Recent changes to Home

Home modified by Dominik

Dominik — Fri, 05 Jun 2015 13:31:52 -0000

--- v4
+++ v5
@@ -8,6 +8,10 @@
 It is all based on list representations of coordinates and matrices.

 The functionality is tested with the unit test script "testPurePythonPolyFit.py". This test actually needs numpy for verification.
+
+Examples:
+====
+In this section you can find examples for polyfitting, QR decomposition and least squares solving

 Example: Polynomial Fitting
 ------------------

Home modified by Dominik

Dominik — Fri, 05 Jun 2015 13:29:35 -0000

--- v3
+++ v4
@@ -9,7 +9,7 @@

 The functionality is tested with the unit test script "testPurePythonPolyFit.py". This test actually needs numpy for verification.

-Example use for polynomial fitting
+Example: Polynomial Fitting
 ------------------
 (conceptual, see also end of  "purePythonPolyFit.py" for example usage):

@@ -33,7 +33,7 @@
     # evaluate N-D
     pn[(0.5, 1.0, 0.2, 0.2)]

-QR decomposition of a Matrix
+Example: QR Decomposition of a Matrix
 ------------------

     :::python
@@ -42,7 +42,7 @@
     # the result:
     Q,R = qr(A)

-Solve least squares
+Example: Solve Least Squares system
 ------------------
 Find a least squares solution x, for the system Ax =y

Home modified by Dominik

Dominik — Fri, 05 Jun 2015 13:28:49 -0000

--- v2
+++ v3
@@ -1,3 +1,5 @@
+pure python polyfit
+==================
 Welcome to pure python polyfit, the polynomial fitting without any third party module like numpy, scipy, etc.

 You can fit polynomials in 1D, 2D or generally in N-D.
@@ -7,7 +9,9 @@

 The functionality is tested with the unit test script "testPurePythonPolyFit.py". This test actually needs numpy for verification.

-Example use for polynomial fitting (conceptual, see also end of  "purePythonPolyFit.py" for example usage):
+Example use for polynomial fitting
+------------------
+(conceptual, see also end of  "purePythonPolyFit.py" for example usage):

     :::python
     # estimate 1D, x and y lists of floats
@@ -28,3 +32,24 @@
     pn = PolyFitND(pts, vals, order=3)
     # evaluate N-D
     pn[(0.5, 1.0, 0.2, 0.2)]
+
+QR decomposition of a Matrix
+------------------
+
+    :::python
+    # matrix are represented with lists of lists/tuples:
+    A=[[1,2,3],[4,5,6]]
+    # the result:
+    Q,R = qr(A)
+
+Solve least squares
+------------------
+Find a least squares solution x, for the system Ax =y 
+
+    :::python
+    # a random overdetermined matrix:
+    A=[[1,2],[2,5],[5,4]]
+    # a noise measurement vector:
+    b=[1,2,3]
+    # the result:
+    solution, residual = leastSquareSolution(A,b)

Home modified by Dominik

Dominik — Fri, 05 Jun 2015 13:21:51 -0000

--- v1
+++ v2
@@ -1,8 +1,30 @@
-Welcome to your wiki!
+Welcome to pure python polyfit, the polynomial fitting without any third party module like numpy, scipy, etc.

-This is the default page, edit it as you see fit. To add a new page simply reference it within brackets, e.g.: [SamplePage].
+You can fit polynomials in 1D, 2D or generally in N-D.

-The wiki uses [Markdown](/p/purepythonpolyfit/wiki/markdown_syntax/) syntax.
+Also you can solve a system of least squares or compute A= Q*R for a matrix A.
+It is all based on list representations of coordinates and matrices.

-[[members limit=20]]
-[[download_button]]
+The functionality is tested with the unit test script "testPurePythonPolyFit.py". This test actually needs numpy for verification.
+
+Example use for polynomial fitting (conceptual, see also end of  "purePythonPolyFit.py" for example usage):
+
+    :::python
+    # estimate 1D, x and y lists of floats
+    p = PolyFit(x, y, order=2)
+    # evaluate 1D
+    p[0.5]
+
+    # estimate 2D, pts list of tuples/list of length 2
+    #  (e.g. pts = [(1.0, 4.1),(4.2, 0.1), ...])
+    # vals: list of floats
+    p2 = PolyFit2D(pts, vals, order=3)
+    # evaluate 2D
+    p2[(0.5, 1.0)]
+
+    # estimate N-D, pts list of tuples/list of length N
+    # (e.g. [(1.0, 4.1, 0, 0),(0, 4.2, 0, 0.1), ...])
+    # vals: list of floats
+    pn = PolyFitND(pts, vals, order=3)
+    # evaluate N-D
+    pn[(0.5, 1.0, 0.2, 0.2)]

Home modified by Dominik

Dominik — Fri, 05 Jun 2015 09:14:39 -0000

Welcome to your wiki!

This is the default page, edit it as you see fit. To add a new page simply reference it within brackets, e.g.: [SamplePage].

The wiki uses Markdown syntax.

Project Members:

Dominik (admin)