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https://github.com/aangelone2/das-c
Lightweight parallel Data Analysis Suite in C
https://github.com/aangelone2/das-c
c correlation-analysis data-analysis monte-carlo multithreading openmp
Last synced: 3 days ago
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Lightweight parallel Data Analysis Suite in C
- Host: GitHub
- URL: https://github.com/aangelone2/das-c
- Owner: aangelone2
- License: gpl-3.0
- Created: 2023-12-08T15:09:02.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-03-07T22:39:25.000Z (8 months ago)
- Last Synced: 2024-03-07T23:34:15.047Z (8 months ago)
- Topics: c, correlation-analysis, data-analysis, monte-carlo, multithreading, openmp
- Language: C
- Homepage:
- Size: 512 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# `das-c`
[](https://clang.llvm.org/docs/ClangFormat.html)
[](https://www.doxygen.nl/)
`das-c` (Data Analysis Suite in C) is a data analysis
suite for (Monte Carlo) numerical data.
The suite is designed as a lightweight, multi-threaded
alternative to its [python
counterpart](https://github.com/aangelone2/das),
offering its basic functionalities.
## Dependencies and Setup
The program only requires a version of `gcc` compatible
with the `gnu17` standard. The version used in
development is `13.2.1`.
The command
```
$ make test
```
will build the static library against which the program
will compile, as well as a battery of tests which will
be immediately executed. When successfully completed,
the output of this command should have the form
```
Beginning testing
cd build/ ; ./01.test-count_fields
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> Test completed successfully
...
All tests completed successfully
```
Independently from the testing command, the command
```
$ make build
```
will build the `build/das` executable and the static
library the latter will link to.
The command
```
$ make clean
```
resets the build environment.
## Current capabilities
The capabilities of `das-c` are programmed in *drivers*,
subcommands specialized for a specific task, and
include:
- Simple averaging and analysis of uncorrelated data
(`avs`);
- Binsize scaling to compute accurate errors for
correlated data (`ave`).
Each driver is invoked as
```
$ das
```
Executing any driver with the `-h` option will display a
help message and exit.
## Documentation
Building the documentation requires
[doxygen](https://www.doxygen.nl/). The command
```
$ make docs
```
re-generates the documentation in html format in the
`html/` directory, which can be accessed by opening in a
web browser the `html/index.html` page.
Most of the documentation (including all the information
related to the UI and the statistical background) can be
consulted on the [github
wiki](https://github.com/aangelone2/das-c/wiki).