def setup(self, ctx):
self.choice = None
self.is_first_run = True
filepaths = ctx.database.get(datatype="spreadsheet")
self.is_missing = True
self.choice = None
if filepaths is not None and len(filepaths) > 0:
self.is_missing = False
self._append_view(TextView("Select the covariates/group data spreadsheet file"))
self.add_file_str = "Add spreadsheet file"
dsp_values = [f'"{value}"' for value in filepaths]
dsp_values = [*dsp_values, self.add_file_str]
self.filepath_by_str = dict(zip(dsp_values, filepaths))
self.input_view = SingleChoiceInputView(dsp_values, isVertical=True)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
self._append_view(TextView("Specify the analysis type"))
self.input_view = SingleChoiceInputView(
list(self.options.keys()), isVertical=self.is_vertical
)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
self.is_first_run = True
self.should_run = True
self.choice = None
if not hasattr(ctx.spec.files[-1], "metadata") or ctx.spec.files[-1].metadata is None:
ctx.spec.files[-1].metadata = dict()
if ctx.spec.files[-1].metadata.get("variables") is None:
ctx.spec.files[-1].metadata["variables"] = []
if any(
variable["type"] == "id"
for variable in ctx.spec.files[-1].metadata["variables"]
):
self.should_run = False
if self.should_run:
self._append_view(TextView("Specify the column containing subject names"))
already_used = set(v["name"] for v in ctx.spec.files[-1].metadata["variables"])
df = loadspreadsheet(ctx.spec.files[-1].path)
columns = [column for column in df if column not in already_used]
options = [format_column(column) for column in columns]
self.varname_by_str = dict(zip(options, columns))
self.input_view = SingleChoiceInputView(options, isVertical=True)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
self._append_view(
TextView("Specify the categorical variable for this contrast"))
self.variables = ctx.database.metadata(ctx.spec.models[-1].spreadsheet,
"variables")
self.variables = apply_filters_to_variables(
ctx.spec.models[-1].filters, self.variables)
contrastvariables = set(
ravel(contrast["variable"]
for contrast in ctx.spec.models[-1].contrasts
if contrast.get("type") == "infer")
) # names of all variables added to the model in the previous step
self.variables = [
variable for variable in self.variables
if variable["type"] == "categorical"
and variable["name"] in contrastvariables
]
varnames = [variable["name"] for variable in self.variables]
options = [format_column(varname) for varname in varnames]
self.varname_by_str = dict(zip(options, varnames))
self.input_view = SingleChoiceInputView(options)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
self._append_view(TextView("Specify the feature type"))
self.input_view = SingleChoiceInputView(list(self.options.keys()),
isVertical=True)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
if hasattr(self, "header_str") and self.header_str is not None:
self._append_view(TextView(self.header_str))
self.input_view = SingleChoiceInputView(
list(self.options.keys()), isVertical=self.is_vertical
)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
self.is_first_run = True
self.existing_spec = loadspec(ctx.workdir,
logger=logging.getLogger("pipeline.ui"))
self.choice = None
if self.existing_spec is not None:
self._append_view(TextView("Found spec file in working directory"))
self.input_view = SingleChoiceInputView(self.options,
isVertical=True)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
self._append_view(TextView("Specify the categorical variable for this contrast"))
self.varname_by_str = {
_format_column(variable.name): variable.name
for variable in ctx.spec.analyses[-1].variables
if variable.type == "categorical"
}
self.options = list(self.varname_by_str.keys())
self.input_view = SingleChoiceInputView(self.options)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
self.choice = None
self.is_first_run = True
self.should_run = self._should_run(ctx)
if self.should_run:
if hasattr(self, "header_str") and self.header_str is not None:
self._append_view(TextView(self.header_str))
self.input_view = SingleChoiceInputView(
list(self.options.keys()), isVertical=self.is_vertical
)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
self.is_first_run = True
self.is_missing = True
if any(variable.type == "id" for variable in ctx.spec.analyses[-1].variables):
self.is_missing = False
if self.is_missing:
self._append_view(TextView("Specify the column containing subject names"))
if ctx.spec.analyses[-1].variables is None:
ctx.spec.analyses[-1].variables = []
already_used = set(variable.name for variable in ctx.spec.analyses[-1].variables)
self.varname_by_str = {
_format_column(column): column for column in self.df if column not in already_used
}
options = list(self.varname_by_str.keys())
self.input_view = SingleChoiceInputView(options, isVertical=True)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
self.is_first_run = True
self.existing_spec = loadspec(ctx.workdir,
logger=logging.getLogger("halfpipe.ui"))
self.choice = None
if self.existing_spec is not None:
self._append_view(TextView("Found spec file in working directory"))
options = self.options[:3]
if len(self.existing_spec.features) > 0:
options.append(self.options[3])
if len(self.existing_spec.models) > 0:
options.append(self.options[4])
self.input_view = SingleChoiceInputView(options, isVertical=True)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
self.is_first_run = True
if self.header_str is not None:
self._append_view(TextView(self.header_str))
self.values = ctx.database.get_tagvaldict(self.entity)
self.is_missing = True
self.choice = None
if self.values is not None and len(self.values) > 0:
self.is_missing = False
self.add_file_str = f"Add {self.filetype_str} file"
dsp_values = []
if len(self.values) > 1:
dsp_values.append(self.all_str)
dsp_values.extend(self._make_tagval_strs())
dsp_values.append(self.add_file_str)
self.input_view = SingleChoiceInputView(dsp_values,
isVertical=True)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
humankey = display_str(self.key).lower()
unit = _get_unit(self.schema, self.key)
field = self.field
header_str = f"Specify {humankey}{self.appendstr}"
if unit is not None and self.key != "slice_timing":
header_str += f" in {unit}"
self._append_view(TextView(header_str))
self.aliases = {}
if field.validate is not None and hasattr(field.validate, "choices") or self.key == "slice_timing":
if self.key == "slice_timing":
choices = [*slice_order_strs, "import from file"]
else:
choices = [*field.validate.choices]
if set(space_codes).issubset(choices):
choices = [*space_codes]
if self.key == "slice_encoding_direction":
choices = list(reversed(choices))
display_choices = [
display_str(direction_code_str(choice, None)) for choice in choices
]
else:
display_choices = [display_str(choice) for choice in choices]
self.aliases = dict(zip(display_choices, choices))
self.input_view = SingleChoiceInputView(display_choices, isVertical=True)
elif isinstance(field, fields.Float):
self.input_view = NumberInputView()
else:
raise ValueError(f'Unsupported metadata field "{field}"')
self._append_view(self.input_view)
self._append_view(SpacerView(1))
def setup(self, ctx):
self.is_first_run = True
self.should_skip = self._should_skip(ctx)
self.choice = None
if self.should_skip:
self.is_missing = True
return
humankey = display_str(self.key).lower()
if self.filters is None:
filepaths = [
fileobj.path for fileobj in ctx.database.fromspecfileobj(ctx.spec.files[-1])
]
else:
filepaths = [*ctx.database.get(**self.filters)]
ctx.database.fillmetadata(self.key, filepaths)
vals = [ctx.database.metadata(filepath, self.key) for filepath in filepaths]
self.suggestion = None
if self.key == "phase_encoding_direction" or self.key == "slice_encoding_direction":
for i, val in enumerate(vals):
if val is not None:
vals[i] = direction_code_str(val, filepaths[i])
elif self.key == "slice_timing":
for i, val in enumerate(vals):
if val is not None:
sts = slice_timing_str(val)
if sts == "unknown":
val = np.asarray(val)
sts = np.array2string(val, max_line_width=16384)
else:
sts = humanize(sts)
vals[i] = sts
if any(val is None for val in vals):
self.is_missing = True
self._append_view(TextView(f"Missing {humankey} values"))
vals = [val if val is not None else "missing" for val in vals]
else:
self.is_missing = False
self._append_view(TextView(f"Check {humankey} values{self.appendstr}"))
uniquevals, counts = np.unique(vals, return_counts=True)
order = np.argsort(counts)
column1 = []
for i in range(min(10, len(order))):
column1.append(f"{counts[i]} images")
column1width = max(len(s) for s in column1)
unit = _get_unit(self.schema, self.key)
if unit is None:
unit = ""
if self.key == "slice_timing":
unit = ""
for i in range(min(10, len(order))):
display = display_str(f"{uniquevals[i]}")
if self.suggestion is None:
self.suggestion = display
tablerow = f" {column1[i]:>{column1width}} - {display}"
if uniquevals[i] != "missing":
tablerow = f"{tablerow} {unit}"
self._append_view(TextView(tablerow))
if len(order) > 10:
self._append_view(TextView("..."))
if self.is_missing is False:
self._append_view(TextView("Proceed with these values?"))
self.input_view = SingleChoiceInputView(["Yes", "No"], isVertical=False)
self._append_view(self.input_view)
self._append_view(SpacerView(1))
