def hessian(output_string):
""" read hessian from the output string
"""
try:
comp_ptt = app.one_of_these(['X', 'Y', 'Z']) + app.UNSIGNED_INTEGER
mat = ar.matrix.read(
output_string,
start_ptt=(app.escape('The second derivative matrix:') +
app.lpadded(app.NEWLINE)),
block_start_ptt=(app.series(comp_ptt, app.LINESPACES) +
app.padded(app.NEWLINE)),
line_start_ptt=comp_ptt,
tril=True)
except TypeError:
comp_ptt = app.UNSIGNED_INTEGER
mat = ar.matrix.read(
output_string,
val_ptt=app.EXPONENTIAL_FLOAT_D,
start_ptt=(
app.escape('Force constants in Cartesian coordinates:') +
app.lpadded(app.NEWLINE)),
block_start_ptt=(app.series(comp_ptt, app.LINESPACES) +
app.padded(app.NEWLINE)),
line_start_ptt=comp_ptt,
tril=True)
mat = [[_cast(apf.replace('d', 'e', dst, case=False)) for dst in row]
for row in mat]
mat = tuple(map(tuple, mat))
return mat
def hessian(output_str):
""" Reads the molecular Hessian (in Cartesian coordinates) from
the output file string. Returns the Hessian in atomic units.
:param output_str: string of the program's output file
:type output_str: str
:rtype: tuple(tuple(float))
"""
comp_ptt = app.one_of_these(['X', 'Y', 'Z']) + app.UNSIGNED_INTEGER
mat = ar.matrix.read(
output_str,
start_ptt=(app.escape('The second derivative matrix:') +
app.lpadded(app.NEWLINE)),
block_start_ptt=(app.series(comp_ptt, app.LINESPACES) +
app.padded(app.NEWLINE)),
line_start_ptt=comp_ptt,
tril=True)
if mat is None:
comp_ptt = app.UNSIGNED_INTEGER
mat = ar.matrix.read(
output_str,
val_ptt=app.EXPONENTIAL_FLOAT_D,
start_ptt=(
app.escape('Force constants in Cartesian coordinates:') +
app.lpadded(app.NEWLINE)),
block_start_ptt=(app.series(comp_ptt, app.LINESPACES) +
app.padded(app.NEWLINE)),
line_start_ptt=comp_ptt,
tril=True)
if mat is not None:
mat = [[_cast(apf.replace('d', 'e', dst, case=False)) for dst in row]
for row in mat]
def hessian(output_str):
""" Reads the molecular Hessian (in Cartesian coordinates) from
the output file string. Returns the Hessian in atomic units.
:param output_str: string of the program's output file
:type output_str: str
:rtype: tuple(tuple(float))
"""
comp_ptt = (app.one_or_more(app.LETTER) +
app.one_of_these(['X', 'Y', 'Z']) + app.UNSIGNED_INTEGER)
mat = ar.matrix.read(
output_str,
start_ptt=(
app.escape('Force Constants (Second Derivatives of the Energy) ') +
app.escape('in [a.u.]') + app.lpadded(app.NEWLINE)),
block_start_ptt=(app.series(comp_ptt, app.LINESPACES) +
app.padded(app.NEWLINE)),
line_start_ptt=comp_ptt,
tril=True)
if mat is not None:
mat = tuple(map(tuple, mat))
return mat
def hessian(output_str):
""" Reads the molecular Hessian (in Cartesian coordinates) from
the output file string. Returns the Hessian in atomic units.
:param output_str: string of the program's output file
:type output_str: str
:rtype: tuple(tuple(float))
"""
comp_ptt = app.UNSIGNED_INTEGER
mat = ar.matrix.read(
output_str,
val_ptt=app.FLOAT,
start_ptt=(
app.escape('Final Hessian.') +
app.lpadded(app.NEWLINE)),
block_start_ptt=(app.series(comp_ptt, app.LINESPACES) +
app.padded(app.NEWLINE)),
line_start_ptt=comp_ptt,
tril=False)
if mat is not None:
mat = tuple(map(tuple, mat))
return mat
def hessian2(output_string):
""" read hessian from the output string
"""
comp_ptt = app.UNSIGNED_INTEGER
mat = ar.matrix.read(
output_string,
val_ptt=app.EXPONENTIAL_FLOAT_D,
start_ptt=(app.escape('Force constants in Cartesian coordinates:') +
app.lpadded(app.NEWLINE)),
block_start_ptt=(app.series(comp_ptt, app.LINESPACES) +
app.padded(app.NEWLINE)),
line_start_ptt=comp_ptt,
tril=True)
mat = [[_cast(apf.replace('d', 'e', dst, case=False)) for dst in row]
for row in mat]
def hessian(output_string):
""" read hessian from the output string
"""
comp_ptt = (app.one_or_more(app.LETTER) +
app.one_of_these(['X', 'Y', 'Z']) + app.UNSIGNED_INTEGER)
mat = ar.matrix.read(
output_string,
start_ptt=(
app.escape('Force Constants (Second Derivatives of the Energy) ') +
app.escape('in [a.u.]') + app.lpadded(app.NEWLINE)),
block_start_ptt=(app.series(comp_ptt, app.LINESPACES) +
app.padded(app.NEWLINE)),
line_start_ptt=comp_ptt,
tril=True)
mat = tuple(map(tuple, mat))
return mat
def test__matrix():
""" test autoread.matrix
"""
# gaussian gradient
string = (' ***** Axes restored to original set *****\n'
' ------------------------------------------------------------\n'
' Center Atomic Forces (Hartrees/Bohr)\n'
' Number Number X Y Z\n'
' ------------------------------------------------------------\n'
' 1 8 0.000000000 -0.000000000 -0.061240635\n'
' 2 1 0.000000000 -0.021691602 0.030622057\n'
' 3 1 -0.000000000 0.021691602 0.030622057\n'
' ------------------------------------------------------------\n'
' Cartesian Forces: Max 0.061240635 RMS 0.027012111\n')
mat = autoread.matrix.read(
string,
start_ptt=app.padded(app.NEWLINE).join([
app.padded(app.escape('Forces (Hartrees/Bohr)'), app.NONNEWLINE),
app.LINE, app.LINE, ''
]),
line_start_ptt=app.LINESPACES.join([app.UNSIGNED_INTEGER] * 2))
assert numpy.allclose(mat, ((0.0, -0.0, -0.061240635),
(0.0, -0.021691602, 0.030622057),
(-0.0, 0.021691602, 0.030622057)))
# gaussian hessian
string = (' The second derivative matrix:\n'
' X1 Y1 Z1 X2 Y2\n'
' X1 -0.21406\n'
' Y1 -0.00000 2.05336\n'
' Z1 -0.00000 0.12105 0.19177\n'
' X2 -0.06169 -0.00000 0.00000 0.03160\n'
' Y2 0.00000 -0.09598 -0.05579 -0.00000 0.12501\n'
' Z2 0.00000 0.08316 -0.38831 -0.00000 -0.06487\n'
' X3 0.27574 0.00000 0.00000 0.03009 -0.00000\n'
' Y3 0.00000 -1.95737 -0.06525 0.00000 -0.02902\n'
' Z3 0.00000 -0.20421 0.19654 -0.00000 0.12066\n'
' Z2 X3 Y3 Z3\n'
' Z2 0.44623\n'
' X3 0.00000 -0.30583\n'
' Y3 -0.01829 -0.00000 1.98640\n'
' Z3 -0.05792 -0.00000 0.08354 -0.13862\n'
' ITU= 0\n'
' Eigenvalues --- 0.06664 0.66895 3.25121\n')
comp_ptt = app.one_of_these(['X', 'Y', 'Z']) + app.UNSIGNED_INTEGER
mat = autoread.matrix.read(
string,
start_ptt=(app.escape('The second derivative matrix:') +
app.lpadded(app.NEWLINE)),
block_start_ptt=(app.series(comp_ptt, app.LINESPACES) +
app.padded(app.NEWLINE)),
line_start_ptt=comp_ptt,
tril=True)
assert numpy.allclose(
mat,
((-0.21406, 0., 0., -0.06169, 0., 0., 0.27574, 0., 0.),
(0., 2.05336, 0.12105, 0., -0.09598, 0.08316, 0., -1.95737, -0.20421),
(0., 0.12105, 0.19177, 0., -0.05579, -0.38831, 0., -0.06525, 0.19654),
(-0.06169, 0., 0., 0.0316, 0., 0., 0.03009, 0., 0.),
(0., -0.09598, -0.05579, 0., 0.12501, -0.06487, 0., -0.02902,
0.12066), (0., 0.08316, -0.38831, 0., -0.06487, 0.44623, 0.,
-0.01829, -0.05792),
(0.27574, 0., 0., 0.03009, 0., 0., -0.30583, 0., 0.),
(0., -1.95737, -0.06525, 0., -0.02902, -0.01829, 0., 1.9864, 0.08354),
(0., -0.20421, 0.19654, 0., 0.12066, -0.05792, 0., 0.08354,
-0.13862)))
# psi4 gradient
string = (' ## Gradient (Symmetry 0) ##\n'
' Irrep: 1 Size: 3 x 3\n'
'\n'
' 1 2 3\n'
'\n'
' 1 0.000 0.000 0.997\n'
' 2 0.000 -0.749 -0.488\n'
' 3 -0.000 0.749 -0.488\n')
mat = autoread.matrix.read(string,
start_ptt=app.padded(app.NEWLINE).join([
app.escape('## Gradient (Symmetry 0) ##'),
app.LINE, '', app.LINE, '', ''
]),
line_start_ptt=app.UNSIGNED_INTEGER)
assert numpy.allclose(mat, ((0.0, 0.0, 0.997), (0.0, -0.749, -0.488),
(-0.0, 0.749, -0.488)))
# psi4 hessian
string = ('-------------------------------------------\n'
' ## Hessian (Symmetry 0) ##\n'
' Irrep: 1 Size: 9 x 9\n'
'\n'
' 1 2 3 4 5 \n'
'\n'
' 1 0.000 0.000 0.000 0.000 0.000\n'
' 2 0.000 0.959 0.000 0.000 -0.452\n'
' 3 0.000 0.000 0.371 0.000 0.222\n'
' 4 0.000 0.000 0.000 0.000 0.000\n'
' 5 0.000 -0.479 0.279 0.000 0.455\n'
' 6 0.000 0.251 -0.185 0.000 -0.247\n'
' 7 0.000 0.000 0.000 0.000 0.000\n'
' 8 0.000 -0.479 -0.279 0.000 -0.003\n'
' 9 0.000 -0.251 -0.185 0.000 0.025\n'
'\n'
' 6 7 8 9\n'
'\n'
' 1 0.000 0.000 0.000 0.000\n'
' 2 0.519 0.000 -0.477 -0.230\n'
' 3 -0.555 0.000 -0.279 -0.128\n'
' 4 0.000 0.000 0.000 0.000\n'
' 5 -0.256 0.000 -0.017 0.051\n'
' 6 0.607 0.000 -0.012 0.090\n'
' 7 0.000 0.000 0.000 0.000\n'
' 8 -0.263 0.000 0.494 0.279\n'
' 9 0.947 0.000 0.292 0.137\n')
mat = autoread.matrix.read(string,
start_ptt=app.padded(app.NEWLINE).join([
app.escape('## Hessian (Symmetry 0) ##'),
app.LINE, ''
]),
block_start_ptt=app.padded(app.NEWLINE).join([
'',
app.series(app.UNSIGNED_INTEGER,
app.LINESPACES), '', ''
]),
line_start_ptt=app.UNSIGNED_INTEGER)
assert numpy.allclose(
mat, ((0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0),
(0.0, 0.959, 0.0, 0.0, -0.452, 0.519, 0.0, -0.477, -0.23),
(0.0, 0.0, 0.371, 0.0, 0.222, -0.555, 0.0, -0.279, -0.128),
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0),
(0.0, -0.479, 0.279, 0.0, 0.455, -0.256, 0.0, -0.017, 0.051),
(0.0, 0.251, -0.185, 0.0, -0.247, 0.607, 0.0, -0.012, 0.09),
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0),
(0.0, -0.479, -0.279, 0.0, -0.003, -0.263, 0.0, 0.494, 0.279),
(0.0, -0.251, -0.185, 0.0, 0.025, 0.947, 0.0, 0.292, 0.137)))
def pattern(start_ptt,
val_ptt=VALUE_PATTERN):
""" energy pattern
"""
return start_ptt + app.lpadded(val_ptt)
def test__matrix():
""" test autoread.matrix
"""
# Gradients
start_ptt = (app.padded(app.NEWLINE).join([
app.padded(app.escape('Forces (Hartrees/Bohr)'), app.NONNEWLINE),
app.LINE, app.LINE, ''
]))
mat = autoread.matrix.read(GRAD1_STR,
start_ptt=start_ptt,
line_start_ptt=app.LINESPACES.join(
[app.UNSIGNED_INTEGER] * 2))
assert numpy.allclose(mat, ((0.0, -0.0, -0.061240635),
(0.0, -0.021691602, 0.030622057),
(-0.0, 0.021691602, 0.030622057)))
start_ptt = (app.padded(app.NEWLINE).join([
app.escape('## Gradient (Symmetry 0) ##'), app.LINE, '', app.LINE, '',
''
]))
mat = autoread.matrix.read(GRAD2_STR,
start_ptt=start_ptt,
line_start_ptt=app.UNSIGNED_INTEGER)
assert numpy.allclose(mat, ((0.0, 0.0, 0.997), (0.0, -0.749, -0.488),
(-0.0, 0.749, -0.488)))
# Hessians
start_ptt = (app.escape('The second derivative matrix:') +
app.lpadded(app.NEWLINE))
comp_ptt = app.one_of_these(['X', 'Y', 'Z']) + app.UNSIGNED_INTEGER
block_start_ptt = (app.series(comp_ptt, app.LINESPACES) +
app.padded(app.NEWLINE))
mat = autoread.matrix.read(HESS1_STR,
start_ptt=start_ptt,
block_start_ptt=block_start_ptt,
line_start_ptt=comp_ptt,
tril=True)
assert numpy.allclose(
mat,
((-0.21406, 0., 0., -0.06169, 0., 0., 0.27574, 0., 0.),
(0., 2.05336, 0.12105, 0., -0.09598, 0.08316, 0., -1.95737, -0.20421),
(0., 0.12105, 0.19177, 0., -0.05579, -0.38831, 0., -0.06525, 0.19654),
(-0.06169, 0., 0., 0.0316, 0., 0., 0.03009, 0., 0.),
(0., -0.09598, -0.05579, 0., 0.12501, -0.06487, 0., -0.02902,
0.12066), (0., 0.08316, -0.38831, 0., -0.06487, 0.44623, 0.,
-0.01829, -0.05792),
(0.27574, 0., 0., 0.03009, 0., 0., -0.30583, 0., 0.),
(0., -1.95737, -0.06525, 0., -0.02902, -0.01829, 0., 1.9864, 0.08354),
(0., -0.20421, 0.19654, 0., 0.12066, -0.05792, 0., 0.08354,
-0.13862)))
start_ptt = (app.padded(app.NEWLINE).join(
[app.escape('## Hessian (Symmetry 0) ##'), app.LINE, '']))
block_start_ptt = (app.padded(app.NEWLINE).join(
['', app.series(app.UNSIGNED_INTEGER, app.LINESPACES), '', '']))
mat = autoread.matrix.read(HESS2_STR,
start_ptt=start_ptt,
block_start_ptt=block_start_ptt,
line_start_ptt=app.UNSIGNED_INTEGER)
assert numpy.allclose(
mat, ((0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0),
(0.0, 0.959, 0.0, 0.0, -0.452, 0.519, 0.0, -0.477, -0.23),
(0.0, 0.0, 0.371, 0.0, 0.222, -0.555, 0.0, -0.279, -0.128),
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0),
(0.0, -0.479, 0.279, 0.0, 0.455, -0.256, 0.0, -0.017, 0.051),
(0.0, 0.251, -0.185, 0.0, -0.247, 0.607, 0.0, -0.012, 0.09),
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0),
(0.0, -0.479, -0.279, 0.0, -0.003, -0.263, 0.0, 0.494, 0.279),
(0.0, -0.251, -0.185, 0.0, 0.025, 0.947, 0.0, 0.292, 0.137)))
# Test finding nothing
mat = autoread.matrix.read('',
start_ptt=start_ptt,
block_start_ptt=block_start_ptt,
line_start_ptt=app.UNSIGNED_INTEGER)
assert mat is None
