pyfunnel 1.0.1

Description:

pyfunnel 1.0.1

pyfunnel

A cross-platform C-based software for comparing two (x, y) data sets given tolerances in x and y directions.
Principles
Overall
A so-called funnel is generated around the reference (x, y) data points.
The funnel is sized according to the absolute or relative tolerance in
both x and y directions.
The algorithm then checks if any test data points are inside the funnel,
and reports these points in the file errors.csv in the output directory.
Four other files are stored in the output directory: reference data points,
test data points, lower bounds and upper bounds of the funnel.
One potential application is to validate the development of building
HVAC control sequences. By comparing data curves from real operation with
data curves from simulation, one can verify if the control sequences
have been implemented such that they produce a similar control response
than a simulation model that is considered to be the original specification.

Method to Compute the Funnel
The funnel is computed as follows.


Tolerance areas (based on L1-norm) are built around each reference data point.


The tolerance parameters correspond to the half-width and half-height of the
tolerance areas. They default to 0.


When using atolx and atoly, the tolerance is considered as absolute
(same unit as x and y).


When using ltolx and ltoly, the tolerance is considered relative
to the local value of x and y.


When using rtolx and rtoly, the tolerance is considered relative
to the range of x and y. This option is available mainly for compatibility with
the algorithm implemented in csv-compare
for relative comparison. It should be used with caution.




The algorithm selects which corners of the tolerance rectangles
are used to build the envelopes based on the change in the derivative sign at
each reference point.


Intersection boundary points are computed when a selected corner
happens not to be in the logical order with the next one on the x scale
(i.e., at a local extremum).
New envelopes are then built encompassing all boundary points, and points strictly
within the envelopes are dropped.


The comparison then simply consists of interpolating the upper and lower envelopes
at the x test values and comparing the yielded y_up and y_low values with the y test values.
By convention, the error is max(0, y - y_up) - min(0, y - y_low) and hence it is always positive.
How to Run
System Requirements
The software is tested on the following platforms.

Linux x64 (Ubuntu 20.04)
Windows x64 (Windows Server 2022)
macOS x64 and arm64 (macOS 12)

A Python binding is available to access the library. It is supported on Python versions 3.8 through 3.9.
Installing
The Python binding is delivered as a package named pyfunnel, available on PyPI.
For development, additional dependencies are needed and can be installed with
pip install -r requirements.txt
Main Functions
The software is primarily intended to be used by means of a Python binding.
The package pyfunnel provides the following functions.


compareAndReport: calls funnel binary with list-like objects as x, y reference and test values.
Outputs errors.csv, lowerBound.csv, upperBound.csv, reference.csv, test.csv
into the output directory (./results by default).


plot_funnel: plots funnel results stored in the directory which path is provided as argument.
Displays plot in default browser. See function docstring for further details.


The module pyfunnel.py can also be run with the following command line interface.
usage: pyfunnel.py [-h] --reference REFERENCE --test TEST [--output OUTPUT] [--atolx ATOLX] [--atoly ATOLY] [--ltolx LTOLX] [--ltoly LTOLY] [--rtolx RTOLX] [--rtoly RTOLY]

Run funnel binary from terminal on two two-column CSV files.

Output `errors.csv`, `lowerBound.csv`, `upperBound.csv`, `reference.csv`, `test.csv` into the output directory (`./results` by default).

optional arguments:
-h, --help show this help message and exit
--output OUTPUT Path of directory to store output data
--atolx ATOLX Absolute tolerance along x axis
--atoly ATOLY Absolute tolerance along y axis
--ltolx LTOLX Relative tolerance along x axis (relatively to the local value)
--ltoly LTOLY Relative tolerance along y axis (relatively to the local value)
--rtolx RTOLX Relative tolerance along x axis (relatively to the range)
--rtoly RTOLY Relative tolerance along y axis (relatively to the range)

required named arguments:
--reference REFERENCE Path of two-column CSV file with reference data
--test TEST Path of two-column CSV file with test data

Full documentation at https://github.com/lbl-srg/funnel

Example
From a Python shell with ./tests/test_bin as the current working directory, run
>>> import pandas as pd
>>> import pyfunnel
>>> ref = pd.read_csv('trended.csv')
>>> test = pd.read_csv('simulated.csv')
>>> pyfunnel.compareAndReport(xReference=ref.iloc(axis=1)[0], yReference=ref.iloc(axis=1)[1],
... xTest=test.iloc(axis=1)[0], yTest=test.iloc(axis=1)[1], atolx=0.002, atoly=0.002)
>>> pyfunnel.plot_funnel('results')

Or from a terminal with ./tests/test_bin as the current working directory, run
$ python ../../pyfunnel/pyfunnel.py --reference trended.csv --test simulated.csv --atolx 0.002 --atoly 0.002

Build from Source
System Requirements
The cross-platform build system relies on CMake (version 3.22).
The distributed binaries are built with Microsoft Visual Studio C/C++ compiler
(Windows), Clang (macOS) and GCC (Linux).
Procedure
To compile, link and install, from the top-level directory, run the following commands
mkdir build
cd build
cmake .. (add `-A x64` on Windows to compile in 64 bits)
cmake --build . --target install (add `--config Release` on Windows)

To run the tests, from ./build run
ctest (add `-C Release` on Windows)

License
Modified 3-clause BSD, see LICENSE.txt.
Copyright
See COPYRIGHT.txt.