691	3.468148e-22	36.44118	0.0	31.60874	3.355576e-26	0.047206	0.001445	0.038217	0.004156	0.015629	0.006058	0.005451	0.002638	0.004265	0.002064	18.81272	5.724689e-23	15.6488	1.906363e-25	0.027419	0.010803	45.47781	0.0	0.080638	0.032965	34.57665	0.0	8.426783	4.756933e-26	22.79576	3.411914e-25	33.26721	8.494775e-26	18.7625	0.0	14.43095	2.230933e-25	0.032167	0.00529	0.020764	0.018191	16.76996	0.0	0.004546	0.0022	0.001977	0.000957	0.002536	0.000782	...	13.37522	1.899922e-25	0.03272	0.030558	0.007778	0.003467	0.011594	0.007695	0.009619	0.008671	0.015899	0.008306	0.013823	0.00897	0.023763	0.010876	14.29888	1.929519e-26	6.310922	0.0	59.923	0.0	99.99299	0.0	14.00829	4.687399e-26	5.560995	6.491837e-26	17.37406	1.893444e-25	126.116	0.0	21.51779	2.191737e-26	0.028714	0.025998	0.036726	0.005907	0.115364	0.003698	0.013126	0.000078	42.03592	1.905105e-25	23.02995	4.290247e-23	117.7475	3.331501e-25	25.77541	0.0	18.48974	0.0	20.08946	1.893138e-25	20.21883	5.148573e-27	71.85966	0.0	24.84862	1.196296e-26	25.31222	1.102300e-25	30.19752	8.331703e-26	36.38173	2.084475e-26	34.99198	8.935195e-26	6.78462	2.116374e-26	33.2108	1.908083e-25	50.19061	3.411726e-25	47.19448	0.0	50.84296	3.236694e-25	50.56349	3.218903e-25	41.89281	1.370205e-24	9.602071	1.350304e-24	25.53992	6.869373e-24	0.011039	0.005319	0.0116	0.005589	0.020583	0.009917	0.016737	0.008065	0.0159	0.007661	35.89539	3.313088e-26	72.46398	3.332966e-25	71.66468	0.0	49.03616	3.333252e-25	54.56744	0.0	92.76953	0.0	0.023111	0.011893	0.019357	0.009632	0.018318	0.009675	0.028447	0.019632	0.005504	0.00211	0.00434	0.001664	0.005004	0.001918	0.006498	0.001853	0.021653	0.018858	0.006376	0.003339	0.002393	0.003292	0.001055	0.001452	0.001503	0.002068	0.007957	0.01258	0.041119	0.012034	0.023626	0.010705	0.005816	0.003685	0.003218	0.002804	0.003273	0.002852	0.00291	0.000911	0.003892	0.001605	0.043215	0.025172	0.042147	0.01164	0.013968	0.002407	0.033753	0.015579	0.084669	0.047416	0.030686	0.007475	0.003897	0.003118	0.002824	0.002259	0.003437	0.001983	0.029106	0.012807	76.11499	0.0	0.046102	0.021898	0.203459	0.005518	0.002682	0.000223	0.00444	0.000369	0.022085	0.001836	0.018817	0.002239	0.004516	0.00075	0.004254	0.000169	0.167143	0.003845	0.001902	0.000929	0.015718	0.015831	0.00178	0.000822	0.001841	0.00085	0.002803	0.000685	0.014642	0.003579	0.027562	0.002526	0.035425	0.007734	0.077527	0.023833	0.027558	0.025218	0.034402	0.005777	0.009633	0.014163	0.012929	0.010933	0.004087	0.01382	0.005108	0.011797	0.005289	0.006377	0.006334	0.006964	0.004437	0.007617	0.004207	0.007222	0.006515	0.005366	0.023215	0.015846	0.010218	0.006975	0.038396	0.006148	22.46283	7.871059e-26	11.13411	3.361424e-25	18.74616	3.296165e-25	27.98768	3.370467e-25	32.47894	8.594241e-26	63.81877	0.0	0.032964	0.015184	0.027192	0.013729	0.007962	0.002383	0.02138	0.008757	0.022239	0.019862	0.036189	0.013256	0.019879	0.008786	0.013771	0.002986	0.004935	0.002378	0.004021	0.001937	10.56986	1.601792e-13	14.57936	2.209403e-13	19.87988	3.012669e-13	24.45074	3.705358e-13	23.61157	3.578183e-13	50.96676	7.723688e-13	21.2934	3.398291e-25	16.31768	0.0	21.15114	8.483442e-26	6.620245	1.161618e-26	5.387928	2.104679e-26	11.07489	0.0	6.690278	0.0	21.84747	0.0	18.86606	7.686560e-26	26.74521	2.125622e-24	17.53896	7.547817e-25	15.2731	7.622792e-25	7.780674	1.373914e-24	35.01923	5.306902e-13	18.98862	2.877589e-13	14.42032	7.631948e-25	16.00222	2.798916e-24	40.99183	7.541643e-25	37.58163	5.383057e-25	3.547835	0.0	34.96974	2.003576e-26	105.8952	0.0	80.62691	3.315878e-22	36.44118	0.0	31.60874	0.0	0.048071	0.00153	0.038926	0.004357	0.01592	0.006248	0.005553	0.002676	0.004345	0.002093	18.81272	7.112188e-23	15.6488	0.0	0.027928	0.011203	45.47781	0.0	0.082113	0.034165	34.57665	0.0	8.426783	2.095524e-26	22.79576	7.565951e-25	33.26721	7.645297e-25	18.7625	1.360533e-24	14.43095	5.837865e-25	0.032542	0.005464	0.021149	0.018736	16.76996	0.0	0.004631	0.002231	0.002014	0.00097	0.002583	0.000796	0.010455	0.005038	0.00451	0.002173	0.00317	0.001528	0.004195	0.004084	0.027372	0.008274	64.70937	0.0	80.91752	0.0	102.0578	7.392213e-25	47.21349	0.0	0.015279	0.007224	0.0169	0.002843	0.028449	0.004785	42.44363	7.013738e-22	12.77701	5.615462e-23	27.49709	2.144340e-26	5.377964	0.0	2.779566	8.363599e-29	2.251996	6.694277e-27	9.412791	1.905699e-25	3.21121	8.308066e-27	2.603956	6.693013e-27	5.753166	1.565872e-25	17.9649	5.368832e-27	0.087385	0.015387	0.017306	0.002236	0.014931	0.001814	26.05582	2.110405e-24	0.008468	0.004144	0.017298	0.008858	25.21477	2.158086e-26	13.48946	8.444945e-26	8.799599	0.0	11.09779	8.548555e-26	26.07811	0.0	17.34526	0.0	20.64109	2.102439e-26	0.002894	0.007571	0.002928	0.007658

3 rows × 1048 columns

Subcase 4: Specific Timestamps + Specific Values + Filtering

If we want to filter for more than just the container, we have to filter tks outside the function and then pass them. Works same way as for model_data.

all_tks = s3s.GetTksofElementType(s3s.ObjectTypes.Pipe)

len(all_tks)

524

good_tks = []

for tk in all_tks:
    if s3s.GetValue(tk, "FkCont")[0] == "5029128874972463118":
        if s3s.GetValue(tk, "bz.Irtrenn")[0] == "0": # Rohr nicht getrennt
            good_tks.append(tk)

len(good_tks)

480

(s3s.generate_element_results_dataframe(element_type=s3s.ObjectTypes.Pipe
                                        ,tks=good_tks # here we specify that not all available tks should be used
                                        ,properties=["DTTR", "PHR"]
                                        ,timestamps=[0, 5, -2]
                                        )).head(3)

[2026-03-15 23:20:39,326] INFO in sir3stoolkit.mantle.dataframes: [results] Generating results dataframe for element type: ObjectTypes.Pipe
[2026-03-15 23:20:39,564] INFO in sir3stoolkit.mantle.dataframes: [Resolving Timestamps] 3 valid timestamp(s) will be used.
[2026-03-15 23:20:39,579] INFO in sir3stoolkit.mantle.dataframes: [Resolving tks] Retrieved 524 element(s) of element type ObjectTypes.Pipe.
[2026-03-15 23:20:39,595] INFO in sir3stoolkit.mantle.dataframes: [Resolving tks] 480 tks remain after filtering for given tks.
[2026-03-15 23:20:39,601] INFO in sir3stoolkit.mantle.dataframes: [results] Using 2 result properties.
[2026-03-15 23:20:39,652] INFO in sir3stoolkit.mantle.dataframes: [results] Retrieving result values...
[2026-03-15 23:20:40,778] INFO in sir3stoolkit.mantle.dataframes: [results] 0 fully NaN columns dropped.
[2026-03-15 23:20:41,137] INFO in sir3stoolkit.mantle.dataframes: [results] Done. Shape: (3, 960)

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timestamp
2023-02-13 00:00:00.000 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2023-02-13 05:00:00.000 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8.48974	0.0	20.08946	1.893138e-25	20.21883	5.148573e-27	24.84862	1.196296e-26	25.31222	1.102300e-25	30.19752	8.331703e-26	36.38173	2.084475e-26	34.99198	8.935195e-26	6.78462	2.116374e-26	33.2108	1.908083e-25	50.19061	3.411726e-25	47.19448	0.0	50.84296	3.236694e-25	50.56349	3.218903e-25	41.89281	1.370205e-24	9.602071	1.350304e-24	0.011039	0.005319	0.0116	0.005589	0.020583	0.009917	0.016737	0.008065	0.0159	0.007661	72.46398	3.332966e-25	71.66468	0.0	49.03616	3.333252e-25	0.023111	0.011893	0.019357	0.009632	0.018318	0.009675	0.028447	0.019632	0.005504	0.00211	0.00434	0.001664	0.005004	0.001918	0.006498	0.001853	0.021653	0.018858	0.006376	0.003339	0.002393	0.003292	0.001055	0.001452	0.001503	0.002068	0.007957	0.01258	0.041119	0.012034	0.023626	0.010705	0.005816	0.003685	0.003218	0.002804	0.003273	0.002852	0.00291	0.000911	0.003892	0.001605	0.043215	0.025172	0.042147	0.01164	0.013968	0.002407	0.033753	0.015579	0.084669	0.047416	0.030686	0.007475	0.003897	0.003118	0.002824	0.002259	0.003437	0.001983	0.029106	0.012807	0.046102	0.021898	0.203459	0.005518	0.002682	0.000223	0.00444	0.000369	0.022085	0.001836	0.018817	0.002239	0.004516	0.00075	0.004254	0.000169	0.167143	0.003845	0.001902	0.000929	0.015718	0.015831	0.00178	0.000822	0.001841	0.00085	0.002803	0.000685	0.014642	0.003579	0.027562	0.002526	0.035425	0.007734	0.077527	0.023833	0.027558	0.025218	0.034402	0.005777	0.009633	0.014163	0.012929	0.010933	0.004087	0.01382	0.005108	0.011797	0.005289	0.006377	0.006334	0.006964	0.004437	0.007617	0.004207	0.007222	0.006515	0.005366	0.023215	0.015846	0.010218	0.006975	0.038396	0.006148	11.13411	3.361424e-25	18.74616	3.296165e-25	27.98768	3.370467e-25	32.47894	8.594241e-26	0.032964	0.015184	0.027192	0.013729	0.007962	0.002383	0.02138	0.008757	0.022239	0.019862	0.036189	0.013256	0.019879	0.008786	0.013771	0.002986	0.004935	0.002378	0.004021	0.001937	10.56986	1.601792e-13	14.57936	2.209403e-13	19.87988	3.012669e-13	24.45074	3.705358e-13	23.61157	3.578183e-13	50.96676	7.723688e-13	21.2934	3.398291e-25	16.31768	0.0	21.15114	8.483442e-26	6.620245	1.161618e-26	5.387928	2.104679e-26	11.07489	0.0	6.690278	0.0	21.84747	0.0	18.86606	7.686560e-26	26.74521	2.125622e-24	17.53896	7.547817e-25	15.2731	7.622792e-25	7.780674	1.373914e-24	35.01923	5.306902e-13	18.98862	2.877589e-13	14.42032	7.631948e-25	16.00222	2.798916e-24	40.99183	7.541643e-25	37.58163	5.383057e-25	3.547835	0.0	34.96974	2.003576e-26	105.8952	0.0	80.62691	3.315878e-22	0.048071	0.00153	0.038926	0.004357	0.01592	0.006248	0.005553	0.002676	0.004345	0.002093	18.81272	7.112188e-23	0.027928	0.011203	0.082113	0.034165	8.426783	2.095524e-26	22.79576	7.565951e-25	33.26721	7.645297e-25	18.7625	1.360533e-24	14.43095	5.837865e-25	0.032542	0.005464	0.021149	0.018736	0.004631	0.002231	0.002014	0.00097	0.002583	0.000796	0.010455	0.005038	0.00451	0.002173	0.00317	0.001528	0.004195	0.004084	0.027372	0.008274	64.70937	0.0	80.91752	0.0	102.0578	7.392213e-25	0.015279	0.007224	0.0169	0.002843	0.028449	0.004785	42.44363	7.013738e-22	12.77701	5.615462e-23	27.49709	2.144340e-26	5.377964	0.0	2.779566	8.363599e-29	2.251996	6.694277e-27	9.412791	1.905699e-25	3.21121	8.308066e-27	2.603956	6.693013e-27	5.753166	1.565872e-25	17.9649	5.368832e-27	0.087385	0.015387	0.017306	0.002236	0.014931	0.001814	26.05582	2.110405e-24	0.008468	0.004144	0.017298	0.008858	25.21477	2.158086e-26	13.48946	8.444945e-26	8.799599	0.0	11.09779	8.548555e-26	26.07811	0.0	17.34526	0.0	20.64109	2.102439e-26	0.002894	0.007571	0.002928	0.007658
2023-02-13 23:00:00.000 +01:00	0.013437	0.010421	0.025371	0.014625	0.017832	0.010872	0.002972	0.001812	0.003259	0.001987	0.00362	0.002207	0.039475	0.018532	0.001627	0.002248	0.002951	0.001065	0.00225	0.000812	0.012035	0.004345	0.015949	0.004761	0.014919	0.009291	0.057364	0.003588	0.057824	0.032887	64.19534	3.053230e-24	51.01035	7.638580e-24	83.9612	2.910067e-24	64.28724	3.057601e-24	43.0797	1.950208e-24	0.092052	0.003742	0.00784	0.002576	0.017054	0.006804	0.032463	0.015606	0.012821	0.008887	0.001881	0.003044	0.005522	0.008423	0.005497	0.008385	0.009616	0.01367	0.00408	0.005393	0.023947	0.022913	13.53016	8.613383e-26	12.6086	1.907738e-25	10.49419	3.382087e-25	8.190004	3.051250e-24	0.032132	0.029687	0.007637	0.003357	0.011384	0.007474	0.009444	0.008443	0.015609	0.008071	0.01357	0.008731	0.023328	0.010592	59.923	0.0	14.00829	3.043193e-24	5.560995	1.187491e-26	17.37406	4.733136e-26	126.116	8.920691e-26	21.51779	0.0	0.028187	0.025678	0.038952	0.004936	0.130386	0.002724	0.016946	0.000045	42.03592	1.073386e-25	23.02995	1.672062e-21	117.7475	8.328753e-24	25.77541	3.081205e-24	18.48974	8.841090e-26	20.08946	2.132400e-24	20.21883	1.330405e-25	24.84862	1.196296e-26	25.31222	1.071969e-25	30.19752	8.543967e-26	36.38173	2.084475e-26	34.99198	1.940497e-25	6.78462	2.116374e-26	33.2108	1.908083e-25	50.19061	8.527610e-26	47.19448	0.0	50.84296	0.0	50.56349	0.0	41.89281	1.290790e-24	9.602071	7.631413e-25	0.010837	0.005245	0.011387	0.005511	0.020205	0.009779	0.01643	0.007952	0.015608	0.007554	72.46398	1.359455e-24	71.66468	0.0	49.03616	0.0	0.022689	0.01168	0.019005	0.009458	0.018562	0.008927	0.030195	0.016532	0.005952	0.001709	0.004693	0.001348	0.005412	0.001554	0.007105	0.001468	0.02445	0.014112	0.008329	0.001894	0.002318	0.003328	0.001022	0.001468	0.001456	0.002091	0.013377	0.003171	0.039901	0.012031	0.022962	0.010703	0.005711	0.003578	0.003159	0.002729	0.003213	0.002776	0.002857	0.000881	0.003821	0.001556	0.042426	0.02448	0.027605	0.031203	0.013715	0.002306	0.033139	0.015126	0.121582	0.016338	0.030131	0.007245	0.003501	0.003602	0.002537	0.002611	0.003056	0.002328	0.028583	0.012432	0.045279	0.021157	0.201245	0.005192	0.002646	0.000212	0.004381	0.000352	0.02179	0.001748	0.018555	0.002141	0.004451	0.00072	0.002772	0.000448	0.164562	0.00366	0.001868	0.000903	0.015436	0.015433	0.001748	0.000796	0.001808	0.000823	0.002753	0.00066	0.014381	0.00345	0.027072	0.002408	0.034794	0.007449	0.076125	0.022934	0.027069	0.024718	0.033999	0.005591	0.00952	0.013961	0.012777	0.010746	0.00404	0.013655	0.005048	0.011634	0.005227	0.006267	0.00626	0.00684	0.004385	0.007488	0.004158	0.0071	0.006439	0.005254	0.022945	0.015466	0.010101	0.006809	0.037958	0.005952	11.13411	1.344570e-24	18.74616	3.296165e-25	27.98768	0.0	32.47894	3.361727e-25	0.032378	0.014523	0.026701	0.013308	0.007818	0.002306	0.020992	0.008493	0.028376	0.01179	0.035534	0.012847	0.01952	0.008507	0.013524	0.002875	0.004844	0.002345	0.003947	0.00191	10.56986	1.001119e-14	14.57936	1.380879e-14	19.87988	1.882906e-14	24.45074	2.315853e-14	23.61157	2.236356e-14	50.96676	4.827315e-14	21.2934	2.114998e-24	16.31768	1.346276e-24	21.15114	1.355253e-24	6.620245	2.245649e-25	5.387928	8.463555e-26	11.07489	1.919456e-25	6.690278	0.0	21.84747	8.901269e-26	18.86606	0.0	26.74521	5.467291e-24	17.53896	1.341834e-24	15.2731	2.117442e-24	7.780674	2.114256e-24	35.01923	3.316817e-14	18.98862	1.798501e-14	14.42032	2.672777e-26	16.00222	8.405074e-26	40.99183	8.478477e-24	37.58163	6.890579e-24	3.547835	6.404327e-25	34.96974	0.0	105.8952	7.490393e-26	80.62691	3.468148e-22	0.047206	0.001445	0.038217	0.004156	0.015629	0.006058	0.005451	0.002638	0.004265	0.002064	18.81272	5.724689e-23	0.027419	0.010803	0.080638	0.032965	8.426783	4.756933e-26	22.79576	3.411914e-25	33.26721	8.494775e-26	18.7625	0.0	14.43095	2.230933e-25	0.032167	0.00529	0.020764	0.018191	0.004546	0.0022	0.001977	0.000957	0.002536	0.000782	0.010263	0.004968	0.004427	0.002143	0.003112	0.001506	0.005878	0.001646	0.026869	0.008126	64.70937	0.0	80.91752	0.0	102.0578	1.663248e-24	0.015003	0.006977	0.016596	0.002722	0.027941	0.004584	42.44363	7.323274e-22	12.77701	5.280877e-23	27.49709	2.123966e-24	5.377964	5.908219e-25	2.779566	2.229998e-25	2.251996	2.236828e-25	9.412791	1.038240e-24	3.21121	3.388132e-25	2.603956	4.532830e-25	5.753166	1.074086e-25	...	51.01035	3.356497e-25	83.9612	1.997850e-24	64.28724	2.228174e-24	43.0797	1.950208e-24	0.093736	0.003953	0.007984	0.002667	0.01737	0.006993	0.033065	0.01598	0.01306	0.009075	0.001917	0.003084	0.005625	0.008539	0.005599	0.008499	0.009795	0.013864	0.004156	0.005472	0.024393	0.0233	13.53016	0.0	12.6086	4.527567e-25	10.49419	7.647321e-25	8.190004	3.390278e-25	0.03272	0.030558	0.007778	0.003467	0.011594	0.007695	0.009619	0.008671	0.015899	0.008306	0.013823	0.00897	0.023763	0.010876	59.923	0.0	14.00829	4.687399e-26	5.560995	6.491837e-26	17.37406	1.893444e-25	126.116	0.0	21.51779	2.191737e-26	0.028714	0.025998	0.036726	0.005907	0.115364	0.003698	0.013126	0.000078	42.03592	1.905105e-25	23.02995	4.290247e-23	117.7475	3.331501e-25	25.77541	0.0	18.48974	0.0	20.08946	1.893138e-25	20.21883	5.148573e-27	24.84862	1.196296e-26	25.31222	1.102300e-25	30.19752	8.331703e-26	36.38173	2.084475e-26	34.99198	8.935195e-26	6.78462	2.116374e-26	33.2108	1.908083e-25	50.19061	3.411726e-25	47.19448	0.0	50.84296	3.236694e-25	50.56349	3.218903e-25	41.89281	1.370205e-24	9.602071	1.350304e-24	0.011039	0.005319	0.0116	0.005589	0.020583	0.009917	0.016737	0.008065	0.0159	0.007661	72.46398	3.332966e-25	71.66468	0.0	49.03616	3.333252e-25	0.023111	0.011893	0.019357	0.009632	0.018318	0.009675	0.028447	0.019632	0.005504	0.00211	0.00434	0.001664	0.005004	0.001918	0.006498	0.001853	0.021653	0.018858	0.006376	0.003339	0.002393	0.003292	0.001055	0.001452	0.001503	0.002068	0.007957	0.01258	0.041119	0.012034	0.023626	0.010705	0.005816	0.003685	0.003218	0.002804	0.003273	0.002852	0.00291	0.000911	0.003892	0.001605	0.043215	0.025172	0.042147	0.01164	0.013968	0.002407	0.033753	0.015579	0.084669	0.047416	0.030686	0.007475	0.003897	0.003118	0.002824	0.002259	0.003437	0.001983	0.029106	0.012807	0.046102	0.021898	0.203459	0.005518	0.002682	0.000223	0.00444	0.000369	0.022085	0.001836	0.018817	0.002239	0.004516	0.00075	0.004254	0.000169	0.167143	0.003845	0.001902	0.000929	0.015718	0.015831	0.00178	0.000822	0.001841	0.00085	0.002803	0.000685	0.014642	0.003579	0.027562	0.002526	0.035425	0.007734	0.077527	0.023833	0.027558	0.025218	0.034402	0.005777	0.009633	0.014163	0.012929	0.010933	0.004087	0.01382	0.005108	0.011797	0.005289	0.006377	0.006334	0.006964	0.004437	0.007617	0.004207	0.007222	0.006515	0.005366	0.023215	0.015846	0.010218	0.006975	0.038396	0.006148	11.13411	3.361424e-25	18.74616	3.296165e-25	27.98768	3.370467e-25	32.47894	8.594241e-26	0.032964	0.015184	0.027192	0.013729	0.007962	0.002383	0.02138	0.008757	0.022239	0.019862	0.036189	0.013256	0.019879	0.008786	0.013771	0.002986	0.004935	0.002378	0.004021	0.001937	10.56986	1.601792e-13	14.57936	2.209403e-13	19.87988	3.012669e-13	24.45074	3.705358e-13	23.61157	3.578183e-13	50.96676	7.723688e-13	21.2934	3.398291e-25	16.31768	0.0	21.15114	8.483442e-26	6.620245	1.161618e-26	5.387928	2.104679e-26	11.07489	0.0	6.690278	0.0	21.84747	0.0	18.86606	7.686560e-26	26.74521	2.125622e-24	17.53896	7.547817e-25	15.2731	7.622792e-25	7.780674	1.373914e-24	35.01923	5.306902e-13	18.98862	2.877589e-13	14.42032	7.631948e-25	16.00222	2.798916e-24	40.99183	7.541643e-25	37.58163	5.383057e-25	3.547835	0.0	34.96974	2.003576e-26	105.8952	0.0	80.62691	3.315878e-22	0.048071	0.00153	0.038926	0.004357	0.01592	0.006248	0.005553	0.002676	0.004345	0.002093	18.81272	7.112188e-23	0.027928	0.011203	0.082113	0.034165	8.426783	2.095524e-26	22.79576	7.565951e-25	33.26721	7.645297e-25	18.7625	1.360533e-24	14.43095	5.837865e-25	0.032542	0.005464	0.021149	0.018736	0.004631	0.002231	0.002014	0.00097	0.002583	0.000796	0.010455	0.005038	0.00451	0.002173	0.00317	0.001528	0.004195	0.004084	0.027372	0.008274	64.70937	0.0	80.91752	0.0	102.0578	7.392213e-25	0.015279	0.007224	0.0169	0.002843	0.028449	0.004785	42.44363	7.013738e-22	12.77701	5.615462e-23	27.49709	2.144340e-26	5.377964	0.0	2.779566	8.363599e-29	2.251996	6.694277e-27	9.412791	1.905699e-25	3.21121	8.308066e-27	2.603956	6.693013e-27	5.753166	1.565872e-25	17.9649	5.368832e-27	0.087385	0.015387	0.017306	0.002236	0.014931	0.001814	26.05582	2.110405e-24	0.008468	0.004144	0.017298	0.008858	25.21477	2.158086e-26	13.48946	8.444945e-26	8.799599	0.0	11.09779	8.548555e-26	26.07811	0.0	17.34526	0.0	20.64109	2.102439e-26	0.002894	0.007571	0.002928	0.007658

3 rows × 960 columns

Subcase 5: Specific Vectorized results + Specific Timestamps

For pipes we have interior point result values. These are usually found as vectors with the postfix VEC.

available_result_props=s3s.GetResultProperties_from_elementType(s3s.ObjectTypes.Pipe,False)

available_result_props

['A',
 'ACALC',
 'CPI',
 'CPK',
 'DH',
 'DP',
 'DRAGRED',
 'DRAKONZ',
 'DSI',
 'DSK',
 'DTTR',
 'DWVERL',
 'DWVERLABS',
 'ETAAV',
 'FS',
 'HR',
 'HVEC',
 'IAKTIV',
 'IRTRENN',
 'JV',
 'JV2',
 'LAMBDA',
 'LECKEINAUS',
 'LECKMENGE',
 'LECKORT',
 'LINEPACK',
 'LINEPACKGEOM',
 'LINEPACKRATE',
 'MAINELEMENT',
 'MAV',
 'MI',
 'MK',
 'MKOND',
 'MMAX_INST',
 'MMIN_INST',
 'MVEC',
 'MVECMAX_INST',
 'MVECMIN_INST',
 'PAV',
 'PDAMPF',
 'PHR',
 'PHVEC',
 'PMAX',
 'PMIN',
 'PR',
 'PVEC',
 'PVECMAX_INST',
 'PVECMIN_INST',
 'QI2',
 'QK2',
 'QMAV',
 'QMI',
 'QMK',
 'QMMAX_INST',
 'QMMIN_INST',
 'QMVEC',
 'QSVB',
 'RHOAV',
 'RHOI',
 'RHOK',
 'RHOVEC',
 'SVEC',
 'TAV',
 'TI',
 'TK',
 'TTRVEC',
 'TVEC',
 'TVECMAX_INST',
 'TVECMIN_INST',
 'VAV',
 'VI',
 'VK',
 'VMAX_INST',
 'VMIN_INST',
 'VOLDA',
 'WALTERI',
 'WALTERK',
 'WVL',
 'ZAUS',
 'ZEIN',
 'ZHKNR',
 'ZVEC']

available_result_vector_props=[available_result_props for available_result_props in available_result_props if "VEC" in available_result_props]

available_result_vector_props

['HVEC',
 'MVEC',
 'MVECMAX_INST',
 'MVECMIN_INST',
 'PHVEC',
 'PVEC',
 'PVECMAX_INST',
 'PVECMIN_INST',
 'QMVEC',
 'RHOVEC',
 'SVEC',
 'TTRVEC',
 'TVEC',
 'TVECMAX_INST',
 'TVECMIN_INST',
 'ZVEC']

df_pipes = s3s.generate_element_results_dataframe(element_type=s3s.ObjectTypes.Pipe
                                        ,properties=["TTRVEC", "MVEC", "DTTR"]
                                        ,timestamps=[0, 5, -2]
                                        )

[2026-03-15 23:20:43,291] INFO in sir3stoolkit.mantle.dataframes: [results] Generating results dataframe for element type: ObjectTypes.Pipe
[2026-03-15 23:20:43,553] INFO in sir3stoolkit.mantle.dataframes: [Resolving Timestamps] 3 valid timestamp(s) will be used.
[2026-03-15 23:20:43,558] INFO in sir3stoolkit.mantle.dataframes: [Resolving tks] Retrieved 524 element(s) of element type ObjectTypes.Pipe.
[2026-03-15 23:20:43,562] INFO in sir3stoolkit.mantle.dataframes: [results] Using 3 result properties.
[2026-03-15 23:20:43,590] INFO in sir3stoolkit.mantle.dataframes: [results] Retrieving result values...
[2026-03-15 23:20:46,265] INFO in sir3stoolkit.mantle.dataframes: [results] 0 fully NaN columns dropped.
[2026-03-15 23:20:46,773] INFO in sir3stoolkit.mantle.dataframes: [results] Done. Shape: (3, 1572)

df_pipes.head(3)

tk	5442010239090746007			4917786378639043296			4762482310382009633			4987229536643024523			5722206630503885118			5089459212485379804			5526871502288882655			4809089329099085219			5170001087020228683			5625716875961234775			5501916898830363065			5192970129555982907			5027225217797463802			5107343838750080243			4840056338230495043			5700872284015490704			5290590848336792638			4781821593135991761			4770083637349644299			5140383994159421977			4615723899944629797			5485743457841402038			5061682782623660813			4868922965129592512			5253822763469470014			5468996363795343031			5339499657518903527			4811306899232458618			4928779983564758026			4965578769510488820			5600841315591171772			4995034655758156710			5209057104414292468			5726827761099671871			5080791944541542127			4996979568467922520			4893521402166887668			4943852467771545411			5294908835443772392			5407639481169980338			5494345815849234157			5559756735287401600			4688455252738739891			5120913591494019846			5189136483684313738			5027271755713739562			4843364651593046845			4763398616537422727			5211657964305638265			4899878437571936054			5017291090985710926			4968195666913259627			4872293615039533867			5073852406571450055			5460451359190976355			5680559127926603859			5701217076123185999			5343389149567015241			5004534437760811077			5638727652971481339			4933247170382646480			5144558095415012328			4676843093813396651			5238385499211955735			5431464167607748731			5021757307925561906			5735390708503613465			5602200558168325137			4976126317058169697			5611058499224570176			4951309552891536851			4734625425618016004			5003475594426980558			5199984776776235548			5146987453990281112			4664282009021425543			4730098385004060223			5143417057295500465			4870893641534242754			4751771958060245818			5431352512414392985			4756919352045195395			4950699445422043390			5443612009555325057			5130272059781459965			5030450908543536722			5425728209090108132			4897883139609927597			5385910423114382788			4815053638180850703			5520594566396266859			4822932207368532352			4943632133505495565			5136719248606301905			5222700144096421193			5209596079625295991			5215757535605464866			5089350764087843246			4922208128354560629			5176883269076091732			4882993749777364317			5374456943006507008			4843836890906700052			5535463940319820632			5012186927559751405			4986912592668362327			5119633900217288954			5293317689029296733			4766100927082653384			5638908776577558151			5244494914545547298			4818046255571175936			4826614335972511296			5223081641641736592			5248841557788033271			5612538195203776712			5446352019210100674			5198739705259994278			5120004980087359327			5081007708328729580			5332936729509410779			5193926613850153217			5669055683311185692			5142801769428353146			5570925755149935463			5089627882145801048			5749509498631743083			5313314888424094938			5672198676406030965			5492269585462839687			4878085949235357089			5009009696813138306			5417154223408487165			4888087184557203150			5482200169109927461			5506250915346749683			5249576152024204638			5377200445080630699			5293057810555927426			4869711570166799356			5116990929886803340			5735615340560878820			4881353465437199724			5621715799375882738			5012002718030878203			5398733809575429001			5028247962181469636			4900101542637177072			5277687384123072302			5494173646602854486			...	5372713622801715679			5449014635431218568			4745781253473544150			4813723342227793459			4832698291978284341			5497524052304204460			5164866772337285491			5535881834434832605			5691580718686834263			4753421910059873362			5102328320686607707			5388236272637760764			5244316939682317750			4629907932103493008			5250108024251858510			5539222534062219365			5724709454522975449			4946907145947093770			5010841248861547024			4946660727138603312			4730481032770365008			4646777926018012533			4685096220994950172			4867029473074725377			5476573944120214165			4757737626092948164			4736379593968735345			5234354459699789538			5519100829614390747			4830938580045344276			5749276576386297901			5205186198770431875			4880674315427701471			5042815752291441380			4720252396094244657			5128607651797435321			5355887361787275905			5397834454637092532			5047118840904603964			5354238701959876646			5191878519166468059			4672178163429150245			4890718426220097002			5545776320196545942			5251654897528003108			4665618379396092129			5526390888327447502			5027758408993827300			4808816045815330468			4719684468262235792			4653917802285889060			5100363997794015782			5542353615796683962			4856621214843687119			5091035922526307609			5462527908760086398			5299893048728663899			5025945677694931826			5216742060270992761			5206715119922080390			5614561155954926685			4974194145964522381			5671958289203153153			4990543560575760524			5247124307283071566			4735975890664373580			4842513789798839810			5285960184348381629			4957901171316760845			5069492939710800234			4751609783097570467			4689288032911398385			5283312165961731762			4716572325333554424			5200557978311528793			5345505431541824275			5763157564781355962		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property	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	...	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR	TTRVEC	MVEC	DTTR
timestamp
2023-02-13 00:00:00.000 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2023-02-13 05:00:00.000 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2023-02-13 23:00:00.000 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t0.002893685	8.40759\t8.40759	0.002894	0.04499983\t0.04207175	-8.407589\t-8.407589	0.002928

3 rows × 1572 columns

As can be seen, the vectorized result values are written as strings with “/” seperators. For better access we can extend these values to a multiindex using add_interior_points_as_multiindex().

df_pipes_interior_points = s3s.add_interior_points_as_multiindex(df_pipes)

df_pipes_interior_points.head(3)

tk	5442010239090746007											4917786378639043296															4762482310382009633													4987229536643024523					5722206630503885118					5089459212485379804					5526871502288882655																					4809089329099085219					5170001087020228683					5625716875961234775					5501916898830363065									5192970129555982907									5027225217797463802									5107343838750080243													4840056338230495043																									5700872284015490704																																					5290590848336792638					4781821593135991761																	4770083637349644299															5140383994159421977																					4615723899944629797																	5485743457841402038													5061682782623660813															4868922965129592512							5253822763469470014											5468996363795343031																	5339499657518903527											4811306899232458618					4928779983564758026							4965578769510488820							5600841315591171772											4995034655758156710							5209057104414292468																	5726827761099671871															5080791944541542127							4996979568467922520							4893521402166887668							4943852467771545411					5294908835443772392							5407639481169980338							...	5547929108205842356				5325979640694265557									5309389718470399165											4858769154205497127							4744152276765399160							4832141333841349233											5685600617346450154											4794261027124244870							5299861566239260044							4919359344392474301					4819106626657300012					5634392781200984475											4895368922126406008							5377073214297285114					4806335761459244120							5445675821666151876																	5151948180726626898																	5216604222073162798																					4922860284273709287																									4623301797443553869													4936935202016711641									5547051071040108641							5320576812120795706									5693000264828698789													5411578293161860891							4905468706944801791									5579607382442232035					5506211537324438173					5542801165145139080					5013949825709681825					4631495679500266540					5268910820355280011					4673529796143308930					5502845593951347652							5269134948859572308																																			5491353045770208506									5351083508550202918									5405503540588733856									5409157591891833907									5288551187767515760													5273136311620767333									5331559348183931626							5263881428814102490					5139154449387664728							4919408196640282331									4957957828740199285							5499776682108862751									5285235772707481262					5373158549695106826
name	Rohr V-K03S V-K13S											Rohr V-K13S V-K23S															Rohr V-K23S V-K33S													Rohr V-K33S V-K43S					Rohr V-K43S V-K53S					Rohr V-K53S V-K63S					Rohr V-K63S V-K73S																					Rohr V-K73S V-K83S					Rohr V-K83S V-K93S					Rohr V-K93S V-K103S					Rohr V-K103S V-K113S									Rohr V-K113S V-K123S									Rohr V-K123S V-K133S									Rohr V-K133S V-K143S													Rohr V-K153S V-K163S																									Rohr V-K163S V-K143S																																					Rohr V-K143S V-K173S					Rohr V-K173S V-K183S																	Rohr V-K183S V-K193S															Rohr V-K193S V-K203S																					Rohr V-K203S V-K213S																	Rohr V-K213S V-K223S													Rohr V-K233S V-K243S															Rohr V-K243S V-K253S							Rohr V-K253S V-K263S											Rohr V-K263S V-K273S																	Rohr V-K273S V-K153S											Rohr V-K283S V-K293S					Rohr V-K293S V-K303S							Rohr V-K303S V-K313S							Rohr V-K313S V-K323S											Rohr V-K323S V-K333S							Rohr V-K333S V-K03S																	Rohr V-K03S V-K343S															Rohr V-K353S V-K363S							Rohr V-K363S V-K373S							Rohr V-K373S V-K383S							Rohr V-K383S V-K393S					Rohr V-K393S V-K403S							Rohr V-K403S V-K413S							...	Rohr R-K4573S R-K4583S				Rohr R-K4583S R-K4593S									Rohr R-K4593S R-K4603S											Rohr R-K4603S R-K4613S							Rohr R-K4613S R-K4313S							Rohr R-K3893S R-K4623S											Rohr R-K3563S R-K4633S											Rohr R-K3303S R-K4523S							Rohr R-K4523S R-K4643S							Rohr R-K4643S R-K4173S					Rohr R-K4653S R-K3413S					Rohr R-K3413S R-K4663S											Rohr R-K4663S R-K4673S							Rohr R-K4673S R-K3363S					Rohr R-K3063S R-K4543S							Rohr R-K4543S R-K4653S																	Rohr R-K4683S R-K4693S																	Rohr R-K4693S R-K4703S																					Rohr R-K4703S R-K4713S																									Rohr R-K4713S R-K2713S													Rohr R-K2643S R-K4723S									Rohr R-K4723S R-K4733S							Rohr R-K4733S R-K4743S									Rohr R-K4743S R-K4753S													Rohr R-K4753S R-K4763S							Rohr R-K4433S R-K4773S									Rohr R-K4773S R-K4783S					Rohr R-K4783S R-K4793S					Rohr R-K4793S R-K4803S					Rohr R-K4803S R-K4813S					Rohr R-K4813S R-K4823S					Rohr R-K4823S R-K4833S					Rohr R-K4833S R-K4843S					Rohr R-K4843S R-K4853S							Rohr R-K2953S R-K4863S																																			Rohr R-K4863S R-K4873S									Rohr R-K4873S R-K2633S									Rohr R-K3243S R-K4353S									Rohr R-K2953S R-K4883S									Rohr R-K4883S R-K3053S													Rohr R-K4893S R-K4903S									Rohr R-K4903S R-K4913S							Rohr R-K4913S R-K4923S					Rohr R-K4923S R-K4933S							Rohr R-K4933S R-K3223S									Rohr R-K4583S R-K4943S							Rohr R-K4943S R-K4953S									Rohr V-TS-S V-K1403S					Rohr R-TS-S R-K3883S
end_nodes	('5669301360686511351', '5397948523091900401', '-1', '-1')											('5397948523091900401', '5239335112004772156', '-1', '-1')															('5239335112004772156', '5298886695042021307', '-1', '-1')													('5298886695042021307', '4993257270457791438', '-1', '-1')					('4993257270457791438', '5317865645994989592', '-1', '-1')					('5317865645994989592', '5085491372308261877', '-1', '-1')					('5085491372308261877', '4989694427717344427', '-1', '-1')																					('4989694427717344427', '5097833100706648505', '-1', '-1')					('5097833100706648505', '5748593725990350490', '-1', '-1')					('5748593725990350490', '5498236250497948633', '-1', '-1')					('5498236250497948633', '4764732356959599958', '-1', '-1')									('4764732356959599958', '5648425495460137243', '-1', '-1')									('5648425495460137243', '5603354735453128217', '-1', '-1')									('5603354735453128217', '5554918259063780747', '-1', '-1')													('4992867596416688120', '4921884425075838112', '-1', '-1')																									('4921884425075838112', '5554918259063780747', '-1', '-1')																																					('5554918259063780747', '4858392140572707635', '-1', '-1')					('4858392140572707635', '5167668521501299921', '-1', '-1')																	('5167668521501299921', '5362725334032147732', '-1', '-1')															('5362725334032147732', '5129584372458662150', '-1', '-1')																					('5129584372458662150', '5332825919690090061', '-1', '-1')																	('5332825919690090061', '5210475429427900126', '-1', '-1')													('5434645737310584056', '4704578559698354879', '-1', '-1')															('4704578559698354879', '5387381929229094663', '-1', '-1')							('5387381929229094663', '5013768275797703467', '-1', '-1')											('5013768275797703467', '4950953160915280698', '-1', '-1')																	('4950953160915280698', '4992867596416688120', '-1', '-1')											('4837439299025862974', '4875518068053211860', '-1', '-1')					('4875518068053211860', '5707217883382799589', '-1', '-1')							('5707217883382799589', '4828712762216403101', '-1', '-1')							('4828712762216403101', '5367059433340055050', '-1', '-1')											('5367059433340055050', '5238084795626970067', '-1', '-1')							('5238084795626970067', '5669301360686511351', '-1', '-1')																	('5669301360686511351', '5465373302536437394', '-1', '-1')															('5410685318833377843', '4802589718533126890', '-1', '-1')							('4802589718533126890', '5632245635473463750', '-1', '-1')							('5632245635473463750', '5230986483568148243', '-1', '-1')							('5230986483568148243', '4801385615342002045', '-1', '-1')					('4801385615342002045', '4904406262418068960', '-1', '-1')							('4904406262418068960', '5703446318103772746', '-1', '-1')							...	('5221401180418699998', '4863932769493405228', '-1', '-1')				('4863932769493405228', '5675189382062604781', '-1', '-1')									('5675189382062604781', '5176124386205223063', '-1', '-1')											('5176124386205223063', '5611267768413515094', '-1', '-1')							('5611267768413515094', '4976642361691228622', '-1', '-1')							('5227412283498738344', '5569330674289915959', '-1', '-1')											('4661083779224541265', '4641873728186434336', '-1', '-1')											('4706689184833447355', '5191457421068378074', '-1', '-1')							('5191457421068378074', '5207603338578264169', '-1', '-1')							('5207603338578264169', '5469753985021987570', '-1', '-1')					('5078930962877391270', '5355274838118702868', '-1', '-1')					('5355274838118702868', '5714466027671261404', '-1', '-1')											('5714466027671261404', '5229890734982792937', '-1', '-1')							('5229890734982792937', '5039855148666634241', '-1', '-1')					('4644079766211329121', '5554757167019358046', '-1', '-1')							('5554757167019358046', '5078930962877391270', '-1', '-1')																	('5043437169764801353', '5531695788918646648', '-1', '-1')																	('5531695788918646648', '4884146225313121431', '-1', '-1')																					('4884146225313121431', '5395214589547810761', '-1', '-1')																									('5395214589547810761', '5186627743244018598', '-1', '-1')													('4781599812820388803', '5106357201076318352', '-1', '-1')									('5106357201076318352', '4817952446236154840', '-1', '-1')							('4817952446236154840', '5250288294065645228', '-1', '-1')									('5250288294065645228', '5248036124336986711', '-1', '-1')													('5248036124336986711', '5304050774275937189', '-1', '-1')							('4832493725368326102', '5020678070865088221', '-1', '-1')									('5020678070865088221', '4927773616466819887', '-1', '-1')					('4927773616466819887', '5138259542701384037', '-1', '-1')					('5138259542701384037', '4863218137164189270', '-1', '-1')					('4863218137164189270', '5268524137370980576', '-1', '-1')					('5268524137370980576', '5277267967688513217', '-1', '-1')					('5277267967688513217', '5680412857076151835', '-1', '-1')					('5680412857076151835', '4736070283705012552', '-1', '-1')					('4736070283705012552', '5713141944622207943', '-1', '-1')							('5633597914934904333', '5574991124367751476', '-1', '-1')																																			('5574991124367751476', '4975214249705490510', '-1', '-1')									('4975214249705490510', '5094432188973309704', '-1', '-1')									('5646336073962561060', '5587691779179476160', '-1', '-1')									('5633597914934904333', '5612942068225970373', '-1', '-1')									('5612942068225970373', '5229197186883323186', '-1', '-1')													('4739104474621250459', '5580718637254253308', '-1', '-1')									('5580718637254253308', '5169329782661335841', '-1', '-1')							('5169329782661335841', '5085846975953784416', '-1', '-1')					('5085846975953784416', '5330057762618897371', '-1', '-1')							('5330057762618897371', '5000360659046308972', '-1', '-1')									('4863932769493405228', '5295548655235318963', '-1', '-1')							('5295548655235318963', '5475286394948521111', '-1', '-1')									('5172212715463480789', '5392476601138952594', '-1', '-1')					('5093129494518007690', '5337935179219974656', '-1', '-1')
property	TTRVEC					MVEC					DTTR	TTRVEC							MVEC							DTTR	TTRVEC						MVEC						DTTR	TTRVEC		MVEC		DTTR	TTRVEC		MVEC		DTTR	TTRVEC		MVEC		DTTR	TTRVEC										MVEC										DTTR	TTRVEC		MVEC		DTTR	TTRVEC		MVEC		DTTR	TTRVEC		MVEC		DTTR	TTRVEC				MVEC				DTTR	TTRVEC				MVEC				DTTR	TTRVEC				MVEC				DTTR	TTRVEC						MVEC						DTTR	TTRVEC												MVEC												DTTR	TTRVEC																		MVEC																		DTTR	TTRVEC		MVEC		DTTR	TTRVEC								MVEC								DTTR	TTRVEC							MVEC							DTTR	TTRVEC										MVEC										DTTR	TTRVEC								MVEC								DTTR	TTRVEC						MVEC						DTTR	TTRVEC							MVEC							DTTR	TTRVEC			MVEC			DTTR	TTRVEC					MVEC					DTTR	TTRVEC								MVEC								DTTR	TTRVEC					MVEC					DTTR	TTRVEC		MVEC		DTTR	TTRVEC			MVEC			DTTR	TTRVEC			MVEC			DTTR	TTRVEC					MVEC					DTTR	TTRVEC			MVEC			DTTR	TTRVEC								MVEC								DTTR	TTRVEC							MVEC							DTTR	TTRVEC			MVEC			DTTR	TTRVEC			MVEC			DTTR	TTRVEC			MVEC			DTTR	TTRVEC		MVEC		DTTR	TTRVEC			MVEC			DTTR	TTRVEC							...	TTRVEC	MVEC		DTTR	TTRVEC				MVEC				DTTR	TTRVEC					MVEC					DTTR	TTRVEC			MVEC			DTTR	TTRVEC			MVEC			DTTR	TTRVEC					MVEC					DTTR	TTRVEC					MVEC					DTTR	TTRVEC			MVEC			DTTR	TTRVEC			MVEC			DTTR	TTRVEC		MVEC		DTTR	TTRVEC		MVEC		DTTR	TTRVEC					MVEC					DTTR	TTRVEC			MVEC			DTTR	TTRVEC		MVEC		DTTR	TTRVEC			MVEC			DTTR	TTRVEC								MVEC								DTTR	TTRVEC								MVEC								DTTR	TTRVEC										MVEC										DTTR	TTRVEC												MVEC												DTTR	TTRVEC						MVEC						DTTR	TTRVEC				MVEC				DTTR	TTRVEC			MVEC			DTTR	TTRVEC				MVEC				DTTR	TTRVEC						MVEC						DTTR	TTRVEC			MVEC			DTTR	TTRVEC				MVEC				DTTR	TTRVEC		MVEC		DTTR	TTRVEC		MVEC		DTTR	TTRVEC		MVEC		DTTR	TTRVEC		MVEC		DTTR	TTRVEC		MVEC		DTTR	TTRVEC		MVEC		DTTR	TTRVEC		MVEC		DTTR	TTRVEC			MVEC			DTTR	TTRVEC																	MVEC																	DTTR	TTRVEC				MVEC				DTTR	TTRVEC				MVEC				DTTR	TTRVEC				MVEC				DTTR	TTRVEC				MVEC				DTTR	TTRVEC						MVEC						DTTR	TTRVEC				MVEC				DTTR	TTRVEC			MVEC			DTTR	TTRVEC		MVEC		DTTR	TTRVEC			MVEC			DTTR	TTRVEC				MVEC				DTTR	TTRVEC			MVEC			DTTR	TTRVEC				MVEC				DTTR	TTRVEC		MVEC		DTTR	TTRVEC		MVEC		DTTR
interior points	0	1	2	3	4	0	1	2	3	4	-1	0	1	2	3	4	5	6	0	1	2	3	4	5	6	-1	0	1	2	3	4	5	0	1	2	3	4	5	-1	0	1	0	1	-1	0	1	0	1	-1	0	1	0	1	-1	0	1	2	3	4	5	6	7	8	9	0	1	2	3	4	5	6	7	8	9	-1	0	1	0	1	-1	0	1	0	1	-1	0	1	0	1	-1	0	1	2	3	0	1	2	3	-1	0	1	2	3	0	1	2	3	-1	0	1	2	3	0	1	2	3	-1	0	1	2	3	4	5	0	1	2	3	4	5	-1	0	1	2	3	4	5	6	7	8	9	10	11	0	1	2	3	4	5	6	7	8	9	10	11	-1	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	-1	0	1	0	1	-1	0	1	2	3	4	5	6	7	0	1	2	3	4	5	6	7	-1	0	1	2	3	4	5	6	0	1	2	3	4	5	6	-1	0	1	2	3	4	5	6	7	8	9	0	1	2	3	4	5	6	7	8	9	-1	0	1	2	3	4	5	6	7	0	1	2	3	4	5	6	7	-1	0	1	2	3	4	5	0	1	2	3	4	5	-1	0	1	2	3	4	5	6	0	1	2	3	4	5	6	-1	0	1	2	0	1	2	-1	0	1	2	3	4	0	1	2	3	4	-1	0	1	2	3	4	5	6	7	0	1	2	3	4	5	6	7	-1	0	1	2	3	4	0	1	2	3	4	-1	0	1	0	1	-1	0	1	2	0	1	2	-1	0	1	2	0	1	2	-1	0	1	2	3	4	0	1	2	3	4	-1	0	1	2	0	1	2	-1	0	1	2	3	4	5	6	7	0	1	2	3	4	5	6	7	-1	0	1	2	3	4	5	6	0	1	2	3	4	5	6	-1	0	1	2	0	1	2	-1	0	1	2	0	1	2	-1	0	1	2	0	1	2	-1	0	1	0	1	-1	0	1	2	0	1	2	-1	0	1	2	3	4	5	6	...	1	0	1	-1	0	1	2	3	0	1	2	3	-1	0	1	2	3	4	0	1	2	3	4	-1	0	1	2	0	1	2	-1	0	1	2	0	1	2	-1	0	1	2	3	4	0	1	2	3	4	-1	0	1	2	3	4	0	1	2	3	4	-1	0	1	2	0	1	2	-1	0	1	2	0	1	2	-1	0	1	0	1	-1	0	1	0	1	-1	0	1	2	3	4	0	1	2	3	4	-1	0	1	2	0	1	2	-1	0	1	0	1	-1	0	1	2	0	1	2	-1	0	1	2	3	4	5	6	7	0	1	2	3	4	5	6	7	-1	0	1	2	3	4	5	6	7	0	1	2	3	4	5	6	7	-1	0	1	2	3	4	5	6	7	8	9	0	1	2	3	4	5	6	7	8	9	-1	0	1	2	3	4	5	6	7	8	9	10	11	0	1	2	3	4	5	6	7	8	9	10	11	-1	0	1	2	3	4	5	0	1	2	3	4	5	-1	0	1	2	3	0	1	2	3	-1	0	1	2	0	1	2	-1	0	1	2	3	0	1	2	3	-1	0	1	2	3	4	5	0	1	2	3	4	5	-1	0	1	2	0	1	2	-1	0	1	2	3	0	1	2	3	-1	0	1	0	1	-1	0	1	0	1	-1	0	1	0	1	-1	0	1	0	1	-1	0	1	0	1	-1	0	1	0	1	-1	0	1	0	1	-1	0	1	2	0	1	2	-1	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	-1	0	1	2	3	0	1	2	3	-1	0	1	2	3	0	1	2	3	-1	0	1	2	3	0	1	2	3	-1	0	1	2	3	0	1	2	3	-1	0	1	2	3	4	5	0	1	2	3	4	5	-1	0	1	2	3	0	1	2	3	-1	0	1	2	0	1	2	-1	0	1	0	1	-1	0	1	2	0	1	2	-1	0	1	2	3	0	1	2	3	-1	0	1	2	0	1	2	-1	0	1	2	3	0	1	2	3	-1	0	1	0	1	-1	0	1	0	1	-1
timestamp
2023-02-13 00:00:00.000 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2023-02-13 05:00:00.000 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621	0.002583	0.197242	0.199856	0.202469	0.205083	0.207697	79.74766	79.74766	79.74766	79.74766	79.74766	0.010455	0.207697	0.209952	0.212207	79.74766	79.74766	79.74766	0.00451	0.212207	0.215378	79.74766	79.74766	0.00317	0.205092	0.207189	0.209287	53.01466	53.01466	53.01466	0.004195	0.204943	0.208853	0.212763	0.216673	0.220584	0.224494	0.228404	0.232315	54.25417	54.25417	54.25417	54.25417	54.25417	54.25417	54.25417	54.25417	0.027372	145.572	145.572	145.572	145.572	145.572	145.572	145.572	145.572	0	0	0	0	0	0	0	0	64.70937	212.8091	212.8091	212.8091	212.8091	212.8091	212.8091	212.8091	212.8091	212.8091	212.8091	0	0	0	0	0	0	0	0	0	0	80.91752	102.0578	92.77982	83.50184	74.22385	64.94587	55.66789	46.38991	37.11193	27.83395	18.55596	9.277985	0	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	102.0578	47.21349	47.21349	47.21349	47.21349	47.21349	47.21349	0	0	0	0	0	0	47.21349	0.046798	0.041705	0.036613	0.03152	-0.89961	-0.89961	-0.89961	-0.89961	0.015279	0.045349	0.036899	0.028449	-0.625276	-0.625276	-0.625276	0.0169	0.028449	0.018966	0.009483	0	-0.625276	-0.625276	-0.625276	-0.625276	0.028449	0	8.488726	16.97745	25.46618	33.9549	42.44363	5.537004e-09	5.537004e-09	5.537004e-09	5.537004e-09	5.537004e-09	5.537004e-09	42.44363	42.44363	48.83213	55.22064	2.867637e-09	2.867637e-09	2.867637e-09	12.77701	32.87505	23.70936	14.54366	5.377964	-3.819878e-11	-3.819878e-11	-3.819878e-11	-3.819878e-11	27.49709	8.066946	8.066946	0	0	5.377964	2.779566	0	-7.503331e-12	-7.503331e-12	2.779566	2.251996	0	-7.457857e-11	-7.457857e-11	2.251996	0	9.412791	1.946319e-10	1.946319e-10	9.412791	5.815166	2.603956	-6.957634e-11	-6.957634e-11	3.21121	2.603956	0	-6.934897e-11	-6.934897e-11	2.603956	0	5.753166	2.256684e-10	2.256684e-10	5.753166	5.753166	14.73561	23.71806	2.364686e-11	2.364686e-11	2.364686e-11	17.9649	0.202644	0.197183	0.191721	0.186259	0.180798	0.175336	0.169875	0.164413	0.158951	0.15349	0.148028	0.142567	0.137105	0.131644	0.126182	0.12072	0.115259	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	0.087385	0.128365	0.122597	0.116828	0.111059	-15.35888	-15.35888	-15.35888	-15.35888	0.017306	0.113464	0.108487	0.10351	0.098533	-15.03341	-15.03341	-15.03341	-15.03341	0.014931	81.08525	89.77052	98.4558	107.1411	3.892637e-10	3.892637e-10	3.892637e-10	3.892637e-10	26.05582	0.153536	0.156359	0.159181	0.162004	24.37467	24.37467	24.37467	24.37467	0.008468	0.159486	0.162945	0.166405	0.169864	0.173324	0.176784	24.7595	24.7595	24.7595	24.7595	24.7595	24.7595	0.017298	38.70423	30.2993	21.89438	13.48946	-4.001777e-11	-4.001777e-11	-4.001777e-11	-4.001777e-11	25.21477	13.48946	6.74473	0	-1.082299e-10	-1.082299e-10	-1.082299e-10	13.48946	14.20205	14.20205	0	0	8.799599	11.09779	5.548895	0	-1.200533e-10	-1.200533e-10	-1.200533e-10	11.09779	80.36217	80.36217	80.36217	80.36217	0	0	0	0	26.07811	26539710.0	26539710.0	26539710.0	0	0	0	17.34526	20.64109	13.76073	6.880363	0	-4.365575e-11	-4.365575e-11	-4.365575e-11	-4.365575e-11	20.64109	0	0.002894	8.40759	8.40759	0.002894	0.045	0.042072	-8.407589	-8.407589	0.002928
2023-02-13 23:00:00.000 +01:00	0.322723	0.326082	0.329441	0.3328	0.336159	14.68007	14.68007	14.68007	14.68007	14.68007	0.013437	0.336159	0.340388	0.344617	0.348845	0.353074	0.357302	0.361531	8.24275	8.24275	8.24275	8.24275	8.24275	8.24275	8.24275	0.025371	0.428837	0.432404	0.43597	0.439537	0.443103	0.44667	8.403428	8.403428	8.403428	8.403428	8.403428	8.403428	0.017832	0.44667	0.449642	8.403428	8.403428	0.002972	0.449642	0.452902	8.403428	8.403428	0.003259	0.452902	0.456521	8.403428	8.403428	0.00362	0.456521	0.460908	0.465294	0.46968	0.474066	0.478452	0.482838	0.487225	0.491611	0.495997	7.680472	7.680472	7.680472	7.680472	7.680472	7.680472	7.680472	7.680472	7.680472	7.680472	0.039475	0.495997	0.497624	6.748159	6.748159	0.001627	0.497624	0.500575	4.251046	4.251046	0.002951	0.500575	0.502825	4.251046	4.251046	0.00225	0.502825	0.506837	0.510848	0.51486	4.251046	4.251046	4.251046	4.251046	0.012035	0.51486	0.520176	0.525492	0.530809	3.980511	3.980511	3.980511	3.980511	0.015949	0.530809	0.535781	0.540754	0.545727	2.725789	2.725789	2.725789	2.725789	0.014919	0.545727	0.5572	0.568673	0.580146	0.591619	0.603092	0.4454	0.4454	0.4454	0.4454	0.4454	0.4454	0.057364	0.33512	0.340376	0.345633	0.35089	0.356146	0.361403	0.36666	0.371917	0.377173	0.38243	0.387687	0.392943	2.641599	2.641599	2.641599	2.641599	2.641599	2.641599	2.641599	2.641599	2.641599	2.641599	2.641599	2.641599	0.057824	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	166.2786	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	165.7806	225.9586	222.1157	-1.764420e-10	-1.764420e-10	3.842942	306.5338	297.3631	288.1923	279.0215	269.8508	260.68	251.5092	242.3385	-2.983143e-10	-2.983143e-10	-2.983143e-10	-2.983143e-10	-2.983143e-10	-2.983143e-10	-2.983143e-10	-2.983143e-10	64.19534	242.3385	233.8368	225.335	216.8333	208.3316	199.8299	191.3281	-5.293259e-10	-5.293259e-10	-5.293259e-10	-5.293259e-10	-5.293259e-10	-5.293259e-10	-5.293259e-10	51.01035	191.3281	181.9991	172.6701	163.3411	154.0121	144.683	135.354	126.025	116.696	107.3669	-2.546585e-10	-2.546585e-10	-2.546585e-10	-2.546585e-10	-2.546585e-10	-2.546585e-10	-2.546585e-10	-2.546585e-10	-2.546585e-10	-2.546585e-10	83.9612	107.3669	98.18304	88.99916	79.81527	70.63138	61.44748	52.2636	43.0797	-2.983143e-10	-2.983143e-10	-2.983143e-10	-2.983143e-10	-2.983143e-10	-2.983143e-10	-2.983143e-10	-2.983143e-10	64.28724	43.0797	34.46376	25.84782	17.23188	8.61594	0	-2.910383e-10	-2.910383e-10	-2.910383e-10	-2.910383e-10	-2.910383e-10	-2.910383e-10	43.0797	0.497351	0.482009	0.466667	0.451325	0.435982	0.42064	0.405298	-0.382465	-0.382465	-0.382465	-0.382465	-0.382465	-0.382465	-0.382465	0.092052	0.405298	0.401379	0.397459	-1.370786	-1.370786	-1.370786	0.00784	0.397459	0.393195	0.388931	0.384668	0.380404	-4.400413	-4.400413	-4.400413	-4.400413	-4.400413	0.017054	0.380404	0.375767	0.371129	0.366492	0.361854	0.357216	0.352579	0.347941	-7.743463	-7.743463	-7.743463	-7.743463	-7.743463	-7.743463	-7.743463	-7.743463	0.032463	0.347941	0.344736	0.34153	0.338325	0.33512	-8.782109	-8.782109	-8.782109	-8.782109	-8.782109	0.012821	0.272179	0.274061	18.87828	18.87828	0.001881	0.274061	0.276822	0.279583	18.50257	18.50257	18.50257	0.005522	0.279583	0.282331	0.285079	18.50257	18.50257	18.50257	0.005497	0.285079	0.287483	0.289887	0.292291	0.294695	18.0628	18.0628	18.0628	18.0628	18.0628	0.009616	0.294695	0.296735	0.298776	17.61799	17.61799	17.61799	0.00408	0.298776	0.302197	0.305618	0.309039	0.31246	0.315881	0.319302	0.322723	15.77509	15.77509	15.77509	15.77509	15.77509	15.77509	15.77509	15.77509	0.023947	218.9278	210.1986	201.4695	192.7403	184.0112	175.282	166.5529	-4.183107e-10	-4.183107e-10	-4.183107e-10	-4.183107e-10	-4.183107e-10	-4.183107e-10	-4.183107e-10	52.3749	13.53016	6.76508	0	-1.091394e-10	-1.091394e-10	-1.091394e-10	13.53016	0	6.304299	12.6086	1.682565e-10	1.682565e-10	1.682565e-10	12.6086	12.6086	17.85569	23.10279	2.455636e-10	2.455636e-10	2.455636e-10	10.49419	23.10279	31.2928	8.349161e-10	8.349161e-10	8.190004	23.81577	30.50338	37.19099	4.329195e-10	4.329195e-10	4.329195e-10	13.37522	0.329083	0.323727	0.318372	0.313017	0.307661	0.302306	0.296951	...	8.426783	6.821210e-11	6.821210e-11	8.426783	42275900.0	42275880.0	42275880.0	42275870.0	-2.492015e-10	-2.492015e-10	-2.492015e-10	-2.492015e-10	22.79576	42275870.0	42275860.0	42275850.0	42275840.0	42275840.0	-2.073648e-10	-2.073648e-10	-2.073648e-10	-2.073648e-10	-2.073648e-10	33.26721	42275840.0	42275830.0	42275820.0	-3.683454e-10	-3.683454e-10	-3.683454e-10	18.7625	42275820.0	42275810.0	42275800.0	-2.751221e-10	-2.751221e-10	-2.751221e-10	14.43095	0.032542	0.024407	0.016271	0.008136	0	-0.624868	-0.624868	-0.624868	-0.624868	-0.624868	0.032542	0.021149	0.015862	0.010575	0.005287	0	-1.120643	-1.120643	-1.120643	-1.120643	-1.120643	0.021149	93.3712	93.3712	93.3712	0	0	0	16.76996	0.301135	0.30345	0.305766	79.74766	79.74766	79.74766	0.004631	0.305766	0.30778	79.74766	79.74766	0.002014	0.230775	0.233358	54.61621	54.61621	0.002583	0.197242	0.199856	0.202469	0.205083	0.207697	79.74766	79.74766	79.74766	79.74766	79.74766	0.010455	0.207697	0.209952	0.212207	79.74766	79.74766	79.74766	0.00451	0.212207	0.215378	79.74766	79.74766	0.00317	0.205092	0.207189	0.209287	53.01466	53.01466	53.01466	0.004195	0.204943	0.208853	0.212763	0.216673	0.220584	0.224494	0.228404	0.232315	54.25417	54.25417	54.25417	54.25417	54.25417	54.25417	54.25417	54.25417	0.027372	145.572	145.572	145.572	145.572	145.572	145.572	145.572	145.572	0	0	0	0	0	0	0	0	64.70937	212.8091	212.8091	212.8091	212.8091	212.8091	212.8091	212.8091	212.8091	212.8091	212.8091	0	0	0	0	0	0	0	0	0	0	80.91752	102.0578	92.77982	83.50184	74.22385	64.94587	55.66789	46.38991	37.11193	27.83395	18.55596	9.277985	0	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	-1.164153e-10	102.0578	47.21349	47.21349	47.21349	47.21349	47.21349	47.21349	0	0	0	0	0	0	47.21349	0.046798	0.041705	0.036613	0.03152	-0.89961	-0.89961	-0.89961	-0.89961	0.015279	0.045349	0.036899	0.028449	-0.625276	-0.625276	-0.625276	0.0169	0.028449	0.018966	0.009483	0	-0.625276	-0.625276	-0.625276	-0.625276	0.028449	0	8.488726	16.97745	25.46618	33.9549	42.44363	5.537004e-09	5.537004e-09	5.537004e-09	5.537004e-09	5.537004e-09	5.537004e-09	42.44363	42.44363	48.83213	55.22064	2.867637e-09	2.867637e-09	2.867637e-09	12.77701	32.87505	23.70936	14.54366	5.377964	-3.819878e-11	-3.819878e-11	-3.819878e-11	-3.819878e-11	27.49709	8.066946	8.066946	0	0	5.377964	2.779566	0	-7.503331e-12	-7.503331e-12	2.779566	2.251996	0	-7.457857e-11	-7.457857e-11	2.251996	0	9.412791	1.946319e-10	1.946319e-10	9.412791	5.815166	2.603956	-6.957634e-11	-6.957634e-11	3.21121	2.603956	0	-6.934897e-11	-6.934897e-11	2.603956	0	5.753166	2.256684e-10	2.256684e-10	5.753166	5.753166	14.73561	23.71806	2.364686e-11	2.364686e-11	2.364686e-11	17.9649	0.202644	0.197183	0.191721	0.186259	0.180798	0.175336	0.169875	0.164413	0.158951	0.15349	0.148028	0.142567	0.137105	0.131644	0.126182	0.12072	0.115259	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	-17.10539	0.087385	0.128365	0.122597	0.116828	0.111059	-15.35888	-15.35888	-15.35888	-15.35888	0.017306	0.113464	0.108487	0.10351	0.098533	-15.03341	-15.03341	-15.03341	-15.03341	0.014931	81.08525	89.77052	98.4558	107.1411	3.892637e-10	3.892637e-10	3.892637e-10	3.892637e-10	26.05582	0.153536	0.156359	0.159181	0.162004	24.37467	24.37467	24.37467	24.37467	0.008468	0.159486	0.162945	0.166405	0.169864	0.173324	0.176784	24.7595	24.7595	24.7595	24.7595	24.7595	24.7595	0.017298	38.70423	30.2993	21.89438	13.48946	-4.001777e-11	-4.001777e-11	-4.001777e-11	-4.001777e-11	25.21477	13.48946	6.74473	0	-1.082299e-10	-1.082299e-10	-1.082299e-10	13.48946	14.20205	14.20205	0	0	8.799599	11.09779	5.548895	0	-1.200533e-10	-1.200533e-10	-1.200533e-10	11.09779	80.36217	80.36217	80.36217	80.36217	0	0	0	0	26.07811	26539710.0	26539710.0	26539710.0	0	0	0	17.34526	20.64109	13.76073	6.880363	0	-4.365575e-11	-4.365575e-11	-4.365575e-11	-4.365575e-11	20.64109	0	0.002894	8.40759	8.40759	0.002894	0.045	0.042072	-8.407589	-8.407589	0.002928

3 rows × 5560 columns

Note that an additional multiindex is created that indexes the interior points. Non-vectorized properties get index -1 in the new multiindex .

We can access individual values as follows.

df_pipes_interior_points.loc[
    "2023-02-13 00:00:00.000 +01:00",
    ("5442010239090746007", slice(None), slice(None), "MVEC", 2)
].item()

14.68007

Merge model_data and Result Dataframes (for one timestamp)

Create Dataframes - For pipes

model_data

df_pipes_model_data = s3s.generate_element_model_data_dataframe(element_type=s3s.ObjectTypes.Pipe
                                                            ,properties=["L", "DN"]
                                                            ,geometry=True
                                                            )

[2026-03-15 23:21:00,683] INFO in sir3stoolkit.mantle.dataframes: [model_data] Generating model_data dataframe for element type: ObjectTypes.Pipe
[2026-03-15 23:21:00,686] INFO in sir3stoolkit.mantle.dataframes: [model_data] Retrieved 524 element(s) of element type ObjectTypes.Pipe.
[2026-03-15 23:21:00,690] INFO in sir3stoolkit.mantle.dataframes: [Resolving model_data Properties] Using 2 model_data properties.
[2026-03-15 23:21:00,691] INFO in sir3stoolkit.mantle.dataframes: [model_data] Retrieving model_data properties ['L', 'DN'], geometry...
[2026-03-15 23:21:01,108] INFO in sir3stoolkit.mantle.dataframes: [model_data] Transforming DataFrame to GeoDataFrame successful with EPSG: 25832
[2026-03-15 23:21:01,110] INFO in sir3stoolkit.mantle.dataframes: [model_data] Done. Shape: (524, 4)

df_pipes_model_data.head(3)

	tk	L	DN	geometry
0	5442010239090746007	36.42935	150	LINESTRING (713620.268 5578828.419, 713602.295...
1	4917786378639043296	57.21781	125	LINESTRING (713602.295 5578860.106, 713574.062...
2	4762482310382009633	40.99482	125	LINESTRING (713574.062 5578909.873, 713553.84 ...

Results

df_pipes_results = s3s.generate_element_results_dataframe(element_type=s3s.ObjectTypes.Pipe
                                                        ,properties=["DTTR", "PHR", "PVEC", "TTRVEC"]
                                                        ,timestamps=[0]
                                                        )

[2026-03-15 23:21:01,167] INFO in sir3stoolkit.mantle.dataframes: [results] Generating results dataframe for element type: ObjectTypes.Pipe
[2026-03-15 23:21:01,421] INFO in sir3stoolkit.mantle.dataframes: [Resolving Timestamps] Only static timestamp 2023-02-13 00:00:00.000 +01:00 is used
[2026-03-15 23:21:01,424] INFO in sir3stoolkit.mantle.dataframes: [Resolving Timestamps] 1 valid timestamp(s) will be used.
[2026-03-15 23:21:01,431] INFO in sir3stoolkit.mantle.dataframes: [Resolving tks] Retrieved 524 element(s) of element type ObjectTypes.Pipe.
[2026-03-15 23:21:01,435] INFO in sir3stoolkit.mantle.dataframes: [results] Using 4 result properties.
[2026-03-15 23:21:01,474] INFO in sir3stoolkit.mantle.dataframes: [results] Retrieving result values...
[2026-03-15 23:21:02,513] INFO in sir3stoolkit.mantle.dataframes: [results] 0 fully NaN columns dropped.
[2026-03-15 23:21:02,943] INFO in sir3stoolkit.mantle.dataframes: [results] Done. Shape: (1, 2096)

df_pipes_results.head(3)

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property	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	...	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC	DTTR	PHR	PVEC	TTRVEC
timestamp
2023-02-13 00:00:00.000 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877\t0.2584653	0.001456	0.002091	4.21881\t4.219005	0.2584653\t0.257009	0.013377	0.003171	4.219005\t4.235845\t4.25269\t4.26953	0.257009\t0.2525501\t0.2480911\t0.2436321	0.039901	0.012031	4.26953\t4.280445\t4.29136\t4.30227\t4.313185\...	0.2436321\t0.2391987\t0.2347652\t0.2303318\t0....	0.022962	0.010703	4.36775\t4.376325\t4.384895\t4.393465\t4.40203...	0.2037313\t0.1999043\t0.1960772\t0.1922502\t0....	0.005711	0.003578	4.54788\t4.565775\t4.58367	0.2477866\t0.2449313\t0.2420759	0.003159	0.002729	4.58367\t4.61103	0.2420759\t0.2389168	0.003213	0.002776	4.61103\t4.6659	0.2389168\t0.2357037	0.002857	0.000881	4.6659\t4.71035	0.2357037\t0.2328462	0.003821	0.001556	...	4.30839\t4.304\t4.29961	0.03752647\t0.0353081\t0.03308972	0.004207	0.007222	4.29961\t4.314795\t4.329985	0.03308972\t0.0309864\t0.02888308	0.006515	0.005366	4.329985\t4.33556\t4.34114	0.03727595\t0.03401849\t0.03076103	0.023215	0.015846	4.34114\t4.33907\t4.337\t4.334935\t4.332865	0.05649423\t0.0506906\t0.04488698\t0.03908335\...	0.010218	0.006975	4.332865\t4.32767\t4.322475	0.03327971\t0.02817051\t0.02306132	0.038396	0.006148	4.322475\t4.32618\t4.32989\t4.333595\t4.3373	0.03839613\t0.02879709\t0.01919806\t0.00959903...	22.46283	7.871059e-26	4.3373\t4.310815\t4.28433\t4.257845	30.58293\t23.09532\t15.60771\t8.120096	11.13411	3.361424e-25	4.257845\t4.23038\t4.20291	11.13411\t5.567055\t0	18.74616	3.296165e-25	4.20291\t4.12787\t4.052825	0\t9.37308\t18.74616	27.98768	3.370467e-25	4.052825\t3.96748\t3.882135\t3.79679	18.74616\t28.07539\t37.40461\t46.73384	32.47894	8.594241e-26	3.79679\t3.78257\t3.768345\t3.754125\t3.7399	32.47894\t24.3592\t16.23947\t8.119736\t0	63.81877	0.0	3.7399\t3.64228\t3.54466\t3.447035\t3.349415\t...	101.601\t101.601\t101.601\t101.601\t101.601\t1...	0.032964	0.015184	2.51727\t2.49828\t2.479285\t2.460295\t2.441305	0\t0.008241023\t0.01648205\t0.02472307\t0.0329...	0.027192	0.013729	2.441305\t2.42949\t2.417675\t2.40586\t2.39405\...	0.01958097\t0.02501935\t0.03045773\t0.03589611...	0.007962	0.002383	2.382235\t2.373805\t2.365375	0.0352097\t0.03919088\t0.04317206	0.02138	0.008757	2.365375\t2.332555\t2.299735\t2.26692\t2.2341	0.03868973\t0.04403469\t0.04937965\t0.0547246\...	0.022239	0.019862	2.441305\t2.467735\t2.494165\t2.520595\t2.547025	0.02223893\t0.0166792\t0.01111946\t0.005559732\t0	0.036189	0.013256	2.14896\t2.14168\t2.134405\t2.127125\t2.11985\...	0.05668244\t0.05065088\t0.04461933\t0.03858777...	0.019879	0.008786	2.10529\t2.10363\t2.10197\t2.100305\t2.098645	0.03060683\t0.02563716\t0.0206675\t0.01569783\...	0.013771	0.002986	2.098645\t2.078915\t2.059185	0.01377144\t0.006885718\t0	0.004935	0.002378	4.0256\t3.98964\t3.953685	0.3167358\t0.3142684\t0.311801	0.004021	0.001937	3.953685\t3.919445\t3.8852	0.311801\t0.3097905\t0.3077799	10.56986	1.601792e-13	1.68863\t1.663125\t1.637625	4.346471E+07\t4.346471E+07\t4.346472E+07	14.57936	2.209403e-13	1.637625\t1.690105\t1.742585	4.346472E+07\t4.346473E+07\t4.346474E+07	19.87988	3.012669e-13	1.742585\t1.830875\t1.91916	4.346474E+07\t4.346474E+07\t4.346476E+07	24.45074	3.705358e-13	1.91916\t1.958395\t1.997635\t2.036875	4.346476E+07\t4.346476E+07\t4.346477E+07\t4.34...	23.61157	3.578183e-13	2.036875\t2.012025\t1.98717\t1.96232	4.346478E+07\t4.346479E+07\t4.34648E+07\t4.346...	50.96676	7.723688e-13	1.96232\t1.934365\t1.906405\t1.87845\t1.85049\...	4.34648E+07\t4.346481E+07\t4.346482E+07\t4.346...	21.2934	3.398291e-25	1.794575\t1.77986\t1.765145\t1.75043	4.346486E+07\t4.346486E+07\t4.346487E+07\t4.34...	16.31768	0.0	1.75043\t1.71855\t1.68667	1.997122E+07\t1.997122E+07\t1.997122E+07	21.15114	8.483442e-26	1.68667\t1.68471\t1.68275\t1.680785	0\t7.05038\t14.10076\t21.15114	6.620245	1.161618e-26	1.680785\t1.68863	21.15114\t27.77139	5.387928	2.104679e-26	1.68863\t1.69746	33.15931\t27.77139	11.07489	0.0	1.69746\t1.68471\t1.671955	44.38372\t44.38372\t44.38372	6.690278	0.0	1.77103\t1.71904	2.113793E+07\t2.113793E+07	21.84747	0.0	1.71904\t1.593475\t1.467915\t1.342355	51.63726\t51.63726\t51.63726\t51.63726	18.86606	7.686560e-26	1.342355\t1.17559\t1.008825	18.86606\t9.43303\t0	26.74521	2.125622e-24	1.116735\t1.18671\t1.25668\t1.326655	107.1411\t116.0561\t124.9712\t133.8863	17.53896	7.547817e-25	1.326655\t1.404645\t1.48263	133.8863\t142.6558\t151.4252	15.2731	7.622792e-25	1.48263\t1.548845\t1.615055	151.4252\t159.0618\t166.6983	7.780674	1.373914e-24	1.615055\t1.68863	166.6983\t174.479	35.01923	5.306902e-13	1.68863\t1.712175\t1.735715\t1.75926\t1.782805	4.346491E+07\t4.34649E+07\t4.346489E+07\t4.346...	18.98862	2.877589e-13	1.782805\t1.78869\t1.794575	4.346487E+07\t4.346486E+07\t4.346486E+07	14.42032	7.631948e-25	1.794575\t1.79163\t1.78869	4.346486E+07\t4.346486E+07\t4.346487E+07	16.00222	2.798916e-24	1.78869\t1.77986\t1.77103	4.346487E+07\t4.346488E+07\t4.346489E+07	40.99183	7.541643e-25	1.01962\t1.0465\t1.073375\t1.100255\t1.127135\...	29.07444\t37.2728\t45.47117\t53.66954\t61.8679...	37.58163	5.383057e-25	1.15401\t1.18393\t1.21385\t1.243765\t1.273685	70.06627\t79.46168\t88.85709\t98.25249\t107.6479	3.547835	0.0	1.273685\t1.285455	92.00916\t92.00916	34.96974	2.003576e-26	1.285455\t1.31464\t1.343825\t1.373005\t1.40219	34.96974\t26.22731\t17.48487\t8.742435\t0	105.8952	0.0	1.40219\t1.43162\t1.46105\t1.49048\t1.51991\t1...	158.8428\t158.8428\t158.8428\t158.8428\t158.84...	80.62691	3.315878e-22	2.26185\t2.261525\t2.2612\t2.260875\t2.26055\t...	0.02615335\t8.984699\t17.94324\t26.90179\t35.8...	36.44118	0.0	2.778475\t2.76482\t2.751165\t2.737515\t2.72386	43.60472\t43.60472\t43.60472\t43.60472\t43.60472	31.60874	0.0	2.72386\t2.72533\t2.726805\t2.728275\t2.729745	31.60874\t31.60874\t31.60874\t31.60874\t31.60874	0.048071	0.00153	2.729745\t2.73181\t2.733875\t2.735935	4.067396E-11\t0.01602369\t0.03204738\t0.04807106	0.038926	0.004357	2.735935\t2.734605\t2.733275\t2.731945\t2.730615	0.03071576\t0.04044738\t0.050179\t0.05991063\t...	0.01592	0.006248	2.730615\t2.73271\t2.73481\t2.736905	0.01629578\t0.02160233\t0.02690887\t0.03221542	0.005553	0.002676	3.707935\t3.71866\t3.72938	0.2912369\t0.2940134\t0.2967899	0.004345	0.002093	3.72938\t3.751485\t3.773595	0.2967899\t0.2989622\t0.3011346	18.81272	7.112188e-23	3.8852\t3.841905\t3.798615	0.3077799\t9.71414\t19.1205	15.6488	0.0	3.798615\t3.814585\t3.830555	96.85868\t96.85868\t96.85868	0.027928	0.011203	3.473825\t3.480245\t3.486665\t3.49308\t3.4995	0.02792781\t0.02094586\t0.01396391\t0.00698195...	45.47781	0.0	2.890205\t2.931055\t2.971905\t3.01275\t3.0536\...	45.56185\t45.56185\t45.56185\t45.56185\t45.561...	0.082113	0.034165	3.09445\t3.082115\t3.06978\t3.05745\t3.045115\...	0\t0.006842781\t0.01368556\t0.02052834\t0.0273...	34.57665	0.0	2.946445\t2.86501\t2.78358\t2.702145\t2.620715	34.68333\t34.68333\t34.68333\t34.68333\t34.68333	8.426783	2.095524e-26	1.629775\t1.638605	0\t8.426783	22.79576	7.565951e-25	1.638605\t1.652665\t1.666725\t1.680785	4.22759E+07\t4.227588E+07\t4.227588E+07\t4.227...	33.26721	7.645297e-25	1.680785\t1.695255\t1.70972\t1.72419\t1.73866	4.227587E+07\t4.227586E+07\t4.227585E+07\t4.22...	18.7625	1.360533e-24	1.73866\t1.75141\t1.764165	4.227584E+07\t4.227583E+07\t4.227582E+07	14.43095	5.837865e-25	1.764165\t1.7676\t1.77103	4.227582E+07\t4.227581E+07\t4.22758E+07	0.032542	0.005464	4.034015\t4.03514\t4.036265\t4.03739\t4.038515	0.03254228\t0.02440671\t0.01627114\t0.00813557\t0	0.021149	0.018736	2.717705\t2.79474\t2.871775\t2.948815\t3.02585	0.02114942\t0.01586206\t0.01057471\t0.00528735...	16.76996	0.0	3.787395\t3.780495\t3.773595	93.3712\t93.3712\t93.3712	0.004631	0.002231	3.773595\t3.812515\t3.85144	0.3011346\t0.3034503\t0.3057659	0.002014	0.00097	3.85144\t3.8852	0.3057659\t0.3077799	0.002583	0.000796	3.532125\t3.53519	0.2307746\t0.2333578	0.010455	0.005038	3.53519\t3.540925\t3.54666\t3.552395\t3.55813	0.1972419\t0.1998557\t0.2024695\t0.2050833\t0....	0.00451	0.002173	3.55813\t3.547395\t3.53666	0.2076971\t0.2099522\t0.2122073	0.00317	0.001528	3.53666\t3.538995	0.2122073\t0.2153777	0.004195	0.004084	3.430635\t3.45223\t3.473825	0.2050919\t0.2071895\t0.209287	0.027372	0.008274	3.473825\t3.482155\t3.49048\t3.49881\t3.50714\...	0.2049427\t0.2088529\t0.2127632\t0.2166735\t0....	64.70937	0.0	4.365185\t4.365185\t4.365185\t4.365185\t4.3651...	145.572\t145.572\t145.572\t145.572\t145.572\t1...	80.91752	0.0	4.365185\t4.365185\t4.365185\t4.365185\t4.3651...	212.8091\t212.8091\t212.8091\t212.8091\t212.80...	102.0578	7.392213e-25	4.365185\t4.17782\t3.99046\t3.803095\t3.61573\...	102.0578\t92.77982\t83.50184\t74.22385\t64.945...	47.21349	0.0	2.30419\t2.309055\t2.313915\t2.31878\t2.323645...	47.21349\t47.21349\t47.21349\t47.21349\t47.213...	0.015279	0.007224	1.875045\t1.9035\t1.93196\t1.960415	0.04679836\t0.04170547\t0.03661257\t0.03151968	0.0169	0.002843	1.960415\t1.963765\t1.967115	0.04534864\t0.03689872\t0.0284488	0.028449	0.004785	1.967115\t1.98093\t1.994745\t2.00856	0.0284488\t0.01896586\t0.009482932\t0	42.44363	7.013738e-22	2.00856\t2.02724\t2.045915\t2.064595\t2.083275...	0\t8.488726\t16.97745\t25.46618\t33.9549\t42.4...	12.77701	5.615462e-23	2.10195\t2.10931\t2.116665	42.44363\t48.83213\t55.22064	27.49709	2.144340e-26	1.285455\t1.303115\t1.320775\t1.33843	32.87505\t23.70936\t14.54366\t5.377964	5.377964	0.0	1.33843\t1.34432	8.066946\t8.066946	2.779566	8.363599e-29	1.34432\t1.346275	2.779566\t0	2.251996	6.694277e-27	1.346275\t1.34824	2.251996\t0	9.412791	1.905699e-25	1.34824\t1.35707	0\t9.412791	3.21121	8.308066e-27	1.35707\t1.36099	5.815166\t2.603956	2.603956	6.693013e-27	1.36099\t1.362955	2.603956\t0	5.753166	1.565872e-25	1.362955\t1.36394	0\t5.753166	17.9649	5.368832e-27	1.36394\t1.372275\t1.380615	5.753166\t14.73561\t23.71806	0.087385	0.015387	2.45854\t2.43894\t2.41934\t2.39974\t2.38014\t2...	0.2026442\t0.1971826\t0.191721\t0.1862594\t0.1...	0.017306	0.002236	2.14494\t2.121245\t2.09755\t2.07385	0.1283654\t0.1225967\t0.1168279\t0.1110592	0.014931	0.001814	2.07385\t2.05323\t2.03261\t2.011985	0.1134637\t0.1084867\t0.1035097\t0.09853268	26.05582	2.110405e-24	1\t1.03891\t1.077825\t1.116735	81.08525\t89.77052\t98.4558\t107.1411	0.008468	0.004144	2.45854\t2.47742\t2.4963\t2.51518	0.1535359\t0.1563585\t0.1591811\t0.1620037	0.017298	0.008858	2.51518\t2.559525\t2.60387\t2.648215\t2.69256\...	0.1594857\t0.1629453\t0.1664049\t0.1698644\t0....	25.21477	2.158086e-26	1.34039\t1.32829\t1.316195\t1.304095	38.70423\t30.2993\t21.89438\t13.48946	13.48946	8.444945e-26	1.304095\t1.29625\t1.2884	13.48946\t6.74473\t0	8.799599	0.0	1.2884\t1.26682	14.20205\t14.20205	11.09779	8.548555e-26	1.26682\t1.241315\t1.21581	11.09779\t5.548895\t0	26.07811	0.0	1.21581\t1.179845\t1.143875\t1.107905	80.36217\t80.36217\t80.36217\t80.36217	17.34526	0.0	1.638605\t1.51108\t1.38355	2.653971E+07\t2.653971E+07\t2.653971E+07	20.64109	2.102439e-26	1.38355\t1.27859\t1.17363\t1.06867	20.64109\t13.76073\t6.880363\t0	0.002894	0.007571	4.839625\t4.8454	0\t0.002893685	0.002928	0.007658	3.981985\t3.997365	0.04499983\t0.04207175

1 rows × 2096 columns

Merge

df_pipes_results.columns = df_pipes_results.columns.droplevel([1, 2])
df_pipes_results = df_pipes_results.T.unstack(level=0).T
df_pipes_results = df_pipes_results.droplevel(0, axis=0)
df_pipes = df_pipes_model_data.merge(on="tk",
                    how="outer",
                    right=df_pipes_results)

df_pipes.head(3)

	tk	L	DN	geometry	DTTR	PHR	PVEC	TTRVEC
0	4614463970292122863	7.780674	999	LINESTRING (714262.483 5578857.42, 714269.543 ...	7.780674	0.0	1.615055\t1.68863	166.6983\t174.479
1	4615723899944629797	64.287240	999	LINESTRING (713738.297 5579219.902, 713793.23 ...	64.28724	0.0	3.30477\t3.34555\t3.38633\t3.42711\t3.46789\t3...	107.3669\t98.18304\t88.99916\t79.81527\t70.631...
2	4621030304810285220	3.956838	100	LINESTRING (713650.613 5578990.488, 713649.498...	0.002291	0.000835	2.21037\t2.19866	0.05545081\t0.05315936

Expand vectorized results

We an use the add_interior_points_to_start_end_sequence() method to replace vector cols by three new cols: vec_start, vec_end, vec_sequence (closed interval with start and end).

df_vector = s3s.add_interior_points_to_start_end_sequence(df_pipes)

df_vector.head(3)

	tk	L	DN	geometry	DTTR	PHR	PVEC_start	PVEC_end	PVEC_sequence	TTRVEC_start	TTRVEC_end	TTRVEC_sequence
0	4614463970292122863	7.780674	999	LINESTRING (714262.483 5578857.42, 714269.543 ...	7.780674	0.0	1.615055	1.68863	(1.615055, 1.68863)	166.698300	174.479000	(166.6983, 174.479)
1	4615723899944629797	64.287240	999	LINESTRING (713738.297 5579219.902, 713793.23 ...	64.28724	0.0	3.304770	3.59023	(3.30477, 3.34555, 3.38633, 3.42711, 3.46789, ...	107.366900	43.079700	(107.3669, 98.18304, 88.99916, 79.81527, 70.63...
2	4621030304810285220	3.956838	100	LINESTRING (713650.613 5578990.488, 713649.498...	0.002291	0.000835	2.210370	2.19866	(2.21037, 2.19866)	0.055451	0.053159	(0.05545081, 0.05315936)