def tomoseq_all_sim(point_mat, func):
axis_list = ["x", "y", "z"]
ts_all = tomo_seq_all_axis(point_mat)
for axis in axis_list:
ts_sim = expression_simulator(point_mat, func, axis)
ts_all.ts_dict[axis] = ts_sim
return (ts_all)
def register_tomoseq(self, prefix, hpf, stage="shield"):
self.stage_time_dict[stage] = hpf
self.t_vec = safe_append(self.t_vec, hpf)
self.ts_t_vec = safe_append(self.ts_t_vec, hpf)
pmat = self.ct.get_pmat(hpf)
ts_all = tomo_seq_all_axis(pmat)
axis_list = ["av", "vd", "lr"]
for i in range(len(axis_list)):
axis = axis_list[i]
divnum = np.arange(-1400, 1400, self.div_width_dict_shield[axis])
filename = prefix + "_" + axis + ".csv"
ts_all.register_axis(filename, axis, divnum)
self.ts_dict[hpf] = ts_all
def register_tomoseq_ss(self, prefix, hpf, stage="10ss", fix_angle=0):
self.stage_time_dict[stage] = hpf
self.t_vec = safe_append(self.t_vec, hpf)
self.ts_t_vec = safe_append(self.ts_t_vec, hpf)
pmat = self.ct.get_pmat(hpf)
ts_all = tomo_seq_all_axis(pmat, fix_angle)
axis_list = ["va", "dv", "lr"]
label_list = ["av", "vd", "lr"]
for i in range(len(axis_list)):
axis = axis_list[i]
label = label_list[i]
divnum = np.arange(-1400, 1400, self.div_width_dict_ss10[axis])
filename = prefix + "_" + label + ".csv"
ts_all.register_axis(filename, axis, divnum)
self.ts_dict[hpf] = ts_all
def register_tomoseq_divnum(self,
prefix,
hpf,
stage,
divnum_dict,
fix_angle,
axis_list=["av", "vd", "lr"],
label_list=["av", "vd", "lr"]):
self.stage_time_dict[stage] = hpf
self.t_vec = safe_append(self.t_vec, hpf)
self.ts_t_vec = safe_append(self.ts_t_vec, hpf)
pmat = self.ct.get_pmat(hpf)
ts_all = tomo_seq_all_axis(pmat, fix_angle)
for i in range(len(axis_list)):
axis = axis_list[i]
label = label_list[i]
filename = prefix + "_" + label + ".csv"
ts_all.register_axis(filename,
axis,
divnum_dict[axis],
divnum_direct=True)
self.ts_dict[hpf] = ts_all
type=str,
help='file prefix for cell density')
parser.add_argument('--sample_num',
'-n',
default=2000,
type=int,
help='number of points sampled from cell density')
parser.add_argument('--time', '-t', default=6.0, type=float, help='hpf')
args = parser.parse_args()
# cell coordinate preparation
gpp = GP_data_processor()
gpp.register_file(args.dens)
point_mat = gpp.sample_point_time(args.time, size=args.sample_num)
divnum = np.arange(-2, 2, 0.055)
# expression data preparation
ts_all = tomo_seq_all_axis(point_mat)
for axis in ['av', 'vd', 'lr']:
fname_av = args.expression + '_' + axis + '.csv'
ts_all.register_axis(fname_av, axis, divnum)
# adding data for STGE
slice_all = ts_all.get_slice_list()
gene_id = args.gene
exp_all = ts_all.get_expression(gene_id)
stge = STGE()
stge.add_region_list(slice_all, exp_all)
# tunig and save hyper parameters
inits = np.random.uniform(0.01, 10, 3)
res = stge.optimize_parameters(sigma_f=inits[0],
l_corr=inits[1],
sigma_obs=inits[2])
gene_param = np.concatenate(([gene_id], res.astype(str))).reshape([1, 4])