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.ALIGNED
in_dir = Pipeline._cache_dir(base=base_dir, enum=Pipeline.Step.SANITIZED)
out_dir = Pipeline._cache_dir(base=base_dir, enum=step)
force = True
max_n_pool = multiprocessing.cpu_count() - 1
n_pool = 6
N_fit_pts = 20
min_F_N = 175e-12 if "+Retinal" in base_dir else 90e-12
data = RetinalUtil.align_data(in_dir,
out_dir,
force=force,
n_pool=n_pool,
min_F_N=min_F_N,
N_fit_pts=N_fit_pts)
plot_subdir = Pipeline._plot_subdir(base_dir, step)
xlim_heatmap_nm = [-40, 100]
ProcessingUtil.heatmap_ensemble_plot(data,
xlim=xlim_heatmap_nm,
out_name=plot_subdir + "heatmap.png")
# get the post-blacklist heapmap, too..
data_filtered = ProcessingUtil._filter_by_bl(data, in_dir)
# align the data...
data_aligned = [RetinalUtil._polish_helper(d) for d in data_filtered]
out_name = plot_subdir + "heatmap_bl.png"
ProcessingUtil.heatmap_ensemble_plot(data_aligned,
xlim=xlim_heatmap_nm,
out_name=out_name)
# make individual plots
ProcessingUtil.make_aligned_plot(base_dir,
step,
data,
xlim=[-30, 150],
use_shift=True)
def make_plot(dir_in, out_name):
dir_aligned = dir_in + "cache_8_aligned/"
dir_polished = dir_in + "cache_10_polish/"
data_unaligned = CheckpointUtilities.lazy_multi_load(dir_aligned)
data_polished = CheckpointUtilities.lazy_multi_load(dir_polished)
data_unaligned = ProcessingUtil._filter_by_bl(data_unaligned, dir_in)
data_polished = ProcessingUtil._filter_by_bl(data_polished, dir_in)
# scootch the data over slightly
for d in data_polished:
d.Separation -= 20e-9
to_x = lambda _x: _x * 1e9
to_y = lambda _y: _y * 1e12
xlim = [-10, 100]
ylim = [-20, 350]
plt.close()
fig = PlotUtilities.figure(figsize=(3.5, 4.5))
kw_plot = dict(linewidth=0.75)
ax1 = plt.subplot(2, 2, 1)
for d in data_unaligned:
plt.plot(to_x(d.Separation), to_y(d.Force), **kw_plot)
ax2 = plt.subplot(2, 2, 2)
for d in data_polished:
plt.plot(to_x(d.Separation), to_y(d.Force), **kw_plot)
for a in [ax1, ax2]:
a.set_ylim(ylim)
a.set_xlim(xlim)
PlotUtilities.lazyLabel("Extension (nm)", "$F$ (pN)", "", ax=a)
PlotUtilities.ylabel("", ax=ax2)
height_pN = 100
min_y, max_y, delta_y = Scalebar.offsets_zero_tick(
limits=ylim, range_scalebar=height_pN)
kw_scale = dict(offset_x=0.7,
offset_y=max_y,
x_kwargs=dict(width=20, unit="nm"),
y_kwargs=dict(height=height_pN, unit="pN"))
for a in [ax1, ax2]:
Scalebar.crossed_x_and_y_relative(ax=a, **kw_scale)
PlotUtilities.no_y_label(ax=a)
PlotUtilities.no_x_label(ax=a)
PlotUtilities.x_label_on_top(ax=a)
num = 200
bins_x = np.linspace(xlim[0], xlim[-1], endpoint=True, num=num)
bins_y = np.linspace(ylim[0], ylim[-1], endpoint=True, num=num)
kw = dict(color='w', use_colorbar=False, bins=(bins_x, bins_y), title="")
kw_scale_heat = dict(**kw_scale)
line_kw_def = dict(color='w', linewidth=2)
font_x, font_y = Scalebar.font_kwargs_modified(x_kwargs=dict(color='w'),
y_kwargs=dict(color='w'))
kw_scale_heat['x_kwargs']['line_kwargs'] = line_kw_def
kw_scale_heat['x_kwargs']['font_kwargs'] = font_x
kw_scale_heat['y_kwargs']['line_kwargs'] = line_kw_def
kw_scale_heat['y_kwargs']['font_kwargs'] = font_y
ax3 = plt.subplot(2, 2, 3)
Plotting.formatted_heatmap(data=data_unaligned, **kw)
Scalebar.crossed_x_and_y_relative(ax=ax3, **kw_scale_heat)
ax4 = plt.subplot(2, 2, 4)
Plotting.formatted_heatmap(data=data_polished, **kw)
Scalebar.crossed_x_and_y_relative(ax=ax4, **kw_scale_heat)
for a in [ax3, ax4]:
PlotUtilities.no_y_label(ax=a)
PlotUtilities.no_x_label(ax=a)
a.set_xlim(xlim)
a.set_ylim(ylim)
PlotUtilities.xlabel("", ax=a)
PlotUtilities.ylabel("", ax=ax4)
PlotUtilities.ylabel("$F$ (pN)", ax=ax3)
PlotUtilities.savefig(fig, out_name)
pass
