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Bienchen
AlphaPulldown-ModelCIF-Conversion
Commits
e4f5df09
Commit
e4f5df09
authored
1 year ago
by
Bienchen
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Simplified command line options for now.
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convert_to_modelcif.py
+62
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62 additions, 42 deletions
convert_to_modelcif.py
with
62 additions
and
42 deletions
convert_to_modelcif.py
+
62
−
42
View file @
e4f5df09
...
...
@@ -3,68 +3,76 @@
"""
Take the output of the AlphaPulldown pipeline and turn it into a ModelCIF
file with a lot of metadata in place.
"""
from
absl
import
app
from
absl
import
flag
s
import
os
import
sy
s
from
absl
import
app
,
flags
,
logging
FLAGS
=
flags
.
FLAGS
flags
.
DEFINE_list
(
"
metadata
"
,
None
,
"
JSON files with information about experiment setup, one file per feature
"
,
# ToDo: Get options properly, best get the same names as used in existing
# scripts, e.g. could '--monomer_objects_dir' be used as feature
# directory/ directory with the feature JSON files?
flags
.
DEFINE_string
(
"
ap_output
"
,
None
,
"
AlphaPulldown pipeline output directory.
"
)
flags
.
DEFINE_string
(
"
af2_output
"
,
None
,
"
Results of AlphaFold2 modelling
"
)
flags
.
DEFINE_integer
(
"
model_selected
"
,
None
,
"
Model to be converted into ModelCIF, use
'
--select_all
'
to convert all
"
+
"
models found in
'
--af2_output
'"
,
)
flags
.
DEFINE_bool
(
"
select_all
"
,
False
,
"
Convert all models found in
'
--af2_output
'
into ModelCIF, excludes
"
+
"'
--model_selected
'"
,
)
flags
.
mark_flags_as_required
([
"
ap_output
"
])
def
_mark_model_selection_as_mutual_exclusive
():
"""
Create & register a validator for model selection.
FLAGS
=
flags
.
FLAGS
# ToDo: implement a flags.register_validator() checking that files/ directories
# exist as expected.
Enforce only one option is set, either
'
--select_all
'
or
'
--model_selected
'
.
Enforce that at least one of
'
--select_all
'
or
'
--model_selected
'
is set
(so this options will not pop up in `flags.mark_flags_as_required`).
"""
def
_validate_mutual_exclusion_model_selection
(
flags_dict
):
not_set_count
=
0
if
flags_dict
[
"
model_selected
"
]
is
None
:
not_set_count
+=
1
if
flags_dict
[
"
select_all
"
]
is
False
:
not_set_count
+=
1
def
alphapulldown_model_to_modelcif
()
->
None
:
"""
Convert an AlphaPulldown model into a ModelCIF formatted mmCIF file.
if
not_set_count
==
1
:
return
True
return
False
Metadata for the ModelCIF categories will be fetched from AlphaPulldown
output as far as possible. This expects modelling projects to exists in
AlphaPulldown
'
s output directory structure.
"""
flags
.
register_multi_flags_validator
(
[
"
model_selected
"
,
"
select_all
"
],
_validate_mutual_exclusion_model_selection
,
"
Exactly one (and only one) argument needs to be set.
"
,
)
def
_get_model_list
(
ap_dir
,
model_selected
)
->
list
:
"""
Get the list of models to be converted.
_mark_model_selection_as_mutual_exclusive
()
flags
.
mark_flags_as_required
([
"
metadata
"
,
"
af2_output
"
])
# ToDo: implement a flags.register_validator() for 'metadata', checking that
# the file exists and is readable.
# ToDo: implement a flags.register_validator() for 'af2_output', checking that
# the file directory exists and is readable (overkill: check directory
# structure).
If `model_selected` is none, all models will be marked for conversion.
"""
# ToDo: Question - use 'ranked_*.pdb' or
# 'unrelaxed_model_*_multimer_v3_pred_0.pdb' models?
if
model_selected
is
not
None
:
mdl_paths
=
os
.
path
.
join
(
ap_dir
,
"
models
"
)
cmplx
=
os
.
listdir
(
mdl_paths
)
# For now, exactly 1 complex is expected in the 'models' subdirectory.
# If there are more, the 'model_selected' mechanism needs to be further
# tuned to get to the right model.
assert
len
(
cmplx
)
==
1
cmplx
=
cmplx
[
0
]
mdl_paths
=
os
.
path
.
join
(
mdl_paths
,
cmplx
,
f
"
ranked_
{
model_selected
}
.pdb
"
)
mdl_paths
=
[
mdl_paths
]
for
mdl
in
mdl_paths
:
if
os
.
path
.
isfile
(
mdl
):
logging
.
info
(
f
"
Model file
'
{
mdl
}
'
does not exist or is not a regular file.
"
)
sys
.
exit
()
# check that files actually exist
return
[]
def
main
(
argv
):
"""
Run as script.
"""
# pylint: disable=pointless-string-statement
"""
Here, the metadata json files for each feature are in features_monomers/
directory. The models are in models/ directory, and usually there are many
...
...
@@ -81,10 +89,22 @@ def main(argv):
AlphaPulldown side and may be added now or later on. Let me know if it is
critical for you now.
"""
# pylint: enable=pointless-string-statement
del
argv
# Unused.
# make list of selected models
model_conversions
=
_get_model_list
(
FLAGS
.
ap_output
,
FLAGS
.
model_selected
)
# assemble selected models into ModelCIF files + associated data archives
alphapulldown_model_to_modelcif
()
if
__name__
==
"
__main__
"
:
app
.
run
(
main
)
# LocalWords: ToDo
# ToDo: Question - option to include all the non-selected models in associated
# data archive? This blows up storage size (especially if PAEs included),
# but we did that already in the past. Idea is to have all models
# available for... reproducibility and whatnot, but show the selected
# (representative) of the modelling experiment/ study more prominently.
# LocalWords: ToDo AlphaPulldown PAEs dir
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