Cope 2.5.0
My personal "standard library" of all the generally useful code I've written for various projects over the years
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Classes | |
class | Space |
Functions | |
def | matrix (string, rows=None, cols=None, cp=False, np=False, immutable=False, verbose=False) |
def | combineMatricies (*mats) |
def | columnspace (M) |
def | eigenspaces (mat) |
def | convert2Equs (mat, vars) |
def | isSimilar (*args) |
def | steadyState (stochastic, accuracy=10000000000000, verbose=False) |
def | randMarkovState (rows, balanced=True, np=False) |
def | isOrthogonal (*vects, innerProduct=None) |
def | vectorLength (v) |
def | EuclideanDist (u, v) |
def | manhattanDist (a, b) |
def | minkowskiDist (a, b, p) |
def | orthonormalize (orthogonalSet) |
list | splitVector ('Matrix' y, 'Space' W, innerProduct=None) |
'(vector in W, vector in W⟂)' | project ('Matrix' y, 'Space' W, innerProduct=None) |
def | normalizePercentage (p, error='Percentage is of the wrong type(int or float expected)') |
def Cope.experimental.linalg.columnspace | ( | M | ) |
def Cope.experimental.linalg.combineMatricies | ( | * | mats | ) |
def Cope.experimental.linalg.convert2Equs | ( | mat, | |
vars | |||
) |
Converts a matrix into the list of equations it represents
def Cope.experimental.linalg.eigenspaces | ( | mat | ) |
def Cope.experimental.linalg.EuclideanDist | ( | u, | |
v | |||
) |
def Cope.experimental.linalg.isOrthogonal | ( | * | vects, |
innerProduct = None |
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) |
def Cope.experimental.linalg.isSimilar | ( | * | args | ) |
def Cope.experimental.linalg.manhattanDist | ( | a, | |
b | |||
) |
def Cope.experimental.linalg.matrix | ( | string, | |
rows = None , |
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cols = None , |
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cp = False , |
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np = False , |
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immutable = False , |
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verbose = False |
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) |
def Cope.experimental.linalg.minkowskiDist | ( | a, | |
b, | |||
p | |||
) |
def Cope.experimental.linalg.normalizePercentage | ( | p, | |
error = 'Percentage is of the wrong type (int or float expected)' |
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) |
def Cope.experimental.linalg.orthonormalize | ( | orthogonalSet | ) |
'(vector in W, vector in W⟂)' Cope.experimental.linalg.project | ( | 'Matrix' | y, |
'Space' | W, | ||
innerProduct = None |
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) |
W = a subspace of R^n we want to describe y with (to get proj_y) y = some y in R^n proj_y = a vector in W z = a vector in W⟂ (W perp)
def Cope.experimental.linalg.randMarkovState | ( | rows, | |
balanced = True , |
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np = False |
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) |
list Cope.experimental.linalg.splitVector | ( | 'Matrix' | y, |
'Space' | W, | ||
innerProduct = None |
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) |
Returns vectors in W which can be linearly combined to get y
def Cope.experimental.linalg.steadyState | ( | stochastic, | |
accuracy = 10000000000000 , |
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verbose = False |
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) |
def Cope.experimental.linalg.vectorLength | ( | v | ) |