def normal():
wanted = json.loads(open("wanted.json").read())
original_path = os.path.abspath(os.getcwd())
for d, v in wanted.items():
for subdir, lins in v.items():
path = os.path.abspath(os.path.join(d, subdir))
print("Processing path:", path)
os.chdir(path)
for lin in lins:
lineage_num = int(lin)
target_file = os.path.join(
"data",
"cell_lines",
"lineage{0:02d}.npy".format(lineage_num)
)
cell_line = np.load(target_file)
spot_plot.plot_images(cell_line, lineage_num)
try:
spot_plot.plot_graphs(cell_line, lineage_num)
except AttributeError:
print("ParA data missing")
get_parA.main()
cell_line = np.load(target_file)
spot_plot.plot_graphs(cell_line, lineage_num)
print("Generated plots for lineage {0}".format(lineage_num))
os.chdir(original_path)
def end(self, discard=False):
if discard:
plt.close()
return
# backup previous lineage file
previous_file = "data/cell_lines/lineage{0:02d}.npy".format(self.lineage_num)
if os.path.exists(previous_file):
if not os.path.exists("data/cell_lines/backups"):
os.mkdir("data/cell_lines/backups")
backup_file = "data/cell_lines/backups/{0}-lineage{1:02d}.npy".format(
datetime.datetime.strftime(datetime.datetime.now(), "%Y%m%d-%H%M"),
self.lineage_num
)
attempt = 2
while os.path.exists(backup_file):
first = backup_file.split(".npy")[0]
backup_file = "{0}.npy-{1}".format(first, attempt)
attempt += 1
print("Backing up previous lineage file to {0}".format(backup_file))
os.rename(previous_file, backup_file)
print("Saving new lineage file")
np.save(
"data/cell_lines/lineage{0:02d}".format(self.lineage_num),
self.cell_line
)
if self.GEN_PLOTS:
print("Saving new PDFs")
spot_plot.plot_images(self.cell_line, int(self.lineage_num))
spot_plot.plot_graphs(self.cell_line, int(self.lineage_num), um=True)
spot_spread.gen_xl(self.cell_line, int(self.lineage_num))
plt.close(self.fig)
def plot_lineages(bonly=False):
if not os.path.exists("ancestry.json"):
cells = init()
else:
cells = json.loads(open("ancestry.json").read())
inverse_cells = {cells[k]: k for k in cells}
lineage = track.Lineage()
already_plotted = []
for lineage_num in sorted(inverse_cells.keys()):
if lineage_num in already_plotted:
continue
print("Processing lineage {0}".format(lineage_num))
cell_line_nums = []
# cell_line_positions = {}
cell_lines = {}
cell_parents = {}
# designations = {
# lineage_num: "",
# }
current_num = int(lineage_num)
buff = []
generations = {}
max_len = 0
labels = {}
while True:
if current_num:
mother_line = np.load("data/cell_lines/lineage{0:02d}.npy".format(current_num))
max_len_ = max([x.length[0][0] * PX for x in mother_line])
if max_len_ > max_len:
max_len = float(max_len_)
cell_lines[current_num] = mother_line
cell_line_nums.append(current_num)
daughters = mother_line[-1].children
gen = 0
# designation = ""
_temp_num = int(current_num)
while True:
if _temp_num not in cell_parents:
break
_temp_num = cell_parents[_temp_num]
gen += 1
generations[current_num] = gen
labels[mother_line[-1].id] = current_num
if daughters:
d1 = lineage.frames.cell(daughters[0]).length[0][0] * PX
d2 = lineage.frames.cell(daughters[1]).length[0][0] * PX
max_len_ = max([max_len_, d1 + d2])
if max_len_ > max_len:
max_len = float(max_len_)
d1n = cells[daughters[0]]
d2n = cells[daughters[1]]
buff.append(d1n)
buff.append(d2n)
# designations[d1n] = designations[current_num] + "A"
# designations[d2n] = designations[current_num] + "B"
cell_parents[d1n] = current_num
cell_parents[d2n] = current_num
print("{0} => {1}, {2}".format(current_num, d1n, d2n))
else:
buff.append(None)
buff.append(None)
print("{0} => None".format(current_num))
else:
cell_line_nums.append(None)
try:
current_num = buff.pop(0)
except IndexError:
break
# max_gen = max(generations.values())
#
# last_xpos = None
# count = 0
# specs = []
# gridspec = matplotlib.gridspec.GridSpec(2 ** max_gen, max_gen + 1)
#
# for num in cell_line_nums:
# if not num:
# count += 1
# continue
# # get generation
# xpos = generations[num]
# if xpos == last_xpos:
# count += 1
# else:
# last_xpos = int(xpos)
# count = 0
# yinterval = 2 ** (max_gen - xpos)
# ypos = count * yinterval
# specs.append(gridspec[ypos, xpos])
#
# fig = plt.figure(
# figsize=(
# (20 * (max_gen + 1)) / 6,
# (5 * (2 ** max_gen)) / 2
# )
# )
#
# i = 0
# for cell_line_num in cell_line_nums:
# if not cell_line_num:
# continue
#
# cell_line = cell_lines[cell_line_num]
# print("Plotting lineage {0}".format(cell_line_num))
#
# ax = fig.add_subplot(specs[i])
# spot_plot._despine(ax)
# ax.set_title("Lineage {0}".format(cell_line_num))
# spot_plot.plot_graphs_parB_only(cell_line, cell_line_num, ax_parB=ax, save=False)
# ylim = (max_len + 5) / 2
# ax.set_ylim([ylim, -ylim])
#
# already_plotted.append(cell_line_num)
# i += 1
#
num_rows = int(round(np.sqrt(len(cell_lines))))
if num_rows ** 2 < len(cell_lines):
gridspec = matplotlib.gridspec.GridSpec(num_rows + 1, num_rows)
else:
gridspec = matplotlib.gridspec.GridSpec(num_rows, num_rows)
fig = plt.figure(
figsize=(
(10 * num_rows) / 3,
(5 * num_rows) / 2
)
)
fig.patch.set_alpha(0)
i = 0
for cell_line_num in cell_line_nums:
if not cell_line_num:
continue
# designation = designations[cell_line_num]
# title = "{0} ({1})".format(designation, cell_line_num)
title = "Cell {0}".format(cell_line_num)
cell_line = cell_lines[cell_line_num]
print("Plotting lineage {0}".format(cell_line_num))
sp = matplotlib.gridspec.SubplotSpec(gridspec, i)
ax = fig.add_subplot(sp)
ax.set_title(title)
if cell_line_num == 1:
ax.set_ylabel(r"Distance from mid-cell (\si{\micro\metre})")
ax.set_xlabel(r"Time (\si{\minute})")
spot_plot._despine(ax)
if bonly:
spot_plot.plot_graphs_parB_only(cell_line, cell_line_num, ax_parB=ax, save=False, labels=labels, um=True)
else:
spot_plot.plot_graphs(cell_line, cell_line_num, parA_heatmap=ax, save=False, num_plots=1, labels=labels, um=True)
ylim = (max_len + (5 * PX)) / 2
ax.set_ylim([-ylim, ylim])
already_plotted.append(cell_line_num)
i += 1
plt.tight_layout()
os.makedirs("data/full_lineages", exist_ok=True)
plt.savefig("data/full_lineages/lineage{0:02d}.pdf".format(lineage_num))
print("Done with tree starting from {0}".format(lineage_num))