file_name large_stringlengths 4 140 | prefix large_stringlengths 0 12.1k | suffix large_stringlengths 0 12k | middle large_stringlengths 0 7.51k | fim_type large_stringclasses 4
values |
|---|---|---|---|---|
dicer.py | 2, cv2.LINE_AA)
pos_img = np.zeros(shape=[100, 100, 1], dtype=np.uint8)
cv2.imshow('Press any key to exit', grey)
print('Error - stopping')
cv2.waitKey() # Taste drücken, zum beenden
elif GPIO.input(18) == 0 and gpios == True: # Temperaturreais prüfen wenn RPi vorhanden
print('Temperature relay is... | or i in range(5):
ret, frame = cap.read()
#cv2.imwrite('frame.png',frame)
# Bildausschnitte von Würfel und Positionserkennung
y = 160
h = 240
x = 220
w = 240
dice_image = frame[y:y + h, x:x + w]
grey = cv2.cvtColor(dice_image, cv2.COLOR_BGR2GRAY)
#cv2.imshow('input', grey)... | s():
f | identifier_name |
dicer.py | ptime):
GPIO.output(17, GPIO.LOW)
GPIO.output(4, GPIO.HIGH)
time.sleep(steptime)
GPIO.output(4, GPIO.LOW)
time.sleep(steptime)
def step_minus(steptime):
GPIO.output(17, GPIO.HIGH)
GPIO.output(4, GPIO.HIGH)
time.sleep(steptime)
GPIO.output(4, GPIO.LOW)
time.sleep(steptime)
G... | two = all_numbers[1]
three = all_numbers[2]
four = all_numbers[3]
five = all_numbers[4]
six = all_numbers[5]
errorcnt = all_numbers[6]
success_rolls= all_numbers[7]
detector = cv2.SimpleBlobDetector_create(blob_params)
keypoints = detector.detect(image)
img_with_keypoints = cv2.... | identifier_body | |
dicer.py |
log_name = 'log_seite2' # Name der Log Datei (Zusammenfassung der Messreihe): Wird NICHT fortgesetzt
raw_numbers_name = 'raw_seite2' # Name der Datei, in der alle Würfe einzeln gespeichert werden: Wird fortgesetzt
email_header = 'dicer - seite2' # Emailbetreff
darknumbers = False # Dunkle Würfelaugen?
send_email = ... | random_line_split | ||
repository.go | Requested record was not found")
type conflictErr struct {
IDs []string
}
func (e conflictErr) Error() string {
return fmt.Sprintf("Operation failed due to conflicts with: %s", e.IDs)
}
type repository struct {
db *sqlx.DB
closers []io.Closer
listMoodsAsc, listMoodsDesc, findMood, deleteMood, setMood ... |
}
var rec moodRec
err := r.findMood.Get(&rec, struct{ UserID, Name string }{userID, name})
if err == sql.ErrNoRows {
return nil, nil
} else if err != nil {
return nil, fmt.Errorf("getting user mood: %v", err)
}
rec.UserDefined = true
rec.id = rec.IntID
return &rec.Mood, nil
}
func (r *repository) SetMo... | {
// Copy to prevent modifying builtins by the caller
mood := *builtin
return &mood, nil
} | conditional_block |
repository.go | ) error {
if isBuiltin(mood.Name) {
return errBuiltinMood
}
var id int
err := r.setMood.QueryRow(struct {
UserID, Name, Eyes, Tongue string
}{
userID, mood.Name, mood.Eyes, mood.Tongue,
}).Scan(&id)
if err != nil {
return fmt.Errorf("upserting user mood: %v", err)
}
if id == 0 {
return fmt.Errorf("u... | sortAsc | identifier_name | |
repository.go | ood(userID string, mood *Mood) error {
if isBuiltin(mood.Name) {
return errBuiltinMood
}
var id int
err := r.setMood.QueryRow(struct {
UserID, Name, Eyes, Tongue string
}{
userID, mood.Name, mood.Eyes, mood.Tongue,
}).Scan(&id)
if err != nil {
return fmt.Errorf("upserting user mood: %v", err)
}
if id ... | random_line_split | ||
repository.go | },
{"borg", "==", " ", false, 0},
{"dead", "xx", "U ", false, 0},
{"greedy", "$$", " ", false, 0},
{"stoned", "**", "U ", false, 0},
{"tired", "--", " ", false, 0},
{"wired", "OO", " ", false, 0},
{"young", "..", " ", false, 0},
}
type moodRec struct {
IntID int
Mood
}
type lineRec struct {
Eyes, Tongu... | {
if isBuiltin(name) {
return errBuiltinMood
}
queryArgs := struct{ UserID, Name string }{userID, name}
if err := doDelete(r.deleteMood, queryArgs); err != nil {
if dbErr, ok := err.(*pq.Error); !ok || dbErr.Code != dbErrFKViolation {
return err
}
// List the lines that are preventing us from deleting ... | identifier_body | |
The Movies Database.py |
#tmdb_movies = sc.textFile('tmdb_5000_movies.csv')
tmdb_movies = sc.textFile(sys.argv[1], 1)
#Remove header and split data
header = tmdb_movies.first()
#Split by , followed by non-whitespace
regex = re.compile(',(?=\\S)')
tmdb_movies = tmdb_movies.filter(lambda x: x != header).map(lambda x: regex.split(x))
print('N... | if (float(p[0])>0 and float(p[8])>0 and float(p[12])>0 and float(p[13])>0 and float(p[18])>0):
if (len(p[1])>2 and len(p[9])>2):
return p | conditional_block | |
The Movies Database.py | 2]),
# Profit(x[12]-x[0]), Runtime(x[13]), Average Rating(x[18]))
tmdb_movies_filtered = tmdb_movies_filtered.map(lambda x: (x[6], float(x[0]), genre(x[1]), float(x[8]),
datetime.strptime(x[11], '%Y-%m-%d'),
... | # Revenue(x[5])
# Profit (x[6])
# Runtime(x[7])
# Average Rating(x[8])
## Top 10 Most Profitable Movie Titles
profit_title = tmdb_movies_filtered.map(lambda x: (x[0], x[6])).\
reduceByKey(add)
profit_title_top = profit_title.top(20, lambda x: x[1])
print('Titles sorted based on Pro... | # Popularity(x[3])
# Release Date(x[4]) | random_line_split |
The Movies Database.py | x[1], (x[0], 1))).\
reduceByKey(lambda x,y: (x[0]+y[0], x[1]+y[1])).\
map(lambda x: (x[0], round(x[1][0]/x[1][1],2)))
avgRating_genre_top = avgRating_genre.top(20, lambda x: x[1])
print('Genres sorted based on Average Rating:', avgRating_genre_top)
x = [i[0] for i in avgRating_g... | return LabeledPoint(line[0], line[1]) | identifier_body | |
The Movies Database.py | flatMapValues(lambda x: x).\
map(lambda x: (x[1], (x[0], 1))).\
reduceByKey(lambda x,y: (x[0]+y[0], x[1]+y[1])).\
map(lambda x: (x[0], round(x[1][0]/x[1][1],2)))
avgRating_genre_top = avgRating_genre.top(20, lambda x: x[1])
print('Genres sorted based on Averag... | parsePoint | identifier_name | |
network.py |
stdout_handler = logging.StreamHandler(sys.stdout)
stdout_handler.setFormatter(formatter)
logger.addHandler(stdout_handler)
def train_emnist(u_epochs):
#######################################################
################### Network setup #####################
# batch_size - Number of images given to ... |
trainData = trainData.astype("float32")
testData = testData.astype("float32")
trainData /= 255
testData /= 255
logger.debug("[INFO] after re-shape")
# print new shape
logger.debug("[INFO] train data shape: {}".format(trainData.shape))
logger.debug("[INFO] test data shape: {}".format(t... | epochs = u_epochs
n_classes = 62
batch_size = 256
train_size = 697932
test_size = 116323
v_length = 784
# split the emnist data into train and test
trainData, trainLabels = emnist.extract_training_samples('byclass')
testData, testLabels = emnist.extract_test_samples('byclass')
# p... | identifier_body |
network.py |
stdout_handler = logging.StreamHandler(sys.stdout)
stdout_handler.setFormatter(formatter)
logger.addHandler(stdout_handler)
def | (u_epochs):
#######################################################
################### Network setup #####################
# batch_size - Number of images given to the model at a particular instance
# v_length - Dimension of flattened input image size i.e. if input image size is [28x28], then v_length... | train_emnist | identifier_name |
network.py | verbose=2)
# print the history keys
logger.debug(history.history.keys())
# evaluate the model
scores = model.evaluate(testData, mTestLabels, verbose=0)
# history plot for accuracy
plt.plot(history.history["accuracy"])
plt.plot(history.history["val_accuracy"])
plt.title("Model Ac... | original_img = test_image
# reshape the test image to [1x784] format so that our model understands
test_image = test_image.reshape(1, 784)
# make prediction on test image using our trained model
prediction = model.predict_classes(test_image, verbose=0)
plate_pre... | conditional_block | |
network.py |
stdout_handler = logging.StreamHandler(sys.stdout)
stdout_handler.setFormatter(formatter)
logger.addHandler(stdout_handler)
def train_emnist(u_epochs):
#######################################################
################### Network setup #####################
# batch_size - Number of images given to ... |
# params: 1- mlmodel, 2- root path to the prediction imgs, 3- how many imgs we have in imgs_path
def identify_plate(model, imgs_path, test_size):
# EMNIST output infos as numbers, so I created a label dict, so it will output it respective class
label_value = {'0':'0', '1':'1', '2':'2', '3':'3', '4':'4', '5':' | plt.subplot(220+i)
plt.imshow(org_image, cmap=plt.get_cmap('gray'))
logger.debug('Press Q to close')
plt.show() | random_line_split |
HOG_SVM_FaceDetection.py | detector was trained. If you are building a webcam or selfie application that uses face detection, you can significantly improve speed by resizing the image to the appropriate size.
#
# ## <font style = "color:rgb(50,120,229)">Classifying a patch</font>
#
# From the previous subsection, we know many patches of the... | der, classLabel):
#change image sizes to match
width = 128
height = 128
dim = (width, height)
images = []
labels = []
imagePaths = getImagePaths(folder, ['.jpg', '.png', '.jpeg'])
for imagePath in imagePaths:
# print(imagePath)
im = cv2.imread(imagePath, cv2.IMREAD_COLOR)
resized = cv2.re... | ataset(fol | identifier_name |
HOG_SVM_FaceDetection.py | this is a good idea.
# In[158]:
# ================================ Query Model =============================================
# Run object detector on a query image to find pedestrians
# We will load the model again and test the model
# This is just to explain how to load an SVM model
# You can use the model directl... | #
# 1. [https://lear.inrialpes.fr/people/triggs/pubs/Dalal-cvpr05.pdf](https://lear.inrialpes.fr/people/triggs/pubs/Dalal-cvpr05.pdf)
#
# 3. [https://en.wikipedia.org/wiki/Support_vector_machine](https://en.wikipedia.org/wiki/Support_vector_machine) | random_line_split | |
HOG_SVM_FaceDetection.py | object detector was trained. If you are building a webcam or selfie application that uses face detection, you can significantly improve speed by resizing the image to the appropriate size.
#
# ## <font style = "color:rgb(50,120,229)">Classifying a patch</font>
#
# From the previous subsection, we know many patches... | eturn imagePaths
#change image sizes to match
width = 128
height = 128
dim = (width, height)
# read images in a folder
# return list of images and labels
def getDataset(folder, classLabel):
#change image sizes to match
width = 128
height = 128
dim = (width, height)
images = []
labels = []
imagePaths ... | h = os.path.join(folder, x)
if os.path.splitext(xPath)[1] in imgExts:
imagePaths.append(xPath)
r | conditional_block |
HOG_SVM_FaceDetection.py | object detector was trained. If you are building a webcam or selfie application that uses face detection, you can significantly improve speed by resizing the image to the appropriate size.
#
# ## <font style = "color:rgb(50,120,229)">Classifying a patch</font>
#
# From the previous subsection, we know many patches... | redict labels for given samples
def svmPredict(model, samples):
return model.predict(samples)[1]
# evaluate a model by comparing
# predicted labels and ground truth
def svmEvaluate(model, samples, labels):
labels = labels[:, np.newaxis]
pred = model.predict(samples)[1]
correct = np.sum((labels == pred))
err... | train(samples, cv2.ml.ROW_SAMPLE, labels)
# p | identifier_body |
cli.py | publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PR... | expose_value=False, is_eager=True)
@click.option('--license', '--lic', is_flag=True, callback=show_license,
expose_value=False, is_eager=True)
def cli():
""" 🗲 Zap: A command line interface to install appimages"""
pass
@cli.command('install')
@click.argument('appname')
@click.opti... | ctx.exit()
@click.group()
@click.option('--version', is_flag=True, callback=show_version, | random_line_split |
cli.py | publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PR... | elif p_url.netloc == 'remove':
z.remove()
else:
print("Invalid url")
@cli.command()
@click.argument('appname')
def get_md5(appname):
"""Get md5 of an appimage"""
z = Zap(appname)
z.get_md5()
@cli.command()
@click.argument('appname')
def is_integrated(appname):
"""Checks if appi... | nt(tag, asset_id)
z.install(tag_name=tag,
download_file_in_tag=asset_id,
downloader=gtk_zap_downloader, always_proceed=True)
| conditional_block |
cli.py | publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PR... |
"""Upgrade all appimages using AppImageUpdate"""
config = ConfigManager()
apps = config['apps']
for i, app in progressbar(enumerate(apps), redirect_stdout=True):
z = Zap(app)
if i == 0:
z.update(show_spinner=False)
else:
z.update(check_appimage_update=Fal... | rade(): | identifier_name |
cli.py | publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PR... | @cli.command()
@click.argument('appname')
def is_integrated(appname):
"""Checks if appimage is integrated with the desktop"""
z = Zap(appname)
z.is_integrated()
@cli.command('list')
def ls():
"""Lists all the appimages"""
cfgmgr = ConfigManager()
apps = cfgmgr['apps']
for i in apps:
... | Get md5 of an appimage"""
z = Zap(appname)
z.get_md5()
| identifier_body |
cmpH5Sort.py | keys() for x in alnGroups]
uPulseDatasets = reduce(lambda x,y: set.union(set(x), set(y)), pulseDatasets)
if (not all(map(lambda x : set(x) == uPulseDatasets, pulseDatasets))):
log.error("All alignment groups need to have the same datasets.")
raise Exception("Can only repack cmp.h5 files with con... |
def write(self, msg, level):
if (self.level >= level): sys.stderr.write(str(msg) + "\n | self.level = level | identifier_body |
cmpH5Sort.py | keys() for x in alnGroups]
uPulseDatasets = reduce(lambda x,y: set.union(set(x), set(y)), pulseDatasets)
if (not all(map(lambda x : set(x) == uPulseDatasets, pulseDatasets))):
log.error("All alignment groups need to have the same datasets.")
raise Exception("Can only repack cmp.h5 files with con... | (inFile, outFile, deep, jobs, log):
"""
This routine takes a cmp.h5 file and sorts the AlignmentIndex
table adding two additional columns for fast access. In addition,
a new top-level attribute is added to the indicate that the file
has been sorted, as well as a table to indicate the blocks of the
... | sortCmpH5 | identifier_name |
cmpH5Sort.py | End = currentStart, currentStart + totalSizes[readIdx]
newDS[gStart:gEnd] = getDataset(read, pulseDataset)[read[format.OFFSET_BEGIN]:read[format.OFFSET_END]]
currentStart = gEnd + 1
newGroup.create_dataset(pulseDataset, data = newDS, dtype = uPDAndType[pulseDataset], maxshape... | cmpH5 = CmpH5Factory.factory.create(outfile, 'a')
cmpH5.log("cmpH5Sort.py", __VERSION__, str(datetime.datetime.now()), ' '.join(sys.argv), "Sorting")
cmpH5.close()
if (len(args) < 2):
shutil.copyfile(outfile, infile)
ofile.close()
exit(0) | conditional_block | |
cmpH5Sort.py | keys() for x in alnGroups]
uPulseDatasets = reduce(lambda x,y: set.union(set(x), set(y)), pulseDatasets)
if (not all(map(lambda x : set(x) == uPulseDatasets, pulseDatasets))):
log.error("All alignment groups need to have the same datasets.")
raise Exception("Can only repack cmp.h5 files with con... | ## Don't really have to do anything if there are no references
## which aligned.
if (lRow == fRow):
continue
## Make a new Group.
newGroup = getRefGroup(offsets[row, 0]).create_group(SORTED)
log.msg("Created new read group: %s" % SORTED)
## Go throu... |
fRow = int(offsets[row, 1])
lRow = int(offsets[row, 2])
| random_line_split |
main.rs | impl TypeMapKey for db::MyDbContext {
type Value = db::MyDbContext;
}
impl TypeMapKey for autopanic::Gramma {
type Value = autopanic::Gramma;
}
struct Handler;
#[async_trait]
impl EventHandler for Handler {
async fn guild_create(&self, ctx: Context, guild: Guild, is_new: bool) {
let mut data = ct... | (ctx: &Context, msg: &Message, error: DispatchError) {
if let DispatchError::Ratelimited(info) = error {
// We notify them only once.
if info.is_first_try {
let _ = msg
.channel_id
.say(
&ctx.http,
&format!("Try this... | dispatch_error | identifier_name |
main.rs | impl TypeMapKey for db::MyDbContext {
type Value = db::MyDbContext;
}
impl TypeMapKey for autopanic::Gramma {
type Value = autopanic::Gramma;
}
struct Handler;
#[async_trait]
impl EventHandler for Handler {
async fn guild_create(&self, ctx: Context, guild: Guild, is_new: bool) {
let mut data = ct... | else {
Some(out)
}
}
async fn greet_new_guild(ctx: &Context, guild: &Guild) {
println!("h");
if let Some(channelvec) = better_default_channel(guild, UserId(802019556801511424_u64)).await {
println!("i");
for channel in channelvec {
println!("{}", channel.name);
... | {
None
} | conditional_block |
main.rs | impl TypeMapKey for db::MyDbContext {
type Value = db::MyDbContext;
}
impl TypeMapKey for autopanic::Gramma {
type Value = autopanic::Gramma;
}
struct Handler;
#[async_trait]
impl EventHandler for Handler {
async fn guild_create(&self, ctx: Context, guild: Guild, is_new: bool) {
let mut data = ct... | pub async fn better_default_channel(guild: &Guild, uid: UserId) -> Option<Vec<&GuildChannel>> {
let member = guild.members.get(&uid)?;
let mut out = vec![];
for channel in guild.channels.values() {
if channel.kind == ChannelType::Text
&& guild
.user_permissions_in(channe... | random_line_split | |
charisma.js | + '<p><b>消息内容：</b>' + obj.guid + '</p>'
+ content;
$('#confirm #txt').html(content);
url = js_getEntry(_project_title, 'Message', 'ajaxdel?guid=' + id);
$('#confirm #btn-submit').attr('data-url', url);
});
$('#confirm #btn-submit').live('click', function(e){
e.preventDefault();
url = $... | 'span10');
}
//highlight current / active link
$('ul.main-menu li a').each(function(){
if($($(this))[0].href==String(window.location))
$(this).parent().addClass('active');
});
//establish history variables
var
History = window.History, // Note: We are using a capital H instead of a lower h
State... | removeClass( | identifier_name |
charisma.js | i += 1)
d1.push([i, parseInt(Math.random() * 30)]);
var d2 = [];
for (var i = 0; i <= 10; i += 1)
d2.push([i, parseInt(Math.random() * 30)]);
var d3 = [];
for (var i = 0; i <= 10; i += 1)
d3.push([i, parseInt(Math.random() * 30)]);
var stack = 0, bars = true, lines = false, steps = false;
funct... | }
if ( oPaging.iPage === oPaging.iTotalPages-1 || oPaging.iTotalPages === 0 ) {
$('li:last', an[i]).addClass('disabled');
} else { | random_line_split | |
charisma.js | });
$('#addBoard').click(function(e){
e.preventDefault();
$('#myModal1').modal('show');
});
$('#addServer').click(function(e){
e.preventDefault();
$('#myModal2').modal('show');
});
$('.modifyBoard').click(function(e){
e.preventDefault();
var srctxt = $(this).attr('data-json');
var txt = '[' +... | }
// we use an inline data source in the example, usually data would
// be fetched from a server
var data = [], totalPoints = 300;
function getRandomData() {
if (data.length > 0)
data = data.slice(1);
| identifier_body | |
api_op_CreateRoute.go | 192.0.2.3 , and the route table includes the following two IPv4
// routes:
// - 192.0.2.0/24 (goes to some target A)
// - 192.0.2.0/28 (goes to some target B)
//
// Both routes apply to the traffic destined for 192.0.2.3 . However, the second
// route in the list covers a smaller number of IP addresses and is ther... |
func (m *opCreateRouteResolveEndpointMiddleware) HandleSerialize(ctx context.Context, in middleware.SerializeInput, next middleware.SerializeHandler) (
out middleware.SerializeOutput, metadata middleware.Metadata, err error,
) {
if awsmiddleware.GetRequiresLegacyEndpoints(ctx) {
return next.HandleSerialize(ctx, i... | {
return "ResolveEndpointV2"
} | identifier_body |
api_op_CreateRoute.go | address 192.0.2.3 , and the route table includes the following two IPv4
// routes:
// - 192.0.2.0/24 (goes to some target A)
// - 192.0.2.0/28 (goes to some target B)
//
// Both routes apply to the traffic destined for 192.0.2.3 . However, the second
// route in the list covers a smaller number of IP addresses and... | for k := range resolvedEndpoint.Headers {
req.Header.Set(
k,
resolvedEndpoint.Headers.Get(k),
)
}
authSchemes, err := internalauth.GetAuthenticationSchemes(&resolvedEndpoint.Properties)
if err != nil {
var nfe *internalauth.NoAuthenticationSchemesFoundError
if errors.As(err, &nfe) {
// if no auth ... | req.URL = &resolvedEndpoint.URI
| random_line_split |
api_op_CreateRoute.go | 192.0.2.3 , and the route table includes the following two IPv4
// routes:
// - 192.0.2.0/24 (goes to some target A)
// - 192.0.2.0/28 (goes to some target B)
//
// Both routes apply to the traffic destined for 192.0.2.3 . However, the second
// route in the list covers a smaller number of IP addresses and is ther... | else {
signingName = *v4Scheme.Sign | {
signingName = "ec2"
} | conditional_block |
api_op_CreateRoute.go | 192.0.2.3 , and the route table includes the following two IPv4
// routes:
// - 192.0.2.0/24 (goes to some target A)
// - 192.0.2.0/28 (goes to some target B)
//
// Both routes apply to the traffic destined for 192.0.2.3 . However, the second
// route in the list covers a smaller number of IP addresses and is ther... | (stack *middleware.Stack, options Options) (err error) {
err = stack.Serialize.Add(&awsEc2query_serializeOpCreateRoute{}, middleware.After)
if err != nil {
return err
}
err = stack.Deserialize.Add(&awsEc2query_deserializeOpCreateRoute{}, middleware.After)
if err != nil {
return err
}
if err = addlegacyEndpoi... | addOperationCreateRouteMiddlewares | identifier_name |
irc_comm.rs | msg: S2,
) -> Result<Option<LibReaction<Message>>>
where
S1: Borrow<str>,
S2: Display,
| ));
Ok(())
})?;
}
match wrapped_msg.len() {
0 => Ok(None),
1 => Ok(Some(wrapped_msg.remove(0))),
_ => Ok(Some(LibReaction::Multi(wrapped_msg.into_vec()))),
}
}
fn compose_msgs<S1, S2, M>(
&self,
... | {
let final_msg = format!(
"{}{}{}",
addressee.borrow(),
if addressee.borrow().is_empty() {
""
} else {
&self.addressee_suffix
},
msg,
);
info!("Sending message to {:?}: {:?}", dest, final_ms... | identifier_body |
irc_comm.rs | msg: S2,
) -> Result<Option<LibReaction<Message>>>
where
S1: Borrow<str>,
S2: Display,
{
let final_msg = format!(
"{}{}{}",
addressee.borrow(),
if addressee.borrow().is_empty() {
""
} else {
&self.addres... | <'a>(msg: Option<Cow<'a, str>>) -> LibReaction<Message> {
let quit = aatxe::Command::QUIT(
msg.map(Cow::into_owned)
.or_else(|| Some(pkg_info::BRIEF_CREDITS_STRING.clone())),
).into();
LibReaction::RawMsg(quit)
}
pub(super) fn handle_msg(
state: &Arc<State>,
server_id: ServerId... | mk_quit | identifier_name |
irc_comm.rs | msg: S2,
) -> Result<Option<LibReaction<Message>>>
where
S1: Borrow<str>,
S2: Display,
{
let final_msg = format!(
"{}{}{}",
addressee.borrow(),
if addressee.borrow().is_empty() {
""
} else {
&self... | state: | random_line_split | |
irc_comm.rs | msg: S2,
) -> Result<Option<LibReaction<Message>>>
where
S1: Borrow<str>,
S2: Display,
{
let final_msg = format!(
"{}{}{}",
addressee.borrow(),
if addressee.borrow().is_empty() {
""
} else {
&self.addres... |
_ => Ok(()),
}
}
fn handle_privmsg(
state | {
push_to_outbox(outbox, server_id, handle_004(state, server_id)?);
Ok(())
} | conditional_block |
wechat_mp.go | Config struct {
AppId string `json:"app_id"` // 公众号appId
AppSecret string `json:"app_secret"` // 公众号appSecret
Token string `json:"token"` // 公众号Token
EncodingAESKey string `json:"encoding_aes_key,omitempty"` // 公众号EncodingAESKey
}
... | ck := CheckWechatAuthSign(msg_signature, timestamp, nonce, wm.Configure.Token, msgEncryptRequest.Encrypt)
var message []byte
if check {
// 验证成功，解密消息，返回正文的二进制数组格式
message, err = wm.aesDecryptMessage(msgEncryptRequest.Encrypt)
if err != nil {
fmt.Fprintf(common.WechatErrorLoggerWriter, "checkMessageSourc... | st
if err = xml.Unmarshal(body, &msgEncryptRequest); err != nil {
fmt.Fprintf(common.WechatErrorLoggerWriter, "checkMessageSource xml.Unmarshal(body, &msgEncryptBody) error: %+v\n", err)
return false, nil
}
che | identifier_body |
wechat_mp.go | checkWechatSource(r *http.Request) bool {
timestamp := r.FormValue(WechatRequestTimestamp)
nonce := r.FormValue(WechatRequestNonce)
signature := r.FormValue(WechatRequestSignature)
return CheckWechatAuthSign(signature, wm.Configure.Token, timestamp, nonce)
}
// 检验消息来源，并且提取消息
func (wm *WechatMp) checkMessageSource... | identifier_name | ||
wechat_mp.go | 微信公众号服务器配置，并开启后，微信会发送一次认证请求，此函数即做此验证用
func (wm *WechatMp) AuthWechatServer(r *http.Request) string {
echostr := r.FormValue(WechatRequestEchostr)
if wm.checkWechatSource(r) {
return echostr
}
return WechatResponseStringInvalid
}
// 检验认证来源是否为微信
func (wm *WechatMp) checkWechatSource(r *http.Request) bool {
timest... | SetTextHandlerFunc(handlerFunc TextMessageHandlerFunc) {
wm.TextMessageHandler = handlerFunc
}
// 设置处理微信image消息事件方法
func (wm *WechatMp) SetImageHand | conditional_block | |
wechat_mp.go | MpConfig struct {
AppId string `json:"app_id"` // 公众号appId
AppSecret string `json:"app_secret"` // 公众号appSecret
Token string `json:"token"` // 公众号Token
EncodingAESKey string `json:"encoding_aes_key,omitempty"` // 公众号EncodingAESKey
... | // 如果消息未加密
signature := r.FormValue(WechatRequestSignature)
return CheckWechatAuthSign(signature, wm.Configure.Token, timestamp, nonce), body
}
// 加密后的微信消息结构
type MsgEncryptRequest struct {
XMLName xml.Name `xml:"xml"`
ToUserName string // 开发者微信号
Encrypt string // 加密的消息正文
}
// 响应加密消息的结构
type MsgEncryp... | }
return check, message
} | random_line_split |
utils.py | '''
Image with dicome attribute [0028,0004] == MONOCHROME1 needs to
be inverted. Otherwise, our way to detect the knee will not work.
:param image_array:
:return:
'''
print('Invert Monochrome ')
print(image_array.shape, np.mean(image_array), np.min(image_array), np.max(image_array))
... | if row_start < 0 or row_end > (image_array.shape[0] - 1):
row_start = round(image_array.shape[0] / 2) - 512
row_end = round(image_array.shape[0] / 2) + 512
#print('Row Indices Final: ', row_start, row_end)
# For right knee, crop columns to be centered at the maximum sum of the LHS of origi... | '''
Extrack knee part from image array
:param image_array:
:param side: 0: left knee; 1: right knee
:param offset: if does not work, you can manually change the shape
:return:
'''
#print('Dimensions of image: ', image_array.shape)
# Compute the sum of each row and column
col_sums = ... | identifier_body |
utils.py | after_y)),'constant'),before_x,before_y
def global_contrast_normalization_oulu(img,lim1,multiplier = 255):
'''
This part is taken from oulu's lab. This how they did global contrast normalization.
:param img:
:param lim1:
:param multiplier:
:return:
'''
img -= lim1
img /= img.max()
... | if -1 in bbox: # if the algorithm says there is no knee in the figure.
return None,None
# process_xray | random_line_split | |
utils.py | '''
Image with dicome attribute [0028,0004] == MONOCHROME1 needs to
be inverted. Otherwise, our way to detect the knee will not work.
:param image_array:
:return:
'''
print('Invert Monochrome ')
print(image_array.shape, np.mean(image_array), np.min(image_array), np.max(image_array))
# ... | (image_dicom, scaling_factor=0.2):
'''
Obtain fixed resolution from image dicom
:param image_dicom:
:param scaling_factor:
:return:
'''
print('Obtain Fix Resolution:')
image_array = image_dicom.pixel_array
print(image_array.shape,np.mean(image_array),np.min(image_array),np.max(image_... | interpolate_resolution | identifier_name |
utils.py | '''
Image with dicome attribute [0028,0004] == MONOCHROME1 needs to
be inverted. Otherwise, our way to detect the knee will not work.
:param image_array:
:return:
'''
print('Invert Monochrome ')
print(image_array.shape, np.mean(image_array), np.min(image_array), np.max(image_array))
... |
else:
before_x,after_x = 0,0
if y_padding > 0:
before_y,after_y = y_padding // 2, y_padding - y_padding // 2
else:
before_y,after_y = 0,0
return np.pad(img,((before_x,after_x),(before_y,after_y)),'constant'),before_x,before_y
def global_contrast_normalization_oulu(img,lim1,mult... | before_x,after_x = x_padding // 2, x_padding - x_padding // 2 | conditional_block |
Assignment 3 notes.py | = (ScimEn.merge(energy, on='Country')
.merge(GDP, on='Country'))
energy[energy['Country'].str.contains('United')]
GDP[GDP['Country'].str.contains('United')]
sub_str = {'^([^\d\(]+).*' : r'\1'}
en2 = energy.iloc[232].replace(to_replace={'Country' : sub_str}, )
energy[energy['Country'].str.contains('Un... | """ Terribly ugly solution, but it works """ | random_line_split | |
Assignment 3 notes.py | ,7,6,14,37,32,7,8,8,18,7,5,11,17,7,7,8,14,16,4,7,6,13,16,5,6,7,7,5,9,6,9,7,10,4,9,8,6,13,6,5,8,7,7,5,9,4,4,7,11,6,5,7,5,6,6,10,5,8,6,10,32,6,7,7,7,5,13,9,10,10,6,8,8,4,5,16,10,10,9,6,10,8,10,10,7,10,7,7,5,5,11,13,11,9,5,7,4,24,6,4,8,5,6,16,8,4,11,6,8,11,5,11,19,7,7,18,6,12,21,11,25,32,5,21,12,7,6,10,12,9,12,8,8,15,7,12... | return res
print(test_gdp(GDP['Country']))
"""
# Alternative merge strategy
# merge the first two, then the third in the requested order
merged2 = pd.merge(ScimEn, energy, how='inner', left_index=True, right_index=True)
merged3 = pd.merge(merged2, GDP, how='inner', left_index=True, right_index=True)
result = (Sci... | s += '\nMismatched countries:\n'
mismatch = GDP.loc[GDP['tested'] != (GDP['actual']), [
'original', 'Country', 'tested', 'actual']].values.tolist()
res += '\n'.join('"{:}" miss-cleaned as "{:}"'.format(o, r)
for o, r, s, v in mismatch)
| conditional_block |
Assignment 3 notes.py | ():
# get the dataframes; all indexed to
energy = read_and_clean_energy_dataframe()
GDP = read_and_clean_GDP_dataframe()
ScimEn = read_and_clean_ScimEn_dataframe()
# merge sequence to get columns in the requested order
result = ScimEn.merge(energy, on='Country').merge(GDP, on='Country')
... | answer_one | identifier_name | |
Assignment 3 notes.py | 1,7,16,9,7,5,7,8,14,40,7,4,6,13,21,5,14,7,5,9,6,11,13,17,6,7,9,9,4,6,11,9,8,38,7,5,7,9,16,9,9,9,8,11,5,14,7,4,4,7,6,5,7,6,5,10,5,15,8,8,19,11,6,6,49,7,7,7,5,9,25,44,10,13,9,19,19,7,25,9,10,6,16,24,7,6,7,10,8,26,6,16,13,14,4,5,7,50,10,8,24,10,10,9,6,8,13,7,13,5,7,9,11,6,5,5,11,12,4,18,8,6,4,11,5,16,6,24,11,25,8,8,27,25,... | 15 = answer_one()
Top15['Population Estimate'] = Top15['Energy Supply'] / Top15['Energy Supply per Capita']
Top15.sort_values('Population Estimate', ascending=False, inplace=True)
return Top15.iloc[2].name
a | identifier_body | |
estimator.py | flags.DEFINE_string('checkpoint_path', None, 'Path to load checkpoint.')
flags.DEFINE_string('gin_file', None, 'Gin config file.')
flags.DEFINE_multi_string('gin_param', None, 'Gin config parameters.')
FLAGS = flags.FLAGS
_CONFIG_GIN = 'operative_config-0.gin'
def main(_):
if FLAGS.gin_file:
gin_paths = ... | (self, batch_size, mode):
if mode == tf.estimator.ModeKeys.TRAIN:
return self._input_fn_train_or_eval(
training=True, batch_size=batch_size)
elif mode == tf.estimator.ModeKeys.EVAL:
return self._input_fn_train_or_eval(
training=False, batch_size=b... | input_fn | identifier_name |
estimator.py | flags.DEFINE_string('checkpoint_path', None, 'Path to load checkpoint.')
flags.DEFINE_string('gin_file', None, 'Gin config file.')
flags.DEFINE_multi_string('gin_param', None, 'Gin config parameters.')
FLAGS = flags.FLAGS
_CONFIG_GIN = 'operative_config-0.gin'
def main(_):
if FLAGS.gin_file:
gin_paths = ... |
else:
gin_paths = []
gin.parse_config_files_and_bindings(gin_paths, FLAGS.gin_param)
estimator = Estimator()
getattr(estimator, FLAGS.do)()
class InputFn(object):
@staticmethod
def create_dir(base_dir):
dir_path = os.path.join(
base_dir,
datetime.date... | checkpoint_dir = FLAGS.checkpoint_dir
if checkpoint_dir is None:
checkpoint_dir = os.path.dirname(FLAGS.checkpoint_path)
gin_paths = [os.path.join(checkpoint_dir, _CONFIG_GIN)] | conditional_block |
estimator.py | flags.DEFINE_string('checkpoint_path', None, 'Path to load checkpoint.')
flags.DEFINE_string('gin_file', None, 'Gin config file.')
flags.DEFINE_multi_string('gin_param', None, 'Gin config parameters.')
FLAGS = flags.FLAGS
_CONFIG_GIN = 'operative_config-0.gin'
def main(_):
if FLAGS.gin_file:
gin_paths = ... | return self._input_fn_train_or_eval(
training=False, batch_size=batch_size)
elif mode == tf.estimator.ModeKeys.PREDICT:
return self._input_fn_predict(
batch_size=batch_size)
class ModelFn(object):
def _get_global_step(self):
return tf_v1.tra... | if mode == tf.estimator.ModeKeys.TRAIN:
return self._input_fn_train_or_eval(
training=True, batch_size=batch_size)
elif mode == tf.estimator.ModeKeys.EVAL: | random_line_split |
estimator.py | flags.DEFINE_string('checkpoint_path', None, 'Path to load checkpoint.')
flags.DEFINE_string('gin_file', None, 'Gin config file.')
flags.DEFINE_multi_string('gin_param', None, 'Gin config parameters.')
FLAGS = flags.FLAGS
_CONFIG_GIN = 'operative_config-0.gin'
def main(_):
if FLAGS.gin_file:
gin_paths = ... |
@property
def result_dir_root(self):
return os.path.join(self.root_dir, 'results')
@property
def split_dir_root(self):
return os.path.join(self.data_dir, 'splits')
@property
def tfrecord_dir_root(self):
return os.path.join(self.data_dir, 'tfrecords')
def _write_t... | return os.path.join(self.root_dir, 'models') | identifier_body |
settings.rs | ::ParsedPkcs12 doesn't impl Clone yet
}
#[derive(Clone)]
pub struct IdentityStore(Vec<u8>, String);
impl TlsSettings {
/// Generate a filled out settings struct from the given optional
/// option set, interpreted as client options. If `options` is
/// `None`, the result is set to defaults (ie empty).
... | {
let options = TlsOptions {
crt_path: Some(TEST_PEM_CRT.into()),
key_path: Some(TEST_PEM_KEY.into()),
..Default::default()
};
let settings =
TlsSettings::from_options(&Some(options)).expect("Failed to load PEM certificate");
assert!(settin... | identifier_body | |
settings.rs | (super) verify_hostname: bool,
authority: Option<X509>,
pub(super) identity: Option<IdentityStore>, // openssl::pkcs12::ParsedPkcs12 doesn't impl Clone yet
}
#[derive(Clone)]
pub struct IdentityStore(Vec<u8>, String);
impl TlsSettings {
/// Generate a filled out settings struct from the given optional
... | () {
let options = TlsOptions {
crt_path: Some(TEST_PKCS12.into()),
key_pass: Some("NOPASS".into()),
..Default::default()
};
let settings =
TlsSettings::from_options(&Some(options)).expect("Failed to load PKCS#12 certificate");
assert!(sett... | from_options_pkcs12 | identifier_name |
settings.rs | (super) verify_hostname: bool,
authority: Option<X509>,
pub(super) identity: Option<IdentityStore>, // openssl::pkcs12::ParsedPkcs12 doesn't impl Clone yet
}
#[derive(Clone)]
pub struct IdentityStore(Vec<u8>, String);
impl TlsSettings {
/// Generate a filled out settings struct from the given optional
... | let name = crt_path.to_string_lossy().to_string();
let cert_data = open_read(crt_path, "certificate")?;
let key_pass: &str = options.key_pass.as_ref().map(|s| s.as_str()).unwrap_or("");
match Pkcs12::from_der(&cert_data) {
// Certifica... | let identity = match options.crt_path {
None => None,
Some(ref crt_path) => { | random_line_split |
calculate_profiles.py | ,
type=str,
help="Path to the output aligned directory. Required."
)
parser.add_argument("--overview",
default=None,
type=str,
help="Path to the output description csv. Required. Pairs with <--aligned... | (df_group, l, dst=dst_func):
sqs = df_group.reset_index()['sq']
n = len(sqs)
if n <= 1:
return np.zeros(n)
dst_matrix = np.zeros((n, n))
for i in range(n):
for j in range(i):
d = dst(sqs[i], sqs[j])
dst_matrix[i, j] = d
dst_matrix[j, i] = d
... | cluster_group | identifier_name |
calculate_profiles.py | =None,
type=str,
help="Path to the output aligned directory. Required."
)
parser.add_argument("--overview",
default=None,
type=str,
help="Path to the output description csv. Required. Pairs with <--al... |
start = time.time()
# print(df.groupby(by='length').get_group(longest))
# print("running on shorter")
with Bar("Processing length groups...", max=len(unique_lengths) - 1) as bar:
for length in unique_lengths[1:]:
bar.next()
df_group = groups.get_group(length).copy()
def getDistanceAndAl... | against.append(alignment)
# df.loc[df['sq'].isin(cluster_df['sq']), 'alignment'] = alignment.ident
# to each sequence | random_line_split |
calculate_profiles.py | ,
type=str,
help="Path to the output aligned directory. Required."
)
parser.add_argument("--overview",
default=None,
type=str,
help="Path to the output description csv. Required. Pairs with <--aligned... |
def cluster_group(df_group, l, dst=dst_func):
sqs = df_group.reset_index()['sq']
n = len(sqs)
if n <= 1:
return np.zeros(n)
dst_matrix = np.zeros((n, n))
for i in range(n):
for j in range(i):
d = dst(sqs[i], sqs[j])
dst_matrix[i, j] = d
dst_m... | for line in open(filename):
sq, count = line.strip('\n').split(';')
yield sq, np.array([int(x) for x in count.split(',')]), count | identifier_body |
calculate_profiles.py | ,
type=str,
help="Path to the output aligned directory. Required."
)
parser.add_argument("--overview",
default=None,
type=str,
help="Path to the output description csv. Required. Pairs with <--aligned... |
i = offset
for base, count in zip(aligned_query, new_counts):
x[bases[base], i] += count
i += 1
self.profile = x
# store new sequence alignment
added_alignment = -np.ones(self.profile.shape[1])
for i, char in enumerate(nice['target_aligned']):
... | value = new_counts[index]
new_counts = np.insert(new_counts, index, value, axis=0) | conditional_block |
game.py | _K: logic.down}
self.setWindowFlags(
QtCore.Qt.CustomizeWindowHint |
QtCore.Qt.FramelessWindowHint)
self.setAttribute(Qt.WA_TranslucentBackground, True)
self.center()
self.settings()
self.restoreStates()
self.fontDatabase = QFontDatabase()
... | if done:
self.stateOfGame()
elif strokeText == "D":
| conditional_block | |
game.py | for j in range(c.GRID_LEN):
new_number = self.matrix[i][j]
if new_number == 0:
self.replaceTile("empty", i, j)
else:
self.replaceTile(new_number, i, j)
# Δημιουργία των αριθμητικών πλακιδίων
def setTile(self, it... | -1]
else:
lst=self.settings().value("gameState")
nums=[]
for i in range(len(lst)):
for j in range(len(lst[0])):
if lst[i][j]!=0:
nums.append(lst[i][j])
print(nums)
return nums
def bHelpClicked(self):
helpDlg... | identifier_body | |
game.py | def __init__(self, parent=None):
# Αρχικοποίηση του γραφικού περιβάλλοντος
super(Game, self).__init__(parent)
print(APP_FOLDER)
self.setupUi(self)
c.SCORE=self.settings().value("score", 0, type=int)
# Μεταβλητές
self.points = []
self.speed = 30
... |
def settings(self):
settings = QSettings()
return settings
| random_line_split | |
game.py | RID_LEN):
for j in range(c.GRID_LEN):
self.gridBoard.addWidget(self.setTile("empty"), i, j)
def generate_next(self):
index = (gen(), gen())
while self.matrix[index[0]][index[1]] != 0:
index = (gen(), gen())
self.matrix[index[0]][index[1]] = 2
def... | = self. | identifier_name | |
key.go | Now := time.Now().UTC().Truncate(time.Second)
if tokenBuildRequest.UtcNotBefore == nil {
tokenBuildRequest.UtcNotBefore = &utcNow
}
tokenBuildRequest.Claims.Issued = jwt.NewNumericTime(utcNow)
tokenBuildRequest.Claims.NotBefore = jwt.NewNumericTime(*tokenBuildRequest.UtcNotBefore)
if tokenBuildRequest.UtcExpires... | {
var cachedItem interface{}
var found bool
cachedItem, found = cache.Get(cacheKey)
if !found {
err = DoKeyvaultBackground()
if err != nil {
log.Fatalf("failed to DoKeyvaultBackground: %v\n", err.Error())
return
}
cachedItem, found = cache.Get(cacheKey)
if !found {
err = errors.New("critical f... | identifier_body | |
key.go |
Claims jwt.Claims
}
type BaseClient2 struct {
azKeyvault.BaseClient
}
func newBaseClient2(base azKeyvault.BaseClient) BaseClient2 {
return BaseClient2{
BaseClient: base,
}
}
func getKeysClient() azKeyvault.BaseClient {
keyClient := azKeyvault.New()
a, _ := iam.GetKeyvaultAuthorizer()
keyClient... | (base64EncodedE string) string {
sDec, _ := b64.StdEncoding.DecodeString(base64Encoded | fixE | identifier_name |
key.go |
Claims jwt.Claims
}
type BaseClient2 struct {
azKeyvault.BaseClient
}
func newBaseClient2(base azKeyvault.BaseClient) BaseClient2 {
return BaseClient2{
BaseClient: base,
}
}
func getKeysClient() azKeyvault.BaseClient {
keyClient := azKeyvault.New()
a, _ := iam.GetKeyvaultAuthorizer()
keyClient... | azKeyvault.Encrypt,
azKeyvault.Decrypt,
},
Kty: azKeyvault.EC,
})
}
func fixE(base64EncodedE string) string {
sDec, _ := b64.StdEncoding.DecodeString(base64EncodedE | Enabled: to.BoolPtr(true),
},
KeySize: to.Int32Ptr(2048), // As of writing this sample, 2048 is the only supported KeySize.
KeyOps: &[]azKeyvault.JSONWebKeyOperation{ | random_line_split |
key.go | Claims jwt.Claims
}
type BaseClient2 struct {
azKeyvault.BaseClient
}
func newBaseClient2(base azKeyvault.BaseClient) BaseClient2 {
return BaseClient2{
BaseClient: base,
}
}
func getKeysClient() azKeyvault.BaseClient {
keyClient := azKeyvault.New()
a, _ := iam.GetKeyvaultAuthorizer()
keyClient.... |
}
}
if !pageResult.NotDone() {
break
}
err = pageResult.Next()
if err != nil {
return
}
}
sort.Slice(finalResult[:], func(i, j int) bool {
notBeforeA := time.Time(*finalResult[i].Attributes.NotBefore)
notBeforeB := time.Time(*finalResult[j].Attributes.NotBefore)
return notBeforeA.After(n... | {
parts := strings.Split(*element.Kid, "/")
lastItemVersion := parts[len(parts)-1]
keyBundle, er := keyClient.GetKey(ctx,
keyVaultUrl,
keyIdentifier,
lastItemVersion)
if er != nil {
err = er
return
}
fixedE := fixE(*keyBundle.Key.E)
*keyBundle.Key.E = fi... | conditional_block |
layout_rope.rs | but we might add more stuff.
pub struct Layout(PietTextLayout);
#[derive(Clone, Default)]
pub struct LayoutRope(Node<LayoutInfo>);
pub struct LayoutRopeBuilder(TreeBuilder<LayoutInfo>);
/// The height metric of the rope, which is in raw Height fractions.
struct HeightMetric;
/// The base metric of the rope, which ... | (&mut self, index: usize) {
let mut b = TreeBuilder::new();
self.push_subseq(&mut b, Interval::new(0, index));
self.push_subseq(&mut b, Interval::new(index + 1, self.len()));
self.0 = b.build();
}
pub fn set(&mut self, index: usize, item: Layout) {
let mut b = TreeBuilde... | remove | identifier_name |
layout_rope.rs | but we might add more stuff.
pub struct Layout(PietTextLayout);
#[derive(Clone, Default)]
pub struct LayoutRope(Node<LayoutInfo>);
pub struct LayoutRopeBuilder(TreeBuilder<LayoutInfo>);
/// The height metric of the rope, which is in raw Height fractions.
struct HeightMetric;
/// The base metric of the rope, which ... |
fn push_subseq(&self, b: &mut TreeBuilder<LayoutInfo>, iv: Interval) {
// TODO: if we make the push_subseq method in xi-rope public, we can save some
// allocations.
b.push(self.0.subseq(iv));
}
}
impl LayoutRopeBuilder {
pub fn new() -> LayoutRopeBuilder {
LayoutRopeBuild... | {
self.0
.count_base_units::<HeightMetric>(height.as_raw_frac())
} | identifier_body |
layout_rope.rs | but we might add more stuff.
pub struct Layout(PietTextLayout);
#[derive(Clone, Default)]
pub struct LayoutRope(Node<LayoutInfo>);
pub struct LayoutRopeBuilder(TreeBuilder<LayoutInfo>);
/// The height metric of the rope, which is in raw Height fractions.
struct HeightMetric;
/// The base metric of the rope, which ... |
}
}
impl From<Vec<(Height, Arc<Layout>)>> for LayoutRope {
fn from(v: Vec<(Height, Arc<Layout>)>) -> Self {
LayoutRope(Node::from_leaf(LayoutLeaf { data: v }))
}
}
impl LayoutRope {
/// The number of layouts in the rope.
pub fn len(&self) -> usize {
self.0.len()
}
/// The... | {
let splitpoint = self.len() / 2;
let right_vec = self.data.split_off(splitpoint);
Some(LayoutLeaf { data: right_vec })
} | conditional_block |
layout_rope.rs | , but we might add more stuff.
pub struct Layout(PietTextLayout);
#[derive(Clone, Default)]
pub struct LayoutRope(Node<LayoutInfo>);
pub struct LayoutRopeBuilder(TreeBuilder<LayoutInfo>);
/// The height metric of the rope, which is in raw Height fractions.
struct HeightMetric;
/// The base metric of the rope, which... | type Output = Self;
fn add(self, other: Self) -> Self {
Height(self.0 + other.0)
}
}
impl std::ops::AddAssign for Height {
fn add_assign(&mut self, other: Self) {
self.0 += other.0
}
}
impl Height {
/// The number of fractional bits in the representation.
pub const HEIGHT_... | random_line_split | |
switching_utils.py | iff you would like to save the simulation as a GIF.
'''
#Initialize planners if not yet done
for car in world.cars:
if (isinstance(car, PlannerCar) and car.planner is None):
car.initialize_planner()
if (world.verbose):
print(f"Executing {exp_name} for {time_steps} time ste... | (reward_ts, model_ts):
'''
Displays reward for each time step gained by the car
in a plot. Color codes by model used and presents
an appropriate legend.
'''
plt.title("Reward by Model")
start_time = 0
cur_model = model_ts[0]
used_models = [cur_model]
for t, model in enumerate(m... | display_rewards | identifier_name |
switching_utils.py | def execute_many_experiments(exp_name, world, time_steps, experiment_args,
ms_car_index = 0):
switching_parameters = {"comp_times": {"Naive": experiment_args.naive_ct,
"Turn": experiment_args.turn_ct,
... | raise Exception(f"Invalid Experiment Type: {exp_type}") | conditional_block | |
switching_utils.py | iff you would like to save the simulation as a GIF.
'''
#Initialize planners if not yet done
for car in world.cars:
if (isinstance(car, PlannerCar) and car.planner is None):
car.initialize_planner()
if (world.verbose):
print(f"Executing {exp_name} for {time_steps} time ste... | def execute_many_experiments(exp_name, world, time_steps, experiment_args,
ms_car_index = 0):
switching_parameters = {"comp_times": {"Naive": experiment_args.naive_ct,
"Turn": experiment_args.turn_ct,
... | clip.speedx(0.5).write_gif(f"{exp_name}.gif", program="ffmpeg")
#return np.mean(reward_ts), avg_step_times['overall'][-1], model_usage
return reward_ts
| random_line_split |
switching_utils.py | iff you would like to save the simulation as a GIF.
'''
#Initialize planners if not yet done
for car in world.cars:
if (isinstance(car, PlannerCar) and car.planner is None):
car.initialize_planner()
if (world.verbose):
print(f"Executing {exp_name} for {time_steps} time ste... | else:
et = (experiment_args.num_run - i) * run_time / (i - 1)
print(f"Running Experiment {i + 1}/{experiment_args.num_run}, Expected Time Left: {et:.0f}s ", end = "\r")
if (i >= 1):
start_time = time.time()
#mean_rew, mean_ct, model_u... | switching_parameters = {"comp_times": {"Naive": experiment_args.naive_ct,
"Turn": experiment_args.turn_ct,
"Tom": experiment_args.tom_ct},
"cooldowns": {"up": experiment_args.up_cd,
... | identifier_body |
sectioning.js | cookieStore.get('username'));
//$('#loginModal').modal('hide');
}
$scope.techTable=[];
$scope.tech={};
$http.get(TECHNICIAN_URL_BASE)
.success(function(data) {
//alert("success loading technicians")
$scope.techTable=data;
console.log($scope.techTable);
})
.error(... | $http.get(url)
.success(function (data) { | random_line_split | |
Object_detection_image.py | is copied from Google's example at
## https://github.com/tensorflow/models/blob/master/research/object_detection/object_detection_tutorial.ipynb
## and some is copied from Dat Tran's example at
## https://github.com/datitran/object_detector_app/blob/master/object_detection_app.py
## but I changed it to make it Suita... |
# This is needed since the notebook is stored in the object_detection folder.
sys.path.append("..")
# Import utilites(utils folder)
from utils import label_map_util
from utils import visualization_utils as vis_util
#CGFC_functions folder
from CGFC_functions import colorDetector as color_Detector
from CGFC_functions ... | #import__color recognition
from sklearn.cluster import KMeans
from sklearn import metrics
| random_line_split |
Object_detection_image.py | copied from Google's example at
## https://github.com/tensorflow/models/blob/master/research/object_detection/object_detection_tutorial.ipynb
## and some is copied from Dat Tran's example at
## https://github.com/datitran/object_detector_app/blob/master/object_detection_app.py
## but I changed it to make it Suitable... |
#Cloth detection whole process start from here
def ClothDetectionAnalyse(image,tagData,gender):
min_score_thresh=CGFCConfig.min_score_thresh
detectedData=Detect_Cloths(image)
boxes=detectedData['boxes'][0]
scores=detectedData['scores'][0]
classes=detectedData['classes'][0]
print("##########... | dominet_colors=color_Detector.dominant_color_detector(crop_img,3) | identifier_body |
Object_detection_image.py | copied from Google's example at
## https://github.com/tensorflow/models/blob/master/research/object_detection/object_detection_tutorial.ipynb
## and some is copied from Dat Tran's example at
## https://github.com/datitran/object_detector_app/blob/master/object_detection_app.py
## but I changed it to make it Suitable... | (image,tagData,gender):
min_score_thresh=CGFCConfig.min_score_thresh
detectedData=Detect_Cloths(image)
boxes=detectedData['boxes'][0]
scores=detectedData['scores'][0]
classes=detectedData['classes'][0]
print("###################################################################################")... | ClothDetectionAnalyse | identifier_name |
Object_detection_image.py | copied from Google's example at
## https://github.com/tensorflow/models/blob/master/research/object_detection/object_detection_tutorial.ipynb
## and some is copied from Dat Tran's example at
## https://github.com/datitran/object_detector_app/blob/master/object_detection_app.py
## but I changed it to make it Suitable... |
crop_image_Data = pd.DataFrame()
for index,bbox in enumerate(bestBBox):
crop_img=cropDetectedCloths(image,bbox)
dominet_colors=color_Detector.dominant_color_detector(crop_img,3)
colors=[]
colorMax=dominet_colors[0]
#print("dominet_colors ... | if ((score>=min_score_thresh) &(className in category_Dic.Attributes)):
bestResults.append(index)
bestBBox.append(normBBoxes[index])
bestScores.append(score)
bestClasses.append(normClasses[index]) | conditional_block |
all8a54.js | -unique-id-'+initIterator;
$t.addClass('swiper-'+index + ' initialized').attr('id', index);
$t.find('.pagination').addClass('pagination-'+index);
var autoPlayVar = parseInt($t.attr('data-autoplay'),10);
var slidesPerViewVar = $t.attr('data-slides-per-view');
if(slidesPerViewVar == 'responsive'){
s... | (data){
if (data.status == 'ok') {
var popup_cont = '';
if (data.type == 'ajax') {
if (data.thumbnail) popup_cont += data.thumbnail;
popup_cont += '<div class="team-desc">';
popup_cont += ' <div class="title">';
popup_cont += ' <h4>' + data.time + '</h4>';
popup_cont += ' <h2>' + data.... | render_content | identifier_name |
all8a54.js |
if ($('.home-slider.anime-slide').length) {
$('.home-slider.anime-slide').closest('.vc_row').addClass('nrg-prod-row-full-height');
};
if ($('.home-slider.arrow-center').length) {
$('.home-slider.arrow-center').closest('.vc_row').addClass('nrg-prod-row-full-height');
};
pageCalculations();
function upda... | {
winW = $(window).width();
winH = $(window).height();
} | identifier_body | |
all8a54.js | _content(data_query,callback){
$.ajax({
url: data_query.ajax_url,
success: function(data){
if (IsJsonString(data)) {
data = jQuery.parseJSON(data);
data.post_url = data_query.post_url;
} else {
var data_r = {};
data_r.status = 'ok';
data_r.type = 'html';
data_r.content =... | {
var pageNum = parseInt(load_more_post.startPage) + 1;
// The maximum number of pages the current query can return.
var max = parseInt(load_more_post.maxPages);
// The link of the next page of posts.
var nextLink = load_more_post.nextLink;
$('.load-more').on('click', function () ... | conditional_block | |
all8a54.js | if(slidesPerViewVar == 'responsive'){
slidesPerViewVar = updateSlidesPerView($t);
}
else slidesPerViewVar = parseInt(slidesPerViewVar,10);
var directionVar = $t.attr('data-direction');
if(!directionVar){ directionVar='horizontal'; }
var loopVar = parseInt($t.attr('data-loop'),10);
var speedVar ... | }
} );
} else { | random_line_split | |
test_dbinterface.py | %s' % __name__)
def tearDownModule():
"""Tear down module after all TestCases are run."""
pass
# logPoint('module %s' % __name__)
class TestDBInterface(unittest.TestCase):
PORT = 29101
HOST = 'localhost'
EXP_ID = 'TEST_EXP_ID'
DATABASE_NAME = 'TFUTILS_TESTDB'
COLLECTION_NAME = 'TFU... |
def test_filter_var_list(self):
var_list = {var.op.name: var for var in tf.global_variables()}
# Test None
self.dbinterface.to_restore = None
filtered_var_list = self.dbinterface.filter_var_list(var_list)
self.assertEqual(filtered_var_list, var_list)
# Test list ... | self.log.info('(name, var.name): ({}, {})'.format(name, var.name))
self.assertEqual(var.op.name, mapping[name]) | conditional_block |
test_dbinterface.py | %s' % __name__)
def tearDownModule():
"""Tear down module after all TestCases are run."""
pass
# logPoint('module %s' % __name__)
class TestDBInterface(unittest.TestCase):
PORT = 29101
HOST = 'localhost'
EXP_ID = 'TEST_EXP_ID'
DATABASE_NAME = 'TFUTILS_TESTDB'
COLLECTION_NAME = 'TFU... | """
self.setup_model()
self.sess = tf.Session(
config=tf.ConfigProto(
allow_soft_placement=True,
gpu_options=tf.GPUOptions(allow_growth=True),
log_device_placement=self.params['log_device_placement'],
))
# TODO:... |
Creates a tensorflow session and instantiates a dbinterface.
| random_line_split |
test_dbinterface.py | %s' % __name__)
def tearDownModule():
"""Tear down module after all TestCases are run."""
pass
# logPoint('module %s' % __name__)
class TestDBInterface(unittest.TestCase):
PORT = 29101
HOST = 'localhost'
EXP_ID = 'TEST_EXP_ID'
DATABASE_NAME = 'TFUTILS_TESTDB'
COLLECTION_NAME = 'TFU... | (self):
self.log.info('Saving checkpoint to {}'.format(self.save_path))
saved_checkpoint_path = self.dbinterface.tf_saver.save(self.sess,
save_path=self.save_path,
global_step=se... | save_test_checkpoint | identifier_name |
test_dbinterface.py |
def tearDownModule():
"""Tear down module after all TestCases are run."""
pass
# logPoint('module %s' % __name__)
class TestDBInterface(unittest.TestCase):
PORT = 29101
HOST = 'localhost'
EXP_ID = 'TEST_EXP_ID'
DATABASE_NAME = 'TFUTILS_TESTDB'
COLLECTION_NAME = 'TFUTILS_TESTCOL'
... | """Set up module once, before any TestCases are run."""
logging.basicConfig()
# logPoint('module %s' % __name__) | identifier_body | |
space_invaders.py | = screen
self.sprite = sprite
self.rect = rect
self.update_dimensions()
self.update_mask()
self.set_exists(True)
# Assigns an id using current time in microseconds
def create_random_id(self):
self.id = int(time() * SECONDS_TO_MICRO_SECONDS)
# Ensures destro... |
# Return front ships
def get_front_line_ships(self):
return self.front_line
# Evenly space out ships within initial allowed range
def setup_ships(self):
start_bottom_edge = int(
float(HEIGHT_FRAME_OPPONENTS) * FACTOR_HEIGHT_FRAME_OPPONENTS)
horizontal_separation = ... | self.direction = DIRECTION_RIGHT
self.direction_previous = self.direction
self.screen = screen
self.row_and_column_size = row_and_column_size
self.ships = {}
self.left = {}
self.right = {}
self.front_line = {}
self.setup_ships() | identifier_body |
space_invaders.py | = screen
self.sprite = sprite
self.rect = rect
self.update_dimensions()
self.update_mask()
self.set_exists(True)
# Assigns an id using current time in microseconds
def create_random_id(self):
self.id = int(time() * SECONDS_TO_MICRO_SECONDS)
# Ensures destro... |
if r == (self.row_and_column_size - 1):
self.right[id] = ship
if c == (self.row_and_column_size - 1):
self.front_line[id] = ship
self.ships[id] = ship
# Check whether left or right ships reached allowed edge/coordinates
de... | self.left[id] = ship | conditional_block |
space_invaders.py | Label
class Text(BasicSprite):
def __init__(self, screen, text, color, font, size):
self.text = text
self.color = color
self.font = font
self.size = size
self.my_font = pygame.font.SysFont(font, size)
self.label = self.my_font.render(text, 1, color)
super()._... | self.screen, text, color, "arial", 60) | random_line_split | |
space_invaders.py |
# Move to position unless outside of allowed coordinates; returns actual
# position delta in contrast with asked
def set_location(self, x, y):
center_change = [
self.rect.centerx,
self.rect.centery]
self.rect.centerx = x
self.rect.centery = y
# Ensur... | __init__ | identifier_name | |
full-site.js | $choicesModal.find('.modal-footer').html("");
var $firstButton;
for (var i in buttons) {
var btn = buttons[i];
var attrsString = "";
for (var key in btn.attrs) {
var value = btn.attrs[key];
attrsString += key + '="' + value + '" ';
}
var $button ... | function sharePopup(url, w, h) {
var left = (screen.width / 2) - (w / 2);
var top = (screen.height / 2) - (h / 2);
return window.open(url, "share window", 'toolbar=no, location=no, directories=no, status=no, menubar=no, scrollbars=yes, copyhistory=no, width=' + w + ', height=' + h + ', top='... | });
| random_line_split |
full-site.js | choicesModal.find('.modal-footer').html("");
var $firstButton;
for (var i in buttons) {
var btn = buttons[i];
var attrsString = "";
for (var key in btn.attrs) {
var value = btn.attrs[key];
attrsString += key + '="' + value + '" ';
}
var $button = ... |
function getprayerTimeData() {
$.ajax({
url: getPrayerInfoUrl,
success: preparePrayerTimeWidget
});
}
// increaseFontSize and decreaseFontSize
var min = 16;
var max = 20;
function increaseFontSize() {
var p = $('.details-text');
for (i = 0; i < p.length; i++... | {
document.getElementById('form_email').value = "";
// $('#form_email').css('text-indent', '35px');
$('#form-modal .help-error').remove();
$('#form-modal .form-group').removeClass('is-invalid');
$('#form-modal').modal('show');
} | identifier_body |
full-site.js | $choicesModal.find('.modal-footer').html("");
var $firstButton;
for (var i in buttons) {
var btn = buttons[i];
var attrsString = "";
for (var key in btn.attrs) {
var value = btn.attrs[key];
attrsString += key + '="' + value + '" ';
}
var $button ... | () {
$('#choices-modal').modal('hide');
}
function userStateChange(data, triggerLoginEvent) {
var data = typeof data == "undefined" ? null : data;
// $('.alert-danger').remove();
$('.login-slid-div').slideUp(300);
if (data) {
if(data.user.avatar){
$(".userImage").html('<i><img sr... | closeDialog | identifier_name |
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