def reformat_args(args):
"""
reformat_args(args)
Returns reformatted args for analyses, specifically
- Sets stimulus parameters to "none" if they are irrelevant to the
stimtype
- Changes stimulus parameters from "both" to actual values
- Sets seed, though doesn't seed
- Modifies analyses (if "all" or "all_" in parameter)
Adds the following args:
- dend (str) : type of dendrites to use ("allen", "extr")
- omit_sess (str): sess to omit
- omit_mice (str): mice to omit
Required args:
- args (Argument parser): parser with the following attributes:
runtype (str) : runtype ("pilot" or "prod")
stimtype (str) : stimulus to analyse (visflow or gabors)
Returns:
- args (Argument parser): input parser, with the following attributes
added:
visflow_dir, visflow_size, gabfr, gabk,
gab_oriomit_sess, omit_mice, dend,
analyses, seed
"""
args = copy.deepcopy(args)
[args.visflow_dir, args.visflow_size, args.gabfr, args.gabk,
args.gab_ori] = sess_gen_util.get_params(args.stimtype, "both", 128,
"any", 16, "any")
if args.plane == "soma":
args.dend = "allen"
args.omit_sess, args.omit_mice = sess_gen_util.all_omit(
args.stimtype, args.runtype, args.visflow_dir, args.visflow_size,
args.gabk)
# choose a seed if none is provided (i.e., args.seed=-1), but seed later
args.seed = rand_util.seed_all(args.seed,
"cpu",
log_seed=False,
seed_now=False)
# collect analysis letters
all_analyses = "".join(get_analysis_fcts().keys())
if "all" in args.analyses:
if "_" in args.analyses:
excl = args.analyses.split("_")[1]
args.analyses, _ = gen_util.remove_lett(all_analyses, excl)
else:
args.analyses = all_analyses
elif "_" in args.analyses:
raise ValueError("Use '_' in args.analyses only with 'all'.")
return args
def get_specific_params(sess_n="1-3",
mouse_n="any",
plane="all",
line="all",
stimtype="gabors",
gabfr=3,
gab_ori="any",
pre=0,
post=0.6,
tails=2,
idx_feature="by_exp",
comp="Dori",
error="sem",
scale=True,
tracked=False,
rem_bad=True,
roi=True,
run=False,
pupil=False):
"""
get_specific_params()
Returns specific parameters for the analysis.
Optional args:
- sess_n (str):
which sessions numbers to include
default: "1-3"
- mouse_n (str):
which mouse number to include
default: "any"
- plane (str):
which planes to include
default: "all"
- line (str):
which lines to include
default: "all"
- stimtype (str):
which stimtypes to include
default: "gabors"
- gabfr (str):
reference Gabor frame
default: 3
- gab_ori (str):
Gabor mean orientations to include
default: "any"
- pre (num):
number of seconds before reference to include
default: 0
- post (num):
number of seconds after reference to include
default: 0.6
- tails (str or int):
p-value tails (2, "hi" or "lo")
default: 2
- idx_feature (str):
type of feature to measure indices on
default: "by_exp"
- comp (str):
logistic regression comparison defining classes to decode
default: "Dori"
- error (str):
type of error statistic to calculate for analyses
default: "sem"
- scale (bool):
whether to use ROI scaling
default: True
- tracked (bool):
if True, only tracked ROIs are included
default: False
- rem_bad (bool):
if True, invalid ROIs are removed, or for pupil/running data,
missing data is interpolated
default: True
- roi (bool):
whether ROI data needs to be loaded
default: True
- run (bool):
whether run data needs to be loaded
default: True
- pupil (bool):
whether pupil data needs to be loaded
default: False
Returns:
- specific_params (dict): dictionary with the specified parameters
"""
visflow_dir, visflow_size, gabfr, gabk, gab_ori = sess_gen_util.get_params(
stimtype, gabfr=gabfr, gab_ori=gab_ori)
specific_params = {
"sess_n": sess_n,
"mouse_n": mouse_n,
"plane": plane,
"line": line,
"stimtype": stimtype,
"visflow_dir": visflow_dir,
"visflow_size": visflow_size,
"gabfr": gabfr,
"gabk": gabk,
"gab_ori": gab_ori,
"pre": pre,
"post": post,
"tails": tails,
"idx_feature": idx_feature,
"comp": comp,
"error": error,
"scale": scale,
"tracked": tracked,
"rem_bad": rem_bad,
"roi": roi,
"run": run,
"pupil": pupil,
}
return specific_params
def reformat_args(args):
"""
reformat_args(args)
Returns reformatted args for analyses, specifically
- Sets stimulus parameters to "none" if they are irrelevant to the
stimtype
- Changes stimulus parameters from "both" to actual values
- Sets seed, though doesn't seed
- Modifies analyses (if "all" or "all_" in parameter)
Adds the following args:
- omit_sess (str): sess to omit
- omit_mice (str): mice to omit
Required args:
- args (Argument parser): parser with the following attributes:
visflow_dir (str) : visual flow direction values to include
(e.g., "right", "left" or "both")
visflow_size (int or str): visual flow size values to include
(e.g., 128, 256, "both")
gabfr (int) : gabor frame value to start sequences at
(e.g., 0, 1, 2, 3)
gabk (int or str) : gabor kappa values to include
(e.g., 4, 16 or "both")
gab_ori (int or str) : gabor orientation values to include
(e.g., 0, 45, 90, 135, 180, 225 or "all")
runtype (str) : runtype ("pilot" or "prod")
stimtype (str) : stimulus to analyse (visflow or gabors)
Returns:
- args (Argument parser): input parser, with the following attributes
modified:
visflow_dir, visflow_size, gabfr, gabk,
gab_ori, grps, analyses, seed
and the following attributes added:
omit_sess, omit_mice
"""
args = copy.deepcopy(args)
[args.visflow_dir, args.visflow_size, args.gabfr, args.gabk,
args.gab_ori] = sess_gen_util.get_params(args.stimtype, args.visflow_dir,
args.visflow_size, args.gabfr,
args.gabk, args.gab_ori)
args.omit_sess, args.omit_mice = sess_gen_util.all_omit(
args.stimtype, args.runtype, args.visflow_dir, args.visflow_size,
args.gabk)
# choose a seed if none is provided (i.e., args.seed=-1), but seed later
args.seed = rand_util.seed_all(args.seed,
"cpu",
log_seed=False,
seed_now=False)
# collect analysis letters
all_analyses = "".join(get_analysis_fcts().keys())
if "all" in args.analyses:
if "_" in args.analyses:
excl = args.analyses.split("_")[1]
args.analyses, _ = gen_util.remove_lett(all_analyses, excl)
else:
args.analyses = all_analyses
elif "_" in args.analyses:
raise ValueError("Use '_' in args.analyses only with 'all'.")
return args
def plot_summ(output, savename, stimtype="gabors", comp="unexp", ctrl=False,
visflow_dir="both", fluor="dff", scale=True, CI=0.95,
plt_bkend=None, fontdir=None, modif=False):
"""
plot_summ(output)
Plots summary data for a specific comparison, for each datatype in a
separate figure and saves figures.
Required args:
- output (str) : general directory in which summary dataframe
is saved (runtype and q1v4 values are inferred from
the directory name)
- savename (str): name of the dataframe containing summary data to plot
Optional args:
- stimtype (str) : stimulus type
default: "gabors"
- comp (str) : type of comparison
default: "unexp"
- ctrl (bool) : if True, control comparisons are analysed
default: False
- visflow_dir (str): visual flow direction
default: "both"
- fluor (str) : fluorescence trace type
default: "dff"
- scale (bool) : whether ROIs are scaled
default: True
- CI (num) : CI for shuffled data
default: 0.95
- plt_bkend (str) : mpl backend to use for plotting (e.g., "agg")
default: None
- fontdir (str) : directory in which additional fonts are located
default: None
- modif (bool) : if True, plots are made in a modified (simplified
way)
default: False
"""
plot_util.manage_mpl(plt_bkend, fontdir=fontdir)
summ_scores_file = Path(output, savename)
if summ_scores_file.is_file():
summ_scores = file_util.loadfile(summ_scores_file)
else:
warnings.warn(f"{summ_scores_file} not found.",
category=RuntimeWarning, stacklevel=1)
return
if len(summ_scores) == 0:
warnings.warn(f"No data in {summ_scores_file}.",
category=RuntimeWarning, stacklevel=1)
return
# drop NaN lines
summ_scores = summ_scores.loc[~summ_scores["epoch_n_mean"].isna()]
data_types = ["epoch_n", "test_acc", "test_acc_bal"]
data_titles = ["Epoch nbrs", "Test accuracy", "Test accuracy (balanced)"]
stats = ["mean", "sem", "sem"]
shuff_stats = ["median"] + math_util.get_percentiles(CI)[1]
q1v4, evu = False, False
if "_q1v4" in str(output):
q1v4 = True
elif "_evu" in str(output):
evu = True
runtype = "prod"
if "pilot" in str(output):
runtype = "pilot"
if stimtype == "gabors":
visflow_dir = "none"
stim_str = "gab"
stim_str_pr = "gabors"
else:
visflow_dir = sess_gen_util.get_params(stimtype, visflow_dir)[0]
if isinstance(visflow_dir, list) and len(visflow_dir) == 2:
visflow_dir = "both"
stim_str = sess_str_util.dir_par_str(visflow_dir, str_type="file")
stim_str_pr = sess_str_util.dir_par_str(visflow_dir, str_type="print")
scale_str = sess_str_util.scale_par_str(scale, "file")
scale_str_pr = sess_str_util.scale_par_str(scale, "file").replace("_", " ")
ctrl_str = sess_str_util.ctrl_par_str(ctrl)
ctrl_str_pr = sess_str_util.ctrl_par_str(ctrl, str_type="print")
modif_str = "_modif" if modif else ""
save_dir = Path(output, f"figures_{fluor}")
save_dir.mkdir(exist_ok=True)
cols = ["scale", "fluor", "visflow_dir", "runtype"]
cri = [scale, fluor, visflow_dir, runtype]
plot_lines = gen_util.get_df_vals(summ_scores, cols, cri)
cri_str = ", ".join([f"{col}: {crit}" for col, crit in zip(cols, cri)])
if len(plot_lines) == 0: # no data
warnings.warn(f"No data found for {cri_str}", category=RuntimeWarning,
stacklevel=1)
return
else: # shuffle or non shuffle missing
skip = False
for shuff in [False, True]:
if shuff not in plot_lines["shuffle"].tolist():
warnings.warn(f"No shuffle={shuff} data found for {cri_str}",
category=RuntimeWarning, stacklevel=1)
skip = True
if skip:
return
for data, data_title in zip(data_types, data_titles):
if not modif:
title = (f"{stim_str_pr.capitalize()} {comp}{ctrl_str_pr} - "
f"{data_title} for log regr on\n" +
u"{} {} ".format(scale_str_pr, fluor) +
f"data ({runtype})")
else:
title = (f"{stim_str_pr.capitalize()} {comp}{ctrl_str_pr}\n"
f"{data_title}")
if "_" in title:
title = title.replace("_", " ")
savename = (f"{data}_{stim_str}_{comp}{ctrl_str}{scale_str}"
f"{modif_str}.svg")
full_savename = Path(save_dir, savename)
plot_data_summ(plot_lines, data, stats, shuff_stats, title,
full_savename, CI, q1v4, evu, comp, modif)
plot_util.cond_close_figs()
def reformat_args(args):
"""
reformat_args(args)
Returns reformatted args for analyses, specifically
- Sets stimulus parameters to "none" if they are irrelevant to the
stimtype
- Changes stimulus parameters from "both" to actual values
- Modifies the session number parameter
- Sets seed, though doesn't seed
- Modifies analyses (if "all" or "all_" in parameter)
- Sets latency parameters based on lat_method
Adds the following args:
- dend (str) : type of dendrites to use ("allen" or "extr")
- omit_sess (str): sess to omit
- omit_mice (str): mice to omit
Required args:
- args (Argument parser): parser with the following attributes:
visflow_dir (str) : visual flow direction values to include
(e.g., "right", "left" or "both")
visflow_size (int or str): visual flow size values to include
(e.g., 128, 256, "both")
gabfr (int) : gabor frame value to start sequences at
(e.g., 0, 1, 2, 3)
gabk (int or str) : gabor kappa values to include
(e.g., 4, 16 or "both")
gab_ori (int or str) : gabor orientation values to include
(e.g., 0, 45, 90, 135, 180, 225 or "all")
mouse_ns (str) : mouse numbers or range
(e.g., 1, "1,3", "1-3", "all")
runtype (str) : runtype ("pilot" or "prod")
sess_n (str) : session number range (e.g., "1-1", "all")
stimtype (str) : stimulus to analyse (visflow or gabors)
Returns:
- args (Argument parser): input parser, with the following attributes
modified:
visflow_dir, visflow_size, gabfr, gabk,
gab_ori, sess_n, mouse_ns, analyses, seed,
lat_p_val_thr, lat_rel_std
and the following attributes added:
omit_sess, omit_mice, dend
"""
args = copy.deepcopy(args)
if args.plane == "soma":
args.dend = "allen"
[args.visflow_dir, args.visflow_size, args.gabfr, args.gabk,
args.gab_ori] = sess_gen_util.get_params(args.stimtype, args.visflow_dir,
args.visflow_size, args.gabfr,
args.gabk, args.gab_ori)
if args.datatype == "run":
args.fluor = "n/a"
if args.plane == "soma":
args.dend = "allen"
args.omit_sess, args.omit_mice = sess_gen_util.all_omit(
args.stimtype, args.runtype, args.visflow_dir, args.visflow_size,
args.gabk)
if "-" in str(args.sess_n):
vals = str(args.sess_n).split("-")
if len(vals) != 2:
raise ValueError(
"If args.sess_n is a range, must have format 1-3.")
st = int(vals[0])
end = int(vals[1]) + 1
args.sess_n = list(range(st, end))
if args.lat_method == "ratio":
args.lat_p_val_thr = None
elif args.lat_method == "ttest":
args.lat_rel_std = None
# choose a seed if none is provided (i.e., args.seed=-1), but seed later
args.seed = rand_util.seed_all(args.seed,
"cpu",
log_seed=False,
seed_now=False)
# collect mouse numbers from args.mouse_ns
if "," in args.mouse_ns:
args.mouse_ns = [int(n) for n in args.mouse_ns.split(",")]
elif "-" in args.mouse_ns:
vals = str(args.mouse_ns).split("-")
if len(vals) != 2:
raise ValueError(
"If args.mouse_ns is a range, must have format 1-3.")
st = int(vals[0])
end = int(vals[1]) + 1
args.mouse_ns = list(range(st, end))
elif args.mouse_ns not in ["all", "any"]:
args.mouse_ns = int(args.mouse_ns)
# collect analysis letters
all_analyses = "".join(get_analysis_fcts().keys())
if "all" in args.analyses:
if "_" in args.analyses:
excl = args.analyses.split("_")[1]
args.analyses, _ = gen_util.remove_lett(all_analyses, excl)
else:
args.analyses = all_analyses
elif "_" in args.analyses:
raise ValueError("Use '_' in args.analyses only with 'all'.")
return args