def launch_instances(host, start_port, instances):
"""Launch multiple instances of Fusion 360"""
launcher = Launcher()
for port in range(start_port, start_port + instances):
print(f"Launching Fusion 360 instance: {host}:{port}")
launcher.launch()
time.sleep(5)
def main(script_name, argv):
species, read_type, job_name, dir_out, fastq_list, fastq_list_r2, library_type, project, run, toolset, \
flag_xenome, cores_per_sample, verbose, sync, genome, targeted_kit, sample_name_list, master_mode, \
novoalign_tune = parse_arguments(script_name, argv)
if not library_type:
library_type = "DNASeq"
if not job_name:
job_name = "{}_job".format(library_type)
if not run:
run = "{}_run".format(library_type)
if not cores_per_sample:
cores_per_sample = "4"
if not novoalign_tune:
novoalign_tune = "NA"
if species == "human":
human_kit = {
'SureSelect_v4': GLOBAL_CONFIG_TOOL_TEMPLATE_NAME_HUMAN_SURE_SELECT_V4,
'SureSelect_v5': GLOBAL_CONFIG_TOOL_TEMPLATE_NAME_HUMAN_SURE_SELECT_V5,
'SureSelect_v6': GLOBAL_CONFIG_TOOL_TEMPLATE_NAME_HUMAN_SURE_SELECT_V6
}
try:
global_config_tool_template_name = human_kit[targeted_kit]
except KeyError as e:
raise ValueError('Only SureSelect_v4, SureSelect_v5, SureSelect_v6 target kits are available for human.',
e.args[0])
elif species == "mouse":
if targeted_kit != "Mouse_Exome_v1":
raise ValueError('Only Mouse_Exome_v1 target kit is available for mouse.')
global_config_tool_template_name = GLOBAL_CONFIG_TOOL_TEMPLATE_NAME_MOUSE_EXOME_V1
else:
raise ValueError('Failed to determine "species" parameter. Available species: "human"/"mouse"')
additional_options = {"novoalign_tune": novoalign_tune}
global_config = GlobalConfig(species, read_type, TEMPLATE, WORKFLOW_NAME, toolset)
global_config_path = global_config.create(global_config_tool_template_name, additional_options,
flag_xenome=flag_xenome, cores_per_sample=cores_per_sample)
if os.path.isdir(fastq_list):
fastq_list = FastqSampleManifest(read_type).create_by_folder(fastq_list, WORKFLOW_NAME, library_type)
elif 'fastq.gz' in str(fastq_list).split(',')[0]:
sample_name_list = list(str(sample_name_list).split(',')) if sample_name_list else None
fastq_list = FastqSampleManifest(read_type).create_by_list(list(str(fastq_list).split(',')),
list(str(fastq_list_r2).split(',')),
WORKFLOW_NAME, library_type,
sample_names=sample_name_list)
study_config = StudyConfig(job_name, dir_out, fastq_list, None, library_type, run, project=project)
study_config_path = study_config.parse(workflow=WORKFLOW_NAME)
Launcher.launch(global_config_path, study_config_path, sync, java_path=global_config.java_path, verbose=verbose,
master=master_mode)
def run(self, problem_id, domain_template, problem_template, facts_pdkb,
goals_pdkb):
"""
Execute the planner and return the parsed output.
Before the planner is executed the pddl problem file is created
dynamically by inserting the knowledge base (kb_files) and the current
goals (goal_files) at the right location in the problem template.
@param problem_id The id for the particular
problem/domain set
@param domain_template The path of the pddl domain template
@param problem_template The name of the pddl problem template that
contains special insertion marks
@param facts_pdkb The fact files to be inserted in
the pddl problem file
@param goals_pdkb The goal files to be inserted in the pddl
problem file
"""
# insert the PDKB files into the PDDL templates
(domain_file,
problem_file) = compile_PDKB_to_PDDL(problem_id, domain_template,
problem_template, facts_pdkb,
goals_pdkb)
# launch the planner and redirect output to parser
l = Launcher(domain_file, problem_file)
l.launch()
p = Parser(l.get_output())
if print_planner_output:
print l.get_output()
# return the parsed plan
return p
def run(self, problem_id, domain_template, problem_template,
facts_pdkb, goals_pdkb):
"""
Execute the planner and return the parsed output.
Before the planner is executed the pddl problem file is created
dynamically by inserting the knowledge base (kb_files) and the current
goals (goal_files) at the right location in the problem template.
@param problem_id The id for the particular
problem/domain set
@param domain_template The path of the pddl domain template
@param problem_template The name of the pddl problem template that
contains special insertion marks
@param facts_pdkb The fact files to be inserted in
the pddl problem file
@param goals_pdkb The goal files to be inserted in the pddl
problem file
"""
# insert the PDKB files into the PDDL templates
(domain_file, problem_file) = compile_PDKB_to_PDDL(
problem_id, domain_template, problem_template,
facts_pdkb, goals_pdkb)
# launch the planner and redirect output to parser
l = Launcher(domain_file, problem_file)
l.launch()
p = Parser(l.get_output())
if print_planner_output:
print l.get_output()
# return the parsed plan
return p
def __launch_gym(self):
"""Launch the Fusion 360 Gym on the given host/port"""
launcher = Launcher()
self.p = launcher.launch()
# We wait for Fusion to start responding to pings
result = self.__wait_for_fusion()
if result is False:
# Fusion is awake but not responding so restart
self.p.kill()
self.p = None
self.__launch_gym()
else:
return result
def main(): launcher = Launcher(sys.argv) obj = launcher.launch() Log.log(sys.argv) try: obj.poll() except BaseException as e: #This is here for debugging purposes if isinstance(e, Exception): Log.log(e) my_log = open(Log.log_file, 'a') traceback.print_exc(file=my_log) obj.cleanup() sys.exit(0)
def main(script_name, argv):
species, read_type, job_name, dir_out, feature_reference, fastq_list, fastq_list_r2, libtype, master, \
expected_cells, forced_cells, chemistry, nosecondary, r1_length, r2_length, genome_build, transcriptome, \
vdj_genome, detect_doublet, project, run, toolset, cores_per_sample, verbose, sync, sample_name_list, \
master_mode, toolchain, target_panel, mem_free = parse_arguments(script_name, argv)
library_type = "scRNASeq"
if not read_type:
read_type = "paired"
if not job_name:
job_name = "{}_job".format(library_type)
if not run:
run = "{}_run".format(library_type)
if not expected_cells:
expected_cells = "3000"
if not forced_cells:
forced_cells = "NA"
if not nosecondary:
nosecondary = "FALSE"
if not cores_per_sample:
cores_per_sample = "8"
if not target_panel:
target_panel = "NA"
additional_options = {
"feature_reference": feature_reference,
"genome_build": genome_build,
"genome": transcriptome,
"transcriptome": transcriptome,
"vdj_genome": vdj_genome,
"expected_cells": expected_cells,
"forced_cells": forced_cells,
"chemistry": chemistry,
"nosecondary": nosecondary,
"r1_length": r1_length,
"r2_length": r2_length,
"target_panel": target_panel,
"maxmem": mem_free
}
if not toolset:
toolset = "count+vdj+qc"
if detect_doublet and "doubletdetection" not in toolset:
toolset += "+doubletdetection"
global_config = GlobalConfig(species, read_type, TEMPLATE, WORKFLOW_NAME,
toolset)
if species == "human":
global_config_tool_template_name = GLOBAL_CONFIG_TOOL_TEMPLATE_NAME_HUMAN_TOOLCHAIN2 \
if toolchain == "Cellranger_v6" else GLOBAL_CONFIG_TOOL_TEMPLATE_NAME_HUMAN_TOOLCHAIN1
elif species == "mouse":
global_config_tool_template_name = GLOBAL_CONFIG_TOOL_TEMPLATE_NAME_MOUSE_TOOLCHAIN2 \
if toolchain == "Cellranger_v6" else GLOBAL_CONFIG_TOOL_TEMPLATE_NAME_MOUSE_TOOLCHAIN1
else:
raise RuntimeError(
'Failed to determine "species" parameter. Available species: "human" and "mouse"'
)
global_config_path = global_config.create(
global_config_tool_template_name,
additional_options,
cores_per_sample=cores_per_sample)
if os.path.isdir(fastq_list):
fastq_list = FastqSampleManifest(read_type).create_by_folder(
fastq_list, WORKFLOW_NAME, library_type)
elif 'fastq.gz' in str(fastq_list).split(',')[0]:
sample_libtype = list(str(libtype).split(',')) if libtype else None
sample_master = list(str(master).split(',')) if master else None
sample_name_list = list(
str(sample_name_list).split(',')) if sample_name_list else None
fastq_list = FastqSampleManifest(read_type).create_by_list(
list(str(fastq_list).split(',')),
list(str(fastq_list_r2).split(',')),
WORKFLOW_NAME,
library_type,
sample_libtype=sample_libtype,
sample_master=sample_master,
sample_names=sample_name_list)
study_config = StudyConfig(job_name,
dir_out,
fastq_list,
None,
library_type,
run,
project=project)
study_config_path = study_config.parse(workflow=WORKFLOW_NAME)
Launcher.launch(global_config_path,
study_config_path,
sync,
java_path=global_config.java_path,
verbose=verbose,
master=master_mode)
