from BasicParticipant import *
from Participant import write_features_tsv
from ValidityProcessing import output_Validity_info_Segments, output_percent_discarded, \
output_Validity_info_Participants
ul = [1]
uids = ul
alogoffset = [0]
# Read participants
ps = read_participants_Basic(user_list=ul, pids=uids, log_time_offsets=alogoffset, datadir=params.EYELOGDATAFOLDER,
prune_length=None, require_valid_segs=False, auto_partition_low_quality_segments=True)
# explore_validation_threshold_segments(ps, auto_partition_low_quality_segments = False)
output_Validity_info_Segments(ps, auto_partition_low_quality_segments_flag=False, validity_method=3)
output_percent_discarded(ps, './outputfolder/smi_disc.csv')
output_Validity_info_Segments(ps, auto_partition_low_quality_segments_flag=False, validity_method=2,
threshold_gaps_list=[100, 200, 250, 300], output_file="./outputfolder/tobiiv3_Seg_val.csv")
output_Validity_info_Participants(ps, include_restored_samples=True, auto_partition_low_quality_segments_flag=False)
# WRITE features to file
print "Exporting:\n--General:", params.featurelist
write_features_tsv(ps, './outputfolder/tobiiv3_sample_features.tsv', featurelist=params.featurelist, id_prefix=False)
# Read participants
ps = read_participants_Basic(user_list=ul,
pids=uids,
log_time_offsets=alogoffset,
datadir=params.EYELOGDATAFOLDER,
prune_length=None,
require_valid_segs=False,
auto_partition_low_quality_segments=True)
# explore_validation_threshold_segments(ps, auto_partition_low_quality_segments = False)
output_Validity_info_Segments(ps,
auto_partition_low_quality_segments_flag=False,
validity_method=3)
output_percent_discarded(ps, './outputfolder/smi_disc.csv')
output_Validity_info_Segments(ps,
auto_partition_low_quality_segments_flag=False,
validity_method=2,
threshold_gaps_list=[100, 200, 250, 300],
output_file="./outputfolder/smi_Seg_val.csv")
output_Validity_info_Participants(
ps,
include_restored_samples=True,
auto_partition_low_quality_segments_flag=False)
# WRITE features to file
print "Exporting:\n--General:", params.featurelist
write_features_tsv(ps,
'./outputfolder/smi_sample_features.tsv',
featurelist=params.featurelist,
id_prefix=False)
require_valid_segs = False, auto_partition_low_quality_segments = True,
rpsfile = "./sampledata/all_rest_pupil_sizes.tsv")
print
######
#explore_validation_threshold_segments(ps, auto_partition_low_quality_segments = False)
output_Validity_info_Segments(ps, auto_partition_low_quality_segments_flag = False, validity_method = 3)
output_percent_discarded(ps,'./outputfolder/disc.csv')
output_Validity_info_Segments(ps, auto_partition_low_quality_segments_flag = False, validity_method = 2, threshold_gaps_list = [100, 200, 250, 300],output_file = "./outputfolder/Seg_val.csv")
output_Validity_info_Participants(ps, include_restored_samples =True, auto_partition_low_quality_segments_flag = False)
##### WRITE features to file
print
aoi_feat_names = (map(lambda x:x, params.aoigeneralfeat))
print "exporting:", params.featurelist, "\n", aoi_feat_names
write_features_tsv(ps, './outputfolder/sample_features.tsv',featurelist = params.featurelist, aoifeaturelist=aoi_feat_names, id_prefix = False)
postprocess_composite_AOIs('./outputfolder/sample_features.tsv', params.aoinames, aoi_feat_names)
#print "exporting:", params.featurelist, "\n", aoi_feat_names
#write_features_tsv(ps, './Data/Bar-Radar/outputfolder/sample_features.tsv',featurelist = params.featurelist, aoifeaturelist=aoi_feat_names, id_prefix = False)
#write_features_tsv(ps, './Data/Bar-Radar/outputfolder/sample_sequences.tsv',featurelist = params.aoisequencefeat, aoifeaturelabels=aoi_feat_names, id_prefix = False)
#write_features_tsv(ps, './Data/Bar-Radar/outputfolder/sample_features.tsv',featurelist = params.featurelist, aoifeaturelabels=aoi_feat_lab, id_prefix = False)
#### Export pupil dilations for each scene to a separate file
#print "exporting: pupil dilatoin trends"
#plot_pupil_dilation_all(ps, './outputfolder\\pupilsizes\\', "problem1")
#plot_pupil_dilation_all(ps, './outputfolder\\pupilsizes\\', "problem2")
###### Read participants
ps = read_participants_Basic(user_list = ul,pids = uids, log_time_offsets = alogoffset, datadir=params.EYELOGDATAFOLDER,
prune_length = None,
aoifile = "./sampledata/general.aoi",
# aoifile = "./sampledata/Dynamic_1.aoi",
require_valid_segs = False, auto_partition_low_quality_segments = True,
rpsfile = "./sampledata/all_rest_pupil_sizes.tsv")
print
######
#explore_validation_threshold_segments(ps, auto_partition_low_quality_segments = False)
output_Validity_info_Segments(ps, auto_partition_low_quality_segments_flag = False, validity_method = 3)
output_percent_discarded(ps,'./outputfolder/disc.csv')
output_Validity_info_Segments(ps, auto_partition_low_quality_segments_flag = False, validity_method = 2, threshold_gaps_list = [100, 200, 250, 300],output_file = "./outputfolder/Seg_val.csv")
output_Validity_info_Participants(ps, include_restored_samples =True, auto_partition_low_quality_segments_flag = False)
##### WRITE features to file
print
aoi_feat_names = (map(lambda x:x, params.aoigeneralfeat))
print "Exporting:\n--General:", params.featurelist, "\n--AOI:", aoi_feat_names, "\n--Sequences:", params.aoisequencefeat
write_features_tsv(ps, './outputfolder/sample_features.tsv',featurelist = params.featurelist, aoifeaturelist=aoi_feat_names, id_prefix = False)
##### WRITE AOI sequences to file
write_features_tsv(ps, './outputfolder/sample_sequences.tsv',featurelist = params.aoisequencefeat, aoifeaturelist=aoi_feat_names, id_prefix = False)
#### Export pupil dilations for each scene to a separate file
#print "--pupil dilation trends"
#plot_pupil_dilation_all(ps, './outputfolder/pupilsizes/', "problem1")
#plot_pupil_dilation_all(ps, './outputfolder/pupilsizes/', "problem2")
# aoifile = "./sampledata/Dynamic_1.aoi",
require_valid_segs=False,
auto_partition_low_quality_segments=True)
print
######
#explore_validation_threshold_segments(ps, auto_partition_low_quality_segments = False)
output_Validity_info_Segments(ps,
auto_partition_low_quality_segments_flag=False,
validity_method=3)
output_percent_discarded(ps, './outputfolder/disc.csv')
output_Validity_info_Segments(ps,
auto_partition_low_quality_segments_flag=False,
validity_method=2,
threshold_gaps_list=[100, 200, 250, 300],
output_file="./outputfolder/Seg_val.csv")
output_Validity_info_Participants(
ps,
include_restored_samples=True,
auto_partition_low_quality_segments_flag=False)
##### WRITE features to file
print
aoi_feat_names = (map(lambda x: "Test" + '_' + x, params.aoigeneralfeat))
print "exporting:", params.featurelist, "\n", aoi_feat_names
write_features_tsv(ps,
'./outputfolder/smaple_features.tsv',
featurelist=params.featurelist,
aoifeaturelabels=aoi_feat_names,
id_prefix=False)
###### Read participants
ps = read_participants_Basic_multiprocessing(cpu_count(), user_list = ul,pids = uids, log_time_offsets = alogoffset, datadir=params.EYELOGDATAFOLDER,
prune_length = None,
aoifile = "./sampledata/general.aoi",
# aoifile = "./sampledata/Dynamic_1.aoi",
require_valid_segs = False, auto_partition_low_quality_segments = True,
rpsfile = "./sampledata/all_rest_pupil_sizes.tsv")
print
######
#explore_validation_threshold_segments(ps, auto_partition_low_quality_segments = False)
output_Validity_info_Segments(ps, auto_partition_low_quality_segments_flag = False, validity_method = 3)
output_percent_discarded(ps,'./outputfolder/disc_multiprocessing.csv')
output_Validity_info_Segments(ps, auto_partition_low_quality_segments_flag = False, validity_method = 2, threshold_gaps_list = [100, 200, 250, 300],output_file = "./outputfolder/Seg_val_multiprocessing.csv")
output_Validity_info_Participants(ps, include_restored_samples =True, auto_partition_low_quality_segments_flag = False)
##### WRITE features to file
print
aoi_feat_names = (map(lambda x:x, params.aoigeneralfeat))
print "Exporting:\n--General:", params.featurelist, "\n--AOI:", aoi_feat_names, "\n--Sequences:", params.aoisequencefeat
write_features_tsv(ps, './outputfolder/sample_features_multiprocessing.tsv',featurelist = params.featurelist, aoifeaturelist=aoi_feat_names, id_prefix = False)
##### WRITE AOI sequences to file
write_features_tsv(ps, './outputfolder/sample_sequences_multiprocessing.tsv',featurelist = params.aoisequencefeat, aoifeaturelist=aoi_feat_names, id_prefix = False)
#### Export pupil dilations for each scene to a separate file
#print "--pupil dilation trends"
#plot_pupil_dilation_all(ps, './outputfolder/pupilsizes/', "problem1")
#plot_pupil_dilation_all(ps, './outputfolder/pupilsizes/', "problem2")
use_actions = False, prune_length = None, aoifiles = ['./data/Static_1.aoi','./data/Static_2.aoi','./data/general.aoi'],
require_valid_segs = True, auto_partition_low_quality_segments = True)
print
######
####### READ All Participants
#ps = read_participants_CSP(user_list = ul,pids = uids, log_time_offsets = alogoffset, datadir='./data/',
# use_actions = True,prune_length = None, aoifiles = ['./data/Static_1.aoi','./data/Static_2.aoi','./data/general.aoi'],
# auto_partition_low_quality_segments = True)
#print
#
##### WRITE features to file
write_features_tsv(ps, 'csp_eye.tsv',featurelist = params.featurelist, aoifeaturelabels=params.aoifeaturelist, id_prefix = False)
###### PRINT features on the screen
#fn,fv = export_features_all(ps, featurelist = params.featurelist, aoifeaturelabels=params.aoifeaturelist, id_prefix = False, require_valid = True)
#print fn
#for v in fv:
# print v
######
####### Read participants without action events for validity check
#ps = read_participants_CSP(user_list = ul,pids = uids, log_time_offsets = alogoffset, datadir='./data/',
# use_actions = False, prune_length = None, aoifiles = ['./data/Static_1.aoi','./data/Static_2.aoi','./data/general.aoi'],
# require_valid_segs = False, auto_partition_low_quality_segments = True)
