def main(args, config):
# Unpack out the cfg file into easier names
in_dir = config.get("Setup", "in_dir")
regex_filter = config.get("Setup", "regex_filter")
regex_filter = None if regex_filter == "None" else regex_filter
analysis_flags = json.loads(config.get("Setup", "analysis_flags"))
tetrode_list = json.loads(config.get("Setup", "tetrode_list"))
should_filter = config.getboolean("Setup", "should_filter")
seaborn_style = config.getboolean("Plot", "seaborn_style")
plot_order = json.loads(config.get("Plot", "plot_order"))
fixed_color = config.get("Plot", "path_color")
fixed_color = None if fixed_color == "None" else fixed_color
if len(fixed_color) > 1:
fixed_color = json.loads(fixed_color)
s_color = config.getboolean("Plot", "should_color")
plot_outname = config.get("Plot", "output_dirname")
dot_size = config.get("Plot", "dot_size")
dot_size = None if dot_size == "None" else int(dot_size)
summary_dpi = int(config.get("Plot", "summary_dpi"))
hd_predict = config.getboolean("Plot", "hd_predict")
output_format = config.get("Output", "output_format")
save_bin_data = config.getboolean("Output", "save_bin_data")
output_spaces = config.getboolean("Output", "output_spaces")
opt_end = config.get("Output", "optional_end")
max_units = int(config.get("Setup", "max_units"))
isi_bound = int(config.get("Params", "isi_bound"))
isi_bin_length = int(config.get("Params", "isi_bin_length"))
setup_logging(in_dir)
if output_format == "pdf":
matplotlib.use("pdf")
if seaborn_style:
sns.set(palette="colorblind")
else:
sns.set_style("ticks", {
'axes.spines.right': False,
'axes.spines.top': False
})
# Automatic extraction of files from starting dir onwards
container = NDataContainer(load_on_fly=True)
out_name = container.add_axona_files_from_dir(in_dir,
tetrode_list=tetrode_list,
recursive=True,
re_filter=regex_filter,
verbose=False,
unit_cutoff=(0, max_units))
container.setup()
if len(container) is 0:
print(
"Unable to find any files matching regex {}".format(regex_filter))
exit(-1)
# Show summary of place
if analysis_flags[0]:
place_cell_summary(container,
dpi=summary_dpi,
out_dirname=plot_outname,
filter_place_cells=should_filter,
filter_low_freq=should_filter,
opt_end=opt_end,
base_dir=in_dir,
output_format=output_format,
isi_bound=isi_bound,
isi_bin_length=isi_bin_length,
output=plot_order,
save_data=save_bin_data,
fixed_color=fixed_color,
point_size=dot_size,
color_isi=s_color,
burst_thresh=6,
hd_predict=hd_predict)
plt.close("all")
# Do numerical analysis of bursting
should_plot = analysis_flags[2]
if analysis_flags[1]:
import re
out_name = remove_extension(out_name) + "csv"
out_name = re.sub(r"file_list_", r"cell_stats_", out_name)
print("Computing cell stats to save to {}".format(out_name))
cell_classification_stats(in_dir,
container,
out_name,
should_plot=should_plot,
opt_end=opt_end,
output_spaces=output_spaces)
# Do PCA based analysis
if analysis_flags[3]:
print("Computing pca clustering")
pca_clustering(container, in_dir, opt_end=opt_end, s_color=s_color)
def add_files_from_excel(self, file_loc, unit_sep=" "):
"""
Add filepaths from an excel file.
These should be setup to be in the order:
directory | position file | spike file | unit numbers | eeg extension
Parameters
----------
file_loc : str
Name of the excel file that contains the data specifications
unit_sep : str
Optional separator character for unit numbers, default " "
Returns
-------
excel_info :
The raw info parsed from the excel file for further use
"""
pos_files = []
spike_files = []
units = []
lfp_files = []
to_merge = []
if os.path.exists(file_loc):
excel_info = pd.read_excel(file_loc, index_col=None)
if excel_info.shape[1] % 5 != 0:
logging.error("Incorrect excel file format, it should be:\n" +
"directory | position file | spike file" +
"| unit numbers | eeg extension")
return
# excel_info = excel_info.iloc[:, 1:] # Can be used to remove index
count = 0
for full_row in excel_info.itertuples():
split = [
full_row[i:i + 5] for i in range(1, len(full_row), 5)
if not pd.isna(full_row[i])
]
merge = True if len(split) > 1 else False
merge_list = []
for row in split:
base_dir = row[0]
pos_name = row[1]
tetrode_name = row[2]
if pos_name[-4:] == '.txt':
spat_file = base_dir + os.sep + pos_name
else:
spat_file = base_dir + os.sep + pos_name + '.txt'
spike_file = base_dir + os.sep + tetrode_name
# Load the unit numbers
unit_info = row[3]
if unit_info == "all":
unit_list = "all"
elif isinstance(unit_info, int):
unit_list = unit_info
elif isinstance(unit_info, float):
unit_list = int(unit_info)
else:
unit_list = [
int(x) for x in unit_info.split(" ") if x != ""
]
# Load the lfp
lfp_ext = row[4]
if lfp_ext[0] != ".":
lfp_ext = "." + lfp_ext
spike_name = remove_extension(spike_file, keep_dot=False)
lfp_file = spike_name + lfp_ext
pos_files.append(spat_file)
spike_files.append(spike_file)
lfp_files.append(lfp_file)
units.append(unit_list)
merge_list.append(count)
count += 1
if merge:
to_merge.append(merge_list)
# Complete the file setup based on parsing from the excel file
self.add_all_files(pos_files, spike_files, lfp_files)
self.setup()
self.set_units(units)
for idx, merge_list in enumerate(to_merge):
self.merge(merge_list)
for j in range(idx + 1, len(to_merge)):
to_merge[j] = [
k - len(merge_list) + 1 for k in to_merge[j]
]
return excel_info
else:
logging.error('Excel file does not exist!')
return None