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Improve docstring to meet numpydoc style
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@KybernetikJo
KybernetikJo committed Aug 26, 2023
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Showing 1 changed file with 55 additions and 55 deletions.
110 changes: 55 additions & 55 deletions slycot/analysis.py
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Original file line number Diff line number Diff line change
Expand Up @@ -67,9 +67,9 @@ def ab01nd(n, m, A, B, jobz='N', tol=0, ldwork=None):
the order of the matrix A. ``n > 0``.
m : int
The number of system inputs, or of columns of B. ``m > 0``.
A : (n,n) array_like
A : (n, n) array_like
The original state dynamics matrix A.
B : (n,m) array_like
B : (n, m) array_like
The input matrix B.
jobz : {'N', 'F', 'I'}, optional
Indicates whether the user wishes to accumulate in a matrix Z
Expand All @@ -92,12 +92,12 @@ def ab01nd(n, m, A, B, jobz='N', tol=0, ldwork=None):
Returns
-------
Ac : (n,n) ndarray
Ac : (n, n) ndarray
The leading ncont-by-ncont part contains the upper block
Hessenberg state dynamics matrix Acont in Ac, given by Z'*A*Z,
of a controllable realization for the original system. The
elements below the first block-subdiagonal are set to zero.
Bc : (n,m) ndarray
Bc : (n, m) ndarray
The leading ncont-by-m part of this array contains the transformed
input matrix Bcont in Bc, given by ``Z'*B``, with all elements but the
first block set to zero.
Expand Down Expand Up @@ -164,16 +164,16 @@ def ab04md(type_t, n, m, p, A, B, C, D, alpha=1.0, beta=1.0, ldwork=None):
p : int
The number of rows of matrix C. It represents the dimension of
the output vector. p > 0.
A : (n,n) array_like
A : (n, n) array_like
The leading n-by-n part of this array must contain the system state
matrix A.
B : (n,m) array_like
B : (n, m) array_like
The leading n-by-m part of this array must contain the system input
matrix B.
C : (p,n) array_like
C : (p, n) array_like
The leading p-by-n part of this array must contain the system output
matrix C.
D : (p,m) array_like
D : (p, m) array_like
The leading p-by-m part of this array must contain the system direct
transmission matrix D.
alpha : double, optional
Expand All @@ -189,13 +189,13 @@ def ab04md(type_t, n, m, p, A, B, C, D, alpha=1.0, beta=1.0, ldwork=None):
ldwork >= max(1, n), default is max(1, n)
Returns
-------
At : (n,n) ndarray
At : (n, n) ndarray
The state matrix At of the transformed system.
Bt : (n,m) ndarray
Bt : (n, m) ndarray
The input matrix Bt of the transformed system.
Ct : (p,n) ndarray
Ct : (p, n) ndarray
The output matrix Ct of the transformed system.
Dt : (p,m) ndarray
Dt : (p, m) ndarray
The transmission matrix Dt of the transformed system.
Raises
------
Expand Down Expand Up @@ -241,28 +241,28 @@ def ab05md(n1,m1,p1,n2,p2,A1,B1,C1,D1,A2,B2,C2,D2,uplo='U'):
of the matrix A2. n2 > 0.
p2 : int
The number of output variables from the second system. p2 > 0.
A1 : (n1,n1) array_like
A1 : (n1, n1) array_like
The leading n1-by-n1 part of this array must contain the state
transition matrix A1 for the first system.
B1 : (n1,m1) array_like
B1 : (n1, m1) array_like
The leading n1-by-m1 part of this array must contain the input/state
matrix B1 for the first system.
C1 : (p1,n1) array_like
C1 : (p1, n1) array_like
The leading p1-by-n1 part of this array must contain the state/output
matrix C1 for the first system.
D1 : (p1,m1) array_like
D1 : (p1, m1) array_like
The leading p1-by-m1 part of this array must contain the input/output
matrix D1 for the first system.
A2 : (n2,n2) array_like
A2 : (n2, n2) array_like
The leading n2-by-n2 part of this array must contain the state
transition matrix A2 for the second system.
B2 : (n2,p1) array_like
B2 : (n2, p1) array_like
The leading n2-by-p1 part of this array must contain the input/state
matrix B2 for the second system.
C2 : (p2,n2) array_like
C2 : (p2, n2) array_like
The leading p2-by-n2 part of this array must contain the state/output
matrix C2 for the second system.
D2 : (p2,p1) array_like
D2 : (p2, p1) array_like
The leading p2-by-p1 part of this array must contain the input/output
matrix D2 for the second system.
uplo : {'U', 'L'}, optional
Expand All @@ -278,16 +278,16 @@ def ab05md(n1,m1,p1,n2,p2,A1,B1,C1,D1,A2,B2,C2,D2,uplo='U'):
The number of state variables (n1 + n2) in the resulting system,
i.e. the order of the matrix A, the number of rows of B and
the number of columns of C.
A : (n1+n2,n1+n2) ndarray
A : (n1+n2, n1+n2) ndarray
The leading N-by-N part of this array contains the state transition
matrix A for the cascaded system.
B : (n1+n2,m1) ndarray
B : (n1+n2, m1) ndarray
The leading n-by-m1 part of this array contains the input/state
matrix B for the cascaded system.
C : (p2,n1+n2) ndarray
C : (p2, n1+n2) ndarray
The leading p2-by-n part of this array contains the state/output
matrix C for the cascaded system.
D : (p2,m1) ndarray
D : (p2, m1) ndarray
The leading p2-by-m1 part of this array contains the input/output
matrix D for the cascaded system.
Expand Down Expand Up @@ -333,28 +333,28 @@ def ab05nd(n1,m1,p1,n2,A1,B1,C1,D1,A2,B2,C2,D2,alpha=1.0,ldwork=None):
n2 : int
The number of state variables in the second system, i.e. the order
of the matrix A2. n2 > 0.
A1 : (n1,n1) array_like
A1 : (n1, n1) array_like
The leading n1-by-n1 part of this array must contain the state
transition matrix A1 for the first system.
B1 : (n1,m1) array_like
B1 : (n1, m1) array_like
The leading n1-by-m1 part of this array must contain the input/state
matrix B1 for the first system.
C1 : (p1,n1) array_like
C1 : (p1, n1) array_like
The leading p1-by-n1 part of this array must contain the state/output
matrix C1 for the first system.
D1 : (p1,m1) array_like
D1 : (p1, m1) array_like
The leading p1-by-m1 part of this array must contain the input/output
matrix D1 for the first system.
A2 : (n2,n2) array_like
A2 : (n2, n2) array_like
The leading n2-by-n2 part of this array must contain the state
transition matrix A2 for the second system.
B2 : (n2,p1) array_like
B2 : (n2, p1) array_like
The leading n2-by-p1 part of this array must contain the input/state
matrix B2 for the second system.
C2 : (m1,n2) array_like
C2 : (m1, n2) array_like
The leading m1-by-n2 part of this array must contain the state/output
matrix C2 for the second system.
D2 : (m1,p1) array_like
D2 : (m1, p1) array_like
The leading m1-by-p1 part of this array must contain the input/output
matrix D2 for the second system.
alpha : float, optional
Expand All @@ -373,16 +373,16 @@ def ab05nd(n1,m1,p1,n2,A1,B1,C1,D1,A2,B2,C2,D2,alpha=1.0,ldwork=None):
The number of state variables (n1 + n2) in the connected system, i.e.
the order of the matrix A, the number of rows of B and the number of
columns of C.
A : (n1+n2,n1+n2) ndarray
A : (n1+n2, n1+n2) ndarray
The leading n-by-n part of this array contains the state transition
matrix A for the connected system.
B : (n1+n2,m1) ndarray
B : (n1+n2, m1) ndarray
The leading n-by-m1 part of this array contains the input/state
matrix B for the connected system.
C : (p1,n1,n2) ndarray
C : (p1, n1, n2) ndarray
The leading p1-by-n part of this array contains the state/output
matrix C for the connected system.
D : (p1,m1) ndarray
D : (p1, m1) ndarray
The leading p1-by-m1 part of this array contains the input/output
matrix D for the connected system.
Expand Down Expand Up @@ -419,19 +419,19 @@ def ab07nd(n,m,A,B,C,D,ldwork=None):
Parameters
----------
n : int
The order of the state matrix A. n >= 0.
The order of the state matrix A. n >= 0.
m : int
The number of system inputs and outputs. m >= 0.
A : (n,n) array_like
The number of system inputs and outputs. m >= 0.
A : (n, n) array_like
The leading n-by-n part of this array must contain the state matrix
A of the original system.
B : (n,m) array_like
B : (n, m) array_like
The leading n-by-m part of this array must contain the input matrix
B of the original system.
C : (m,n) array_like
C : (m, n) array_like
The leading m-by-n part of this array must contain the output matrix
C of the original system.
D : (m,m) array_like
D : (m, m) array_like
The leading m-by-m part of this array must contain the feedthrough
matrix D of the original system.
ldwork : int, optional
Expand All @@ -440,16 +440,16 @@ def ab07nd(n,m,A,B,C,D,ldwork=None):
Returns
-------
Ai : (n,n) ndarray
Ai : (n, n) ndarray
The leading n-by-n part of this array contains the state matrix Ai
of the inverse system.
Bi : (n,m) ndarray
Bi : (n, m) ndarray
The leading n-by-m part of this array contains the input matrix Bi
of the inverse system.
Ci : (m,n) ndarray
Ci : (m, n) ndarray
The leading m-by-n part of this array contains the output matrix Ci
of the inverse system.
Di : (m,m) ndarray
Di : (m, m) ndarray
The leading m-by-m part of this array contains the feedthrough
matrix Di of the inverse system.
rcond : float
Expand Down Expand Up @@ -707,11 +707,11 @@ def ab09ad(dico,job,equil,n,m,p,A,B,C,nr=None,tol=0,ldwork=None):
Balance `B` or not `N`
equil : {'S', 'N'}
Scale `S` or not `N`
n : input int
n : int
The number of state variables. n >= 0.
m : input int
m : int
The number of system inputs. m >= 0.
p : input int
p : int
The number of system outputs. p >= 0.
A : (n, n) array_like
The leading n-by-n part of this array must contain the state
Expand Down Expand Up @@ -994,7 +994,7 @@ def ab09bd(dico,job,equil,n,m,p,A,B,C,D,nr=None,tol1=0,tol2=0,ldwork=None):
nr is the desired order of
the resulting reduced order system. 0 <= nr <= n.
Default is None.
tol1 : double precision, optional
tol1 : float, optional
If ordsel = 'A', tol1 contains the tolerance for
determining the order of reduced system.
For model reduction, the recommended value is
Expand All @@ -1007,7 +1007,7 @@ def ab09bd(dico,job,equil,n,m,p,A,B,C,D,nr=None,tol1=0,tol2=0,ldwork=None):
This value is used by default if tol1 <= 0 on entry.
If ordsel = 'F', the value of tol1 is ignored.
Default is `0.0`.
tol2 : double precision, optional
tol2 : float, optional
The tolerance for determining the order of a minimal
realization of the given system. The recommended value is
tol2 = n*eps*hnorm(A,B,C). This value is used by default
Expand Down Expand Up @@ -1148,7 +1148,7 @@ def ab09md(dico,job,equil,n,m,p,A,B,C,alpha=None,nr=None,tol=0,ldwork=None):
On entry with ordsel = 'F', nr is the desired order of the
resulting reduced order system. 0 <= nr <= n.
Default is None.
tol : double precision, optional
tol : float, optional
If ordsel = 'A', tol contains the tolerance for
determining the order of reduced system.
For model reduction, the recommended value is
Expand Down Expand Up @@ -1322,7 +1322,7 @@ def ab09nd(dico,job,equil,n,m,p,A,B,C,D,alpha=None,nr=None,tol1=0,tol2=0,ldwork=
nr is the desired order of
the resulting reduced order system. 0 <= nr <= n.
Default is None.
tol1 : double precision, optional
tol1 : float, optional
If ordsel = 'A', tol1 contains the tolerance for
determining the order of reduced system.
For model reduction, the recommended value is
Expand All @@ -1338,7 +1338,7 @@ def ab09nd(dico,job,equil,n,m,p,A,B,C,D,alpha=None,nr=None,tol1=0,tol2=0,ldwork=
of the alpha-stable part.
If ordsel = 'F', the value of tol1 is ignored.
Default is `0.0`.
tol2 : double precision, optional
tol2 : float, optional
The tolerance for determining the order of a minimal
realization of the alpha-stable part of the given system.
The recommended value is tol2 = ns*eps*hnorm(As,Bs,Cs).
Expand Down Expand Up @@ -1670,7 +1670,7 @@ def ab13ed(n, A, tol = 9.0):
----------
n : int
The order of the matrix A. ``n >= 0.``
A : (n,n) array_like
A : (n, n) array_like
The leading n-by-n part of this array must contain the matrix A.
tol : float, optional
Specifies the accuracy with which low and high approximate
Expand Down

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