tra-analysis/analysis-master/tra_analysis/Fit.py
Arthur Lu 60beaa4563 tra-analysis v 3.0.0 aggregate PR (#73)
* reflected doc changes to README.md

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* tra_analysis v 2.1.0-alpha.1

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* changed setup.py to use __version__ from source
added Topic and keywords

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* updated Supported Platforms in README.md

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* moved required files back to parent

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* moved security back to parent

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* moved security back to parent
moved contributing back to parent

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* add PR template

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* moved to parent folder

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* moved meta files to .github folder

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* Analysis.py v 3.0.1

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* updated test_analysis for submodules, and added missing numpy import in Sort.py

* fixed item one of Issue #58

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* readded cache searching in postCreateCommand

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* added myself as an author

* feat: created kivy gui boilerplate

* added Kivy to requirements.txt

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* feat: gui with placeholders

* fix: changed config.json path

* migrated docker base image to debian

Signed-off-by: ltcptgeneral <learthurgo@gmail.com>

* style: spaces to tabs

* migrated to ubuntu

Signed-off-by: ltcptgeneral <learthurgo@gmail.com>

* fixed issues

Signed-off-by: ltcptgeneral <learthurgo@gmail.com>

* fix: docker build?

* fix: use ubuntu bionic

* fix: get kivy installed

* @ltcptgeneral can't spell

* optim dockerfile for not installing unused packages

* install basic stuff while building the container

* use prebuilt image for development

* install pylint on base image

* rename and use new kivy

* tests: added tests for Array and CorrelationTest

Both are not working due to errors

* use new thing

* use 20.04 base

* symlink pip3 to pip

* use pip instead of pip3

* equation.Expression.py v 0.0.1-alpha
added corresponding .pyc to .gitignore

* parser.py v 0.0.2-alpha

* added pyparsing to requirements.txt

* parser v 0.0.4-alpha

* Equation v 0.0.1-alpha

* added Equation to tra_analysis imports

* tests: New unit tests for submoduling (#66)

* feat: created kivy gui boilerplate

* migrated docker base image to debian

Signed-off-by: ltcptgeneral <learthurgo@gmail.com>

* migrated to ubuntu

Signed-off-by: ltcptgeneral <learthurgo@gmail.com>

* fixed issues

Signed-off-by: ltcptgeneral <learthurgo@gmail.com>

* fix: docker build?

* fix: use ubuntu bionic

* fix: get kivy installed

* @ltcptgeneral can't spell

* optim dockerfile for not installing unused packages

* install basic stuff while building the container

* use prebuilt image for development

* install pylint on base image

* rename and use new kivy

* tests: added tests for Array and CorrelationTest

Both are not working due to errors

* fix: Array no longer has *args and CorrelationTest functions no longer have self in the arguments

* use new thing

* use 20.04 base

* symlink pip3 to pip

* use pip instead of pip3

* tra_analysis v 2.1.0-alpha.2
SVM v 1.0.1
added unvalidated SVM unit tests

Signed-off-by: ltcptgeneral <learthurgo@gmail.com>

* fixed version number

Signed-off-by: ltcptgeneral <learthurgo@gmail.com>

* tests: added tests for ClassificationMetric

* partially fixed and commented out svm unit tests

* fixed some SVM unit tests

* added installing pytest to devcontainer.json

* fix: small fixes to KNN

Namely, removing self from parameters and passing correct arguments to KNeighborsClassifier constructor

* fix, test: Added tests for KNN and NaiveBayes.

Also made some small fixes in KNN, NaiveBayes, and RegressionMetric

* test: finished unit tests except for StatisticalTest

Also made various small fixes and style changes

* StatisticalTest v 1.0.1

* fixed RegressionMetric unit test
temporarily disabled CorrelationTest unit tests

* tra_analysis v 2.1.0-alpha.3

* readded __all__

* fix: floating point issues in unit tests for CorrelationTest

Co-authored-by: AGawde05 <agawde05@gmail.com>
Co-authored-by: ltcptgeneral <learthurgo@gmail.com>
Co-authored-by: Dev Singh <dev@devksingh.com>
Co-authored-by: jzpan1 <panzhenyu2014@gmail.com>

* fixed depreciated escape sequences

* ficed tests, indent, import in test_analysis

* changed version to 3.0.0
added backwards compatibility

* ficed pytest install in container

* removed GUI changes

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* incremented version to rc.1 (release candidate 1)

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* fixed NaiveBayes __changelog__

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* fix: __setitem__  == to single =

* Array v 1.0.1

* Revert "Array v 1.0.1"

This reverts commit 59783b79f7.

* Array v 1.0.1

* Array.py v 1.0.2
added more Array unit tests

* cleaned .gitignore
tra_analysis v 3.0.0-rc2

Signed-off-by: Arthur Lu <learthurgo@gmail.com>

* added *.pyc to gitignore
finished subdividing test_analysis

* feat: gui layout + basic func

* Froze and removed superscript (data-analysis)

* remove data-analysis deps install for devcontainer

* tukey pairwise comparison and multicomparison but no critical q-values

* quick patch for devcontainer.json

* better fix for devcontainer.json

* fixed some styling in StatisticalTest
removed print statement in StatisticalTest unit tests

* update analysis tests to be more effecient

* don't use loop for test_nativebayes

* removed useless secondary docker files

* tra-analysis v 3.0.0

Co-authored-by: James Pan <panzhenyu2014@gmail.com>
Co-authored-by: AGawde05 <agawde05@gmail.com>
Co-authored-by: zpan1 <72054510+zpan1@users.noreply.github.com>
Co-authored-by: Dev Singh <dev@devksingh.com>
Co-authored-by: = <=>
Co-authored-by: Dev Singh <dsingh@imsa.edu>
Co-authored-by: zpan1 <zpan@imsa.edu>
2021-04-28 19:33:50 -05:00

87 lines
2.5 KiB
Python

# Titan Robotics Team 2022: CPU fitting models
# Written by Dev Singh
# Notes:
# this module is cuda-optimized (as appropriate) and vectorized (except for one small part)
# setup:
__version__ = "0.0.2"
# changelog should be viewed using print(analysis.fits.__changelog__)
__changelog__ = """changelog:
0.0.2:
- renamed module to Fit
0.0.1:
- initial release, add circle fitting with LSC
"""
__author__ = (
"Dev Singh <dev@devksingh.com>"
)
__all__ = [
'CircleFit'
]
import numpy as np
class CircleFit:
"""Class to fit data to a circle using the Least Square Circle (LSC) method"""
# For more information on the LSC method, see:
# http://www.dtcenter.org/sites/default/files/community-code/met/docs/write-ups/circle_fit.pdf
def __init__(self, x, y, xy=None):
self.ournp = np #todo: implement cupy correctly
if type(x) == list:
x = np.array(x)
if type(y) == list:
y = np.array(y)
if type(xy) == list:
xy = np.array(xy)
if xy != None:
self.coords = xy
else:
# following block combines x and y into one array if not already done
self.coords = self.ournp.vstack(([x.T], [y.T])).T
def calc_R(x, y, xc, yc):
"""Returns distance between center and point"""
return self.ournp.sqrt((x-xc)**2 + (y-yc)**2)
def f(c, x, y):
"""Returns distance between point and circle at c"""
Ri = calc_R(x, y, *c)
return Ri - Ri.mean()
def LSC(self):
"""Fits given data to a circle and returns the center, radius, and variance"""
x = self.coords[:, 0]
y = self.coords[:, 1]
# guessing at a center
x_m = self.ournp.mean(x)
y_m = self.ournp.mean(y)
# calculation of the reduced coordinates
u = x - x_m
v = y - y_m
# linear system defining the center (uc, vc) in reduced coordinates:
# Suu * uc + Suv * vc = (Suuu + Suvv)/2
# Suv * uc + Svv * vc = (Suuv + Svvv)/2
Suv = self.ournp.sum(u*v)
Suu = self.ournp.sum(u**2)
Svv = self.ournp.sum(v**2)
Suuv = self.ournp.sum(u**2 * v)
Suvv = self.ournp.sum(u * v**2)
Suuu = self.ournp.sum(u**3)
Svvv = self.ournp.sum(v**3)
# Solving the linear system
A = self.ournp.array([ [ Suu, Suv ], [Suv, Svv]])
B = self.ournp.array([ Suuu + Suvv, Svvv + Suuv ])/2.0
uc, vc = self.ournp.linalg.solve(A, B)
xc_1 = x_m + uc
yc_1 = y_m + vc
# Calculate the distances from center (xc_1, yc_1)
Ri_1 = self.ournp.sqrt((x-xc_1)**2 + (y-yc_1)**2)
R_1 = self.ournp.mean(Ri_1)
# calculate residual error
residu_1 = self.ournp.sum((Ri_1-R_1)**2)
return (xc_1, yc_1, R_1, residu_1)