def main(name, arguments):
parser.prog = name
options, args = parser.parse_args(arguments)
args = cli_tools.glob_args(args)
reference = cli_tools.glob_args(options.reference)
if (len(args) < 2) or (len(args) + len(reference) < 3):
raise ValueError(
'A data column and at least two datasets (at least one of which must not be a reference) must be provided!'
)
data_column, datasets = args[0], args[1:]
# if the data column is convertible to an integer, do so and
# then convert from 1-indexed to 0-indexed
try:
data_column = int(data_column)
data_column -= 1
except:
pass
if options.show_progress:
datasets = terminal_tools.progress_list(datasets, "Reading input data")
names, pops = read_files(datasets, data_column)
if options.show_progress and len(reference) > 0:
reference = terminal_tools.progress_list(reference,
"Reading reference data")
ref_names, ref_pops = read_files(reference, data_column)
if options.show_progress:
pb = terminal_tools.IndeterminantProgressBar("Resampling data")
if len(ref_pops) > 0:
pvals = ks_resample.compare_to_ref(pops, ref_pops, options.n)
if len(ref_names) > 1:
ref_name = 'reference (%s)' % (', '.join(ref_names))
else:
ref_name = ref_names[0]
rows = [[None, 'difference from %s' % ref_name]]
for name, p in zip(names, pvals):
rows.append([name, format_pval(p, options.n)])
else: # no ref pops
pvals = ks_resample.symmetric_comparison(pops, options.n)
rows = [[None] + names]
for i, (name, p_row) in enumerate(zip(names, pvals)):
rows.append([name] + [format_pval(p, options.n) for p in p_row])
rows[-1][i +
1] = None # empty out the self-self comparison diagonal
datafile.write_data_file(rows, options.output_file)
def main(name, arguments):
parser.prog = name
options, args = parser.parse_args(arguments)
args = cli_tools.glob_args(args)
if len(args) == 0:
raise ValueError('Some contour files must be specified!')
filenames = [path.path(arg) for arg in args]
contours = simple_interface.load_contours(
filenames, show_progress=options.show_progress)
if options.reference is not None:
reference = contour_class.from_file(options.reference)
contours = simple_interface.align_contours_to(
contours,
reference,
align_steps=options.alignment_steps,
allow_reflection=options.allow_reflection,
show_progress=options.show_progress)
else:
contours = simple_interface.align_contours(
contours,
options.alignment_steps,
options.allow_reflection,
max_iters=options.max_iterations,
show_progress=options.show_progress)
destination = path.path(options.destination)
if not destination.exists():
destination.makedirs()
# note that with path objects, the '/' operator means 'join path components.'
names = [destination / filename.name for filename in filenames]
simple_interface.save_contours(contours, names, options.show_progress)
def main(name, arguments):
parser.prog = name
options, args = parser.parse_args(arguments)
args = cli_tools.glob_args(args)
if len(args) == 0:
raise ValueError('Some contour and image files must be specified!')
matches = match_files.match_contours_and_images(args,
options.match_by_name,
options.show_progress)
contours, image_names, unmatched_contours, unmatched_image_names = matches
destination = path.path(options.destination)
if not destination.exists():
destination.makedirs()
if options.file_type is not None:
new_names = [
destination / contour.simple_name() + '.' + options.file_type
for contour in contours
]
else:
new_names = [
destination / contour.simple_name() + image.ext
for image, contour in zip(image_names, contours)
]
simple_interface.reorient_images(contours,
image_names,
new_names,
pad_factor=options.pad_factor,
mask=options.mask_background,
show_progress=options.show_progress)
def main(name, arguments):
parser.prog = name
options, args = parser.parse_args(arguments)
args = cli_tools.glob_args(args)
if len(args) == 0:
raise ValueError('Some contour files must be specified!')
contours = simple_interface.load_contours(
args, show_progress=options.show_progress)
shape_model, header, rows, norm_header, norm_rows = simple_interface.make_shape_model(
contours, options.variance_explained)
shape_model.to_file(options.output_prefix + '.contour')
if options.write_data:
datafile.write_data_file([header] + rows,
options.output_prefix + '-positions.csv')
datafile.write_data_file([norm_header] + norm_rows,
options.output_prefix +
'-normalized-positions.csv')
def main(name, arguments):
parser.prog = name
options, args = parser.parse_args(arguments)
args = cli_tools.glob_args(args)
if len(args) == 0:
raise ValueError('Some contour files must be specified!')
contours = simple_interface.load_contours(
args, show_progress=options.show_progress)
if options.grid:
contours = simple_interface.grid_contours(contours)
# Transform (begin, end) from a one-indexed, inclusive range (normal for humans)
# to a zero-indexed inclusive range.
if options.begin is not None:
options.begin -= 1
if options.end is not None:
options.end -= 1
if options.color_by == 'none':
gradient_factory = None
else:
gradient_factory = plot_tools.default_gradient
if options.color_by == 'points' or options.begin or options.end or options.label_points:
# do point ordering plot
colorbar = options.color_by == 'points'
color_by_point = options.color_by == 'points'
# use a color bar if we're doing a gradient
plot_tools.point_order_plot(contours,
options.output_file,
plot_title=options.title,
label_points=options.label_points,
colorbar=colorbar,
begin=options.begin,
end=options.end,
gradient_factory=gradient_factory,
color_by_point=color_by_point,
scale=options.scale,
show_progress=options.show_progress)
else:
plot_tools.contour_plot(contours,
options.output_file,
plot_title=options.title,
gradient_factory=gradient_factory,
scale=options.scale,
show_progress=options.show_progress)
def main(name, arguments):
parser.prog = name
options, args = parser.parse_args(arguments)
args = cli_tools.glob_args(args)
if len(args) != 1:
raise ValueError(
'Only a single PCA contour can be plotted at a time -- please specify only one model file on the command line.'
)
pca_contour = contour_class.from_file(args[0], contour_class.PCAContour)
if not options.output_file:
output_file = pca_contour.simple_name() + '.svg'
else:
output_file = options.output_file
plot_tools.pca_modes_plot(pca_contour,
output_file,
modes=options.modes,
positions=options.positions,
scale=options.scale)
def main(name, arguments):
parser.prog = name
options, args = parser.parse_args(arguments)
args = cli_tools.glob_args(args)
if len(args) == 0:
raise ValueError('Some contour files must be specified!')
filenames = [path.path(arg) for arg in args]
contours = simple_interface.load_contours(filenames, show_progress = options.show_progress)
if options.endpoints is None:
endpoints = options.endpoint_method
else:
endpoints = options.endpoints
contours = simple_interface.find_centerlines(contours, options.axis_points, endpoints, options.show_progress)
destination = path.path(options.destination)
if not destination.exists():
destination.makedirs()
# note that with path objects, the '/' operator means 'join path components.'
names = [destination / filename.name for filename in filenames]
simple_interface.save_contours(contours, names, options.show_progress)
def main(name, arguments):
parser.prog = name
options, args = parser.parse_args(arguments)
args = cli_tools.glob_args(args)
if len(args) == 0:
raise ValueError('Some contour files must be specified!')
filenames = [path.path(arg) for arg in args]
contours = simple_interface.load_contours(
filenames, show_progress=options.show_progress)
if options.first_point is not None:
options.first_point -= 1
if options.scale is not None or options.rotate is not None or options.units is not None or options.first_point is not None:
in_radians = False
if options.units is not None and options.units.lower() in ('um',
'micron',
'microns'):
options.units = u'\N{MICRO SIGN}m'
contours = simple_interface.transform_contours(
contours,
options.scale,
options.rotate,
in_radians,
options.units,
options.first_point,
options.show_progress,
title='Modifying Contours')
if options.weights is not None:
contours = simple_interface.reweight_landmarks(contours,
options.weights,
options.show_progress)
destination = path.path(options.destination)
if not destination.exists():
destination.makedirs()
# note that with path objects, the '/' operator means 'join path components.'
names = [destination / filename.name for filename in filenames]
simple_interface.save_contours(contours, names, options.show_progress)
def main(name, arguments):
parser.prog = name
options, args = parser.parse_args(arguments)
args = cli_tools.glob_args(args)
if len(args) == 0:
raise ValueError('Some image files must be specified!')
filenames = [path.path(arg) for arg in args]
contours_groups = simple_interface.extract_contours(filenames, options.contour_value,
options.min_area, options.max_area, options.show_progress)
contours = []
names = []
destination = path.path(options.destination)
if not destination.exists():
destination.makedirs()
for contour_group, image_name in zip(contours_groups, filenames):
num_contours = len(contour_group)
if num_contours == 1:
contours.append(contour_group[0])
# note that with path objects, the '/' operator means 'join path components.'
names.append(destination / image_name.namebase + '.contour')
contour_group[0]._filename = image_name.namebase
else:
width = len(str(num_contours))
for i, contour in enumerate(contour_group):
contours.append(contour)
names.append(destination / image_name.namebase + '-%.*d.contour'%(width, i+1))
contour._filename = image_name.namebase + '-%.*d'%(width, i+1)
if options.scale is not None:
# if not rescaling, contours are already denominated in pixels, so do nothing.
units = options.units
if units.lower() in ('um', 'micron', 'microns'):
units = u'\N{MICRO SIGN}m'
contours = simple_interface.transform_contours(contours, scale_factor=options.scale,
units=units, show_progress=options.show_progress, title='Rescaling Contours')
if options.resample:
contours = simple_interface.resample_contours(contours, options.resample_points, options.smoothing_factor, options.show_progress)
simple_interface.save_contours(contours, names, options.show_progress)
def main(name, arguments):
parser.prog = name
options, args = parser.parse_args(arguments)
args = cli_tools.glob_args(args)
if len(args) == 0:
raise ValueError('Some contour and image files must be specified!')
intensity_ranges = []
for r in options.intensity_ranges:
try:
low, high = r
except:
low = high = r
intensity_ranges.append([low, high])
if options.weights is None or len(options.weights) == 0:
options.weights = [0.5]
elif len(options.weights) != 1 and len(
options.weights) != len(intensity_ranges):
raise optparse.OptionValueError(
"Either one or %d weights are required; %d sepcified." %
(len(intensity_ranges), len(options.weights)))
elif sum(options.weights) > 1:
raise optparse.OptionValueError("The sum of the weights must be <= 1.")
matches = match_files.match_contours_and_images(args,
options.match_by_name,
options.show_progress)
contours, image_names, unmatched_contours, unmatched_image_names = matches
filenames = [path.path(contour._filename) for contour in contours]
contours = simple_interface.add_image_landmarks_to_contours(
contours, image_names, intensity_ranges, options.weights,
options.image_type, options.show_progress)
destination = path.path(options.destination)
if not destination.exists():
destination.makedirs()
# note that with path objects, the '/' operator means 'join path components.'
names = [destination / filename.name for filename in filenames]
simple_interface.save_contours(contours, names, options.show_progress)
def main(name, arguments):
parser.prog = name
options, args = parser.parse_args(arguments)
data_files = []
new_args = []
for arg in args:
if type(arg) == list:
data_files.append(arg)
else:
new_args.append(arg)
args = cli_tools.glob_args(new_args)
if len(args) == 0:
raise ValueError('Some data files (and optionally contour files, for 2D plots) must be specified!')
# if the x, y, and name columns are convertible to integers, do so and
# then convert them from 1-indexed to 0-indexed
try:
options.name_column = int(options.name_column)
options.name_column -= 1
except:
pass
try:
options.x_column = int(options.x_column)
options.x_column -= 1
except:
pass
try:
options.y_column = int(options.y_column)
options.y_column -= 1
except:
pass
contours = {}
if options.show_progress:
args = terminal_tools.progress_list(args, "Reading input data and contours")
for arg in args:
contour = None
try:
contour = contour_class.from_file(arg)
except:
data_files.append(arg)
if contour is not None:
contours[contour.simple_name()] = contour
if len(data_files) == 0:
raise ValueError('No data files were specified!')
headers, data_ranges, data_names, data_files, row_ranges = get_data(data_files)
if not options.x_title:
if isinstance(options.x_column, int):
try: options.x_title = headers[0][options.x_column]
except: pass
else:
options.x_title = options.x_column
if options.y_column is not None:
# make scatterplot
if not options.y_title:
if isinstance(options.y_column, int):
try: options.y_title = headers[0][options.y_column]
except: pass
else:
options.y_title = options.y_column
contour_groups = get_contour_groups(data_ranges, contours, data_files, row_ranges, options.name_column, options.x_column, options.y_column)
if numpy.alltrue([len(cg)==0 for cg in contour_groups]):
raise RuntimeError('No contours found for data rows specified (perhaps the names mismatch or there were no data rows?).')
plot_tools.contour_scatterplot(contour_groups, options.output_file, options.scale,
(options.x_title, options.y_title), options.title, names=data_names,
axes_at_origin=options.axes_at_origin, fix_xrange=(options.x_min, options.x_max),
fix_yrange=(options.y_min, options.y_max), show_contour_axes=options.contour_axes,
show_progress=options.show_progress)
else:
data_groups = [[row[options.x_column] for row in data_range] for data_range in data_ranges]
plot_tools.distribution_plot(data_groups, options.output_file, options.x_title,
options.title, names=data_names, axes_at_origin=options.axes_at_origin,
fix_xrange=(options.x_min, options.x_max))
