def folder_parser(sup_parser: argparse):
folder_parser = sup_parser.add_parser(
'folder', help='Manage folders. Folders allows to group tasks')
folder_subparser = folder_parser.add_subparsers(
dest='action', metavar='', description='Commands to work with folders')
folder_subparser.required = True
create = folder_subparser.add_parser('create', help='Create new folder')
create.add_argument('name', help='Folder name')
show = folder_subparser.add_parser('show', help='Show folders info')
folder_show_parser(show)
populate = folder_subparser.add_parser(
'populate', help='Populate folder with provided task')
populate.add_argument('-fid', '--folder_id', required=True, type=valid_int)
populate.add_argument('-tid', '--task_id', required=True, type=valid_int)
unpopulate = folder_subparser.add_parser('unpopulate',
help='delete task from folder')
unpopulate.add_argument('-fid',
'--folder_id',
required=True,
type=valid_int)
unpopulate.add_argument('-tid', '--task_id', required=True, type=valid_int)
edit = folder_subparser.add_parser('edit', help='Edit folder by id')
edit.add_argument('folder_id', type=valid_int)
edit.add_argument('name', help='Folder name')
delete = folder_subparser.add_parser('delete', help='Delete folder by id')
delete.add_argument('folder_id', type=valid_int)
def reminder_parser(sup_parser: argparse):
reminder_parser = sup_parser.add_parser(
'reminder',
help='Manage reminders. Reminders remind you about your tasks')
reminder_subparser = reminder_parser.add_subparsers(
dest='action',
metavar='',
description='Commands to work with reminders')
reminder_subparser.required = True
create = reminder_subparser.add_parser(
'create', help='Create reminder for existing task')
create.add_argument('task_id', help='Task id', type=valid_int)
create.add_argument('date', help='Reminder date', type=valid_future_date)
show = reminder_subparser.add_parser('show', help='Show reminders info')
reminder_show_parser(show)
edit = reminder_subparser.add_parser('edit', help='Edit reminder')
edit.add_argument('reminder_id', help='Reminder id', type=valid_int)
edit.add_argument('date', help='Reminder date', type=valid_future_date)
delete = reminder_subparser.add_parser('delete',
help='Delete reminder by id')
delete.add_argument('reminder_id', type=valid_int)
def plan_parser(sup_parser: argparse):
plan_parser = sup_parser.add_parser(
'plan', help='Manage plans. Plans allows to automate tasks creation')
plan_subparser = plan_parser.add_subparsers(
dest='action', metavar='', description='Commands to work with plans')
plan_subparser.required = True
create = plan_subparser.add_parser('create',
help='Create plan for existing task')
create.add_argument('task_id', help='task id', type=valid_int)
create.add_argument('period_amount', help='Period amount', type=valid_int)
create.add_argument('period',
help='Period type',
choices=[x.name.lower() for x in Period])
create.add_argument('-s',
'--start_date',
type=valid_future_date,
help='Plan start date.',
required=True)
create.add_argument('-r',
'--plan_amount',
type=valid_int,
help='How much times plan should be executed')
create.add_argument('-e',
'--end_date',
type=valid_future_date,
help='Plan end date.')
show = plan_subparser.add_parser('show', help='Show plans info')
plan_show_parser(show)
edit = plan_subparser.add_parser('edit', help='Edit plan')
edit.add_argument('plan_id', help='plan_id', type=valid_int)
edit.add_argument('-p',
'--period_amount',
help='Period amount',
type=valid_int)
edit.add_argument('-t',
'--period',
help='Period type',
choices=[x.name.lower() for x in Period])
edit.add_argument('-r',
'--plan_amount',
type=valid_int,
help='How much plan should be executed')
edit.add_argument('-e',
'--end_date',
type=valid_future_date,
help='Plan end date.')
delete = plan_subparser.add_parser('delete', help='Delete plan by id')
delete.add_argument('plan_id', type=valid_int)
def append_service_interfaces_to_parser(
parent_parser: argparse,
interfaces: Dict[str, BaseInterface],
interface_group_name: Optional[str] = 'sub_interface'
) -> argparse.ArgumentParser:
"""
Append multiple service interfaces to a single parser
:param parent_parser:
:param interfaces: A dictionary service interface packages where the key is the name of that interface,
and the value is the interface object itself.
:param interface_group_name: A name identifying where in the component, interface, sub-interface hierarchy these
service_interfaces should be placed
:return: The parser object
"""
for name, value in interfaces.items():
if isinstance(value, tuple):
interfaces, help_str = value
new_section_parser = parent_parser.add_parser(name=name,
help=help_str)
new_section_subparsers = new_section_parser.add_subparsers()
append_service_interfaces_to_parser(
parent_parser=new_section_subparsers,
interfaces=interfaces,
interface_group_name=interface_group_name)
elif isinstance(value, dict):
new_section_parser = parent_parser.add_parser(name=name,
help='<None Given>')
new_section_subparsers = new_section_parser.add_subparsers()
append_service_interfaces_to_parser(
parent_parser=new_section_subparsers,
interfaces=value,
interface_group_name=interface_group_name)
else:
append_service_interface_to_parser(
parent_parser=parent_parser,
interface_name=name,
interface=value,
interface_group_name=interface_group_name)
return parent_parser
def user_parser(sup_parser: argparse):
user_parser = sup_parser.add_parser(
'user', help='Manage users. Sign up, login, logout, list all users')
user_subparser = user_parser.add_subparsers(
dest='action', metavar='', description='Commands to work with user')
user_subparser.required = True
create = user_subparser.add_parser('create', help='Register new user')
create.add_argument('username')
login = user_subparser.add_parser('login', help='Auth by username')
login.add_argument('username')
user_subparser.add_parser('logout', help='Logout user')
user_subparser.add_parser('current', help='Show current user')
user_subparser.add_parser('all', help='Show all users in app')
def append_service_interface_to_parser(
parent_parser: argparse,
interface_name: str,
interface: BaseInterface,
interface_group_name: Optional[str] = 'interface'
) -> argparse.ArgumentParser:
"""
Add an interface to an existing parser.
:param parent_parser: The parent parser to add the interface too
:param interface_name: The name of this interface as it will appear in the commandline utility
:param interface: The interface object itself
:param interface_group_name: A name identifying where in the component, interface, sub-interface hierarchy this
service_interface should be placed
:return: The parser object
"""
from dynamite_nsm.cmd import service_interfaces
from dynamite_nsm.cmd import config_object_interfaces
from dynamite_nsm.cmd.config_object_interfaces import AnalyzersInterface, FilebeatTargetsInterface
from dynamite_nsm.cmd.service_interfaces import MultipleResponsibilityInterface, SingleResponsibilityInterface, \
SimpleConfigManagerInterface
if not interface:
return argparse.ArgumentParser()
interface_group_name_kwargs = {interface_group_name: interface_name}
sub_interface_parser = parent_parser.add_parser(
interface_name, help=interface.interface_description)
sub_interface_parser.set_defaults(**interface_group_name_kwargs)
if isinstance(interface, SimpleConfigManagerInterface):
service_interfaces.append_service_simple_config_management_interface_to_parser(
parser=sub_interface_parser, interface=interface)
elif isinstance(interface, SingleResponsibilityInterface):
service_interfaces.append_service_single_responsibility_interface_to_parser(
parser=sub_interface_parser, interface=interface)
elif isinstance(interface, MultipleResponsibilityInterface):
service_interfaces.append_service_multiple_responsibility_interface_to_parser(
parser=sub_interface_parser, interface=interface)
elif isinstance(interface, AnalyzersInterface):
config_object_interfaces.append_config_object_analyzer_interface_to_parser(
parser=sub_interface_parser, interface=interface)
elif isinstance(interface, FilebeatTargetsInterface):
config_object_interfaces.append_config_object_filebeat_targets_to_parser(
parser=sub_interface_parser, interface=interface)
return parent_parser
def add_subparser_args(subparsers: argparse) -> argparse:
"""Add tool-specific arguments for remove-background.
Args:
subparsers: Parser object before addition of arguments specific to
remove-background.
Returns:
parser: Parser object with additional parameters.
"""
subparser = subparsers.add_parser("remove-background",
description="Remove background RNA "
"from count matrix.",
help="Remove background ambient RNA "
"and barcode-swapped reads from "
"a count matrix, producing a "
"new count matrix and "
"determining which barcodes "
"contain real cells.")
subparser.add_argument("--input", nargs=None, type=str,
dest='input_file', default=None,
required=True,
help="Data file on which to run tool, as either "
"_raw_gene_barcode_matrices_h5.h5 file, or "
"as the path containing the raw "
"matrix.mtx, barcodes.tsv, and genes.tsv "
"files. Supported for outputs of "
"CellRanger v2 and v3.")
subparser.add_argument("--output", nargs=None, type=str,
dest='output_file', default=None,
required=True,
help="Output file location (the path must "
"exist, and the file name must have .h5 "
"extension).")
subparser.add_argument("--expected-cells", nargs=None, type=int,
default=None,
dest="expected_cell_count",
help="Number of cells expected in the dataset "
"(a rough estimate within a factor of 2 "
"is sufficient).")
subparser.add_argument("--total-droplets-included",
nargs=None, type=int,
default=consts.TOTAL_DROPLET_DEFAULT,
dest="total_droplets",
help="The number of droplets from the "
"rank-ordered UMI plot that will be "
"analyzed. The largest 'total_droplets' "
"droplets will have their cell "
"probabilities inferred as an output. (default: %(default)s)")
subparser.add_argument("--model", nargs=None, type=str,
default="full",
choices=["simple", "ambient", "swapping", "full"],
dest="model",
help="Which model is being used for count data. "
" 'simple' does not model either ambient "
"RNA or random barcode swapping (for "
"debugging purposes -- not recommended). "
"'ambient' assumes background RNA is "
"incorporated into droplets. 'swapping' "
"assumes background RNA comes from random "
"barcode swapping. 'full' uses a "
"combined ambient and swapping model. "
"(default: %(default)s)")
subparser.add_argument("--epochs", nargs=None, type=int, default=150,
dest="epochs",
help="Number of epochs to train. (default: %(default)s)")
subparser.add_argument("--cuda",
dest="use_cuda", action="store_true",
help="Including the flag --cuda will run the "
"inference on a GPU.")
subparser.add_argument("--low-count-threshold", type=int,
default=consts.LOW_UMI_CUTOFF,
dest="low_count_threshold",
help="Droplets with UMI counts below this "
"number are completely excluded from the "
"analysis. This can help identify the "
"correct prior for empty droplet counts "
"in the rare case where empty counts "
"are extremely high (over 200). (default: %(default)s)")
subparser.add_argument("--z-dim", type=int, default=100,
dest="z_dim",
help="Dimension of latent variable z. (default: %(default)s)")
subparser.add_argument("--z-layers", nargs="+", type=int, default=[500],
dest="z_hidden_dims",
help="Dimension of hidden layers in the encoder "
"for z. (default: %(default)s)")
subparser.add_argument("--training-fraction",
type=float, nargs=None,
default=consts.TRAINING_FRACTION,
dest="training_fraction",
help="Training detail: the fraction of the "
"data used for training. The rest is never "
"seen by the inference algorithm. Speeds up "
"learning. (default: %(default)s)")
subparser.add_argument("--empty-drop-training-fraction",
type=float, nargs=None,
default=consts.FRACTION_EMPTIES,
dest="fraction_empties",
help="Training detail: the fraction of the "
"training data each epoch "
"that is drawn (randomly sampled) from "
"surely empty droplets. (default: %(default)s)")
subparser.add_argument("--blacklist-genes", nargs="+", type=int,
default=[],
dest="blacklisted_genes",
help="Integer indices of genes to ignore "
"entirely. In the output count matrix, "
"the counts for these genes will be set "
"to zero.")
subparser.add_argument("--fpr", nargs="+",
type=float, default=[0.01],
dest="fpr",
help="Target false positive rate in (0, 1). A false "
"positive is a true signal count that is "
"erroneously removed. More background removal "
"is accompanied by more signal removal "
"at high values of FPR. You can specify "
"multiple values, which will create multiple "
"output files. (default: %(default)s)")
subparser.add_argument("--exclude-antibody-capture",
dest="exclude_antibodies", action="store_true",
help="Including the flag --exclude-antibody-capture "
"will cause remove-background to operate on "
"gene counts only, ignoring other features.")
subparser.add_argument("--learning-rate", nargs=None,
type=float, default=1e-4,
dest="learning_rate",
help="Training detail: lower learning rate for "
"inference. A OneCycle learning rate schedule "
"is used, where the upper learning rate is ten "
"times this value. (For this value, probably "
"do not exceed 1e-3). (default: %(default)s)")
subparser.add_argument("--final-elbo-fail-fraction", type=float,
help="Training is considered to have failed if "
"final_training_ELBO >= best_training_ELBO*(1+FINAL_ELBO_FAIL_FRACTION). "
"(default: do not fail training based on final_training_ELBO)")
subparser.add_argument("--epoch-elbo-fail-fraction", type=float,
help="Training is considered to have failed if "
"current_epoch_training_ELBO >= previous_epoch_training_ELBO*(1+EPOCH_ELBO_FAIL_FRACTION). "
"(default: do not fail training based on epoch_training_ELBO)")
subparser.add_argument("--num-training-tries", type=int, default=1,
help="Number of times to attempt to train the model. Each subsequent "
"attempt the learning rate is multiplied by LEARNING_RATE_RETRY_MULT. "
"(default: %(default)s)")
subparser.add_argument("--learning-rate-retry-mult", type=float, default=0.5,
help="Learning rate is multiplied by this amount each time "
"(default: %(default)s)")
subparser.add_argument("--posterior-batch-size", type=int, default=consts.PROP_POSTERIOR_BATCH_SIZE,
dest="posterior_batch_size",
help="Size of batches when creating the posterior. Reduce this to avoid "
"running out of GPU memory creating the posterior (will be slower). "
"(default: %(default)s)")
subparser.add_argument("--cells-posterior-reg-calc", type=int, default=consts.CELLS_POSTERIOR_REG_CALC,
dest="cells_posterior_reg_calc",
help="Number of cells used to estimate posterior regularization lambda. "
"(default: %(default)s)")
return subparsers
def add_subparser_args(self, subparsers: argparse) -> argparse:
"""Add tool-specific arguments for remove_background.
Args:
subparsers: Parser object before addition of arguments specific to
remove_background.
Returns:
parser: Parser object with additional parameters.
"""
subparser = subparsers.add_parser(
self.name,
description="Remove background RNA from "
"count matrix.",
help="Remove background ambient RNA and "
"barcode-swapped reads from a count "
"matrix, producing a new count matrix "
"and determining which barcodes "
"contain real cells.")
subparser.add_argument("--input",
nargs="+",
type=str,
dest='input_files',
default=[],
help="Data files on which to run tool, as "
"_raw_gene_barcode_matrices_h5.h5 files.")
subparser.add_argument(
"--output",
nargs="+",
type=str,
dest='output_files',
default=[],
help="Path to location of output data files, which "
"will be .h5 files.")
subparser.add_argument("--epochs",
type=int,
default=150,
dest="epochs",
help="Number of epochs to train.")
subparser.add_argument("--z_dim",
type=int,
default=20,
dest="z_dim",
help="Dimension of latent variable z.")
subparser.add_argument(
"--z_layers",
nargs="+",
type=int,
default=[500],
dest="z_hidden_dims",
help="Dimension of hidden layers in the encoder for z.")
subparser.add_argument(
"--d_layers",
nargs="+",
type=int,
default=[5, 2, 2],
dest="d_hidden_dims",
help="Dimension of hidden layers in the encoder for d.")
subparser.add_argument(
"--p_layers",
nargs="+",
type=int,
default=[100, 10],
dest="p_hidden_dims",
help="Dimension of hidden layers in the encoder for p.")
subparser.add_argument(
"--expected_cells",
nargs="+",
type=int,
default=[None],
dest="expected_cell_count",
help="Number of cells expected in each dataset.")
subparser.add_argument(
"--additional_barcodes",
nargs="+",
type=int,
default=[None],
dest="additional_barcodes",
help="The number of additional droplets after the "
"number of expected cells "
"that have any chance of containing cells.")
subparser.add_argument(
"--empty_drop_training_fraction",
type=float,
default=0.5,
dest="fraction_empties",
help="Fraction of the training data that should be "
"empty droplets.")
subparser.add_argument(
"--training_fraction",
type=float,
default=0.95,
dest="training_fraction",
help="Fraction of the data to use for training.")
subparser.add_argument("--blacklist_genes",
nargs="+",
type=int,
default=[],
dest="blacklisted_genes",
help="Indices of genes to ignore entirely.")
subparser.add_argument(
"--model",
nargs="+",
type=str,
default=["full"],
choices=["simple", "ambient", "swapping", "full"],
dest="model",
help="Which model is being used for count data. "
"'simple' does not model background or ambient "
"RNA. 'ambient' assumes background RNA is "
"incorporated into droplets. 'swapping' assumes "
"background RNA comes from barcode swapping. "
"'full' uses a combined ambient and swapping "
"model.")
subparser.add_argument(
"--transform_counts",
nargs=1,
type=str,
default=["identity"],
choices=["identity", "log", "sqrt"],
dest="transform",
help="Transformation to apply to count data prior "
"to running inference.")
subparser.add_argument(
"--learning_rate",
type=float,
default=1e-3,
dest="learning_rate",
help="Learning rate for inference (probably don't "
"exceed 1e-3).")
# subparser.add_argument("--lambda", type=float, default=0.,
# dest="lambda_reg",
# help="Regularization parameter. Default zero. "
# "L1 regularizer applied to decoder.")
subparser.add_argument(
"--cuda",
dest="use_cuda",
action="store_true",
help="Including the flag --cuda will run the inference "
"on a GPU.")
subparser.add_argument("--decaying_average_baseline",
dest="use_decaying_average_baseline",
action="store_true",
help="Including the flag "
"--decaying_average_baseline will use a "
"decaying average baseline during inference.")
subparser.add_argument("--use_IAF",
dest="use_IAF",
action="store_true",
help="Including the flag "
"--use_IAF will use an inverse autoregressive "
"flow during inference to allow more "
"flexibility in the learned posterior.")
subparser.add_argument("--low_count_threshold",
type=int,
default=30,
dest="low_count_threshold",
help="Droplets with UMI counts below this are"
"completely excluded from the analysis. This "
"can help adjust the prior for empty droplet "
"counts in the rare case where empty counts "
"are extremely high (over 200).")
subparser.add_argument(
"--test",
dest="test",
action="store_true",
help="Including the flag --test will run tests only, "
"and disregard other input parameters.")
return subparsers
def task_parser(sup_parser: argparse):
task_parser = sup_parser.add_parser(
'task', help='Manage tasks. Task is the main application object.')
task_subparser = task_parser.add_subparsers(
dest='action', metavar='', description='Commands to work with tasks')
task_subparser.required = True
create = task_subparser.add_parser('create', help='Create new task')
create.add_argument('name', help='Task name')
create.add_argument('-d', '--description', help='Task description')
create.add_argument('-s',
'--start_date',
type=valid_date,
help='Start date (current time by default)')
create.add_argument('-e', '--end_date', type=valid_date, help='End date')
create.add_argument('-p',
'--parent_task_id',
type=valid_int,
help='Parent task id')
create.add_argument('--priority',
type=str,
choices=[x.name.lower() for x in TaskPriority])
create.add_argument('--status',
type=str,
choices=[x.name.lower() for x in TaskStatus])
create.add_argument('--event',
help='Mark as event. No by default settings',
choices=['yes', 'no'])
show = task_subparser.add_parser('show', help='Show tasks')
task_show_parser(show)
edit = task_subparser.add_parser('edit', help='Edit task with provided id')
edit.add_argument('-tid', '--task_id', required=True, type=valid_int)
edit.add_argument('-n', '--name', help='Task name')
edit.add_argument('-d', '--description', help='Task description')
edit.add_argument('-s', '--start_date', type=valid_date, help='Start date')
edit.add_argument('-e', '--end_date', type=valid_date, help='End date')
edit.add_argument('--priority',
type=str,
choices=[x.name.lower() for x in TaskPriority])
edit.add_argument('--status',
type=str,
choices=[x.name.lower() for x in TaskStatus])
edit.add_argument('--event',
choices=['yes', 'no'],
help='Mark as event. No by default settings')
share = task_subparser.add_parser('share', help='Share task with user')
share.add_argument('-tid',
'--task_id',
type=valid_int,
help='Id of task to be shared',
required=True)
share.add_argument('-ur',
'--user_receiver',
type=str,
help='User name to share task with',
required=True)
unshare = task_subparser.add_parser('unshare',
help='Unshare shared task with user')
unshare.add_argument('-tid',
'--task_id',
help='Task id',
required=True,
type=valid_int)
unshare.add_argument('-urn',
'--user_receiver',
help='User name to unshare task with',
required=True,
type=str)
assign = task_subparser.add_parser('assign', help='Assign task executor')
assign.add_argument('-tid',
'--task_id',
help='Task id',
required=True,
type=valid_int)
assign.add_argument('-urn',
'--user_receiver',
help='User name to assign task',
required=True,
type=str)
subtask = task_subparser.add_parser(
'add_subtask',
help='Set task with task_id as the subtask of task with parent_id')
subtask.add_argument('-tid',
'--task_id',
required=True,
help='Task id',
type=valid_int)
subtask.add_argument('-pid',
'--parent_task_id',
help='Parent task id',
required=True,
type=valid_int)
subtask = task_subparser.add_parser(
'detach', help='Remove relation between task and parent task')
subtask.add_argument('-tid',
'--task_id',
required=True,
help='Task id to detach from parent task',
type=valid_int)
archive = task_subparser.add_parser('archive', help='Archive task')
archive.add_argument('--subtasks',
action='store_true',
help='Archive subtasks too')
archive.add_argument('task_id', help='task id', type=valid_int)
done = task_subparser.add_parser('done', help='Done task')
done.add_argument('task_id', help='task id', type=valid_int)
search = task_subparser.add_parser(
'search', help='Case insensitive task search by name')
search.add_argument('name', help='Task name')
filter = task_subparser.add_parser('filter',
help='Search tasks by specified params')
filter.add_argument('-n', '--name', help='Task name')
filter.add_argument('-d', '--description', help='Task description')
filter.add_argument('-s',
'--start_date',
type=valid_date,
help='Task start date from')
filter.add_argument('-e',
'--end_date',
type=valid_date,
help='Task end date till to')
filter.add_argument('-p',
'--parent_task_id',
type=valid_int,
help='Parent task id')
filter.add_argument('--priority',
choices=[x.name.lower() for x in TaskPriority],
help='Task priority')
filter.add_argument('--status',
choices=[x.name.lower() for x in TaskStatus],
help='Task status')
filter.add_argument('--event', choices=['yes', 'no'], help='Is Event')
delete = task_subparser.add_parser('delete',
help='Delete task with provided id')
delete.add_argument('task_id', type=valid_int)
def add_subparser_args(subparsers: argparse) -> argparse:
"""Add tool-specific arguments for remove-background.
Args:
subparsers: Parser object before addition of arguments specific to
remove-background.
Returns:
parser: Parser object with additional parameters.
"""
subparser = subparsers.add_parser("remove-background",
description="Remove background RNA "
"from count matrix.",
help="Remove background ambient RNA "
"and barcode-swapped reads from "
"a count matrix, producing a "
"new count matrix and "
"determining which barcodes "
"contain real cells.")
subparser.add_argument("--input", nargs=None, type=str,
dest='input_file', default=None,
required=True,
help="Data file on which to run tool, as either "
"_raw_gene_barcode_matrices_h5.h5 file, or "
"as the path containing the raw "
"matrix.mtx, barcodes.tsv, and genes.tsv "
"files. Supported for outputs of "
"CellRanger v2 and v3.")
subparser.add_argument("--output", nargs=None, type=str,
dest='output_file', default=None,
required=True,
help="Output file location (the path must "
"exist, and the file name must have .h5 "
"extension).")
subparser.add_argument("--expected-cells", nargs=None, type=int,
default=None,
dest="expected_cell_count",
help="Number of cells expected in the dataset "
"(a rough estimate within a factor of 2 "
"is sufficient).")
subparser.add_argument("--total-droplets-included",
nargs=None, type=int,
default=consts.TOTAL_DROPLET_DEFAULT,
dest="total_droplets",
help="The number of droplets from the "
"rank-ordered UMI plot that will be "
"analyzed. The largest 'total_droplets' "
"droplets will have their cell "
"probabilities inferred as an output.")
subparser.add_argument("--model", nargs=None, type=str, default="full",
choices=["simple", "ambient",
"swapping", "full"],
dest="model",
help="Which model is being used for count data. "
" 'simple' does not model either ambient "
"RNA or random barcode swapping (for "
"debugging purposes -- not recommended). "
"'ambient' assumes background RNA is "
"incorporated into droplets. 'swapping' "
"assumes background RNA comes from random "
"barcode swapping. 'full' uses a "
"combined ambient and swapping model. "
"Defaults to 'full'.")
subparser.add_argument("--epochs", nargs=None, type=int, default=150,
dest="epochs",
help="Number of epochs to train.")
subparser.add_argument("--cuda",
dest="use_cuda", action="store_true",
help="Including the flag --cuda will run the "
"inference on a GPU.")
subparser.add_argument("--low-count-threshold", type=int,
default=consts.LOW_UMI_CUTOFF,
dest="low_count_threshold",
help="Droplets with UMI counts below this "
"number are completely excluded from the "
"analysis. This can help identify the "
"correct prior for empty droplet counts "
"in the rare case where empty counts "
"are extremely high (over 200).")
subparser.add_argument("--z-dim", type=int, default=20,
dest="z_dim",
help="Dimension of latent variable z.")
subparser.add_argument("--z-layers", nargs="+", type=int, default=[500],
dest="z_hidden_dims",
help="Dimension of hidden layers in the encoder "
"for z.")
subparser.add_argument("--d-layers", nargs="+", type=int,
default=[5, 2, 2],
dest="d_hidden_dims",
help="Dimension of hidden layers in the encoder "
"for d.")
subparser.add_argument("--p-layers", nargs="+", type=int,
default=[100, 10],
dest="p_hidden_dims",
help="Dimension of hidden layers in the encoder "
"for p.")
subparser.add_argument("--empty-drop-training-fraction",
type=float, nargs=None,
default=consts.FRACTION_EMPTIES,
dest="fraction_empties",
help="Training detail: the fraction of the "
"training data each epoch "
"that is drawn (randomly sampled) from "
"surely empty droplets.")
subparser.add_argument("--blacklist-genes", nargs="+", type=int,
default=[],
dest="blacklisted_genes",
help="Integer indices of genes to ignore "
"entirely. In the output count matrix, "
"the counts for these genes will be set "
"to zero.")
subparser.add_argument("--learning-rate", nargs=None,
type=float, default=1e-3,
dest="learning_rate",
help="Training detail: learning rate for "
"inference (probably "
"do not exceed 1e-3).")
return subparsers