library for handling NRG Systems data files
Project description
nrgpy
nrgpy is the Python package for processing NRG Data Files
Website and source | https://github.com/nrgpy/nrgpy |
Documentation | https://nrgpy.github.io/nrgpy/index.html |
IEA Task 43 Parser | https://github.com/nrgpy/nrg-parser |
Support | support@nrgsystems.com |
It provides tools for:
- Converting binary ".rld" and ".rwd" files to text format
- using locally installed SymphoniePRO Desktop Software and Symphonie Data Retriever
- using NRG Cloud API (compatible with Linux!) *(SymphoniePRO only at this time)
- Reading Symphonie text exports, LOGR dat, and Spidar zip/csv files into Pandas dataframes
- Timestamp adjustment (of text files)
- Simple quality checks on data
Contributing
See our Contributing guidelines for how to be a part of this project.
Installation
pip install nrgpy
Log and token files
Log files and NRG Cloud token files will be generated when using the app. These files can be found in your '''home''' directory:
Windows
C:\Users\{username}\.nrgpy\
Linux/Mac
/home/{username}/.nrgpy/
Examples
For more examples see the Documentation: https://nrgpy.github.io/nrgpy/index.html
RLD files
Convert a folder of RLD files to Text with SymphoniePRO Desktop Software
import nrgpy
date_filter = '2018-10' # filter on any text in the filenames
text_folder_name = 'text_outputs/'
converter = nrgpy.local_rld(rld_dir='', out_dir=text_folder_name, file_filter=date_filter)
converter.convert()
Convert a folder of RLD files to Text with NRG Cloud Convert API
import nrgpy
file_filter = "000110"
rld_directory = "rlds"
client_id = "https://cloud.nrgsystems.com/data-manager/api-setup"
client_secret = ""
converter = nrgpy.cloud_convert(
file_filter=file_filter,
rld_dir=rld_directory,
client_id=client_id,
client_secret=client_secret,
start_date="2019-11-01",
end_date="2019-11-30",
)
converter.process()
Convert a single RLD file to Text with NRG Cloud API
import nrgpy
filename = "path/to/rld"
txt_dir = "path/to/txt/"
client_id = "https://cloud.nrgsystems.com/data-manager/api-setup"
client_secret = ""
converter = nrgpy.CloudConvert(
filename=filename,
client_id=client_id,
client_secret=client_secret,
)
Read files
file_filter = "000110"
import nrgpy
reader = nrgpy.SymProTextRead()
reader.concat_txt(
txt_dir=text_folder_name,
file_filter=file_filter,
start_date="2019-11-01",
end_date="2019-11-30",
)
RWD files
Convert a folder of RWD files to Text with Symphonie Data Retriever
import nrgpy
file_filter = '0434201902' # for Feb 2019 files from site 0434
rwd_directory = 'C:/Users/[user]/rwd/'
out_directory = 'C:/Users/[user]/txt/'
converter = nrgpy.local_rwd(file_filter=file_filter, rwd_dir=rwd_directory, out_dir=out_directory)
converter.convert()
Convert a folder of RWD files to Text with Symphonie Data Retriever on Linux
import nrgpy
rwd_directory = '/home/user/datafiles/rwd'
out_directory = '/home/user/datafiles/txt'
wine_directory = '/home/user/prefix32/drive_c/' # path to wine's "C:\" drive
converter = nrgpy.local_rwd(
file_filter=file_filter,
rwd_dir=rwd_directory,
out_dir=out_directory,
wine_folder=wine_directory,
use_site_file=False # set to True to use site files
)
converter.convert()
You can also convert a single file with SDR, and save it in the same directory:
import nrgpy
filename = '/path/to/file'
converter = nrgpy.local_rwd(filename=filename)
Read TXT files exported from RWD files
import nrgpy
dt = 'rwd'
txt_file = '/path/to/file.txt'
reader = nrgpy.read_text_data(data_type=dt, filename=txt_file)
or concatenate a whole lot of files:
dt = 'rwd'
txt_dir = '/path/to/text/files'
file_filter = 'text_in_filenames_you_want'
reader = nrgpy.read_text_data(data_type=dt, txt_dir=txt_dir, file_filter=file_filter)
reader.concat()
Spidar files
Spidar Vertical Profiler remote sensors generate archived csv data files in a Zip format.
These can be read directly into the spidar_txt_read method. See the docstring in spidar_txt.py for more information.
Eg.
In [1]: import nrgpy
In [2]: fname = "/spidar/1922AG7777_CAG70-SPPP-LPPP_NRG1_AVGWND_2019-07-07_1.zip"
In [3]: reader = nrgpy.SpidarRead(filename=fname)
In [4]: reader.heights
Out[4]: [40, 60, 80, 90, 100, 120, 130, 160, 180, 200]
In [5]: reader.data
Out[5]:
pressure[mmHg] temperature[C] ... dir_200_std[Deg] wind_measure_200_quality[%]
Timestamp ...
2019-07-06 23:40:00 749.66 24.13 ... 28.77 68
2019-07-06 23:50:00 749.63 24.08 ... 14.31 0
2019-07-07 00:00:00 749.64 23.99 ... 20.59 0
...
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