_id stringlengths 2 7 | title stringlengths 1 88 | partition stringclasses 3
values | text stringlengths 31 13.1k | language stringclasses 1
value | meta_information dict |
|---|---|---|---|---|---|
q7300 | IIIFAuth.login_service_description | train | def login_service_description(self):
"""Login service description.
The login service description _MUST_ include the token service
description. The authentication pattern is indicated via the
profile URI which is built using self.auth_pattern.
"""
label = 'Login to ' + self.name
if (self.auth_type):
label = label + ' (' + self.auth_type + ')'
desc = {"@id": self.login_uri,
| python | {
"resource": ""
} |
q7301 | IIIFAuth.logout_service_description | train | def logout_service_description(self):
"""Logout service description."""
label = 'Logout from ' + self.name
if (self.auth_type):
| python | {
"resource": ""
} |
q7302 | IIIFAuth.access_token_response | train | def access_token_response(self, token, message_id=None):
"""Access token response structure.
Success if token is set, otherwise (None, empty string) give error
response. If message_id is set then an extra messageId attribute is
set in the response to handle postMessage() responses.
"""
if (token):
data = {"accessToken": token,
"expiresIn": self.access_token_lifetime}
| python | {
"resource": ""
} |
q7303 | IIIFAuth._generate_random_string | train | def _generate_random_string(self, container, length=20):
"""Generate a random cookie or token string not in container.
The cookie or token should be secure in the sense that it should not
be likely to be able guess a value. Because it is not derived from
| python | {
"resource": ""
} |
q7304 | IIIFAuth.access_cookie | train | def access_cookie(self, account):
"""Make and store access cookie for a given account.
If account is allowed then make a cookie and add it to the dict
of accepted access cookies with current timestamp as the value.
Return the access cookie.
Otherwise return None.
""" | python | {
"resource": ""
} |
q7305 | IIIFAuth.access_cookie_valid | train | def access_cookie_valid(self, cookie, log_msg):
"""Check access cookie validity.
Returns true if the access cookie is valid. The set of allowed
access cookies is stored in self.access_cookies.
Uses log_msg as prefix to info level log message of accetance or
rejection.
"""
if (cookie in self.access_cookies):
age = int(time.time()) - self.access_cookies[cookie]
if (age <= (self.access_cookie_lifetime + 1)):
self.logger.info(log_msg + " " + cookie +
" ACCEPTED COOKIE (%ds old)" % age)
return True
# Expired...
self.logger.info(log_msg + " " + cookie +
" | python | {
"resource": ""
} |
q7306 | IIIFAuth.access_token | train | def access_token(self, cookie):
"""Make and store access token as proxy for the access cookie.
Create an access token to act as a proxy for access cookie, add it to
the dict of accepted access tokens with (cookie, current timestamp)
as the value. Return the access token. Return None if cookie is not set.
"""
| python | {
"resource": ""
} |
q7307 | IIIFAuth.access_token_valid | train | def access_token_valid(self, token, log_msg):
"""Check token validity.
Returns true if the token is valid. The set of allowed access tokens
is stored in self.access_tokens.
Uses log_msg as prefix to info level log message of acceptance or
rejection.
"""
if (token in self.access_tokens):
(cookie, issue_time) = self.access_tokens[token]
age = int(time.time()) - issue_time
if (age <= (self.access_token_lifetime + 1)):
self.logger.info(log_msg + " " + token +
" ACCEPTED TOKEN (%ds old)" % age)
return True
# Expired...
self.logger.info(log_msg + " " + token +
" | python | {
"resource": ""
} |
q7308 | IIIFAuthFlask.info_authn | train | def info_authn(self):
"""Check to see if user if authenticated for info.json.
Must have Authorization header with value that has the form
"Bearer TOKEN", where TOKEN is an appropriate and valid access
token.
"""
authz_header = request.headers.get('Authorization', '[none]')
| python | {
"resource": ""
} |
q7309 | IIIFAuthFlask.image_authn | train | def image_authn(self):
"""Check to see if user if authenticated for image requests.
Must have access cookie with an appropriate value.
| python | {
"resource": ""
} |
q7310 | IIIFAuthFlask.logout_handler | train | def logout_handler(self, **args):
"""Handler for logout button.
Delete cookies and return HTML that immediately closes window
"""
response = make_response(
"<html><script>window.close();</script></html>", 200,
{'Content-Type': "text/html"})
| python | {
"resource": ""
} |
q7311 | IIIFManipulatorNetpbm.find_binaries | train | def find_binaries(cls, tmpdir=None, shellsetup=None, pnmdir=None):
"""Set instance variables for directory and binary locations.
FIXME - should accept params to set things other than defaults.
"""
cls.tmpdir = ('/tmp' if (tmpdir is None) else tmpdir)
# Shell setup command (e.g set library path)
cls.shellsetup = ('' if (shellsetup is None) else shellsetup)
if (pnmdir is None):
cls.pnmdir = '/usr/bin'
for dir in ('/usr/local/bin', '/sw/bin'):
if (os.path.isfile(os.path.join(dir, 'pngtopnm'))):
cls.pnmdir = dir
else:
cls.pnmdir = pnmdir
# Recklessly assume everything else under cls.pnmdir
cls.pngtopnm = os.path.join(cls.pnmdir, 'pngtopnm')
cls.jpegtopnm = os.path.join(cls.pnmdir, 'jpegtopnm')
cls.pnmfile = os.path.join(cls.pnmdir, 'pnmfile')
| python | {
"resource": ""
} |
q7312 | IIIFManipulatorNetpbm.do_first | train | def do_first(self):
"""Create PNM file from input image file."""
pid = os.getpid()
self.basename = os.path.join(self.tmpdir, 'iiif_netpbm_' + str(pid))
outfile = self.basename + '.pnm'
# Convert source file to pnm
filetype = self.file_type(self.srcfile)
if (filetype == 'png'):
if (self.shell_call(self.pngtopnm + ' ' + self.srcfile + ' > ' + outfile)):
raise IIIFError(text="Oops... got error from pngtopnm.")
elif (filetype == 'jpg'):
if (self.shell_call(self.jpegtopnm + ' ' + self.srcfile + ' > ' + outfile)):
| python | {
"resource": ""
} |
q7313 | IIIFManipulatorNetpbm.file_type | train | def file_type(self, file):
"""Use python-magic to determine file type.
Returns 'png' or 'jpg' on success, nothing on failure.
"""
try:
magic_text = magic.from_file(file)
if (isinstance(magic_text, bytes)):
| python | {
"resource": ""
} |
q7314 | IIIFManipulatorNetpbm.image_size | train | def image_size(self, pnmfile):
"""Get width and height of pnm file.
simeon@homebox src>pnmfile /tmp/214-2.png
/tmp/214-2.png:PPM raw, 100 by 100 maxval 255
"""
pout = os.popen(self.shellsetup + self.pnmfile + ' ' + pnmfile, 'r')
pnmfileout = pout.read(200)
pout.close()
m = re.search(', (\d+) by (\d+) ', pnmfileout)
if (m is None):
raise IIIFError(
| python | {
"resource": ""
} |
q7315 | IIIFManipulatorNetpbm.shell_call | train | def shell_call(self, shellcmd):
"""Shell call with necessary setup first."""
| python | {
"resource": ""
} |
q7316 | IIIFManipulatorNetpbm.cleanup | train | def cleanup(self):
"""Clean up any temporary files."""
for | python | {
"resource": ""
} |
q7317 | IIIFError.image_server_response | train | def image_server_response(self, api_version=None):
"""Response, code and headers for image server error response.
api_version selects the format (XML of 1.0). The return value is
a tuple of
response - body of HTTP response
status - the HTTP status code
headers - a dict of HTTP headers which | python | {
"resource": ""
} |
q7318 | IIIFError.as_xml | train | def as_xml(self):
"""XML representation of the error to be used in HTTP response.
This XML format follows the IIIF Image API v1.0 specification,
see <http://iiif.io/api/image/1.0/#error>
"""
# Build tree
spacing = ("\n" if (self.pretty_xml) else "")
root = Element('error', {'xmlns': I3F_NS})
root.text = spacing
e_parameter = Element('parameter', {})
e_parameter.text = self.parameter
e_parameter.tail = spacing
root.append(e_parameter)
if (self.text):
e_text = Element('text', {})
e_text.text = self.text
| python | {
"resource": ""
} |
q7319 | IIIFError.as_txt | train | def as_txt(self):
"""Text rendering of error response.
Designed for use with Image API version 1.1 and above where the
error response is suggested to be text or html but not otherwise
specified. Intended to provide useful information for debugging.
"""
s = "IIIF Image Server Error\n\n"
s += self.text if (self.text) else 'UNKNOWN_ERROR'
s += "\n\n"
if (self.parameter):
s += | python | {
"resource": ""
} |
q7320 | IIIFAuthGoogle.login_handler | train | def login_handler(self, config=None, prefix=None, **args):
"""OAuth starts here, redirect user to Google."""
params = {
'response_type': 'code',
'client_id': self.google_api_client_id,
'redirect_uri': self.scheme_host_port_prefix(
'http', config.host, config.port, prefix) + '/home',
| python | {
"resource": ""
} |
q7321 | IIIFAuthGoogle.google_get_token | train | def google_get_token(self, config, prefix):
"""Make request to Google API to get token."""
params = {
'code': self.request_args_get(
'code',
default=''),
'client_id': self.google_api_client_id,
'client_secret': self.google_api_client_secret,
| python | {
"resource": ""
} |
q7322 | IIIFAuthGoogle.google_get_data | train | def google_get_data(self, config, response):
"""Make request to Google API to get profile data for the user."""
params = {
'access_token': response['access_token'],
| python | {
"resource": ""
} |
q7323 | IIIFManipulator.compliance_uri | train | def compliance_uri(self):
"""Compliance URI based on api_version.
Value is based on api_version and complicance_level, will be
None if either are unset/unrecognized. The assumption here is
that the api_version and level are orthogonal, override this
method if that isn't true.
"""
if (self.api_version == '1.0'):
uri_pattern = r'http://library.stanford.edu/iiif/image-api/compliance.html#level%d'
elif (self.api_version == '1.1'):
| python | {
"resource": ""
} |
q7324 | IIIFManipulator.derive | train | def derive(self, srcfile=None, request=None, outfile=None):
"""Do sequence of manipulations for IIIF to derive output image.
Named argments:
srcfile -- source image file
request -- IIIFRequest object with parsed parameters
outfile -- output image file. If set the the output file will be
written to that file, otherwise a new temporary file
will be created and outfile set to its location.
See order in spec: http://www-sul.stanford.edu/iiif/image-api/#order
Region THEN Size THEN Rotation THEN Quality THEN Format
Typical use:
r = IIIFRequest(region=...)
m = IIIFManipulator()
try:
m.derive(srcfile='a.jpg',request=r)
# .. serve m.outfile
except IIIFError as e:
# ..
finally:
m.cleanup() #removes temp m.outfile
"""
# set if specified
if (srcfile is not None):
self.srcfile = srcfile
if (request | python | {
"resource": ""
} |
q7325 | IIIFManipulator.do_region | train | def do_region(self, x, y, w, h):
"""Null implementation of region selection."""
if (x is not None):
raise IIIFError(code=501, parameter="region",
| python | {
"resource": ""
} |
q7326 | IIIFManipulator.do_quality | train | def do_quality(self, quality):
"""Null implementation of quality."""
if (self.api_version >= '2.0'):
if (quality != "default"):
raise IIIFError(code=501, parameter="default",
| python | {
"resource": ""
} |
q7327 | IIIFManipulator.do_format | train | def do_format(self, format):
"""Null implementation of format selection.
This is the last step, this null implementation does not accept any
specification of a format because we don't even know what the input
format is.
"""
if (format is not None):
raise IIIFError(code=415, parameter="format",
text="Null manipulator does not support specification of output format.")
#
if (self.outfile is None):
self.outfile = | python | {
"resource": ""
} |
q7328 | IIIFManipulator.region_to_apply | train | def region_to_apply(self):
"""Return the x,y,w,h parameters to extract given image width and height.
Assume image width and height are available in self.width and
self.height, and self.request is IIIFRequest object
Expected use:
(x,y,w,h) = self.region_to_apply()
if (x is None):
# full image
else:
# extract
Returns (None,None,None,None) if no extraction is required.
"""
if (self.request.region_full or
(self.request.region_pct and
self.request.region_xywh == (0, 0, 100, 100))):
return(None, None, None, None)
# Cannot do anything else unless we know size (in self.width and
# self.height)
if (self.width <= 0 or self.height <= 0):
raise IIIFError(code=501, parameter='region',
text="Region parameters require knowledge of image size which is not implemented.")
if (self.request.region_square):
if (self.width <= self.height):
y_offset = (self.height - self.width) / 2
return(0, y_offset, self.width, self.width)
else: # self.width>self.height
x_offset = (self.width - self.height) / 2
return(x_offset, 0, self.height, self.height)
# pct or | python | {
"resource": ""
} |
q7329 | IIIFManipulator.size_to_apply | train | def size_to_apply(self):
"""Calculate size of image scaled using size parameters.
Assumes current image width and height are available in self.width and
self.height, and self.request is IIIFRequest object.
Formats are: w, ,h w,h pct:p !w,h full max
Returns (None,None) if no scaling is required.
If max is requested and neither max_area or max_width are
specified then this is the same as full. Otherwise the limits
are used to determine the size.
"""
if (self.request.size_full or self.request.size_pct == 100.0):
# full size
return(None, None)
# Not trivially full size, look at possibilities in turn
w = self.width
h = self.height
if (self.request.size_max):
# use size limits if present, else full
if (self.max_area and self.max_area < (w * h)):
scale = (float(self.max_area) / float(w * h)) ** 0.5
w = int(w * scale + 0.5)
h = int(h * scale + 0.5)
if (self.max_width):
max_height = self.max_height if self.max_height is not None else self.max_width
if (self.max_width < w):
# calculate wrt original width, height rather than
# w, h to avoid compounding rounding issues
scale = float(self.max_width) / float(self.width)
w = int(self.width * scale + 0.5)
h = int(self.height * scale + 0.5)
if (max_height < h):
scale = float(max_height) / float(self.height)
w = int(self.width * scale + 0.5)
h = int(self.height * scale + 0.5)
elif (self.request.size_pct is not None):
w = int(self.width * self.request.size_pct / 100.0 + 0.5)
h = int(self.height * self.request.size_pct / 100.0 + 0.5)
elif (self.request.size_bang):
# Have "!w,h" form
(mw, mh) = self.request.size_wh
# | python | {
"resource": ""
} |
q7330 | IIIFManipulator.quality_to_apply | train | def quality_to_apply(self):
"""Value of quality parameter to use in processing request.
Simple substitution of 'native' or 'default' if no quality
parameter is specified.
"""
if (self.request.quality is None):
| python | {
"resource": ""
} |
q7331 | IIIFManipulator.scale_factors | train | def scale_factors(self, tile_width, tile_height=None):
"""Return a set of scale factors for given tile and window size.
Gives a set of scale factors, starting at 1, and in multiples
of 2. Largest scale_factor is so that one tile will cover the
entire image (self.width,self.height).
If tile_height is not specified then tiles are assumed to be
squares of tile_width pixels.
"""
if (not tile_height):
tile_height = tile_width
sf = 1
| python | {
"resource": ""
} |
q7332 | PixelGen.color | train | def color(self, n):
"""Color of pixel that reached limit after n iterations.
Returns a color tuple for use with PIL, tending toward
red as we tend toward self.max_iter iterations.
"""
red = | python | {
"resource": ""
} |
q7333 | PixelGen.mpixel | train | def mpixel(self, z, n=0):
"""Iteration in Mandlebrot coordinate z."""
z = z * z + self.c
if (abs(z) > 2.0):
return self.color(n)
n += 1
| python | {
"resource": ""
} |
q7334 | static_partial_tile_sizes | train | def static_partial_tile_sizes(width, height, tilesize, scale_factors):
"""Generator for partial tile sizes for zoomed in views.
Positional arguments:
width -- width of full size image
height -- height of full size image
tilesize -- width and height of tiles
scale_factors -- iterable of scale factors, typically [1,2,4..]
Yields ([rx,ry,rw,rh],[sw,sh]), the region and size for each tile
"""
for sf in scale_factors:
if (sf * tilesize >= width and sf * tilesize >= height):
continue # avoid any full-region tiles
rts = tilesize * sf # tile size in original region
xt = (width - 1) // rts + 1
yt = (height - 1) // rts + 1
for nx in range(xt):
rx = nx * rts
rxe = rx + rts
if (rxe > width):
| python | {
"resource": ""
} |
q7335 | static_full_sizes | train | def static_full_sizes(width, height, tilesize):
"""Generator for scaled-down full image sizes.
Positional arguments:
width -- width of full size image
height -- height of full size image
tilesize -- width and height of tiles
Yields [sw,sh], the size for each full-region tile that is less than
the tilesize. This includes tiles up to the full image size if that
is smaller than the tilesize.
"""
# FIXME - Not sure what correct algorithm is for this, from
# observation of Openseadragon it seems that one keeps halving
# the pixel size of the full image until until both width and
# height are less than the tile size. After that all subsequent
# halving of the image size are used, all the way down to 1,1.
# It seems that without these reduced size full-region images,
# OpenSeadragon will not display any unzoomed image in small windows.
#
| python | {
"resource": ""
} |
q7336 | IIIFStatic.parse_extra | train | def parse_extra(self, extra):
"""Parse extra request parameters to IIIFRequest object."""
if extra.startswith('/'):
extra = extra[1:]
r = IIIFRequest(identifier='dummy',
api_version=self.api_version)
| python | {
"resource": ""
} |
q7337 | IIIFStatic.get_osd_config | train | def get_osd_config(self, osd_version):
"""Select appropriate portion of config.
If the version requested is not supported the raise an exception with
a helpful error message listing the versions supported.
"""
if (osd_version in self.osd_config):
return(self.osd_config[osd_version])
| python | {
"resource": ""
} |
q7338 | IIIFStatic.generate | train | def generate(self, src=None, identifier=None):
"""Generate static files for one source image."""
self.src = src
self.identifier = identifier
# Get image details and calculate tiles
im = self.manipulator_klass()
im.srcfile = self.src
im.set_max_image_pixels(self.max_image_pixels)
im.do_first()
width = im.width
height = im.height
scale_factors = im.scale_factors(self.tilesize)
# Setup destination and IIIF identifier
self.setup_destination()
# Write out images
for (region, size) in static_partial_tile_sizes(width, height, self.tilesize, scale_factors):
self.generate_tile(region, size)
sizes = []
for size in static_full_sizes(width, height, self.tilesize):
# See https://github.com/zimeon/iiif/issues/9
sizes.append({'width': size[0], 'height': size[1]})
self.generate_tile('full', size)
for request in self.extras:
request.identifier = self.identifier
if (request.is_scaled_full_image()):
sizes.append({'width': request.size_wh[0],
'height': request.size_wh[1]})
self.generate_file(request)
# Write info.json
qualities = ['default'] if (self.api_version > '1.1') else ['native']
info = IIIFInfo(level=0, server_and_prefix=self.prefix, identifier=self.identifier, | python | {
"resource": ""
} |
q7339 | IIIFStatic.generate_tile | train | def generate_tile(self, region, size):
"""Generate one tile for this given region, size of this image."""
r = IIIFRequest(identifier=self.identifier,
api_version=self.api_version)
if (region == 'full'):
| python | {
"resource": ""
} |
q7340 | IIIFStatic.generate_file | train | def generate_file(self, r, undistorted=False):
"""Generate file for IIIFRequest object r from this image.
FIXME - Would be nicer to have the test for an undistorted image request
based on the IIIFRequest object, and then know whether to apply canonicalization
or not.
Logically we might use `w,h` instead of the Image API v2.0 canonical
form `w,` if the api_version is 1.x. However, OSD 1.2.1 and 2.x assume
the new canonical form even in the case where the API version is declared
earlier. Thus, determine whether to use the canonical or `w,h` form based
solely on the setting of osd_version.
"""
use_canonical = self.get_osd_config(self.osd_version)['use_canonical']
height = None
if (undistorted and use_canonical):
height = r.size_wh[1]
r.size_wh = [r.size_wh[0], None] # [sw,sh] -> [sw,]
path = r.url()
# Generate...
if (self.dryrun):
self.logger.info("%s / %s" % (self.dst, path))
else:
m = self.manipulator_klass(api_version=self.api_version)
try:
m.derive(srcfile=self.src, request=r,
outfile=os.path.join(self.dst, path))
self.logger.info("%s / %s" % (self.dst, path))
except IIIFZeroSizeError:
self.logger.info("%s / %s - zero size, skipped" %
(self.dst, path))
return # done if zero size
if (r.region_full and use_canonical and height is not None):
# In v2.0 of the spec, the canonical URI form `w,` for scaled
# images of the full region was introduced. This is somewhat at
# odds with the requirement for `w,h` specified in `sizes` to
# be available, and has problems of precision with tall narrow
| python | {
"resource": ""
} |
q7341 | IIIFStatic.setup_destination | train | def setup_destination(self):
"""Setup output directory based on self.dst and self.identifier.
Returns the output directory name on success, raises and exception on
failure.
"""
# Do we have a separate identifier?
if (not self.identifier):
# No separate identifier specified, split off the last path segment
# of the source name, strip the extension to get the identifier
self.identifier = os.path.splitext(os.path.split(self.src)[1])[0]
# Done if dryrun, else setup self.dst first
if (self.dryrun):
return
if (not self.dst):
raise IIIFStaticError("No destination directory specified!")
dst = self.dst
if (os.path.isdir(dst)):
# Exists, OK
pass
elif (os.path.isfile(dst)):
raise IIIFStaticError(
"Can't write to directory %s: a file of that name exists" % dst)
else:
os.makedirs(dst)
| python | {
"resource": ""
} |
q7342 | IIIFStatic.write_html | train | def write_html(self, html_dir='/tmp', include_osd=False,
osd_width=500, osd_height=500):
"""Write HTML test page using OpenSeadragon for the tiles generated.
Assumes that the generate(..) method has already been called to set up
identifier etc. Parameters:
html_dir - output directory for HTML files, will be created if it
does not already exist
include_osd - true to include OpenSeadragon code
osd_width - width of OpenSeadragon pane in pixels
osd_height - height of OpenSeadragon pane in pixels
"""
osd_config = self.get_osd_config(self.osd_version)
osd_base = osd_config['base']
osd_dir = osd_config['dir'] # relative to base
osd_js = os.path.join(osd_dir, osd_config['js'])
osd_images = os.path.join(osd_dir, osd_config['images'])
if (os.path.isdir(html_dir)):
# Exists, fine
pass
elif (os.path.isfile(html_dir)):
raise IIIFStaticError(
"Can't write to directory %s: a file of that name exists" % html_dir)
else:
os.makedirs(html_dir)
self.logger.info("Writing HTML to %s" % (html_dir))
with open(os.path.join(self.template_dir, 'static_osd.html'), 'r') as f:
template = f.read()
outfile = self.identifier + '.html'
outpath = os.path.join(html_dir, outfile)
with open(outpath, 'w') as f:
info_json_uri = '/'.join([self.identifier, 'info.json'])
if (self.prefix):
info_json_uri = '/'.join([self.prefix, info_json_uri])
d = dict(identifier=self.identifier,
api_version=self.api_version,
osd_version=self.osd_version,
osd_uri=osd_js,
osd_images_prefix=osd_images,
osd_height=osd_width,
osd_width=osd_height,
info_json_uri=info_json_uri)
f.write(Template(template).safe_substitute(d))
self.logger.info("%s / %s" % (html_dir, outfile))
| python | {
"resource": ""
} |
q7343 | get_value | train | def get_value(key, obj, default=missing):
"""Helper for pulling a keyed value off various types of objects""" | python | {
"resource": ""
} |
q7344 | validate_headers | train | def validate_headers(spec, data):
"""Validates headers data and creates the config objects"""
validated_data = {
spec.VERSION: data[spec.VERSION],
spec.KIND: data[spec.KIND],
}
if data.get(spec.LOGGING):
validated_data[spec.LOGGING] = LoggingConfig.from_dict(
data[spec.LOGGING])
if data.get(spec.TAGS):
| python | {
"resource": ""
} |
q7345 | validate | train | def validate(spec, data):
"""Validates the data and creates the config objects"""
data = copy.deepcopy(data)
validated_data = {}
def validate_keys(section, config, section_data):
if not isinstance(section_data, dict) or section == spec.MODEL:
return
extra_args = [key for key in section_data.keys() if key not in config.SCHEMA().fields]
if extra_args:
raise PolyaxonfileError('Extra arguments passed for `{}`: {}'.format(
section, extra_args))
def add_validated_section(section, config):
if data.get(section):
section_data = data[section]
validate_keys(section=section, config=config, section_data=section_data)
| python | {
"resource": ""
} |
q7346 | ExperimentSchema.validate_replicas | train | def validate_replicas(self, data):
"""Validate distributed experiment"""
environment = data.get('environment')
| python | {
"resource": ""
} |
q7347 | GroupSpecification.get_experiment_spec | train | def get_experiment_spec(self, matrix_declaration):
"""Returns an experiment spec for this group spec and the given matrix declaration."""
parsed_data = Parser.parse(self, self._data, matrix_declaration)
del parsed_data[self.HP_TUNING]
| python | {
"resource": ""
} |
q7348 | GroupSpecification.get_build_spec | train | def get_build_spec(self):
"""Returns a build spec for this group spec."""
if BaseSpecification.BUILD not in self._data:
return None
| python | {
"resource": ""
} |
q7349 | HPTuningSchema.validate_matrix | train | def validate_matrix(self, data):
"""Validates matrix data and creates the config objects"""
is_grid_search = (
data.get('grid_search') is not None or
(data.get('grid_search') is None and
data.get('random_search') is None and
data.get('hyperband') is None | python | {
"resource": ""
} |
q7350 | TableOne._generate_remark_str | train | def _generate_remark_str(self, end_of_line = '\n'):
"""
Generate a series of remarks that the user should consider
when interpreting the summary statistics.
"""
warnings = {}
msg = '{}'.format(end_of_line)
# generate warnings for continuous variables
if self._continuous:
# highlight far outliers
outlier_mask = self.cont_describe.far_outliers > 1
outlier_vars = list(self.cont_describe.far_outliers[outlier_mask].dropna(how='all').index)
if outlier_vars:
warnings["Warning, Tukey test indicates far outliers in"] = outlier_vars
# highlight possible multimodal distributions using hartigan's dip test
| python | {
"resource": ""
} |
q7351 | TableOne._detect_categorical_columns | train | def _detect_categorical_columns(self,data):
"""
Detect categorical columns if they are not specified.
Parameters
----------
data : pandas DataFrame
The input dataset.
Returns
----------
likely_cat : list
List of variables that appear to be categorical.
"""
# assume all non-numerical and date columns are categorical
numeric_cols = set(data._get_numeric_data().columns.values)
date_cols = set(data.select_dtypes(include=[np.datetime64]).columns)
| python | {
"resource": ""
} |
q7352 | TableOne._std | train | def _std(self,x):
"""
Compute standard deviation with ddof degrees of freedom
"""
| python | {
"resource": ""
} |
q7353 | TableOne._tukey | train | def _tukey(self,x,threshold):
"""
Count outliers according to Tukey's rule.
Where Q1 is the lower quartile and Q3 is the upper quartile,
an outlier is an observation outside of the range:
[Q1 - k(Q3 - Q1), Q3 + k(Q3 - Q1)]
k = 1.5 indicates an outlier
k = 3.0 indicates an outlier that is "far out"
"""
vals = x.values[~np.isnan(x.values)]
try:
q1, q3 = np.percentile(vals, [25, 75])
| python | {
"resource": ""
} |
q7354 | TableOne._outliers | train | def _outliers(self,x):
"""
Compute number of outliers
"""
outliers | python | {
"resource": ""
} |
q7355 | TableOne._far_outliers | train | def _far_outliers(self,x):
"""
Compute number of "far out" outliers
"""
| python | {
"resource": ""
} |
q7356 | TableOne._create_cat_describe | train | def _create_cat_describe(self,data):
"""
Describe the categorical data.
Parameters
----------
data : pandas DataFrame
The input dataset.
Returns
----------
df_cat : pandas DataFrame
Summarise the categorical variables.
"""
group_dict = {}
for g in self._groupbylvls:
if self._groupby:
d_slice = data.loc[data[self._groupby] == g, self._categorical]
else:
d_slice = data[self._categorical].copy()
# create a dataframe with freq, proportion
df = d_slice.copy()
# convert type to string to avoid int converted to boolean, avoiding nans
for column in df.columns:
df[column] = [str(row) if not pd.isnull(row) else None for row in df[column].values]
df = df.melt().groupby(['variable','value']).size().to_frame(name='freq')
df.index.set_names('level', level=1, inplace=True)
df['percent'] = df['freq'].div(df.freq.sum(level=0),level=0).astype(float)* 100
# set number of decimal places for percent
if isinstance(self._decimals,int):
n = self._decimals
f = '{{:.{}f}}'.format(n)
df['percent'] = df['percent'].astype(float).map(f.format)
elif isinstance(self._decimals,dict):
df.loc[:,'percent'] = df.apply(self._format_cat, axis=1)
else:
n = 1
f = '{{:.{}f}}'.format(n)
df['percent'] = df['percent'].astype(float).map(f.format)
# add n column, listing total non-null values for each variable
ct = d_slice.count().to_frame(name='n')
ct.index.name = 'variable'
df = df.join(ct)
# add null count
nulls = d_slice.isnull().sum().to_frame(name='isnull')
| python | {
"resource": ""
} |
q7357 | TableOne._create_significance_table | train | def _create_significance_table(self,data):
"""
Create a table containing p-values for significance tests. Add features of
the distributions and the p-values to the dataframe.
Parameters
----------
data : pandas DataFrame
The input dataset.
Returns
----------
df : pandas DataFrame
A table containing the p-values, test name, etc.
"""
# list features of the variable e.g. matched, paired, n_expected
df=pd.DataFrame(index=self._continuous+self._categorical,
columns=['continuous','nonnormal','min_observed','pval','ptest'])
df.index.rename('variable', inplace=True)
df['continuous'] = np.where(df.index.isin(self._continuous),True,False)
df['nonnormal'] = np.where(df.index.isin(self._nonnormal),True,False)
# list values for each variable, grouped by groupby levels
for v in df.index:
| python | {
"resource": ""
} |
q7358 | TableOne._create_cont_table | train | def _create_cont_table(self,data):
"""
Create tableone for continuous data.
Returns
----------
table : pandas DataFrame
A table summarising the continuous variables.
"""
# remove the t1_summary level
table = self.cont_describe[['t1_summary']].copy()
table.columns = table.columns.droplevel(level=0)
# add a column of null counts as 1-count() from previous function
nulltable = data[self._continuous].isnull().sum().to_frame(name='isnull')
try:
table = table.join(nulltable)
except TypeError: # if columns form a CategoricalIndex, need to convert to string first
table.columns = table.columns.astype(str)
| python | {
"resource": ""
} |
q7359 | TableOne._create_cat_table | train | def _create_cat_table(self,data):
"""
Create table one for categorical data.
Returns
----------
table : pandas DataFrame
A table summarising the categorical variables.
"""
table = self.cat_describe['t1_summary'].copy()
# add the total count of null values across all levels
isnull = data[self._categorical].isnull().sum().to_frame(name='isnull')
isnull.index.rename('variable', inplace=True)
try:
table = table.join(isnull)
except TypeError: # if columns form a CategoricalIndex, need to convert to string first
table.columns = table.columns.astype(str)
| python | {
"resource": ""
} |
q7360 | TableOne._create_row_labels | train | def _create_row_labels(self):
"""
Take the original labels for rows. Rename if alternative labels are
provided. Append label suffix if label_suffix is True.
Returns
----------
labels : dictionary
Dictionary, keys are original column name, values are final label.
"""
# start with the original column names
labels = {}
for c in self._columns:
labels[c] = c
| python | {
"resource": ""
} |
q7361 | bandwidth_factor | train | def bandwidth_factor(nbr_data_pts, deriv_order=0):
'''
Scale factor for one-dimensional plug-in bandwidth selection.
'''
if deriv_order == 0:
return (3.0*nbr_data_pts/4)**(-1.0/5)
if | python | {
"resource": ""
} |
q7362 | make_html_tag | train | def make_html_tag(tag, text=None, **params):
"""Create an HTML tag string.
tag
The HTML tag to use (e.g. 'a', 'span' or 'div')
text
The text to enclose between opening and closing tag. If no text is specified then only
the opening tag is returned.
Example::
make_html_tag('a', text="Hello", href="/another/page")
-> <a href="/another/page">Hello</a>
To use reserved Python keywords like "class" as a parameter prepend it with
an underscore. Instead of "class='green'" use "_class='green'".
Warning: Quotes and apostrophes are not escaped."""
params_string = ""
# Parameters are passed. Turn the dict into a string like "a=1 b=2 c=3" string.
for key, value in sorted(params.items()):
# Strip off a leading underscore from the attribute's key to allow attributes | python | {
"resource": ""
} |
q7363 | Page._range | train | def _range(self, link_map, radius):
"""
Return range of linked pages to substiture placeholder in pattern
"""
leftmost_page = max(self.first_page, (self.page - radius))
rightmost_page = min(self.last_page, (self.page + radius))
nav_items = []
# Create a link to the first page (unless we are on the first page
# or there would be no need to insert '..' spacers)
if self.page != self.first_page and self.first_page < leftmost_page:
page = link_map["first_page"].copy()
page["value"] = unicode(page["number"])
nav_items.append(self.link_tag(page))
for item in link_map["range_pages"]:
nav_items.append(self.link_tag(item)) | python | {
"resource": ""
} |
q7364 | Page.default_link_tag | train | def default_link_tag(item):
"""
Create an A-HREF tag that points to another page.
"""
text = item["value"]
target_url = item["href"]
if not item["href"] or item["type"] in ("span", "current_page"):
if item["attrs"]:
| python | {
"resource": ""
} |
q7365 | PerceptronTagger.tag | train | def tag(self, corpus, tokenize=True):
'''Tags a string `corpus`.'''
# Assume untokenized corpus has \n between sentences and ' ' between words
s_split = SentenceTokenizer().tokenize if tokenize else lambda t: t.split('\n')
w_split = WordTokenizer().tokenize if tokenize else lambda s: s.split()
def split_sents(corpus):
for s in s_split(corpus):
yield w_split(s)
prev, prev2 = self.START
tokens = []
for words in split_sents(corpus):
context = self.START + [self._normalize(w) for w | python | {
"resource": ""
} |
q7366 | PerceptronTagger.train | train | def train(self, sentences, save_loc=None, nr_iter=5):
'''Train a model from sentences, and save it at ``save_loc``. ``nr_iter``
controls the number of Perceptron training iterations.
:param sentences: A list of (words, tags) tuples.
:param save_loc: If not ``None``, saves a pickled model in this location.
:param nr_iter: Number of training iterations.
'''
self._make_tagdict(sentences)
self.model.classes = self.classes
for iter_ in range(nr_iter):
c = 0
n = 0
for words, tags in sentences:
prev, prev2 = self.START
context = self.START + [self._normalize(w) for w in words] \
+ self.END
for i, word in enumerate(words):
guess = self.tagdict.get(word)
| python | {
"resource": ""
} |
q7367 | PerceptronTagger.load | train | def load(self, loc):
'''Load a pickled model.'''
try:
w_td_c = pickle.load(open(loc, 'rb'))
except IOError:
msg = ("Missing trontagger.pickle file.")
raise MissingCorpusError(msg)
| python | {
"resource": ""
} |
q7368 | PerceptronTagger._normalize | train | def _normalize(self, word):
'''Normalization used in pre-processing.
- All words are lower cased
- Digits in the range 1800-2100 are represented as !YEAR;
- Other digits are represented as !DIGITS
:rtype: str
'''
if '-' in word and | python | {
"resource": ""
} |
q7369 | PerceptronTagger._make_tagdict | train | def _make_tagdict(self, sentences):
'''Make a tag dictionary for single-tag words.'''
counts = defaultdict(lambda: defaultdict(int))
for words, tags in sentences:
for word, tag in zip(words, tags):
counts[word][tag] += 1
self.classes.add(tag)
| python | {
"resource": ""
} |
q7370 | train | train | def train(nr_iter, examples):
'''Return an averaged perceptron model trained on ``examples`` for
``nr_iter`` iterations.
'''
model = AveragedPerceptron()
for i in range(nr_iter):
random.shuffle(examples)
for features, class_ in examples:
scores = model.predict(features)
| python | {
"resource": ""
} |
q7371 | RtpPacket.decode | train | def decode(self, byteStream):
"""Decode the RTP packet."""
| python | {
"resource": ""
} |
q7372 | RtpPacket.timestamp | train | def timestamp(self):
"""Return timestamp."""
timestamp = self.header[4] | python | {
"resource": ""
} |
q7373 | preview_stream | train | def preview_stream(stream):
""" Display stream in an OpenCV window until "q" key is pressed """
# together with waitkeys later, helps to close the video window effectively
_cv2.startWindowThread()
for frame in stream.frame_generator():
if frame is not None:
_cv2.imshow('Video', frame)
| python | {
"resource": ""
} |
q7374 | printrec | train | def printrec(recst):
""" Pretty-printing rtsp strings
"""
try:
recst = recst.decode('UTF-8')
except AttributeError:
pass
| python | {
"resource": ""
} |
q7375 | get_resources | train | def get_resources(connection):
""" Do an RTSP-DESCRIBE request, then parse out available resources from the response """
resp = connection.describe(verbose=False).split('\r\n')
| python | {
"resource": ""
} |
q7376 | FFmpegClient.fetch_image | train | def fetch_image(self,rtsp_server_uri = _source,timeout_secs = 15):
""" Fetch a single frame using FFMPEG. Convert to PIL Image. Slow. """
self._check_ffmpeg()
cmd = "ffmpeg -rtsp_transport tcp -i {} -loglevel quiet -frames 1 -f image2pipe -".format(rtsp_server_uri)
#stdout = _sp.check_output(ffmpeg_cmd,timeout = timeout_secs)
with _sp.Popen(cmd, shell=True, stdout=_sp.PIPE) as process:
| python | {
"resource": ""
} |
q7377 | Client.setupMovie | train | def setupMovie(self):
"""Setup button handler."""
if self.state == self.INIT:
| python | {
"resource": ""
} |
q7378 | Client.exitClient | train | def exitClient(self):
"""Teardown button handler."""
self.sendRtspRequest(self.TEARDOWN)
#self.handler()
os.remove(CACHE_FILE_NAME + | python | {
"resource": ""
} |
q7379 | Client.pauseMovie | train | def pauseMovie(self):
"""Pause button handler.""" | python | {
"resource": ""
} |
q7380 | Client.updateMovie | train | def updateMovie(self, imageFile):
"""Update the image file as video frame in the GUI."""
try:
photo = ImageTk.PhotoImage(Image.open(imageFile)) #stuck here !!!!!!
except:
print("photo error")
| python | {
"resource": ""
} |
q7381 | Client.sendRtspRequest | train | def sendRtspRequest(self, requestCode):
"""Send RTSP request to the server."""
#-------------
# TO COMPLETE
#-------------
# Setup request
if requestCode == self.SETUP and self.state == self.INIT:
threading.Thread(target=self.recvRtspReply).start()
# Update RTSP sequence number.
# ...
self.rtspSeq = 1
# Write the RTSP request to be sent.
# request = ...
request = "SETUP " + str(self.fileName) + "\n" + str(self.rtspSeq) + "\n" + " RTSP/1.0 RTP/UDP " + str(self.rtpPort)
self.rtspSocket.send(request)
# Keep track of the sent request.
# self.requestSent = ...
self.requestSent = self.SETUP
# Play request
elif requestCode == self.PLAY and self.state == self.READY:
# Update RTSP sequence number.
# ...
self.rtspSeq = self.rtspSeq + 1
# Write the RTSP request to be sent.
# request = ...
request = "PLAY " + "\n" + str(self.rtspSeq)
self.rtspSocket.send(request)
print('-'*60 + "\nPLAY request sent to Server...\n" + '-'*60)
# Keep track of the sent request.
# self.requestSent = ...
self.requestSent = self.PLAY
# Pause request
elif requestCode == self.PAUSE and self.state == self.PLAYING:
# Update RTSP sequence number.
# ...
self.rtspSeq = self.rtspSeq + 1
# Write the RTSP request to be sent.
| python | {
"resource": ""
} |
q7382 | Client.recvRtspReply | train | def recvRtspReply(self):
"""Receive RTSP reply from the server."""
while True:
reply = self.rtspSocket.recv(1024)
if reply:
self.parseRtspReply(reply)
# Close the RTSP socket upon requesting Teardown | python | {
"resource": ""
} |
q7383 | Client.parseRtspReply | train | def parseRtspReply(self, data):
print("Parsing Received Rtsp data...")
"""Parse the RTSP reply from the server."""
lines = data.split('\n')
seqNum = int(lines[1].split(' ')[1])
# Process only if the server reply's sequence number is the same as the request's
if seqNum == self.rtspSeq:
session = int(lines[2].split(' ')[1])
# New RTSP session ID
if self.sessionId == 0:
self.sessionId = session
# Process only if the session ID is the same
if self.sessionId == session:
if int(lines[0].split(' ')[1]) == 200:
if self.requestSent == self.SETUP:
#-------------
# TO COMPLETE
#-------------
# Update RTSP state.
print("Updating RTSP state...")
# self.state = ...
self.state = self.READY
# Open RTP port.
#self.openRtpPort()
| python | {
"resource": ""
} |
q7384 | LocalVideoFeed.preview | train | def preview(self):
""" Blocking function. Opens OpenCV window to display stream. """
win_name = 'Camera'
cv2.namedWindow(win_name, cv2.WINDOW_AUTOSIZE)
cv2.moveWindow(win_name,20,20)
self.open()
while(self.isOpened()):
cv2.imshow(win_name,self._stream.read()[1])
| python | {
"resource": ""
} |
q7385 | Client.createWidgets | train | def createWidgets(self):
"""Build GUI."""
# Create Setup button
self.setup = Button(self.master, width=20, padx=3, pady=3)
self.setup["text"] = "Setup"
self.setup["command"] = self.setupMovie
self.setup.grid(row=1, column=0, padx=2, pady=2)
# Create Play button
self.start = Button(self.master, width=20, padx=3, pady=3)
self.start["text"] = "Play"
self.start["command"] = self.playMovie
self.start.grid(row=1, column=1, padx=2, pady=2)
# Create Pause button
self.pause = Button(self.master, width=20, padx=3, pady=3)
self.pause["text"] = "Pause"
self.pause["command"] = self.pauseMovie | python | {
"resource": ""
} |
q7386 | Client.playMovie | train | def playMovie(self):
"""Play button handler."""
if self.state == self.READY:
# Create a new thread to listen for RTP packets
print "Playing Movie"
threading.Thread(target=self.listenRtp).start()
| python | {
"resource": ""
} |
q7387 | Client.writeFrame | train | def writeFrame(self, data):
"""Write the received frame to a temp image file. Return the image file."""
cachename = CACHE_FILE_NAME + str(self.sessionId) + CACHE_FILE_EXT | python | {
"resource": ""
} |
q7388 | Client.handler | train | def handler(self):
"""Handler on explicitly closing the GUI window."""
self.pauseMovie()
if tkMessageBox.askokcancel("Quit?", "Are you sure you want to quit?"):
self.exitClient()
| python | {
"resource": ""
} |
q7389 | ChatThreadParser.skip | train | def skip(self):
"""
Eats through the input iterator without recording the content.
"""
for pos, element in self.element_iter:
tag, class_attr = | python | {
"resource": ""
} |
q7390 | MessageHtmlParser.should_record_thread | train | def should_record_thread(self, participants):
"""
Determines if the thread should be parsed based on the
participants and the filter given.
For example, if the filter states ['jack', 'billy joe'],
then only threads with exactly two participants
(excluding the owner of the chat history) containing
someone with the first or last name 'Jack' and someone
named 'Billy Joel' will be included.
Any of the following would match that criteria:
- Jack Stevenson, Billy Joel
- Billy Joel, Jack Stevens
- Jack Jenson, Billy Joel
- Jack Jack, Billy Joel
participants -- the participants of the thread
(excluding the history owner)
"""
if not self.thread_filter:
return True
if len(participants) != len(self.thread_filter):
return False
| python | {
"resource": ""
} |
q7391 | MessageHtmlParser.parse_thread | train | def parse_thread(self, participants, element_iter, require_flush):
"""
Parses a thread with appropriate CLI feedback.
:param participants: The participants in this thread.
:param element_iter: The XML iterator to parse the data from.
:param require_flush: Whether the iterator needs to be flushed if it is
determined that the thread should be skipped.
:return: A `ChatThread` object if not skipped, otherwise `None`.
"""
# Very rarely threads may lack information on who the
# participants are. We will consider those threads corrupted
# and skip them.
participants_text = _truncate(', '.join(participants), 60)
if participants:
skip_thread = not self.should_record_thread(participants)
participants_text = yellow("[%s]" % participants_text)
else:
participants_text = "unknown participants"
skip_thread = True
if skip_thread:
line = "\rSkipping chat thread with %s..." % \
yellow(participants_text)
else:
participants_key = ", ".join(participants)
if participants_key in self.chat_threads:
| python | {
"resource": ""
} |
q7392 | LegacyMessageHtmlParser.parse_impl | train | def parse_impl(self):
"""
Parses the HTML content as a stream. This is far less memory
intensive than loading the entire HTML file into memory, like
BeautifulSoup does.
"""
# Cast to str to ensure not unicode under Python 2, as the parser
# doesn't like that.
parser = XMLParser(encoding=str('UTF-8'))
element_iter = ET.iterparse(self.handle, events=("start", "end"), parser=parser)
for pos, element in element_iter:
tag, class_attr = _tag_and_class_attr(element)
if tag == "h1" and pos == "end":
if not self.user: | python | {
"resource": ""
} |
q7393 | messages | train | def messages(path, thread, fmt, nocolor, timezones, utc, noprogress, resolve, directory):
"""
Conversion of Facebook chat history.
"""
with colorize_output(nocolor):
try:
chat_history = _process_history(
path=path, thread=thread, timezones=timezones,
| python | {
"resource": ""
} |
q7394 | stats | train | def stats(path, fmt, nocolor, timezones, utc, noprogress, most_common, resolve, length):
"""Analysis of Facebook chat history."""
with colorize_output(nocolor):
try:
chat_history = _process_history(
path=path, thread='', timezones=timezones,
utc=utc, noprogress=noprogress, resolve=resolve)
except ProcessingFailure:
return
statistics = ChatHistoryStatistics(
chat_history, most_common=None if most_common < 0 else most_common)
if fmt == 'text':
| python | {
"resource": ""
} |
q7395 | set_stream_color | train | def set_stream_color(stream, disabled):
"""
Remember what our original streams were so that we
can colorize them separately, which colorama doesn't
seem to natively support.
"""
original_stdout = sys.stdout
original_stderr = sys.stderr
init(strip=disabled)
if stream != original_stdout:
sys.stdout = original_stdout
| python | {
"resource": ""
} |
q7396 | FacebookNameResolver._manual_lookup | train | def _manual_lookup(self, facebook_id, facebook_id_string):
"""
People who we have not communicated with in a long time
will not appear in the look-ahead cache that Facebook keeps.
We must manually resolve them.
:param facebook_id: Profile ID of the user to lookup.
:return:
"""
resp = self._session.get(
'https://www.facebook.com/%s' % facebook_id,
allow_redirects=True, timeout=10
)
# No point in trying to get this using BeautifulSoup. The HTML here
| python | {
"resource": ""
} |
q7397 | get_exporter | train | def get_exporter(obj, name):
"""
Get an exporter for the
:param obj: object to export
:type obj: :class:`Component <cqparts.Component>`
:param name: registered name of exporter
:type name: :class:`str`
:return: an exporter instance of the given type
:rtype: :class:`Exporter`
:raises TypeError: if exporter cannot be found
"""
if name not in exporter_index:
raise TypeError(
("exporter type '%s' is not registered: " % name) +
("registered types: %r" % sorted(exporter_index.keys()))
| python | {
"resource": ""
} |
q7398 | get_importer | train | def get_importer(cls, name):
"""
Get an importer for the given registered type.
:param cls: class to import
:type cls: :class:`type`
:param name: registered name of importer
:type name: :class:`str`
:return: an importer instance of the given type
:rtype: :class:`Importer`
:raises TypeError: if importer cannot be found
"""
if name not in importer_index:
raise TypeError(
("importer type '%s' is not registered: " % name) +
("registered types: %r" % sorted(importer_index.keys()))
| python | {
"resource": ""
} |
q7399 | BunningsProductSpider.parse | train | def parse(self, response):
"""Parse pagenated list of products"""
# Check if page is out of range
no_more_products = re.search(
r'No matching products were found',
response.css('div.paged-results').extract_first(),
flags=re.I
)
if no_more_products:
pass # no more pages to populate, stop scraping
else:
# Scrape products list
for product in response.css('article.product-list__item'):
product_url = product.css('a::attr("href")').extract_first()
| python | {
"resource": ""
} |
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