import sys
import os
join = os.path.join

import numpy as np
import pandas as pd
import datetime

path_to_trackml = os.path.expanduser("~/trackml")
path_to_trackmllib = os.path.join(path_to_trackml, "trackml-library")
sys.path.append(path_to_trackmllib)
from trackml.dataset import load_dataset
from trackml.score import score_event

sys.path.append("..")
import make_candidates
import merge
import score_track

def run():
    print(datetime.datetime.now(), sys.argv[0], " begin")
    
    path_to_input = os.path.join(path_to_trackml, "train_1")
    th1_len = 13
    th2_len = 10
    
    for event_id, hits in load_dataset(path_to_input, parts=["hits"],
                                       skip=0, nevents=1):
        submission0 = pd.read_csv("step0.submission.csv")
        tscore = score_track.score_by_length(submission0, hits)
        outlier_mask = tscore < th1_len
        
        df = submission0[outlier_mask]
        print(submission0.head(10))
        print(df)
        df.to_csv("step{0}_outlier.submission.csv".format(istep-1), index=None)
        df = submission0[~outlier_mask]
        df.to_csv("step{0}_good.submission.csv".format(istep-1), index=None)

    print(datetime.datetime.now(), sys.argv[0], " end")

if __name__=="__main__":
    run()

491bda0726f8d0c66e5c8b8b4eb728f11ae85fde
<mask token>


def run():
    print(datetime.datetime.now(), sys.argv[0], ' begin')
    path_to_input = os.path.join(path_to_trackml, 'train_1')
    th1_len = 13
    th2_len = 10
    for event_id, hits in load_dataset(path_to_input, parts=['hits'], skip=
        0, nevents=1):
        submission0 = pd.read_csv('step0.submission.csv')
        tscore = score_track.score_by_length(submission0, hits)
        outlier_mask = tscore < th1_len
        df = submission0[outlier_mask]
        print(submission0.head(10))
        print(df)
        df.to_csv('step{0}_outlier.submission.csv'.format(istep - 1), index
            =None)
        df = submission0[~outlier_mask]
        df.to_csv('step{0}_good.submission.csv'.format(istep - 1), index=None)
    print(datetime.datetime.now(), sys.argv[0], ' end')


<mask token>

<mask token>
sys.path.append(path_to_trackmllib)
<mask token>
sys.path.append('..')
<mask token>


def run():
    print(datetime.datetime.now(), sys.argv[0], ' begin')
    path_to_input = os.path.join(path_to_trackml, 'train_1')
    th1_len = 13
    th2_len = 10
    for event_id, hits in load_dataset(path_to_input, parts=['hits'], skip=
        0, nevents=1):
        submission0 = pd.read_csv('step0.submission.csv')
        tscore = score_track.score_by_length(submission0, hits)
        outlier_mask = tscore < th1_len
        df = submission0[outlier_mask]
        print(submission0.head(10))
        print(df)
        df.to_csv('step{0}_outlier.submission.csv'.format(istep - 1), index
            =None)
        df = submission0[~outlier_mask]
        df.to_csv('step{0}_good.submission.csv'.format(istep - 1), index=None)
    print(datetime.datetime.now(), sys.argv[0], ' end')


if __name__ == '__main__':
    run()

<mask token>
join = os.path.join
<mask token>
path_to_trackml = os.path.expanduser('~/trackml')
path_to_trackmllib = os.path.join(path_to_trackml, 'trackml-library')
sys.path.append(path_to_trackmllib)
<mask token>
sys.path.append('..')
<mask token>


def run():
    print(datetime.datetime.now(), sys.argv[0], ' begin')
    path_to_input = os.path.join(path_to_trackml, 'train_1')
    th1_len = 13
    th2_len = 10
    for event_id, hits in load_dataset(path_to_input, parts=['hits'], skip=
        0, nevents=1):
        submission0 = pd.read_csv('step0.submission.csv')
        tscore = score_track.score_by_length(submission0, hits)
        outlier_mask = tscore < th1_len
        df = submission0[outlier_mask]
        print(submission0.head(10))
        print(df)
        df.to_csv('step{0}_outlier.submission.csv'.format(istep - 1), index
            =None)
        df = submission0[~outlier_mask]
        df.to_csv('step{0}_good.submission.csv'.format(istep - 1), index=None)
    print(datetime.datetime.now(), sys.argv[0], ' end')


if __name__ == '__main__':
    run()

import sys
import os
join = os.path.join
import numpy as np
import pandas as pd
import datetime
path_to_trackml = os.path.expanduser('~/trackml')
path_to_trackmllib = os.path.join(path_to_trackml, 'trackml-library')
sys.path.append(path_to_trackmllib)
from trackml.dataset import load_dataset
from trackml.score import score_event
sys.path.append('..')
import make_candidates
import merge
import score_track


def run():
    print(datetime.datetime.now(), sys.argv[0], ' begin')
    path_to_input = os.path.join(path_to_trackml, 'train_1')
    th1_len = 13
    th2_len = 10
    for event_id, hits in load_dataset(path_to_input, parts=['hits'], skip=
        0, nevents=1):
        submission0 = pd.read_csv('step0.submission.csv')
        tscore = score_track.score_by_length(submission0, hits)
        outlier_mask = tscore < th1_len
        df = submission0[outlier_mask]
        print(submission0.head(10))
        print(df)
        df.to_csv('step{0}_outlier.submission.csv'.format(istep - 1), index
            =None)
        df = submission0[~outlier_mask]
        df.to_csv('step{0}_good.submission.csv'.format(istep - 1), index=None)
    print(datetime.datetime.now(), sys.argv[0], ' end')


if __name__ == '__main__':
    run()

import sys
import os
join = os.path.join

import numpy as np
import pandas as pd
import datetime

path_to_trackml = os.path.expanduser("~/trackml")
path_to_trackmllib = os.path.join(path_to_trackml, "trackml-library")
sys.path.append(path_to_trackmllib)
from trackml.dataset import load_dataset
from trackml.score import score_event

sys.path.append("..")
import make_candidates
import merge
import score_track

def run():
    print(datetime.datetime.now(), sys.argv[0], " begin")
    
    path_to_input = os.path.join(path_to_trackml, "train_1")
    th1_len = 13
    th2_len = 10
    
    for event_id, hits in load_dataset(path_to_input, parts=["hits"],
                                       skip=0, nevents=1):
        submission0 = pd.read_csv("step0.submission.csv")
        tscore = score_track.score_by_length(submission0, hits)
        outlier_mask = tscore < th1_len
        
        df = submission0[outlier_mask]
        print(submission0.head(10))
        print(df)
        df.to_csv("step{0}_outlier.submission.csv".format(istep-1), index=None)
        df = submission0[~outlier_mask]
        df.to_csv("step{0}_good.submission.csv".format(istep-1), index=None)

    print(datetime.datetime.now(), sys.argv[0], " end")

if __name__=="__main__":
    run()
