def run():
"""
<Description>
Args:
param1: This is the first param.
Returns:
This is a description of what is returned.
"""
base_dir = RetinalUtil._landscape_base()
step = Pipeline.Step.REDUCED
in_dir = Pipeline._cache_dir(base=base_dir, enum=Pipeline.Step.SANITIZED)
out_dir = Pipeline._cache_dir(base=base_dir, enum=step)
force = True
limit = None
functor = lambda: to_iwt(in_dir)
data = CheckpointUtilities.multi_load(cache_dir=out_dir,
load_func=functor,
force=force,
limit=limit,
name_func=FEC_Util.fec_name_func)
ProcessingUtil.plot_data(base_dir, step, data, xlim=[-50, 150])
plot_subdir = Pipeline._plot_subdir(base_dir, step)
out_name = plot_subdir + "heatmap.png"
ProcessingUtil.heatmap_ensemble_plot(data, out_name=out_name)
def run():
"""
<Description>
Args:
param1: This is the first param.
Returns:
This is a description of what is returned.
"""
default_base = "../../../Data/170321FEC/"
base_dir = Pipeline._base_dir_from_cmd(default=default_base)
step = Pipeline.Step.FILTERED
in_dir = Pipeline._cache_dir(base=base_dir, enum=Pipeline.Step.READ)
out_dir = Pipeline._cache_dir(base=base_dir, enum=step)
force = True
limit = None
f_filter_Hz = 5e3
# filter to X s
t_filter_s = 1 / f_filter_Hz
# t_filter -> n_filter_points
# after filtering, take every N points, where
# N = f_decimate * n_filter_points
# in other words, we oversample by 1/f_decimate
f_decimate = 0.33
assert f_decimate < 1 and f_decimate > 0
data = filter_data(in_dir, out_dir, force, t_filter_s, f_decimate)
ProcessingUtil.plot_data(base_dir, step, data, markevery=1)
def run():
"""
<Description>
Args:
param1: This is the first param.
Returns:
This is a description of what is returned.
"""
base_input_processing = RetinalUtil._processing_base()
base_dir = RetinalUtil._landscape_base()
step = Pipeline.Step.MANUAL
in_dir = Pipeline._cache_dir(base=base_input_processing,
enum=Pipeline.Step.POLISH)
out_dir = Pipeline._cache_dir(base=base_dir,enum=step)
data_input = CheckpointUtilities.lazy_multi_load(in_dir)
force = True
functor = lambda : ProcessingUtil.\
_filter_by_bl(data_input,base_input_processing)
data = CheckpointUtilities.multi_load(cache_dir=out_dir,load_func=functor,
force=force,
name_func=FEC_Util.fec_name_func)
# plot each individual
ProcessingUtil.plot_data(base_dir,step,data,xlim=[-50,150])
plot_subdir = Pipeline._plot_subdir(base_dir, step)
out_name = plot_subdir + "heatmap.png"
ProcessingUtil.heatmap_ensemble_plot(data, out_name=out_name)
def run():
"""
<Description>
Args:
param1: This is the first param.
Returns:
This is a description of what is returned.
"""
base_dir = RetinalUtil._landscape_base()
step = Pipeline.Step.SANITIZED
in_dir = Pipeline._cache_dir(base=base_dir, enum=Pipeline.Step.MANUAL)
out_dir = Pipeline._cache_dir(base=base_dir, enum=step)
force = True
limit = None
min_sep = RetinalUtil.min_sep_landscape()
max_sep = min_sep + 100e-9
functor = lambda: slice_data(in_dir, min_sep=min_sep, max_sep=max_sep)
data = CheckpointUtilities.multi_load(cache_dir=out_dir,
load_func=functor,
force=force,
limit=limit,
name_func=FEC_Util.fec_name_func)
plot_dir = Pipeline._plot_subdir(base=base_dir, enum=step)
ProcessingUtil.heatmap_ensemble_plot(data,
out_name=plot_dir + "heatmap.png",
xlim=[-20, max_sep * 1e9])
# plot each individual
ProcessingUtil.plot_data(base_dir, step, data)
def run():
"""
<Description>
Args:
param1: This is the first param.
Returns:
This is a description of what is returned.
"""
default_base = "../../../Data/170321FEC/"
base_dir = Pipeline._base_dir_from_cmd(default=default_base)
step = Pipeline.Step.CORRECTED
in_dir = Pipeline._cache_dir(base=base_dir, enum=Pipeline.Step.FILTERED)
out_dir = Pipeline._cache_dir(base=base_dir, enum=step)
force = True
n_filter = 10
data = filter_data(in_dir, out_dir, force, n_filter)
ProcessingUtil.plot_data(base_dir, step, data, markevery=1)
def run():
"""
<Description>
Args:
param1: This is the first param.
Returns:
This is a description of what is returned.
"""
default_base = "../../../Data/170321FEC/"
base_dir = Pipeline._base_dir_from_cmd(default=default_base)
step = Pipeline.Step.READ
cache_dir = Pipeline._cache_dir(base=base_dir, enum=step)
force = True
limit = None
functor = lambda: read_all_data(base_dir)
data = CheckpointUtilities.multi_load(cache_dir=cache_dir,
load_func=functor,
force=force,
limit=limit,
name_func=FEC_Util.fec_name_func)
ProcessingUtil.plot_data(base_dir, step, data, markevery=100)