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probe_alignment_data_io.py
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# -*- coding: utf-8 -*-
"""
Created on Thu Jul 15 17:39:32 2021
@author: svc_ccg
"""
import numpy as np
import os, glob
import json
import logging
import pandas as pd
import time
import json
import re
import urllib.request as request
logging.basicConfig(level=logging.INFO)
class bold_text:
BOLD = '\033[1m'
END = '\033[0m'
def get_exp_day1_session_dir(mouseID, basedir, output=True):
sessions = get_session_dirs(mouseID, basedir, restrictions="exp_only")
return get_session_idx(sessions, idx = 0, output=True)
def get_last_session_directory(mouseID, basedir, output=True):
sessions = get_session_dirs(mouseID, basedir)
return get_session_idx(sessions, idx = -1, output=True)
def get_last_hab_dir(mouseID, basedir, output=True):
sessions = get_session_dirs(mouseID, basedir, restrictions='hab_only')
return get_session_idx(sessions, idx = -1, output=True)
def get_session_idx(sessions, idx = 0, output=True):
session_dates = [s.split('_')[-1] for s in sessions]
sorted_inds = np.argsort(session_dates)
session = sessions[sorted_inds[idx]]
if output:
print('\nUsing session: ' + session)
return session
def get_session_dirs(mouseID, basedir, restrictions=None):
mouseID = str(mouseID)
sessions = glob_file(basedir, '*'+mouseID+'*')
sessions = [s for s in sessions if validate_session_dir(s, restrictions=restrictions)]
if len(sessions) == 0:
print('\n Could not find session directories for mouse {} in {]'.format(mouseID, basedir))
return sessions
def validate_session_dir(d, restrictions=None):
base = os.path.basename(d)
match = re.search('[0-9]{10}_[0-9]{6}_[0-9]{8}', base)
validated = True
if restrictions=='exp_only':
filename = '*surface-image3*'
look_for = os.path.join(d, filename)
if not(len(glob.glob(look_for))):
validated = False
if restrictions=='hab_only':
filename = '*surface-image4*'
look_for = os.path.join(d, filename)
if len(glob.glob(look_for)):
validated = False
return (match is not None) and (validated)
def glob_file(basedir, file_string):
result = []
if isinstance(basedir, list):
for b in basedir:
this_result = glob.glob(os.path.join(b, file_string))
result.extend(this_result)
else:
result = glob.glob(os.path.join(basedir, file_string))
if len(result) == 0:
print('\nCould not find file of format {} '
'in base directory {}'.format(file_string, basedir))
else:
return result
def read_motor_locs_into_dataframe(motor_locs_csv_path):
motor_locs = pd.read_csv(motor_locs_csv_path, header=None, names=['time', 'serialNum', 'x', 'y', 'z', 'relx', 'rely', 'relz'])
motor_locs['time'] = pd.to_datetime(motor_locs['time'])
motor_locs = motor_locs.set_index('time')
return motor_locs
def get_modified_timestamp_from_file(file, date_format='%Y/%m/%d %H:%M:%S'):
#t = os.path.getctime(file)
t = os.path.getmtime(file)
t = time.localtime(t)
t = time.strftime(date_format, t)
return t
def map_newscale_SNs_to_probes(motor_locs):
serial_numbers = motor_locs['serialNum'].unique()
# Known serial number to probe mappings for NP rigs. Update here if new motors are added.
NP0_serialToProbeDict = {' SN32148': 'A', ' SN32142': 'B', ' SN32144':'C', ' SN32149':'D', ' SN32135':'E', ' SN24273':'F'}
NP1_serialToProbeDict = {' SN34027': 'A', ' SN31056': 'B', ' SN32141':'C', ' SN32146':'D', ' SN32139':'E', ' SN32145':'F'}
NP3_serialToProbeDict = {' SN31212': 'A', ' SN34029': 'B', ' SN31058':'C', ' SN24272':'D', ' SN32152':'E', ' SN36800':'F'}
known_serial_to_probe_mapping = {}
[known_serial_to_probe_mapping.update(d) for d in [NP0_serialToProbeDict, NP1_serialToProbeDict, NP3_serialToProbeDict]]
# Grab the probe mapping for all known serial numbers and leave unknown serial numbers unmapped
try:
assert(all([s in known_serial_to_probe_mapping for s in serial_numbers]))
except Exception as e:
unknown = []
for s in serial_numbers:
if s not in known_serial_to_probe_mapping:
unknown.append(s)
known_serial_to_probe_mapping[s] = ''
warning_string = ('\nWARNING: Unknown newscale serial numbers {} encountered, '
'please update serial number dictionary in data_io.py file'.format(unknown))
print(warning_string)
finally:
serialToProbeDict = {s:known_serial_to_probe_mapping[s] for s in serial_numbers}
serialToProbeDict = {k: v for k, v in sorted(serialToProbeDict.items(), key=lambda item: item[1])}
print('\nUsing following mapping between serial numbers and probe IDs: {}'.format(serialToProbeDict))
return serialToProbeDict
def find_tap_coordinates(motor_locs, serialToProbeDict, tap_time):
tap_time = pd.to_datetime(tap_time)
pcoordsDict = {}
for pSN in serialToProbeDict:
pid = serialToProbeDict[pSN]
probe_locs = motor_locs.loc[motor_locs.serialNum==pSN]
probe_locs['relz'] = 6000-probe_locs['relz'] #correct for weird z logging
probe_locs = probe_locs.loc[(probe_locs.index<tap_time)]
closest_motor_log_index = np.argmin(np.abs(probe_locs.index - tap_time))
closest_motor_log = probe_locs.iloc[closest_motor_log_index]
#print('motor time: ', closest_motor_log)
pcoordsDict[pid] = closest_motor_log[['relx', 'rely', 'relz']].to_list()
return {pid: pcoordsDict[pid] for pid in 'ABCDEF' if pid in pcoordsDict}
def get_mouse_rig(mouseID, habituation_directories, raise_error=False):
mouseID = str(mouseID)
last_hab_session = get_last_session_directory(mouseID, habituation_directories, output=False)
platform_json = glob_file(last_hab_session, '*platformD1.json')
with open(platform_json[0]) as f:
data = json.load(f)
suggested_rig = data['rig_id']
return suggested_rig
def verify_mouse_rig(mouseID, habituation_directories, rig, raise_error=False):
suggested_rig = get_mouse_rig(mouseID, habituation_directories, raise_error)
mouseID = str(mouseID)
rig_match = all([c in suggested_rig for c in rig.upper()])
if not rig_match:
err_str = (
'\n WARNING: Rig {} does not match rig {} from last '
'habituation session for mouse {}\n'.format(rig, suggested_rig, mouseID)
)
print(bold_text.BOLD+err_str+
bold_text.END)
if raise_error:
raise(AssertionError(err_str))
else:
print('\nRig id validated: Specified rig matches last habituation session rig\n')
def save_coords(coords, name, save_directory, append_datetime=True):
coords_to_list = {k:list(v) for k,v in coords.items()}
if append_datetime:
now = time.localtime(time.time())
now_str = time.strftime('%Y%m%d%H%M%S', now)
name = name.split('.json')[0]+'_'+now_str+'.json'
save_file = os.path.join(save_directory, name)
with open(save_file, 'w') as f:
json.dump(coords_to_list, f, sort_keys=True, indent=4)
print('\nSaving coordinates to {}'.format(save_file))
def validate_LIMS_points(lims_points, name):
if lims_points is False or len(lims_points)==0:
print('Could not find point on LIMS {}'.format(name))
elif len(lims_points) == 6:
print('6 LIMS points found on {} as expected'.format(name))
else:
print(bold_text.BOLD+'\n WARNING: Found {} points on LIMS '
'{}\n'.format(len(lims_points), name)+bold_text.END)
assert(len(lims_points)==6)
#retrieve pixel coords from CSV
def get_pixel_coords(session_dir):
newscale_csv = glob_file(session_dir, '*areaClassifications.csv')[0]
#print(newscale_csv)
current_csv_df = pd.read_csv(newscale_csv, index_col=False)
coords = current_csv_df.loc[:, ['ISI Pixel Coordinate X', 'ISI Pixel Coordinate Y']]
#y_coords = current_csv_df.loc[:, 'ISI Pixel Coordinate Y']
#print(x_coords, y_coords)
coords = numpify(coords)
return coords
#need to get them in an appropriate array, will have to see what format is best
def make_appropriate_basis_array(array):
num_points = np.shape(array)[0]
#we add ones to account for the shift of the origin
X = np.concatenate((np.ones([num_points,1]), array),1)
return X
def fit_pixel_reticle_params(mouse_num):
reticle_coords = get_isi_coords(mouse_num, line_type='insertion_targets', space_str='reticle_space' )
reticle_coords = numpify_list_of_dicts(reticle_coords)
pixel_coords = get_isi_coords(mouse_num, line_type='insertion_targets', space_str='image_space' )
pixel_coords = numpify_list_of_dicts(pixel_coords)
print(reticle_coords)
print(pixel_coords)
X = make_appropriate_basis_array(pixel_coords)
print(X)
y = reticle_coords#[:, 0]
print('y', y)
#slove the linear system of equations
betaHat = np.linalg.solve(X.T.dot(X), X.T.dot(y))
print(betaHat)
#show that we can recover y from only X
est_y = X.dot(betaHat)
print('est y', est_y)
return betaHat
def numpify(iterable):
if not(type(iterable)==np.ndarray):
iterable = np.array(iterable)
return iterable
def numpify_list_of_dicts(list_of_dicts):
value_list = [list(element.values()) for element in list_of_dicts]
return np.array(value_list)
def get_isi_coords(mouse_num, line_type='insertion_targets', space_str='reticle_space' ):
json_string = request.urlopen("http://lims2/specimens/isi_experiment_details/" + mouse_num + ".json").read()
info = json.loads(json_string)
experiments = info[0]['isi_experiments']
found = False
for exp in experiments:
#print(exp['targets'][line_type])
if exp['targets'][line_type][space_str] is not None:
if found:
raise(AssertionError(f'There are multiple maps with line type {line_type} on them'))
#print('############################################'+str(exp['targets'].keys()))
coords = exp['targets'][line_type][space_str]
found = True
return coords
def pixel_to_reticle(pixel_pts, mouse_num):
R = fit_pixel_reticle_params(mouse_num)
numpify(pixel_pts)
X = make_appropriate_basis_array(pixel_pts)
print(X)
reticle_pt = np.dot(X, R)
return reticle_pt
def mouse_num_from_session_dir(session_dir):
location, dirname = os.path.split(session_dir)
return dirname.split('_')[1]
def get_located_reticle_coords(session_dir):
located_pixel_insertion_coords = get_pixel_coords(session_dir)
mouse_num = mouse_num_from_session_dir(session_dir)
located_reticle_insertion_coords = pixel_to_reticle(located_pixel_insertion_coords, mouse_num)
#located_reticle_insertion_coords = []
#for idx, probe in enumerate('ABCDEF'):
# pixel_pt = located_pixel_insertion_coords[idx]
# located_reticle_insertion_coords.append(pixel_to_reticle(pixel_pt, mouse_num))
#located_reticle_insertion_coords = np.array(located_reticle_insertion_coords)
return located_reticle_insertion_coords
def hab_dir_from_date(mouseID, tap_date, basedir, output=True):
sessions = get_session_dirs(mouseID, basedir, restrictions='hab_only')
return get_session_date(sessions, tap_date, output)
def get_session_date(sessions, date, output=True):
session_dates = [s.split('_')[-1] for s in sessions]
session = sessions[session_dates.index(date)]
if output:
print('\nUsing session: ' + session)
return session