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Zahra Rajabi
pymdptoolbox
Commits
8bfd8e84
Commit
8bfd8e84
authored
Aug 24, 2013
by
Steven Cordwell
Browse files
make some changes to the exception system, but it is still not how it should be
parent
969abd92
Changes
2
Show whitespace changes
Inline
Sidebyside
src/mdptoolbox/mdp.py
View file @
8bfd8e84
...
...
@@ 104,58 +104,6 @@ from scipy.sparse import csr_matrix as sparse
from
utils
import
check
,
getSpan
# These need to be fixed so that we use classes derived from Error.
mdperr
=
{
"mat_nonneg"
:
"PyMDPtoolbox: Probabilities must be nonnegative."
,
"mat_square"
:
"PyMDPtoolbox: The matrix must be square."
,
"mat_stoch"
:
"PyMDPtoolbox: Rows of the matrix must sum to one (1)."
,
"mask_numpy"
:
"PyMDPtoolbox: mask must be a numpy array or matrix; i.e. type(mask) is "
"ndarray or type(mask) is matrix."
,
"mask_SbyS"
:
"PyMDPtoolbox: The mask must have shape SxS; i.e. mask.shape = (S, S)."
,
"obj_shape"
:
"PyMDPtoolbox: Object arrays for transition probabilities and rewards "
"must have only 1 dimension: the number of actions A. Each element of "
"the object array contains an SxS ndarray or matrix."
,
"obj_square"
:
"PyMDPtoolbox: Each element of an object array for transition "
"probabilities and rewards must contain an SxS ndarray or matrix; i.e. "
"P[a].shape = (S, S) or R[a].shape = (S, S)."
,
"P_type"
:
"PyMDPtoolbox: The transition probabilities must be in a numpy array; "
"i.e. type(P) is ndarray."
,
"P_shape"
:
"PyMDPtoolbox: The transition probability array must have the shape "
"(A, S, S) with S : number of states greater than 0 and A : number of "
"actions greater than 0. i.e. R.shape = (A, S, S)"
,
"PR_incompat"
:
"PyMDPtoolbox: Incompatibility between P and R dimensions."
,
"prob_in01"
:
"PyMDPtoolbox: Probability p must be in [0; 1]."
,
"R_type"
:
"PyMDPtoolbox: The rewards must be in a numpy array; i.e. type(R) is "
"ndarray, or numpy matrix; i.e. type(R) is matrix."
,
"R_shape"
:
"PyMDPtoolbox: The reward matrix R must be an array of shape (A, S, S) or "
"(S, A) with S : number of states greater than 0 and A : number of "
"actions greater than 0. i.e. R.shape = (S, A) or (A, S, S)."
,
"R_gt_0"
:
"PyMDPtoolbox: The rewards must be greater than 0."
,
"S_gt_1"
:
"PyMDPtoolbox: Number of states S must be greater than 1."
,
"SA_gt_1"
:
"PyMDPtoolbox: The number of states S and the number of actions A must be "
"greater than 1."
,
"discount_rng"
:
"PyMDPtoolbox: Discount rate must be in ]0; 1]"
,
"maxi_min"
:
"PyMDPtoolbox: The maximum number of iterations must be greater than 0"
}
class
MDP
(
object
):
"""A Markov Decision Problem.
...
...
@@ 210,7 +158,7 @@ class MDP(object):
# in its computations
if
type
(
discount
)
in
(
int
,
float
):
if
(
discount
<=
0
)
or
(
discount
>
1
):
raise
ValueError
(
mdperr
[
"discount_rng"
]
)
raise
ValueError
(
"Discount rate must be in ]0; 1]"
)
else
:
if
discount
==
1
:
print
(
"PyMDPtoolbox WARNING: check conditions of "
...
...
@@ 224,7 +172,8 @@ class MDP(object):
# in its computations
if
type
(
max_iter
)
in
(
int
,
float
):
if
max_iter
<=
0
:
raise
ValueError
(
mdperr
[
"maxi_min"
])
raise
ValueError
(
"The maximum number of iterations must be "
"greater than 0"
)
else
:
self
.
max_iter
=
max_iter
elif
max_iter
is
not
None
:
...
...
src/mdptoolbox/utils.py
View file @
8bfd8e84
...
...
@@ 7,6 +7,54 @@ Created on Sun Aug 18 14:30:09 2013
from
numpy
import
absolute
,
ones
# These need to be fixed so that we use classes derived from Error.
mdperr
=
{
"mat_nonneg"
:
"Probabilities must be nonnegative."
,
"mat_square"
:
"The matrix must be square."
,
"mat_stoch"
:
"Rows of the matrix must sum to one (1)."
,
"mask_numpy"
:
"mask must be a numpy array or matrix; i.e. type(mask) is "
"ndarray or type(mask) is matrix."
,
"mask_SbyS"
:
"The mask must have shape SxS; i.e. mask.shape = (S, S)."
,
"obj_shape"
:
"Object arrays for transition probabilities and rewards "
"must have only 1 dimension: the number of actions A. Each element of "
"the object array contains an SxS ndarray or matrix."
,
"obj_square"
:
"Each element of an object array for transition "
"probabilities and rewards must contain an SxS ndarray or matrix; i.e. "
"P[a].shape = (S, S) or R[a].shape = (S, S)."
,
"P_type"
:
"The transition probabilities must be in a numpy array; "
"i.e. type(P) is ndarray."
,
"P_shape"
:
"The transition probability array must have the shape "
"(A, S, S) with S : number of states greater than 0 and A : number of "
"actions greater than 0. i.e. R.shape = (A, S, S)"
,
"PR_incompat"
:
"Incompatibility between P and R dimensions."
,
"prob_in01"
:
"Probability p must be in [0; 1]."
,
"R_type"
:
"The rewards must be in a numpy array; i.e. type(R) is "
"ndarray, or numpy matrix; i.e. type(R) is matrix."
,
"R_shape"
:
"The reward matrix R must be an array of shape (A, S, S) or "
"(S, A) with S : number of states greater than 0 and A : number of "
"actions greater than 0. i.e. R.shape = (S, A) or (A, S, S)."
,
"R_gt_0"
:
"The rewards must be greater than 0."
,
"S_gt_1"
:
"Number of states S must be greater than 1."
,
"SA_gt_1"
:
"The number of states S and the number of actions A must be "
"greater than 1."
}
def
check
(
P
,
R
):
"""Check if P and R define a valid Markov Decision Process (MDP).
...
...
@@ 38,8 +86,7 @@ def check(P, R):
>>>
>>> import numpy as np
>>> P_invalid = np.random.rand(5, 100, 100)
>>> mdptoolbox.utils.check(P_invalid, R_valid)
Error
>>> mdptoolbox.utils.check(P_invalid, R_valid) # Raises an exception
"""
# Checking P
...
...
@@ 241,3 +288,21 @@ def getSpan(W):
"""
return
(
W
.
max
()

W
.
min
())
class
Error
(
Exception
):
"""Base class for exceptions in this module."""
def
__init__
(
self
):
Exception
.
__init__
(
self
)
self
.
message
=
"PyMDPToolbox: "
def
__str__
(
self
):
return
repr
(
self
.
message
)
class
InvalidMDPError
(
Error
):
"""Class for invalid definitions of a MDP."""
def
__init__
(
self
,
msg
):
Error
.
__init__
(
self
)
self
.
message
+=
msg
self
.
args
=
tuple
(
msg
)
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