def parse_csv(csv_path: Path):
"""
Parse csv file to return rows for storing
"""
epiweek = int(csv_path.stem)
sub = submission.Submission(csv=csv_path)
n_regions = len(submission.MAP_REGION)
index = {"epiweek": [epiweek] * n_regions, "region": []}
matrices = {
1: np.zeros((n_regions, 131)),
2: np.zeros((n_regions, 131)),
3: np.zeros((n_regions, 131)),
4: np.zeros((n_regions, 131)),
"onset_wk": np.zeros((n_regions, 34)),
"peak_wk": np.zeros((n_regions, 33)),
"peak": np.zeros((n_regions, 131))
}
for idx, item in enumerate(submission.MAP_REGION.items()):
index["region"].append(item[0])
for target in matrices:
# NOTE: The data from ensemble loader uses log values instead of normal
# Here we are using normal values directly
try:
(X, bin_starts) = sub.get_X(item[0], target)
matrices[target][idx, :] = X
except ValueError:
print(
f"Shape error: {X.shape} {target} for region {item[0]} file name : {csv_path}"
)
return [pd.DataFrame(index), matrices]
def diagnose(code, error):
sub = submission.Submission(lexer.begin_lex(code), error)
for poss_error in possible_errors:
detected = poss_error[0](sub)
if detected:
with open('errors/' + detected, "r") as f:
data = f.read()
if poss_error[1]:
line = poss_error[1](sub)
print "Can render"
if line:
print "GOt line - " + line
data = data.replace("<LINE>", line)
else:
print "no line"
data = data.replace(
"""<div style = "margin: 20px;">
<p style="font-family: courier; font-size: 120%; color: #000;">
<span style = "background-color: #ffff99; padding: 10px; border: 1px solid #cc0;">
<LINE>
</span>
</p>
</div>""", "")
return data
if not detected:
return '<pre>' + error + '</pre>'
def loadSubmissionsFromJson(filename):
file = open(filename, 'r')
# Ugh...
lines = file.readlines()
text = u''.join(lines)
# Fix the formatting so the json module understands it
text = "[{}]".format(text[1:-3])
dictSubmissions = json.loads(text)
submissions = []
for dictSubmission in dictSubmissions:
submission = Submissions.Submission()
submission.initFromDict(dictSubmission)
submissions.append(submission)
return submissions
def testDatabase():
db = LikedSavedDatabase('test.db')
testSubmission = Submissions.Submission()
testSubmission.source = "source"
testSubmission.title = "title"
testSubmission.author = "author"
testSubmission.subreddit = "subreddit"
testSubmission.subredditTitle = "subredditTitle"
testSubmission.body = "body"
testSubmission.bodyUrl = "bodyUrl"
testSubmission.postUrl = "postUrl"
db.addSubmission(testSubmission)
dbSubmission = db.getSubmissionsByTitle("title")
dbCollection = db.createCollection("myCollection")
print(dbSubmission[0])
print(dbCollection)
db.addSubmissionToCollection(dbSubmission[0], dbCollection[0])
print(db.getAllSubmissionsInCollection(dbCollection[0]))
def saveRequestedUrls(pipeConnection, urls):
if pipeConnection:
logger.setPipe(pipeConnection)
initialize()
logger.log(
'Attempting to save {} requested urls. This may take several minutes...'
.format(len(urls)))
submissions = []
# Create Submission for each URL
for url in urls:
convertedSubmission = submission.Submission()
convertedSubmission.source = "UserRequested"
convertedSubmission.title = "UserRequested"
convertedSubmission.author = "(Requested by user)"
convertedSubmission.subreddit = "Requested_Downloads"
convertedSubmission.subredditTitle = "Requested Downloads"
convertedSubmission.body = "(Requested by user)"
convertedSubmission.bodyUrl = url
convertedSubmission.postUrl = url
submissions.append(convertedSubmission)
if len(submissions) != len(urls):
logger.log(
'Could not parse {} URLs!'.format(len(urls) - len(submissions)))
unsupportedSubmissions = imageSaver.saveAllImages(
settings.settings['Output_dir'],
submissions,
imgur_auth=imgurDownloader.getImgurAuth(),
only_download_albums=settings.settings['Only_download_albums'],
skip_n_percent_submissions=settings.
settings['Skip_n_percent_submissions'],
soft_retrieve_imgs=settings.settings['Should_soft_retrieve'],
only_important_messages=settings.settings['Only_important_messages'])
logger.log(
'Download finished. Output to \'Requested Downloads\' directory')
if pipeConnection:
logger.log(scriptFinishedSentinel)
pipeConnection.close()
def submissionsFromJsonFiles(jsonFilesToRead):
submissions = []
for filename in jsonFilesToRead:
file = open(filename, 'r')
# Ugh...
lines = file.readlines()
text = u''.join(lines)
# Fix the formatting so the json module understands it
text = "[{}]".format(text[1:-3])
dictSubmissions = json.loads(text)
for dictSubmission in dictSubmissions:
submission = Submissions.Submission()
submission.initFromDict(dictSubmission)
submissions.append(submission)
print("Read {} submissions from file {}".format(
len(dictSubmissions), filename))
totalSubmissions = len(submissions)
return (submissions, totalSubmissions)
def saveRequestedSubmissions(pipeConnection, submissionIds):
if pipeConnection:
logger.setPipe(pipeConnection)
initialize()
logger.log(
'Attempting to save {} requested submissions. This will take several minutes...'
.format(len(submissionIds)))
dbSubmissions = LikedSavedDatabase.db.getSubmissionsByIds(submissionIds)
submissions = []
# Convert from database submissions to Submission
for dbSubmission in dbSubmissions:
convertedSubmission = submission.Submission()
convertedSubmission.initFromDict(dbSubmission)
submissions.append(convertedSubmission)
if len(submissions) != len(submissionIds):
logger.log('Could not find {} submissions in database!'.format(
len(submissionIds) - len(submissions)))
unsupportedSubmissions = imageSaver.saveAllImages(
settings.settings['Output_dir'],
submissions,
imgur_auth=imgurDownloader.getImgurAuth(),
only_download_albums=settings.settings['Only_download_albums'],
skip_n_percent_submissions=settings.
settings['Skip_n_percent_submissions'],
soft_retrieve_imgs=settings.settings['Should_soft_retrieve'],
only_important_messages=settings.settings['Only_important_messages'])
logger.log(
'Download finished. Please refresh the page to see updated entries')
if pipeConnection:
logger.log(scriptFinishedSentinel)
pipeConnection.close()
def main():
# read arguments
input_dir = os.path.abspath(sys.argv[1])
output_dir = os.path.abspath(sys.argv[2])
program_dir = os.path.abspath(sys.argv[3])
submission_dir = os.path.abspath(sys.argv[4])
log_files = list()
# create output dir if not existing
if not os.path.exists(output_dir):
os.makedirs(output_dir)
if VERBOSE:
print("input dir: {}".format(input_dir))
print("output dir: {}".format(output_dir))
print("program dir: {}".format(program_dir))
print("submission dir: {}".format(submission_dir))
print("input content", os.listdir(input_dir))
print("output content", os.listdir(output_dir))
print("program content", os.listdir(program_dir))
print("submission content", os.listdir(submission_dir))
# add proper directories to path
sys.path.append(program_dir)
sys.path.append(submission_dir)
try:
import submission
except ImportError:
raise ImportError(
'The submission folder should contain a file submission.py containing your controler named '
'as the class Submission.')
# Instantiate and run the agents on both validation and test sets (simultaneously)
with open(os.path.abspath(os.path.join(input_dir, "chronic_names.json")),
'r') as f:
chronics = json.load(f)
for i, chronic in enumerate(chronics):
environment = pypownet.environment.RunEnv(
parameters_folder=input_dir,
game_level=chronic["GAME_LEVEL"],
chronic_looping_mode='natural',
start_id=int(chronic["START_ID"]),
game_over_mode=GAME_OVER_MODE)
try:
submitted_controler = submission.Submission(environment)
except:
raise Exception(
'Did not find a class named Submission within submission.py; your submission controler should'
' be a class named Submission in submission.py file directly within the ZIP submission file.'
)
log_path = os.path.abspath(os.path.join(output_dir, 'runner.log'))
print('log file path', log_path)
open(log_path, 'w').close() #what the hek
# Instanciate a runner, that will save the run statistics within the log_path file, to be parsed and processed
# by the scoring program
current_machine_log = "machine_log_" + str(i) + ".json"
log_files.append(current_machine_log)
from runner import Runner
pypownet.runner.Runner = Runner #delete after
phase_runner = pypownet.runner.Runner(
environment,
submitted_controler,
verbose=VERBOSE,
vverbose=VVERBOSE,
level=chronic["GAME_LEVEL"],
log_filepath=log_path,
machinelog_filepath=os.path.abspath(
os.path.join(output_dir, current_machine_log)
)) # vverbose should be False otherwise any one
# can see the testing phase injections and co
phase_runner.ch.setLevel(logging.ERROR)
# Run the planned experiment of this phase with the submitted model
phase_runner.loop(iterations=int(chronic["NUMBER_ITERATIONS"]) - 1)
overall_time_spent = time.time() - overall_start
with open(os.path.abspath(os.path.join(output_dir, 'log_files.json')),
'w') as files:
json.dump(log_files, files)
if VERBOSE:
print("Overall time spent %5.2f sec " % overall_time_spent)
print(word)
pattern_b = map(to_bool, pattern)
hor(pattern_b[0])
vert(pattern_b[1], pattern_b[2], pattern_b[3])
vert(pattern_b[4], pattern_b[5], pattern_b[6])
number = 0
for i in range(0, 4):
if pattern_b[7 + i]:
number += pow(2, i)
print(int(number))
submission = submission.Submission("michael_rollins")
submission.header("Michael Rollins")
six = [1, 1, -1, 1, 1, 1, 1, -1, 1, 1, -1]
three = [1, -1, 1, 1, -1, 1, 1, 1, 1, -1, -1]
one = [-1, -1, 1, -1, -1, 1, -1, 1, -1, -1, -1]
seven_segment(three)
seven_segment(six)
seven_segment(one)
##this assumes you have called your weight matrix "weight_matrix"
submission.section("Weight matrix")
submission.matrix_print("W", weight_matrix)
print("test1")