def _init():
"""
This must be called once before any work
"""
RadiometryContext.struct_fixup()
if local.env.get("PLASTER_C_COMPILE"):
with local.cwd(c_radiometry_path):
fp = StringIO()
with redirect_stdout(fp):
print(
f"// This file was code-generated by sigproc_v2.c_radiometry.c_radiometry.load_lib and should be version controlled"
)
print()
print("#ifndef RADIOMETRY_H")
print("#define RADIOMETRY_H")
print()
print('#include "stdint.h"')
print('#include "c_common.h"')
print()
RadiometryContext.struct_emit_header(fp)
print("#endif")
header_file_path = "./_radiometry.h"
existing_h = utils.load(header_file_path,
return_on_non_existing="")
if existing_h != fp.getvalue():
utils.save(header_file_path, fp.getvalue())
build_dev()
def _init():
"""
Must be called before anything else in this module
"""
SurveyV2Context.struct_fixup()
if local.env.get("PLASTER_C_COMPILE"):
with local.cwd(lib_folder):
fp = StringIO()
with redirect_stdout(fp):
print(
f"// This file was code-generated by survey_v2.c.survey_v2.init and should be version controlled"
)
print()
print("#ifndef SIM_V2_H")
print("#define SIM_V2_H")
print()
print('#include "stdint.h"')
print('#include "c_common.h"')
print()
SurveyV2Context.struct_emit_header(fp)
print("#endif")
header_file_path = "./_survey_v2.h"
existing_h = utils.load(header_file_path, return_on_non_existing="")
if existing_h != fp.getvalue():
utils.save(header_file_path, fp.getvalue())
build_dev()
def zest_survey_integration():
"""
Show that a survey gen and run can execute
"""
csv_file = "/tmp/__zest_survey_integration.csv"
utils.save(
csv_file,
utils.smart_wrap(
"""
Name,Seq,Abundance,POI
pep0,ALNCLVMQL,1,1
pep1,APHGVVFL,1,1
pep2,KIADYNYML,1,1
pep3,MLPDDFTGC,4,1
pep4,CCQSLQTYV,1,1
pep5,TLMSKTQSL,1,1
pep6,VLCMNQKLI,1,1
pep7,ACCDFTAKV,1,0
""",
assert_if_exceeds_width=True,
),
)
local["p"]["gen", "survey", "--sample=zest_survey_integration",
f"--protein_csv={csv_file}", "--label_set=C,M", "--n_pres=1",
"--n_mocks=0", "--n_edmans=15", "--force",
"--job=./jobs_folder/__zest_survey_integration", ] & FG
local["p"]["run", "./jobs_folder/__zest_survey_integration"] & FG
zest()
def _init():
"""
Must be called before anything else in this module
"""
NNV2Context.struct_fixup()
if local.env.get("PLASTER_C_COMPILE"):
with local.cwd(c_nn_v2_path):
fp = StringIO()
with redirect_stdout(fp):
print(
f"// This file was code-generated by nn_v2.c.nn_v2.load_lib and should be version controlled"
)
print()
print("#ifndef NN_V2_H")
print("#define NN_V2_H")
print()
print('#include "pthread.h"')
print('#include "stdint.h"')
print('#include "c_common.h"')
print()
NNV2ScoringVerboseFields.emit_col_name_defines(fp)
print()
NNV2Context.struct_emit_header(fp)
print("#endif")
header_file_path = "./_nn_v2.h"
existing_h = utils.load(header_file_path,
return_on_non_existing="")
if existing_h != fp.getvalue():
utils.save(header_file_path, fp.getvalue())
build_dev()
def _init():
"""
Must be called before anything else in this module
"""
SimV2Context.struct_fixup()
# Dyt.struct_fixup()
PCB.struct_fixup()
Counts.struct_fixup()
DyePepRec.struct_fixup()
if local.env.get("PLASTER_C_COMPILE"):
with local.cwd(lib_folder):
fp = StringIO()
with redirect_stdout(fp):
print(
f"// This file was code-generated by sim_v2.c.sim_v2.init and should be version controlled"
)
print()
print("#ifndef SIM_V2_H")
print("#define SIM_V2_H")
print()
print('#include "stdint.h"')
print('#include "c_common.h"')
print()
print(
textwrap.dedent("""\
typedef struct {
Size count;
Index dyt_i;
DyeType chcy_dye_counts[];
// Note, this is a variable sized record
// See dyt_* functions for manipulating it
} Dyt; // Dye-track record
"""))
print()
SimV2Context.struct_emit_header(fp)
# Dyt.struct_emit_header(fp)
PCB.struct_emit_header(fp)
Counts.struct_emit_header(fp)
print("#endif")
header_file_path = "./_sim_v2.h"
existing_h = utils.load(header_file_path,
return_on_non_existing="")
if existing_h != fp.getvalue():
utils.save(header_file_path, fp.getvalue())
build_dev()
def cache_source(cache_folder, source, copy_to):
"""
If this is a URL or S3 fetch and cache at cache_folder. Local files
can be loaded from //jobs_folder/... only.
In all cases, the cached file is optionally copied to copy_to so that
that job folders contain a copy of all gen source data.
Returns:
the contents of the file
"""
def make_cache_path():
local.path(cache_folder).mkdir()
return (
local.path(cache_folder) / hashlib.md5(source.encode("utf-8")).hexdigest()
)
file_contents = None
if source.startswith("http://") or source.startswith("https://"):
cache_path = make_cache_path()
if not cache_path.exists():
important(f"Fetching {source}... (TO {cache_path})")
file_contents = _url_get(source)
utils.save(cache_path, file_contents)
else:
file_contents = utils.load(cache_path)
elif source.startswith("s3://"):
cache_path = make_cache_path()
if not cache_path.exists():
tell(f"Syncing from {source} to {cache_path}")
local["aws"]["s3", "cp", source, cache_path] & FG
# s3 cp already saves it to disk, fall thru & load
file_contents = utils.load(cache_path)
else:
file_contents = utils.load(source)
assert file_contents is not None
if copy_to:
assert local.path(copy_to).exists()
filename = local.path(source).basename
utils.save(copy_to / filename, file_contents)
return file_contents
def lnfit(lnfit_params, sigproc_result):
csv = _alex_track_photometries_csv(sigproc_result, lnfit_params.dye_on_threshold)
# This photometry_filename will get mounted into the container
photometry_filename = "track_photometries.csv"
utils.save(photometry_filename, csv)
if not lnfit_params.photometry_only:
# If we're running in a docker context then the path will start with
# /app, which we need to substitute for the real host OS path.
# This has to come from the environment since it might vary from host to host
data_folder = os.environ.get("HOST_PLASTER_DATA_FOLDER", "./jobs_folder")
data_folder = os.path.join(data_folder, "") # Adds a slash if needed
lnfit_path = str(local.path(".")).replace("/app/jobs_folder/", data_folder)
def run_docker_command(command):
local["bash"]["-c", utils.get_ecr_login_string()] & FG
aws_creds = []
if local.env.get("ON_AWS", "0") == "0":
aws_creds = [
f"--env",
f"AWS_ACCESS_KEY_ID={local.env['AWS_ACCESS_KEY_ID']}",
f"--env",
f"AWS_SECRET_ACCESS_KEY={local.env['AWS_SECRET_ACCESS_KEY']}",
f"--env",
f"AWS_DEFAULT_REGION={local.env['AWS_DEFAULT_REGION']}",
]
local["docker"][
[
f"run",
f"-it",
*aws_creds,
f"--mount",
f"type=bind,source={lnfit_path},target=/lnfit",
f"188029688209.dkr.ecr.us-east-1.amazonaws.com/alex:latest",
f"bash",
f"-c",
command,
]
] & FG(retcode=None)
container_command = (
f"cd /home/proteanseq "
f"&& python ./pflib/lognormal_fitter_v2.py "
f" {lnfit_params.lognormal_fitter_v2_params} "
f" /lnfit/{photometry_filename} "
f" >/lnfit/LN.OUT 2>/lnfit/LN.ERR"
)
try:
run_docker_command(container_command)
except CommandNotFound as e:
raise LnFitError
return LNFitResult(
params=lnfit_params,
photometry_rows=csv.count("\n") - 1,
dye_on_threshold=lnfit_params.dye_on_threshold,
did_fit=not lnfit_params.photometry_only,
)