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)