# Access transient data from Ensight files inside a script
**URL:** https://discourse.paraview.org/t/access-transient-data-from-ensight-files-inside-a-script/8231
**Category:** ParaView Support
**Tags:** vtk
**Created:** [October 21, 2021, 2:21pm UTC](https://discourse.paraview.org/t/access-transient-data-from-ensight-files-inside-a-script/8231 "2021-10-21T14:21:13Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@Sandeep\_Jella](https://discourse.paraview.org/u/Sandeep_Jella)
#### Post date: [October 21, 2021, 2:21pm UTC](https://discourse.paraview.org/t/access-transient-data-from-ensight-files-inside-a-script/8231/1 "2021-10-21T14:21:13Z")
Hi All,
I’m reading in an Ensight gold case file which consists of a single 2D slice with scalars for a number of time-steps.
I would like to do some eigenvalue work on the transient data but need to access the data at each time-step within a loop for a given scalar. In a sense this similar to what the “Temporal Statistics” filter is doing.
So the script I hope to have so far runs like this :
1. Read in the Ensight file.
2. Use the numpy-to-vtk adapter to access data.
3. Loop over time-steps and store the data
4. Apply temporal statistical analysis
5. Write the result back by appending the output as a new array
My script:
```auto
from paraview.simple import *
from paraview import servermanager as sm
from paraview.vtk.numpy_interface import dataset_adapter as dsa
dat = EnSightReader(CaseFileName='C:/scratch/F1_.case')
mg=MergeBlocks(Input=dat,MergePoints=0)
vtk_data = sm.Fetch(mg)
vtk_data = dsa.WrapDataObject(vtk_data)
data = vtk_data.PointData
```
So here am able to call `data[0]` to display the raw data for the first scalar.
How can I then “step through” the rest of the time-steps while appending data[0] to some array?
Many thanks for any direction here,
Sandeep
---
### Author:  [@Sandeep\_Jella](https://discourse.paraview.org/u/Sandeep_Jella)
#### Post date: [November 13, 2021, 5:10pm UTC](https://discourse.paraview.org/t/access-transient-data-from-ensight-files-inside-a-script/8231/2 "2021-11-13T17:10:05Z")
Just in case someone has the same question, my workaround is detailed below.
I finally wrote the ensight time-series using Paraview’s writer to a set of \*.vtu (VTK Unstructured) or \*.vtp (Polydata) as required and used the VTK modules in an external python script to extract the data I needed.
Some code below. Note that additional code should be written for error handling so follow standard I/O safe practice.
Naturally, the thing can be done faster via encapsulating the relevant lines in python multiprocessing code. Watch the RAM!
```auto
import vtk
import numpy as np
from vtk.util import numpy_support
from vtk.util.numpy_support import vtk_to_numpy
location='C:/scratch/'
scal = 'qprime'
scalar=[]
reader = vtk.vtkXMLUnstructuredGridReader() # Note change to PolyData if necessary.
# Read the first ten files which are named as "f1_0.vtu" to "f1_10.vtu"
for n in np.arange(0,10):
vtk_file_name = 'f1_'+str(n)+'.vtu'
reader.SetFileName(location+vtk_file_name)
reader.Update()
#Modify the following lines as relevant to VTK data type
data = reader.GetOutput()
point_data = data.GetPointData()
point_data.GetNumberOfArrays()
# Get the scalar and append as in the OP request
scalar_data1 = point_data.GetAbstractArray(scal)
scalar.append(np.array([scalar_data1.GetValue(i) for i in range(data.GetNumberOfPoints())]))
# 'scalar' is now a nice array of the time-series of the 2D slice.
```
Lines may need modification if legacy vtk files (e.g. ‘Update Scalars()’ etc) are used . Also, the above is NOT recommended for large data since the array `scalar` can become obese and more fancy arrays ([DASK](https://dask.org)?) might be help. This workaround was enough for my purposes but perhaps someone else can suggest a better way to do things (e.g. within paraview itself).