Load SParamData from CPython
Michael Wollensack METAS
Michael Wollensack METAS
Hi,
you would need the following python packages:
https://pypi.org/project/pythonnet/
https://pypi.org/project/metas-unclib/
and the VNA Tools and the METAS UncLib versions should be the same. I'f not you've to modify the metas_unclib.py file that it loads the METAS UncLib from the VNA Tools installation path.
The following script is an example which loads an SParamData file:
Load SParamData using METAS UncLib and VNA Tools
Michael Wollensack METAS - 28.06.2019
In [1]:
vnatools_path = r'C:\Program Files (x86)\METAS\Metas.Vna.Tools'
In [2]:
data_path = r'C:\Users\Public\Documents\Metas.Vna.Tools\Matlab\Example_01.sdatb'
In [3]:
import os as _os
import clr as _clr
In [4]:
_clr.AddReference(_os.path.join(vnatools_path, "Metas.Vna.Data"))
Out[4]:
<System.Reflection.RuntimeAssembly at 0x22fbab7d128>
In [5]:
from metas_unclib import *
In [6]:
from Metas.UncLib.LinProp import UncNumber as _UncNumber
from Metas.Vna.Data.FileIO import Generic as _Generic
In [7]:
sdata = _Generic.LoadSParamData[_UncNumber](data_path)
In [8]:
print(sdata.NFreq)
3
In [9]:
print(sdata.NPorts)
2
In [10]:
frequency = np.asarray([float(fi) for fi in sdata.Frequency])
print(frequency)
[1.e+09 2.e+09 3.e+09]
In [11]:
ports = [str(pi) for pi in sdata.Ports]
print(ports)
['1', '2']
In [12]:
portzr = np.asarray([ucomplex(pi) for pi in sdata.PortZr])
print(portzr)
[(50+0j) ± 0j (50+0j) ± 0j]
In [13]:
_d = sdata.GetNArrayData()
_d2 = np.asarray([ucomplex(di) for di in _d.data])
_s = [si for si in _d.size]
data = _d2.reshape(_s, order='F')
print(data)
[[[(-0.00372+0.00539j) ± (0.0002828427124746192+0.0002803569007957765j)
(0.235-0.214j) ± (0.00021213203435596438+0.00022360679774997925j)]
[(0.235-0.213j) ± (0.00021166010488516752+0.00022315907859602344j)
(-0.0039+0.00639j) ± (0.0002908607914449798+0.000292403830344269j)]]
[[(-0.000499+0.00912j) ± (0.00028530682766003245+0.00028231188426986186j)
(0.0305-0.315j) ± (0.00025961509971494354+0.0001466287829861519j)]
[(0.0305-0.315j) ± (0.00025865034312755125+0.0001456021977856104j)
(0.00182+0.0088j) ± (0.00028390139133156755+0.00028722813232690144j)]]
[[(0.00381+0.0116j) ± (0.00038209923832536+0.00038078835761351054j)
(-0.189-0.254j) ± (0.00021725560982400444+0.00018947295321496425j)]
[(-0.189-0.254j) ± (0.00021725560982400425+0.0001894729532149644j)
(0.00737+0.00774j) ± (0.0003885869230130046+0.00038858711885494306j)]]]
Regards
Michael