code
string
signature
string
docstring
string
loss_without_docstring
float64
loss_with_docstring
float64
factor
float64
while True: s = ''.join([random.SystemRandom().choice(string.digits + string.ascii_letters) for n in range(length)]) if (s not in container): break return s
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 anything else, there is no vulnerability of the token from computation, or possible leakage ...
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3.036939
0.988371
if (self.account_allowed(account)): cookie = self._generate_random_string(self.access_cookies) self.access_cookies[cookie] = int(time.time()) return cookie else: return None
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.
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1.185417
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) ...
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.
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3.107763
1.041649
if (cookie): token = self._generate_random_string(self.access_tokens) self.access_tokens[token] = (cookie, int(time.time())) return token else: return None
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.
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1.207434
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 T...
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.
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1.025273
authz_header = request.headers.get('Authorization', '[none]') if (not authz_header.startswith('Bearer ')): return False token = authz_header[7:] return self.access_token_valid( token, "info_authn: Authorization header")
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.
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authn_cookie = request.cookies.get( self.access_cookie_name, default='[none]') return self.access_cookie_valid(authn_cookie, "image_authn: auth cookie")
def image_authn(self)
Check to see if user if authenticated for image requests. Must have access cookie with an appropriate value.
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1.233969
response = make_response( "<html><script>window.close();</script></html>", 200, {'Content-Type': "text/html"}) response.set_cookie(self.account_cookie_name, expires=0) response.set_cookie(self.access_cookie_name, expires=0) response.headers['Access-Contro...
def logout_handler(self, **args)
Handler for logout button. Delete cookies and return HTML that immediately closes window
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2.58467
1.025939
message_id = request.args.get('messageId', default=None) origin = request.args.get('origin', default='unknown_origin') self.logger.info("access_token_handler: origin = " + origin) account = request.cookies.get(self.account_cookie_name, default='') token = self.access_tok...
def access_token_handler(self, **args)
Get access token based on cookie sent with this request. This handler deals with two cases: 1) Non-browser client (indicated by no messageId set in request) where the response is a simple JSON response. 2) Browser client (indicate by messageId setin request) where the request ...
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1.142537
response = make_response( "<html><script>window.close();</script></html>", 200, {'Content-Type': "text/html"}) response.set_cookie(self.account_cookie_name, account_cookie_value) return response
def set_cookie_close_window_response(self, account_cookie_value)
Response to set account cookie and close window HTML/JavaScript.
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2.619893
1.030998
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'): ...
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.
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1.023517
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 + ' ...
def do_first(self)
Create PNM file from input image file.
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infile = self.tmpfile outfile = self.basename + '.reg' # simeon@ice ~>cat m.pnm | pnmcut 10 10 100 200 > m1.pnm if (x is None): # print "region: full" self.tmpfile = infile else: # print "region: (%d,%d,%d,%d)" % (x,y,w,h) ...
def do_region(self, x, y, w, h)
Apply region selection.
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# simeon@ice ~>cat m1.pnm | pnmscale -width 50 > m2.pnm infile = self.tmpfile outfile = self.basename + '.siz' if (w is None): # print "size: no scaling" self.tmpfile = infile else: # print "size: scaling to (%d,%d)" % (w,h) ...
def do_size(self, w, h)
Apply size scaling.
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infile = self.tmpfile outfile = self.basename + '.col' # Quality (bit-depth): if (quality == 'grey' or quality == 'gray'): if (self.shell_call('cat ' + infile + ' | ' + self.ppmtopgm + ' > ' + outfile)): raise IIIFError( text="Oops...
def do_quality(self, quality)
Apply value of quality parameter.
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infile = self.tmpfile outfile = self.basename + '.out' outfile_jp2 = self.basename + '.jp2' # Now convert finished pnm file to output format # simeon@ice ~>cat m3.pnm | pnmtojpeg > m4.jpg # simeon@ice ~>cat m3.pnm | pnmtotiff > m4.jpg # pnmtotiff: comput...
def do_format(self, format)
Apply format selection.
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try: magic_text = magic.from_file(file) if (isinstance(magic_text, bytes)): # In python2 and travis python3 (?!) decode to get unicode string magic_text = magic_text.decode('utf-8') except (TypeError, IOError): return i...
def file_type(self, file)
Use python-magic to determine file type. Returns 'png' or 'jpg' on success, nothing on failure.
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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( text="Bad output from pnmfile when trying to get size...
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
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return(subprocess.call(self.shellsetup + shellcmd, shell=True))
def shell_call(self, shellcmd)
Shell call with necessary setup first.
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for file in glob.glob(self.basename + '*'): os.unlink(file)
def cleanup(self)
Clean up any temporary files.
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headers = dict(self.headers) if (api_version < '1.1'): headers['Content-Type'] = 'text/xml' response = self.as_xml() else: headers['Content-Type'] = 'text/plain' response = self.as_txt() return(response, self.code, headers)
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 will include the Content-Type ...
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1.136991
# 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) ...
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>
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s = "IIIF Image Server Error\n\n" s += self.text if (self.text) else 'UNKNOWN_ERROR' s += "\n\n" if (self.parameter): s += "parameter=%s\n" % self.parameter if (self.code): s += "code=%d\n\n" % self.code for header in sorted(self.headers):...
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.
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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', 'scope': self.google_api_scope, 'state': self.reques...
def login_handler(self, config=None, prefix=None, **args)
OAuth starts here, redirect user to Google.
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gresponse = self.google_get_token(config, prefix) gdata = self.google_get_data(config, gresponse) email = gdata.get('email', 'NO_EMAIL') name = gdata.get('name', 'NO_NAME') # Make and store cookie from identity, set and close window cookie = self.access_cookie(na...
def home_handler(self, config=None, prefix=None, **args)
Handler for /home redirect path after Google auth. OAuth ends up back here from Google. Set the account cookie and close window to trigger next step.
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params = { 'code': self.request_args_get( 'code', default=''), 'client_id': self.google_api_client_id, 'client_secret': self.google_api_client_secret, 'redirect_uri': self.scheme_host_port_prefix( 'http', co...
def google_get_token(self, config, prefix)
Make request to Google API to get token.
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params = { 'access_token': response['access_token'], } payload = urlencode(params) url = self.google_api_url + 'userinfo?' + payload req = Request(url) json_str = urlopen(req).read() return json.loads(json_str.decode('utf-8'))
def google_get_data(self, config, response)
Make request to Google API to get profile data for the user.
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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'): uri_pattern = r'http://library.stanford.edu/iiif/image-api/1.1/compliance.html#level%d' elif (self.api_version ==...
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.
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# set if specified if (srcfile is not None): self.srcfile = srcfile if (request is not None): self.request = request if (outfile is not None): self.outfile = outfile if (self.outfile is not None): # create path to output di...
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 tempo...
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if (x is not None): raise IIIFError(code=501, parameter="region", text="Null manipulator supports only region=/full/.")
def do_region(self, x, y, w, h)
Null implementation of region selection.
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if (mirror): raise IIIFError(code=501, parameter="rotation", text="Null manipulator does not support mirroring.") if (rot != 0.0): raise IIIFError(code=501, parameter="rotation", text="Null manipulator supports only...
def do_rotation(self, mirror, rot)
Null implementation of rotate and/or mirror.
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if (self.api_version >= '2.0'): if (quality != "default"): raise IIIFError(code=501, parameter="default", text="Null manipulator supports only quality=default.") else: # versions 1.0 and 1.1 if (quality != "native"): ...
def do_quality(self, quality)
Null implementation of quality.
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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 = self.srcfile else: try: ...
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.
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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...
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 ima...
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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 pres...
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 i...
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rotation = self.request.rotation_deg if (no_mirror and self.request.rotation_mirror): raise IIIFError(code=501, parameter="rotation", text="This implementation does not support mirroring.") if (only90s and (rotation != 0.0 and rotation != 90.0 and...
def rotation_to_apply(self, only90s=False, no_mirror=False)
Check and interpret rotation. Returns a truth value as to whether to mirror, and a floating point number 0 <= angle < 360 (degrees).
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if (self.request.quality is None): if (self.api_version <= '1.1'): return('native') else: return('default') return(self.request.quality)
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.
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if (not tile_height): tile_height = tile_width sf = 1 scale_factors = [sf] for j in range(30): # limit of 2^30, should be enough! sf = 2 * sf if (tile_width * sf > self.width and tile_height * sf > self.height): ...
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 ...
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3.544992
1.042434
if (size is None): size = self.sz # Have we go to the smallest element? if (size <= 3): if (_not_diagonal(x, y)): return None else: return (0, 0, 0) divisor = size // 3 if (_not_diagonal(x // divisor, y ...
def pixel(self, x, y, size=None)
Return color for a pixel.
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red = int(n * self.shade_factor) if (red > 255): red = 255 return (red, 50, 100)
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.
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z = z * z + self.c if (abs(z) > 2.0): return self.color(n) n += 1 if (n > self.max_iter): return None return self.mpixel(z, n)
def mpixel(self, z, n=0)
Iteration in Mandlebrot coordinate z.
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x = (ix - self.xoffset + 0.5) / self.scale y = (iy - self.yoffset + 0.5) / self.scale z = complex(x, y) self.set_c(z) return self.mpixel(z)
def pixel(self, ix, iy)
Return color for a pixel. Does translation from image coordinates (ix,iy) into the complex plane coordinate z = x+yi, and then calls self.mpixel(z) to find the color at point z.
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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): ...
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...
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1.030414
# 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 ...
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 im...
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if extra.startswith('/'): extra = extra[1:] r = IIIFRequest(identifier='dummy', api_version=self.api_version) r.parse_url(extra) if (r.info): raise IIIFStaticError("Attempt to specify Image Information in extras.") return(r...
def parse_extra(self, extra)
Parse extra request parameters to IIIFRequest object.
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if (osd_version in self.osd_config): return(self.osd_config[osd_version]) else: raise IIIFStaticError("OpenSeadragon version %s not supported, available versions are %s" % (osd_version, ', '.join(sorted(self.osd_config.keys()))))
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.
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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 ...
def generate(self, src=None, identifier=None)
Generate static files for one source image.
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r = IIIFRequest(identifier=self.identifier, api_version=self.api_version) if (region == 'full'): r.region_full = True else: r.region_xywh = region # [rx,ry,rw,rh] r.size_wh = size # [sw,sh] r.format = 'jpg' self.g...
def generate_tile(self, region, size)
Generate one tile for this given region, size of this image.
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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.dryru...
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...
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# 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]...
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.
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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))...
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_...
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1.013285
if isinstance(key, int): return _get_value_for_key(key, obj, default) return _get_value_for_keys(key.split('.'), obj, default)
def get_value(key, obj, default=missing)
Helper for pulling a keyed value off various types of objects
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for key, val in original.items(): if key not in self.fields: data[key] = val return data
def _handle_load_unknown(self, data, original)
Preserve unknown keys during deserialization.
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for key, val in original.items(): if key not in self.fields: data[key] = val return data
def _handle_dump_unknown(self, data, original)
Preserve unknown keys during deserialization.
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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): validated_data[spec.TAGS] = data[spec.TAGS]...
def validate_headers(spec, data)
Validates headers data and creates the config objects
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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_a...
def validate(spec, data)
Validates the data and creates the config objects
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environment = data.get('environment') if environment and environment.replicas: validate_replicas(data.get('framework'), environment.replicas)
def validate_replicas(self, data)
Validate distributed experiment
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parsed_data = Parser.parse(self, self._data, matrix_declaration) del parsed_data[self.HP_TUNING] validator.validate(spec=self, data=parsed_data) return ExperimentSpecification(values=[parsed_data, {'kind': self._EXPERIMENT}])
def get_experiment_spec(self, matrix_declaration)
Returns an experiment spec for this group spec and the given matrix declaration.
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if BaseSpecification.BUILD not in self._data: return None return BuildConfig.from_dict(self._data[BaseSpecification.BUILD])
def get_build_spec(self)
Returns a build spec for this group spec.
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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 and data.get('bo') is None) ) is_bo = data.get('bo') is not N...
def validate_matrix(self, data)
Validates matrix data and creates the config objects
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if not self._anchor: self._anchor = str(uuid.uuid4()) return self._anchor
def anchor(self)
Generate a html anchor name :return:
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0.999569
cases = [x.html() for x in self.cases] return .format(anchor=self.anchor(), name=tag.text(self.name), count=len(cases), cases="".join(cases))
def html(self)
Render this test class as html :return:
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0.964845
return .format(name=tag.text(self.name), value=tag.text(self.value))
def html(self)
Render those properties as html :return:
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failure = "" skipped = None stdout = tag.text(self.stdout) stderr = tag.text(self.stderr) if self.skipped: skipped = .format(msg=tag.text(self.skipped_msg), skip=tag.text(self.skipped)) if self.failed(): failure = ...
def html(self)
Render this test case as HTML :return:
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tests = list() for testclass in self.classes: tests.extend(self.classes[testclass].cases) return tests
def all(self)
Return all testcases :return:
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return [test for test in self.all() if not test.failed() and not test.skipped()]
def passed(self)
Return all the passing testcases :return:
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fails = "" skips = "" if len(self.failed()): faillist = list() for failure in self.failed(): faillist.append( .format(anchor=failure.anchor(), name=tag.text( fa...
def toc(self)
Return a html table of contents :return:
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classes = list() package = "" if self.package is not None: package = "Package: " + self.package + "<br/>" for classname in self.classes: classes.append(self.classes[classname].html()) errs = "" for error in self.errors: if n...
def html(self)
Render this as html. :return:
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thisdir = os.path.dirname(os.path.abspath(__file__)) with open(os.path.join(thisdir, self.css), "r") as cssfile: return cssfile.read()
def get_css(self)
Return the content of the css file :return:
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suites = None if isinstance(self.tree, ET.Element): root = self.tree else: root = self.tree.getroot() if root.tag == "testrun": root = root[0] if root.tag == "testsuite": suites = [root] if root.tag == "testsuite...
def process(self)
populate the report from the xml :return:
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if len(self.suites) > 1: tochtml = "<ul>" for suite in self.suites: tochtml += '<li><a href="#{anchor}">{name}</a></li>'.format( anchor=suite.anchor(), name=tag.text(suite.name)) tochtml += "</ul>" ...
def toc(self)
If this report has multiple suite results, make a table of contents listing each suite :return:
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page = self.get_html_head() page += "<body><h1>Test Report</h1>" page += self.toc() for suite in self.suites: page += suite.html() page += "</body></html>" return page
def html(self)
Render the test suite as a HTML report with links to errors first. :return:
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(opts, args) = PARSER.parse_args(args) if args else PARSER.parse_args() if not len(args): PARSER.print_usage() sys.exit(1) outfilename = args[0] + ".html" if len(args) > 1: outfilename = args[1] report = parser.Junit(args[0]) html = report.html() with open(out...
def run(args)
Run this tool :param args: :return:
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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[out...
def _generate_remark_str(self, end_of_line = '\n')
Generate a series of remarks that the user should consider when interpreting the summary statistics.
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# 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) likely_cat = set(data.columns) - numeric_cols likely_cat = list(likely_cat - date_...
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.
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return np.nanstd(x.values,ddof=self._ddof)
def _std(self,x)
Compute standard deviation with ddof degrees of freedom
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vals = x.values[~np.isnan(x.values)] try: q1, q3 = np.percentile(vals, [25, 75]) iqr = q3 - q1 low_bound = q1 - (iqr * threshold) high_bound = q3 + (iqr * threshold) outliers = np.where((vals > high_bound) | (vals < low_bound)) ...
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"
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outliers = self._tukey(x, threshold = 1.5) return np.size(outliers)
def _outliers(self,x)
Compute number of outliers
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outliers = self._tukey(x, threshold = 3.0) return np.size(outliers)
def _far_outliers(self,x)
Compute number of "far out" outliers
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# set decimal places if isinstance(self._decimals,int): n = self._decimals elif isinstance(self._decimals,dict): try: n = self._decimals[x.name] except: n = 1 else: n = 1 warnings.warn('T...
def _t1_summary(self,x)
Compute median [IQR] or mean (Std) for the input series. Parameters ---------- x : pandas Series Series of values to be summarised.
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aggfuncs = [pd.Series.count,np.mean,np.median,self._std, self._q25,self._q75,min,max,self._t1_summary,self._diptest, self._outliers,self._far_outliers,self._normaltest] # coerce continuous data to numeric cont_data = data[self._continuous].apply(pd.to_numeric, e...
def _create_cont_describe(self,data)
Describe the continuous data. Parameters ---------- data : pandas DataFrame The input dataset. Returns ---------- df_cont : pandas DataFrame Summarise the continuous variables.
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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 ...
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.
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# 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.inde...
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 ...
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# 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') ...
def _create_cont_table(self,data)
Create tableone for continuous data. Returns ---------- table : pandas DataFrame A table summarising the continuous variables.
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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) ...
def _create_cat_table(self,data)
Create table one for categorical data. Returns ---------- table : pandas DataFrame A table summarising the categorical variables.
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# start with the original column names labels = {} for c in self._columns: labels[c] = c # replace column names with alternative names if provided if self._alt_labels: for k in self._alt_labels.keys(): labels[k] = self...
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.
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''' Scale factor for one-dimensional plug-in bandwidth selection. ''' if deriv_order == 0: return (3.0*nbr_data_pts/4)**(-1.0/5) if deriv_order == 2: return (7.0*nbr_data_pts/4)**(-1.0/9) raise ValueError('Not implemented for derivative of order {}'.format(deriv_order))
def bandwidth_factor(nbr_data_pts, deriv_order=0)
Scale factor for one-dimensional plug-in bandwidth selection.
4.533295
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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 like '_class' # to be used as a CSS class specification instead of ...
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") ...
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4.388627
0.95489
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.p...
def _range(self, link_map, radius)
Return range of linked pages to substiture placeholder in pattern
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text = item["value"] target_url = item["href"] if not item["href"] or item["type"] in ("span", "current_page"): if item["attrs"]: text = make_html_tag("span", **item["attrs"]) + text + "</span>" return text return make_html_tag("a", text...
def default_link_tag(item)
Create an A-HREF tag that points to another page.
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'''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)...
def tag(self, corpus, tokenize=True)
Tags a string `corpus`.
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'''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 ...
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 it...
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'''Load a pickled model.''' try: w_td_c = pickle.load(open(loc, 'rb')) except IOError: msg = ("Missing trontagger.pickle file.") raise MissingCorpusError(msg) self.model.weights, self.tagdict, self.classes = w_td_c self.model.classes = self.cla...
def load(self, loc)
Load a pickled model.
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'''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 word[0] != '-': return '!HYPHEN' elif ...
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
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'''Map tokens into a feature representation, implemented as a {hashable: float} dict. If the features change, a new model must be trained. ''' def add(name, *args): features[' '.join((name,) + tuple(args))] += 1 i += len(self.START) features = default...
def _get_features(self, i, word, context, prev, prev2)
Map tokens into a feature representation, implemented as a {hashable: float} dict. If the features change, a new model must be trained.
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'''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) freq_thresh = 20 ambiguity_th...
def _make_tagdict(self, sentences)
Make a tag dictionary for single-tag words.
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'''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) guess, score = max(...
def train(nr_iter, examples)
Return an averaged perceptron model trained on ``examples`` for ``nr_iter`` iterations.
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2.816963
1.409017
timestamp = int(time()) header = bytearray(HEADER_SIZE) # Fill the header bytearray with RTP header fields # ... header[0] = header[0] | V << 6; header[0] = header[0] | P << 5; header[0] = header[0] | X << 4; header[0] = header[0] | CC; ...
def encode(self, V, P, X, CC, seqNum, M, PT, SSRC, payload)
Encode the RTP packet with header fields and payload.
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self.header = bytearray(byteStream[:HEADER_SIZE]) self.payload = byteStream[HEADER_SIZE:]
def decode(self, byteStream)
Decode the RTP packet.
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timestamp = self.header[4] << 24 | self.header[5] << 16 | self.header[6] << 8 | self.header[7] return int(timestamp)
def timestamp(self)
Return timestamp.
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