body stringlengths 26 98.2k | body_hash int64 -9,222,864,604,528,158,000 9,221,803,474B | docstring stringlengths 1 16.8k | path stringlengths 5 230 | name stringlengths 1 96 | repository_name stringlengths 7 89 | lang stringclasses 1
value | body_without_docstring stringlengths 20 98.2k |
|---|---|---|---|---|---|---|---|
def norm_image(img):
' normalize image input '
img = img.astype(np.float32)
var = np.var(img, axis=(0, 1), keepdims=True)
mean = np.mean(img, axis=(0, 1), keepdims=True)
return ((img - mean) / (np.sqrt(var) + 1e-07)) | -7,654,316,233,144,809,000 | normalize image input | pointmvsnet/utils/preprocess.py | norm_image | HelenYang1999/PointMVSNet | python | def norm_image(img):
' '
img = img.astype(np.float32)
var = np.var(img, axis=(0, 1), keepdims=True)
mean = np.mean(img, axis=(0, 1), keepdims=True)
return ((img - mean) / (np.sqrt(var) + 1e-07)) |
def mask_depth_image(depth_image, min_depth, max_depth):
' mask out-of-range pixel to zero '
(ret, depth_image) = cv2.threshold(depth_image, min_depth, 100000, cv2.THRESH_TOZERO)
(ret, depth_image) = cv2.threshold(depth_image, max_depth, 100000, cv2.THRESH_TOZERO_INV)
depth_image = np.expand_dims(depth_... | 8,688,576,601,985,990,000 | mask out-of-range pixel to zero | pointmvsnet/utils/preprocess.py | mask_depth_image | HelenYang1999/PointMVSNet | python | def mask_depth_image(depth_image, min_depth, max_depth):
' '
(ret, depth_image) = cv2.threshold(depth_image, min_depth, 100000, cv2.THRESH_TOZERO)
(ret, depth_image) = cv2.threshold(depth_image, max_depth, 100000, cv2.THRESH_TOZERO_INV)
depth_image = np.expand_dims(depth_image, 2)
return depth_imag... |
def scale_camera(cam, scale=1):
' resize input in order to produce sampled depth map '
new_cam = np.copy(cam)
new_cam[1][0][0] = (cam[1][0][0] * scale)
new_cam[1][1][1] = (cam[1][1][1] * scale)
new_cam[1][0][2] = (cam[1][0][2] * scale)
new_cam[1][1][2] = (cam[1][1][2] * scale)
return new_cam | 4,383,178,012,230,633,500 | resize input in order to produce sampled depth map | pointmvsnet/utils/preprocess.py | scale_camera | HelenYang1999/PointMVSNet | python | def scale_camera(cam, scale=1):
' '
new_cam = np.copy(cam)
new_cam[1][0][0] = (cam[1][0][0] * scale)
new_cam[1][1][1] = (cam[1][1][1] * scale)
new_cam[1][0][2] = (cam[1][0][2] * scale)
new_cam[1][1][2] = (cam[1][1][2] * scale)
return new_cam |
def scale_image(image, scale=1, interpolation='linear'):
' resize image using cv2 '
if (interpolation == 'linear'):
return cv2.resize(image, None, fx=scale, fy=scale, interpolation=cv2.INTER_LINEAR)
if (interpolation == 'nearest'):
return cv2.resize(image, None, fx=scale, fy=scale, interpola... | -4,197,485,392,155,788,300 | resize image using cv2 | pointmvsnet/utils/preprocess.py | scale_image | HelenYang1999/PointMVSNet | python | def scale_image(image, scale=1, interpolation='linear'):
' '
if (interpolation == 'linear'):
return cv2.resize(image, None, fx=scale, fy=scale, interpolation=cv2.INTER_LINEAR)
if (interpolation == 'nearest'):
return cv2.resize(image, None, fx=scale, fy=scale, interpolation=cv2.INTER_NEAREST... |
def scale_dtu_input(images, cams, depth_image=None, scale=1):
' resize input to fit into the memory '
for view in range(len(images)):
images[view] = scale_image(images[view], scale=scale)
cams[view] = scale_camera(cams[view], scale=scale)
if (depth_image is None):
return (images, cam... | 1,560,582,490,733,520,600 | resize input to fit into the memory | pointmvsnet/utils/preprocess.py | scale_dtu_input | HelenYang1999/PointMVSNet | python | def scale_dtu_input(images, cams, depth_image=None, scale=1):
' '
for view in range(len(images)):
images[view] = scale_image(images[view], scale=scale)
cams[view] = scale_camera(cams[view], scale=scale)
if (depth_image is None):
return (images, cams)
else:
depth_image = ... |
def crop_dtu_input(images, cams, height, width, base_image_size, depth_image=None):
' resize images and cameras to fit the network (can be divided by base image size) '
for view in range(len(images)):
(h, w) = images[view].shape[0:2]
new_h = h
new_w = w
if (new_h > height):
... | -1,744,585,627,397,484,500 | resize images and cameras to fit the network (can be divided by base image size) | pointmvsnet/utils/preprocess.py | crop_dtu_input | HelenYang1999/PointMVSNet | python | def crop_dtu_input(images, cams, height, width, base_image_size, depth_image=None):
' '
for view in range(len(images)):
(h, w) = images[view].shape[0:2]
new_h = h
new_w = w
if (new_h > height):
new_h = height
else:
new_h = int((math.floor((h / bas... |
def name_conversion(caffe_layer_name):
' Convert a caffe parameter name to a tensorflow parameter name as\n defined in the above model '
NAME_MAP = {'bn_conv1/beta': 'conv0/bn/beta', 'bn_conv1/gamma': 'conv0/bn/gamma', 'bn_conv1/mean/EMA': 'conv0/bn/mean/EMA', 'bn_conv1/variance/EMA': 'conv0/bn/variance/... | 4,674,075,818,243,747,000 | Convert a caffe parameter name to a tensorflow parameter name as
defined in the above model | OLD/models/resnet/old/resnet_orig.py | name_conversion | ivankreso/semseg | python | def name_conversion(caffe_layer_name):
' Convert a caffe parameter name to a tensorflow parameter name as\n defined in the above model '
NAME_MAP = {'bn_conv1/beta': 'conv0/bn/beta', 'bn_conv1/gamma': 'conv0/bn/gamma', 'bn_conv1/mean/EMA': 'conv0/bn/mean/EMA', 'bn_conv1/variance/EMA': 'conv0/bn/variance/... |
def get_user():
'Get some information on the currently logged in user.\n\n :return: a dictionary representing user data (see\n `here <https://okpy.github.io/documentation/ok-api.html#users-view-a-specific-user>`_\n for an example)\n '
key = session.get('access_token')
if (key in USER_CAC... | 6,196,782,119,812,872,000 | Get some information on the currently logged in user.
:return: a dictionary representing user data (see
`here <https://okpy.github.io/documentation/ok-api.html#users-view-a-specific-user>`_
for an example) | common/oauth_client.py | get_user | Cal-CS-61A-Staff/cs61a-apps | python | def get_user():
'Get some information on the currently logged in user.\n\n :return: a dictionary representing user data (see\n `here <https://okpy.github.io/documentation/ok-api.html#users-view-a-specific-user>`_\n for an example)\n '
key = session.get('access_token')
if (key in USER_CAC... |
def is_logged_in():
'Get whether the current user is logged into the current session.\n\n :return: ``True`` if the user is logged in, ``False`` otherwise\n '
return ('access_token' in session) | -8,151,700,589,570,362,000 | Get whether the current user is logged into the current session.
:return: ``True`` if the user is logged in, ``False`` otherwise | common/oauth_client.py | is_logged_in | Cal-CS-61A-Staff/cs61a-apps | python | def is_logged_in():
'Get whether the current user is logged into the current session.\n\n :return: ``True`` if the user is logged in, ``False`` otherwise\n '
return ('access_token' in session) |
def is_staff(course):
'Get whether the current user is enrolled as staff, instructor, or grader\n for ``course``.\n\n :param course: the course code to check\n :type course: str\n\n :return: ``True`` if the user is on staff, ``False`` otherwise\n '
return is_enrolled(course, roles=AUTHORIZED_ROLE... | -8,157,216,457,308,771,000 | Get whether the current user is enrolled as staff, instructor, or grader
for ``course``.
:param course: the course code to check
:type course: str
:return: ``True`` if the user is on staff, ``False`` otherwise | common/oauth_client.py | is_staff | Cal-CS-61A-Staff/cs61a-apps | python | def is_staff(course):
'Get whether the current user is enrolled as staff, instructor, or grader\n for ``course``.\n\n :param course: the course code to check\n :type course: str\n\n :return: ``True`` if the user is on staff, ``False`` otherwise\n '
return is_enrolled(course, roles=AUTHORIZED_ROLE... |
def is_enrolled(course, *, roles=None):
'Check whether the current user is enrolled as any of the ``roles`` for\n ``course``.\n\n :param course: the course code to check\n :type course: str\n\n :param roles: the roles to check for the user\n :type roles: list-like\n\n :return: ``True`` if the user... | 5,020,490,595,609,173,000 | Check whether the current user is enrolled as any of the ``roles`` for
``course``.
:param course: the course code to check
:type course: str
:param roles: the roles to check for the user
:type roles: list-like
:return: ``True`` if the user is any of ``roles``, ``False`` otherwise | common/oauth_client.py | is_enrolled | Cal-CS-61A-Staff/cs61a-apps | python | def is_enrolled(course, *, roles=None):
'Check whether the current user is enrolled as any of the ``roles`` for\n ``course``.\n\n :param course: the course code to check\n :type course: str\n\n :param roles: the roles to check for the user\n :type roles: list-like\n\n :return: ``True`` if the user... |
def login():
'Store the current URL as the redirect target on success, then redirect\n to the login endpoint for the current app.\n\n :return: a :func:`~flask.redirect` to the login endpoint for the current\n :class:`~flask.Flask` app.\n '
session[REDIRECT_KEY] = urlparse(request.url)._replace(net... | 1,697,452,798,553,529,900 | Store the current URL as the redirect target on success, then redirect
to the login endpoint for the current app.
:return: a :func:`~flask.redirect` to the login endpoint for the current
:class:`~flask.Flask` app. | common/oauth_client.py | login | Cal-CS-61A-Staff/cs61a-apps | python | def login():
'Store the current URL as the redirect target on success, then redirect\n to the login endpoint for the current app.\n\n :return: a :func:`~flask.redirect` to the login endpoint for the current\n :class:`~flask.Flask` app.\n '
session[REDIRECT_KEY] = urlparse(request.url)._replace(net... |
def create_oauth_client(app: flask.Flask, consumer_key, secret_key=None, success_callback=None, return_response=None):
'Add Okpy OAuth for ``consumer_key`` to the current ``app``.\n\n Specifically, adds an endpoint ``/oauth/login`` that redirects to the Okpy\n login process, ``/oauth/authorized`` that receive... | -9,096,652,486,940,746,000 | Add Okpy OAuth for ``consumer_key`` to the current ``app``.
Specifically, adds an endpoint ``/oauth/login`` that redirects to the Okpy
login process, ``/oauth/authorized`` that receives the successful result
of authentication, ``/api/user`` that acts as a test endpoint, and a
:meth:`~flask_oauthlib.client.OAuthRemoteA... | common/oauth_client.py | create_oauth_client | Cal-CS-61A-Staff/cs61a-apps | python | def create_oauth_client(app: flask.Flask, consumer_key, secret_key=None, success_callback=None, return_response=None):
'Add Okpy OAuth for ``consumer_key`` to the current ``app``.\n\n Specifically, adds an endpoint ``/oauth/login`` that redirects to the Okpy\n login process, ``/oauth/authorized`` that receive... |
def check_req(uri, headers, body):
'Add access_token to the URL Request.'
if (('access_token' not in uri) and session.get('access_token')):
params = {'access_token': session.get('access_token')[0]}
url_parts = list(urllib.parse.urlparse(uri))
query = dict(urllib.parse.parse_qsl(url_parts... | 7,666,162,397,214,519,000 | Add access_token to the URL Request. | common/oauth_client.py | check_req | Cal-CS-61A-Staff/cs61a-apps | python | def check_req(uri, headers, body):
if (('access_token' not in uri) and session.get('access_token')):
params = {'access_token': session.get('access_token')[0]}
url_parts = list(urllib.parse.urlparse(uri))
query = dict(urllib.parse.parse_qsl(url_parts[4]))
query.update(params)
... |
def test_basic(self):
'\n Nothing special. Just test basic things.\n '
seed = 12
n = 100
alpha = 0.01
for d in [1, 4]:
mean = np.zeros(d)
variance = 1
isonorm = density.IsotropicNormal(mean, variance)
draw_mean = (mean + 0)
draw_variance = (varia... | 5,533,466,314,435,505,000 | Nothing special. Just test basic things. | sbibm/third_party/kgof/test/test_goftest.py | test_basic | mackelab/sbibm | python | def test_basic(self):
'\n \n '
seed = 12
n = 100
alpha = 0.01
for d in [1, 4]:
mean = np.zeros(d)
variance = 1
isonorm = density.IsotropicNormal(mean, variance)
draw_mean = (mean + 0)
draw_variance = (variance + 1)
X = ((util.randn(n, d, ... |
def test_optimized_fssd(self):
'\n Test FSSD test with parameter optimization.\n '
seed = 4
n = 179
alpha = 0.01
for d in [1, 3]:
mean = np.zeros(d)
variance = 1.0
p = density.IsotropicNormal(mean, variance)
ds = data.DSIsotropicNormal((mean + 4), (varia... | -1,259,890,528,971,646,200 | Test FSSD test with parameter optimization. | sbibm/third_party/kgof/test/test_goftest.py | test_optimized_fssd | mackelab/sbibm | python | def test_optimized_fssd(self):
'\n \n '
seed = 4
n = 179
alpha = 0.01
for d in [1, 3]:
mean = np.zeros(d)
variance = 1.0
p = density.IsotropicNormal(mean, variance)
ds = data.DSIsotropicNormal((mean + 4), (variance + 0))
dat = ds.sample(n, seed=s... |
def test_auto_init_opt_fssd(self):
'\n Test FSSD-opt test with automatic parameter initialization.\n '
seed = 5
n = 191
alpha = 0.01
for d in [1, 4]:
mean = np.zeros(d)
variance = 1.0
p = density.IsotropicNormal(mean, variance)
ds = data.DSIsotropicNorma... | 1,894,790,402,833,506,300 | Test FSSD-opt test with automatic parameter initialization. | sbibm/third_party/kgof/test/test_goftest.py | test_auto_init_opt_fssd | mackelab/sbibm | python | def test_auto_init_opt_fssd(self):
'\n \n '
seed = 5
n = 191
alpha = 0.01
for d in [1, 4]:
mean = np.zeros(d)
variance = 1.0
p = density.IsotropicNormal(mean, variance)
ds = data.DSIsotropicNormal((mean + 4), (variance + 0))
dat = ds.sample(n, se... |
def get_credential(file_path):
'\n Read credential json file and return\n username and password\n '
with open(file_path) as json_file:
config = json.load(json_file)
assert ('username' in config.keys())
assert ('password' in config.keys())
return (config['username'], config['... | 6,389,215,783,756,562,000 | Read credential json file and return
username and password | geeup/config.py | get_credential | thipokKub/geeup | python | def get_credential(file_path):
'\n Read credential json file and return\n username and password\n '
with open(file_path) as json_file:
config = json.load(json_file)
assert ('username' in config.keys())
assert ('password' in config.keys())
return (config['username'], config['... |
def _get_brew_commands(brew_path_prefix):
'To get brew default commands on local environment'
brew_cmd_path = (brew_path_prefix + BREW_CMD_PATH)
return [name[:(- 3)] for name in os.listdir(brew_cmd_path) if name.endswith(('.rb', '.sh'))] | -7,131,222,363,745,886,000 | To get brew default commands on local environment | therandy/rules/brew_unknown_command.py | _get_brew_commands | benmonro/thefuck | python | def _get_brew_commands(brew_path_prefix):
brew_cmd_path = (brew_path_prefix + BREW_CMD_PATH)
return [name[:(- 3)] for name in os.listdir(brew_cmd_path) if name.endswith(('.rb', '.sh'))] |
def _get_brew_tap_specific_commands(brew_path_prefix):
"To get tap's specific commands\n https://github.com/Homebrew/homebrew/blob/master/Library/brew.rb#L115"
commands = []
brew_taps_path = (brew_path_prefix + TAP_PATH)
for user in _get_directory_names_only(brew_taps_path):
taps = _get_direc... | 2,850,429,382,632,408,600 | To get tap's specific commands
https://github.com/Homebrew/homebrew/blob/master/Library/brew.rb#L115 | therandy/rules/brew_unknown_command.py | _get_brew_tap_specific_commands | benmonro/thefuck | python | def _get_brew_tap_specific_commands(brew_path_prefix):
"To get tap's specific commands\n https://github.com/Homebrew/homebrew/blob/master/Library/brew.rb#L115"
commands = []
brew_taps_path = (brew_path_prefix + TAP_PATH)
for user in _get_directory_names_only(brew_taps_path):
taps = _get_direc... |
def deredden(wl, Av, thres=None, mags=True):
'Takes in wavelength array in microns. Valid between .1200 um and 1e4 microns.'
if (thres is not None):
Av_lo = thresh
else:
Av_lo = 0.0
Av_me = 2.325
if (Av_lo >= Av_me):
Av_lo = 0.0
Av_hi = 7.75
if (Av >= Av_hi):
... | 4,073,037,764,587,191,300 | Takes in wavelength array in microns. Valid between .1200 um and 1e4 microns. | deredden.py | deredden | Circumstellar/MichaelJordan | python | def deredden(wl, Av, thres=None, mags=True):
if (thres is not None):
Av_lo = thresh
else:
Av_lo = 0.0
Av_me = 2.325
if (Av_lo >= Av_me):
Av_lo = 0.0
Av_hi = 7.75
if (Av >= Av_hi):
AA = A3
AvAk = 7.75
if ((Av >= Av_me) and (Av < Av_hi)):
AA... |
def av_point(wl):
'call this, get grid. multiply grid by Av to get redenning at that wavelength.'
AK_AV = (1 / 7.75)
Alambda_func = interp1d(awl, (AK_AV * A2), kind='linear')
return Alambda_func(wl) | -2,218,628,577,367,212,000 | call this, get grid. multiply grid by Av to get redenning at that wavelength. | deredden.py | av_point | Circumstellar/MichaelJordan | python | def av_point(wl):
AK_AV = (1 / 7.75)
Alambda_func = interp1d(awl, (AK_AV * A2), kind='linear')
return Alambda_func(wl) |
def plot_curve():
'To test implementation'
fig = plt.figure()
ax = fig.add_subplot(111)
wl = np.linspace(0.13, 10, num=300)
ax.plot(wl, deredden(wl, 0.2, mags=False), label='0.2 mags')
ax.plot(wl, deredden(wl, 1.0, mags=False), label='1.0 mags')
ax.plot(wl, deredden(wl, 2.0, mags=False), lab... | -1,493,725,952,206,239,700 | To test implementation | deredden.py | plot_curve | Circumstellar/MichaelJordan | python | def plot_curve():
fig = plt.figure()
ax = fig.add_subplot(111)
wl = np.linspace(0.13, 10, num=300)
ax.plot(wl, deredden(wl, 0.2, mags=False), label='0.2 mags')
ax.plot(wl, deredden(wl, 1.0, mags=False), label='1.0 mags')
ax.plot(wl, deredden(wl, 2.0, mags=False), label='2.0 mags')
avs =... |
def crossword_puzzle(crossword, words):
'resuelve el puzzle'
palabras = words.split(';')
puzzle_y = len(crossword)
puzzle_x = len(crossword[0])
pos = []
for i in palabras:
pos.append([0, 0, 'x', 1])
cruces = []
sig = 0
j = 0
while (j < puzzle_y):
i = 0
whi... | -4,003,197,384,186,380,300 | resuelve el puzzle | Interview Preparation Kit/Crossword puzzle/test.py | crossword_puzzle | pablosambuco/hackerrank | python | def crossword_puzzle(crossword, words):
palabras = words.split(';')
puzzle_y = len(crossword)
puzzle_x = len(crossword[0])
pos = []
for i in palabras:
pos.append([0, 0, 'x', 1])
cruces = []
sig = 0
j = 0
while (j < puzzle_y):
i = 0
while (i < puzzle_x):
... |
def __init__(self, examples: List[InputExample], model: SentenceTransformer):
'\n Create a new SentencesDataset with the tokenized texts and the labels as Tensor\n\n :param examples\n A list of sentence.transformers.readers.InputExample\n :param model:\n SentenceTransforme... | -3,154,989,297,737,877,000 | Create a new SentencesDataset with the tokenized texts and the labels as Tensor
:param examples
A list of sentence.transformers.readers.InputExample
:param model:
SentenceTransformerModel | ai/KoSentenceBERTchatbot/KoSentenceBERT/sentence_transformers/datasets/SentencesDataset.py | __init__ | 21WelfareForEveryone/WelfareForEveryOne | python | def __init__(self, examples: List[InputExample], model: SentenceTransformer):
'\n Create a new SentencesDataset with the tokenized texts and the labels as Tensor\n\n :param examples\n A list of sentence.transformers.readers.InputExample\n :param model:\n SentenceTransforme... |
def __init__(self, arg):
'Initializer.'
self.unicode = arg | -8,964,490,851,056,809,000 | Initializer. | pywikibot/exceptions.py | __init__ | 5j9/pywikibot-core | python | def __init__(self, arg):
self.unicode = arg |
def __unicode__(self):
'Return a unicode string representation.'
return self.unicode | 1,624,013,564,949,944,000 | Return a unicode string representation. | pywikibot/exceptions.py | __unicode__ | 5j9/pywikibot-core | python | def __unicode__(self):
return self.unicode |
def __init__(self, page, message=None):
'\n Initializer.\n\n @param page: Page that caused the exception\n @type page: Page object\n '
if message:
self.message = message
if (self.message is None):
raise Error("PageRelatedError is abstract. Can't instantiate it!")
... | 7,965,796,348,036,239,000 | Initializer.
@param page: Page that caused the exception
@type page: Page object | pywikibot/exceptions.py | __init__ | 5j9/pywikibot-core | python | def __init__(self, page, message=None):
'\n Initializer.\n\n @param page: Page that caused the exception\n @type page: Page object\n '
if message:
self.message = message
if (self.message is None):
raise Error("PageRelatedError is abstract. Can't instantiate it!")
... |
def getPage(self):
'Return the page related to the exception.'
return self.page | -1,200,712,620,631,938,600 | Return the page related to the exception. | pywikibot/exceptions.py | getPage | 5j9/pywikibot-core | python | def getPage(self):
return self.page |
@property
def args(self):
'Expose args.'
return UnicodeType(self) | -8,302,144,525,297,302,000 | Expose args. | pywikibot/exceptions.py | args | 5j9/pywikibot-core | python | @property
def args(self):
return UnicodeType(self) |
def __init__(self, page, reason):
'Initializer.\n\n @param reason: Details of the problem\n @type reason: Exception or basestring\n '
self.reason = reason
super(OtherPageSaveError, self).__init__(page) | -3,950,668,738,290,114,000 | Initializer.
@param reason: Details of the problem
@type reason: Exception or basestring | pywikibot/exceptions.py | __init__ | 5j9/pywikibot-core | python | def __init__(self, page, reason):
'Initializer.\n\n @param reason: Details of the problem\n @type reason: Exception or basestring\n '
self.reason = reason
super(OtherPageSaveError, self).__init__(page) |
@property
def args(self):
'Expose args.'
return UnicodeType(self.reason) | 7,017,165,845,139,401,000 | Expose args. | pywikibot/exceptions.py | args | 5j9/pywikibot-core | python | @property
def args(self):
return UnicodeType(self.reason) |
def __init__(self, page, actual):
'Initializer.\n\n @param page: Page that caused the exception\n @type page: Page object\n @param actual: title obtained by query\n @type reason: basestring\n\n '
self.message = "Query on %s returned data on '{0}'".format(actual)
super(Inco... | 2,277,487,012,330,932 | Initializer.
@param page: Page that caused the exception
@type page: Page object
@param actual: title obtained by query
@type reason: basestring | pywikibot/exceptions.py | __init__ | 5j9/pywikibot-core | python | def __init__(self, page, actual):
'Initializer.\n\n @param page: Page that caused the exception\n @type page: Page object\n @param actual: title obtained by query\n @type reason: basestring\n\n '
self.message = "Query on %s returned data on '{0}'".format(actual)
super(Inco... |
def __init__(self, page, target_page):
'Initializer.\n\n @param target_page: Target page of the redirect.\n @type reason: Page\n '
self.target_page = target_page
self.target_site = target_page.site
super(InterwikiRedirectPage, self).__init__(page) | -5,216,264,096,626,498,000 | Initializer.
@param target_page: Target page of the redirect.
@type reason: Page | pywikibot/exceptions.py | __init__ | 5j9/pywikibot-core | python | def __init__(self, page, target_page):
'Initializer.\n\n @param target_page: Target page of the redirect.\n @type reason: Page\n '
self.target_page = target_page
self.target_site = target_page.site
super(InterwikiRedirectPage, self).__init__(page) |
def __init__(self, page, url):
'Initializer.'
self.url = url
super(SpamfilterError, self).__init__(page) | 3,758,174,467,263,864,300 | Initializer. | pywikibot/exceptions.py | __init__ | 5j9/pywikibot-core | python | def __init__(self, page, url):
self.url = url
super(SpamfilterError, self).__init__(page) |
def read_xml(in_path):
"''读取并解析xml文件\n in_path: xml路径\n return: ElementTree"
tree = ET.parse(in_path)
return tree | 8,835,205,006,990,970,000 | ''读取并解析xml文件
in_path: xml路径
return: ElementTree | development/server/algorithm/tf_faster_rcnn/data_processing/utils/xml_utils.py | read_xml | FMsunyh/re_com | python | def read_xml(in_path):
"读取并解析xml文件\n in_path: xml路径\n return: ElementTree"
tree = ET.parse(in_path)
return tree |
def write_xml(tree, out_path):
"''将xml文件写出\n tree: xml树\n out_path: 写出路径"
tree.write(out_path, encoding='utf-8', xml_declaration=True) | -1,444,820,771,893,487,400 | ''将xml文件写出
tree: xml树
out_path: 写出路径 | development/server/algorithm/tf_faster_rcnn/data_processing/utils/xml_utils.py | write_xml | FMsunyh/re_com | python | def write_xml(tree, out_path):
"将xml文件写出\n tree: xml树\n out_path: 写出路径"
tree.write(out_path, encoding='utf-8', xml_declaration=True) |
def if_match(node, kv_map):
"''判断某个节点是否包含所有传入参数属性\n node: 节点\n kv_map: 属性及属性值组成的map"
for key in kv_map:
if (node.get(key) != kv_map.get(key)):
return False
return True | 127,641,780,045,138,930 | ''判断某个节点是否包含所有传入参数属性
node: 节点
kv_map: 属性及属性值组成的map | development/server/algorithm/tf_faster_rcnn/data_processing/utils/xml_utils.py | if_match | FMsunyh/re_com | python | def if_match(node, kv_map):
"判断某个节点是否包含所有传入参数属性\n node: 节点\n kv_map: 属性及属性值组成的map"
for key in kv_map:
if (node.get(key) != kv_map.get(key)):
return False
return True |
def find_nodes(tree, path):
"''查找某个路径匹配的所有节点\n tree: xml树\n path: 节点路径"
return tree.findall(path) | -5,645,736,712,039,072,000 | ''查找某个路径匹配的所有节点
tree: xml树
path: 节点路径 | development/server/algorithm/tf_faster_rcnn/data_processing/utils/xml_utils.py | find_nodes | FMsunyh/re_com | python | def find_nodes(tree, path):
"查找某个路径匹配的所有节点\n tree: xml树\n path: 节点路径"
return tree.findall(path) |
def get_node_by_keyvalue(nodelist, kv_map):
"''根据属性及属性值定位符合的节点，返回节点\n nodelist: 节点列表\n kv_map: 匹配属性及属性值map"
result_nodes = []
for node in nodelist:
if if_match(node, kv_map):
result_nodes.append(node)
return result_nodes | -5,938,531,185,539,646,000 | ''根据属性及属性值定位符合的节点，返回节点
nodelist: 节点列表
kv_map: 匹配属性及属性值map | development/server/algorithm/tf_faster_rcnn/data_processing/utils/xml_utils.py | get_node_by_keyvalue | FMsunyh/re_com | python | def get_node_by_keyvalue(nodelist, kv_map):
"根据属性及属性值定位符合的节点，返回节点\n nodelist: 节点列表\n kv_map: 匹配属性及属性值map"
result_nodes = []
for node in nodelist:
if if_match(node, kv_map):
result_nodes.append(node)
return result_nodes |
def change_node_properties(nodelist, kv_map, is_delete=False):
"''修改/增加 /删除 节点的属性及属性值\n nodelist: 节点列表\n kv_map:属性及属性值map"
for node in nodelist:
for key in kv_map:
if is_delete:
if (key in node.attrib):
del node.attrib[key]
else:
... | 779,558,524,508,461,300 | ''修改/增加 /删除 节点的属性及属性值
nodelist: 节点列表
kv_map:属性及属性值map | development/server/algorithm/tf_faster_rcnn/data_processing/utils/xml_utils.py | change_node_properties | FMsunyh/re_com | python | def change_node_properties(nodelist, kv_map, is_delete=False):
"修改/增加 /删除 节点的属性及属性值\n nodelist: 节点列表\n kv_map:属性及属性值map"
for node in nodelist:
for key in kv_map:
if is_delete:
if (key in node.attrib):
del node.attrib[key]
else:
... |
def change_node_text(nodelist, text, is_add=False, is_delete=False):
"''改变/增加/删除一个节点的文本\n nodelist:节点列表\n text : 更新后的文本"
for node in nodelist:
if is_add:
node.text += text
elif is_delete:
node.text = ''
else:
node.text = text | 3,084,204,722,422,220,000 | ''改变/增加/删除一个节点的文本
nodelist:节点列表
text : 更新后的文本 | development/server/algorithm/tf_faster_rcnn/data_processing/utils/xml_utils.py | change_node_text | FMsunyh/re_com | python | def change_node_text(nodelist, text, is_add=False, is_delete=False):
"改变/增加/删除一个节点的文本\n nodelist:节点列表\n text : 更新后的文本"
for node in nodelist:
if is_add:
node.text += text
elif is_delete:
node.text =
else:
node.text = text |
def create_node(tag, property_map, content):
"''新造一个节点\n tag:节点标签\n property_map:属性及属性值map\n content: 节点闭合标签里的文本内容\n return 新节点"
element = Element(tag, property_map)
element.text = content
return element | -192,267,518,851,284,300 | ''新造一个节点
tag:节点标签
property_map:属性及属性值map
content: 节点闭合标签里的文本内容
return 新节点 | development/server/algorithm/tf_faster_rcnn/data_processing/utils/xml_utils.py | create_node | FMsunyh/re_com | python | def create_node(tag, property_map, content):
"新造一个节点\n tag:节点标签\n property_map:属性及属性值map\n content: 节点闭合标签里的文本内容\n return 新节点"
element = Element(tag, property_map)
element.text = content
return element |
def add_child_node(nodelist, element):
"''给一个节点添加子节点\n nodelist: 节点列表\n element: 子节点"
for node in nodelist:
node.append(element) | 5,085,192,923,313,646,000 | ''给一个节点添加子节点
nodelist: 节点列表
element: 子节点 | development/server/algorithm/tf_faster_rcnn/data_processing/utils/xml_utils.py | add_child_node | FMsunyh/re_com | python | def add_child_node(nodelist, element):
"给一个节点添加子节点\n nodelist: 节点列表\n element: 子节点"
for node in nodelist:
node.append(element) |
def del_node_by_tagkeyvalue(nodelist, tag, kv_map):
"''同过属性及属性值定位一个节点，并删除之\n nodelist: 父节点列表\n tag:子节点标签\n kv_map: 属性及属性值列表"
for parent_node in nodelist:
children = parent_node.getchildren()
for child in children:
if ((child.tag == tag) and if_match(child, kv_map)):... | 4,421,945,444,155,979,000 | ''同过属性及属性值定位一个节点，并删除之
nodelist: 父节点列表
tag:子节点标签
kv_map: 属性及属性值列表 | development/server/algorithm/tf_faster_rcnn/data_processing/utils/xml_utils.py | del_node_by_tagkeyvalue | FMsunyh/re_com | python | def del_node_by_tagkeyvalue(nodelist, tag, kv_map):
"同过属性及属性值定位一个节点，并删除之\n nodelist: 父节点列表\n tag:子节点标签\n kv_map: 属性及属性值列表"
for parent_node in nodelist:
children = parent_node.getchildren()
for child in children:
if ((child.tag == tag) and if_match(child, kv_map)):
... |
@property
def autobinx(self):
"\n Obsolete: since v1.42 each bin attribute is auto-determined\n separately and `autobinx` is not needed. However, we accept\n `autobinx: true` or `false` and will update `xbins` accordingly\n before deleting `autobinx` from the trace.\n\n The 'autob... | 4,493,837,154,316,828,700 | Obsolete: since v1.42 each bin attribute is auto-determined
separately and `autobinx` is not needed. However, we accept
`autobinx: true` or `false` and will update `xbins` accordingly
before deleting `autobinx` from the trace.
The 'autobinx' property must be specified as a bool
(either True, or False)
Returns
-------... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | autobinx | labaran1/plotly.py | python | @property
def autobinx(self):
"\n Obsolete: since v1.42 each bin attribute is auto-determined\n separately and `autobinx` is not needed. However, we accept\n `autobinx: true` or `false` and will update `xbins` accordingly\n before deleting `autobinx` from the trace.\n\n The 'autob... |
@property
def autobiny(self):
"\n Obsolete: since v1.42 each bin attribute is auto-determined\n separately and `autobiny` is not needed. However, we accept\n `autobiny: true` or `false` and will update `ybins` accordingly\n before deleting `autobiny` from the trace.\n\n The 'autob... | -8,390,623,379,121,540,000 | Obsolete: since v1.42 each bin attribute is auto-determined
separately and `autobiny` is not needed. However, we accept
`autobiny: true` or `false` and will update `ybins` accordingly
before deleting `autobiny` from the trace.
The 'autobiny' property must be specified as a bool
(either True, or False)
Returns
-------... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | autobiny | labaran1/plotly.py | python | @property
def autobiny(self):
"\n Obsolete: since v1.42 each bin attribute is auto-determined\n separately and `autobiny` is not needed. However, we accept\n `autobiny: true` or `false` and will update `ybins` accordingly\n before deleting `autobiny` from the trace.\n\n The 'autob... |
@property
def autocolorscale(self):
"\n Determines whether the colorscale is a default palette\n (`autocolorscale: true`) or the palette determined by\n `colorscale`. In case `colorscale` is unspecified or\n `autocolorscale` is true, the default palette will be chosen\n according ... | -7,501,531,800,070,667,000 | Determines whether the colorscale is a default palette
(`autocolorscale: true`) or the palette determined by
`colorscale`. In case `colorscale` is unspecified or
`autocolorscale` is true, the default palette will be chosen
according to whether numbers in the `color` array are all
positive, all negative or mixed.
The '... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | autocolorscale | labaran1/plotly.py | python | @property
def autocolorscale(self):
"\n Determines whether the colorscale is a default palette\n (`autocolorscale: true`) or the palette determined by\n `colorscale`. In case `colorscale` is unspecified or\n `autocolorscale` is true, the default palette will be chosen\n according ... |
@property
def autocontour(self):
"\n Determines whether or not the contour level attributes are\n picked by an algorithm. If True, the number of contour levels\n can be set in `ncontours`. If False, set the contour level\n attributes in `contours`.\n\n The 'autocontour' property m... | 1,903,994,080,076,454,400 | Determines whether or not the contour level attributes are
picked by an algorithm. If True, the number of contour levels
can be set in `ncontours`. If False, set the contour level
attributes in `contours`.
The 'autocontour' property must be specified as a bool
(either True, or False)
Returns
-------
bool | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | autocontour | labaran1/plotly.py | python | @property
def autocontour(self):
"\n Determines whether or not the contour level attributes are\n picked by an algorithm. If True, the number of contour levels\n can be set in `ncontours`. If False, set the contour level\n attributes in `contours`.\n\n The 'autocontour' property m... |
@property
def bingroup(self):
"\n Set the `xbingroup` and `ybingroup` default prefix For example,\n setting a `bingroup` of 1 on two histogram2d traces will make\n them their x-bins and y-bins match separately.\n\n The 'bingroup' property is a string and must be specified as:\n ... | -7,806,760,232,344,569,000 | Set the `xbingroup` and `ybingroup` default prefix For example,
setting a `bingroup` of 1 on two histogram2d traces will make
them their x-bins and y-bins match separately.
The 'bingroup' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | bingroup | labaran1/plotly.py | python | @property
def bingroup(self):
"\n Set the `xbingroup` and `ybingroup` default prefix For example,\n setting a `bingroup` of 1 on two histogram2d traces will make\n them their x-bins and y-bins match separately.\n\n The 'bingroup' property is a string and must be specified as:\n ... |
@property
def coloraxis(self):
'\n Sets a reference to a shared color axis. References to these\n shared color axes are "coloraxis", "coloraxis2", "coloraxis3",\n etc. Settings for these shared color axes are set in the\n layout, under `layout.coloraxis`, `layout.coloraxis2`, etc.\n ... | -5,672,586,063,930,786,000 | Sets a reference to a shared color axis. References to these
shared color axes are "coloraxis", "coloraxis2", "coloraxis3",
etc. Settings for these shared color axes are set in the
layout, under `layout.coloraxis`, `layout.coloraxis2`, etc.
Note that multiple color scales can be linked to the same color
axis.
The 'col... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | coloraxis | labaran1/plotly.py | python | @property
def coloraxis(self):
'\n Sets a reference to a shared color axis. References to these\n shared color axes are "coloraxis", "coloraxis2", "coloraxis3",\n etc. Settings for these shared color axes are set in the\n layout, under `layout.coloraxis`, `layout.coloraxis2`, etc.\n ... |
@property
def colorbar(self):
'\n The \'colorbar\' property is an instance of ColorBar\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.ColorBar`\n - A dict of string/value properties that will be passed\n to the ColorBar construc... | 8,347,786,571,676,000,000 | The 'colorbar' property is an instance of ColorBar
that may be specified as:
- An instance of :class:`plotly.graph_objs.histogram2dcontour.ColorBar`
- A dict of string/value properties that will be passed
to the ColorBar constructor
Supported dict properties:
bgcolor
Sets the color of ... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | colorbar | labaran1/plotly.py | python | @property
def colorbar(self):
'\n The \'colorbar\' property is an instance of ColorBar\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.ColorBar`\n - A dict of string/value properties that will be passed\n to the ColorBar construc... |
@property
def colorscale(self):
"\n Sets the colorscale. The colorscale must be an array containing\n arrays mapping a normalized value to an rgb, rgba, hex, hsl,\n hsv, or named color string. At minimum, a mapping for the\n lowest (0) and highest (1) values are required. For example,\n ... | -4,131,337,462,506,183,700 | Sets the colorscale. The colorscale must be an array containing
arrays mapping a normalized value to an rgb, rgba, hex, hsl,
hsv, or named color string. At minimum, a mapping for the
lowest (0) and highest (1) values are required. For example,
`[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the
bounds of the c... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | colorscale | labaran1/plotly.py | python | @property
def colorscale(self):
"\n Sets the colorscale. The colorscale must be an array containing\n arrays mapping a normalized value to an rgb, rgba, hex, hsl,\n hsv, or named color string. At minimum, a mapping for the\n lowest (0) and highest (1) values are required. For example,\n ... |
@property
def contours(self):
'\n The \'contours\' property is an instance of Contours\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Contours`\n - A dict of string/value properties that will be passed\n to the Contours construc... | -2,937,291,570,203,305,500 | The 'contours' property is an instance of Contours
that may be specified as:
- An instance of :class:`plotly.graph_objs.histogram2dcontour.Contours`
- A dict of string/value properties that will be passed
to the Contours constructor
Supported dict properties:
coloring
Determines the co... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | contours | labaran1/plotly.py | python | @property
def contours(self):
'\n The \'contours\' property is an instance of Contours\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Contours`\n - A dict of string/value properties that will be passed\n to the Contours construc... |
@property
def customdata(self):
'\n Assigns extra data each datum. This may be useful when\n listening to hover, click and selection events. Note that,\n "scatter" traces also appends customdata items in the markers\n DOM elements\n\n The \'customdata\' property is an array that m... | 5,251,881,149,598,622,000 | Assigns extra data each datum. This may be useful when
listening to hover, click and selection events. Note that,
"scatter" traces also appends customdata items in the markers
DOM elements
The 'customdata' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | customdata | labaran1/plotly.py | python | @property
def customdata(self):
'\n Assigns extra data each datum. This may be useful when\n listening to hover, click and selection events. Note that,\n "scatter" traces also appends customdata items in the markers\n DOM elements\n\n The \'customdata\' property is an array that m... |
@property
def customdatasrc(self):
"\n Sets the source reference on Chart Studio Cloud for\n `customdata`.\n\n The 'customdatasrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
return self['... | 190,073,433,557,564,500 | Sets the source reference on Chart Studio Cloud for
`customdata`.
The 'customdatasrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | customdatasrc | labaran1/plotly.py | python | @property
def customdatasrc(self):
"\n Sets the source reference on Chart Studio Cloud for\n `customdata`.\n\n The 'customdatasrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
return self['... |
@property
def histfunc(self):
'\n Specifies the binning function used for this histogram trace.\n If "count", the histogram values are computed by counting the\n number of values lying inside each bin. If "sum", "avg", "min",\n "max", the histogram values are computed using the sum, the\... | -866,892,611,725,270,400 | Specifies the binning function used for this histogram trace.
If "count", the histogram values are computed by counting the
number of values lying inside each bin. If "sum", "avg", "min",
"max", the histogram values are computed using the sum, the
average, the minimum or the maximum of the values lying inside
each bin ... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | histfunc | labaran1/plotly.py | python | @property
def histfunc(self):
'\n Specifies the binning function used for this histogram trace.\n If "count", the histogram values are computed by counting the\n number of values lying inside each bin. If "sum", "avg", "min",\n "max", the histogram values are computed using the sum, the\... |
@property
def histnorm(self):
'\n Specifies the type of normalization used for this histogram\n trace. If "", the span of each bar corresponds to the number of\n occurrences (i.e. the number of data points lying inside the\n bins). If "percent" / "probability", the span of each bar\n ... | 4,216,207,442,372,483,000 | Specifies the type of normalization used for this histogram
trace. If "", the span of each bar corresponds to the number of
occurrences (i.e. the number of data points lying inside the
bins). If "percent" / "probability", the span of each bar
corresponds to the percentage / fraction of occurrences with
respect to the t... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | histnorm | labaran1/plotly.py | python | @property
def histnorm(self):
'\n Specifies the type of normalization used for this histogram\n trace. If , the span of each bar corresponds to the number of\n occurrences (i.e. the number of data points lying inside the\n bins). If "percent" / "probability", the span of each bar\n ... |
@property
def hoverinfo(self):
"\n Determines which trace information appear on hover. If `none`\n or `skip` are set, no information is displayed upon hovering.\n But, if `none` is set, click and hover events are still fired.\n\n The 'hoverinfo' property is a flaglist and may be specifie... | 6,830,983,078,671,705,000 | Determines which trace information appear on hover. If `none`
or `skip` are set, no information is displayed upon hovering.
But, if `none` is set, click and hover events are still fired.
The 'hoverinfo' property is a flaglist and may be specified
as a string containing:
- Any combination of ['x', 'y', 'z', 'text', '... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | hoverinfo | labaran1/plotly.py | python | @property
def hoverinfo(self):
"\n Determines which trace information appear on hover. If `none`\n or `skip` are set, no information is displayed upon hovering.\n But, if `none` is set, click and hover events are still fired.\n\n The 'hoverinfo' property is a flaglist and may be specifie... |
@property
def hoverinfosrc(self):
"\n Sets the source reference on Chart Studio Cloud for\n `hoverinfo`.\n\n The 'hoverinfosrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
return self['hov... | -6,067,047,752,679,904,000 | Sets the source reference on Chart Studio Cloud for
`hoverinfo`.
The 'hoverinfosrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | hoverinfosrc | labaran1/plotly.py | python | @property
def hoverinfosrc(self):
"\n Sets the source reference on Chart Studio Cloud for\n `hoverinfo`.\n\n The 'hoverinfosrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
return self['hov... |
@property
def hoverlabel(self):
"\n The 'hoverlabel' property is an instance of Hoverlabel\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Hoverlabel`\n - A dict of string/value properties that will be passed\n to the Hoverlabel ... | -2,954,766,182,626,349,600 | The 'hoverlabel' property is an instance of Hoverlabel
that may be specified as:
- An instance of :class:`plotly.graph_objs.histogram2dcontour.Hoverlabel`
- A dict of string/value properties that will be passed
to the Hoverlabel constructor
Supported dict properties:
align
Sets the hor... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | hoverlabel | labaran1/plotly.py | python | @property
def hoverlabel(self):
"\n The 'hoverlabel' property is an instance of Hoverlabel\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Hoverlabel`\n - A dict of string/value properties that will be passed\n to the Hoverlabel ... |
@property
def hovertemplate(self):
'\n Template string used for rendering the information that appear\n on hover box. Note that this will override `hoverinfo`.\n Variables are inserted using %{variable}, for example "y: %{y}"\n as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. W... | -4,780,456,981,960,301,000 | Template string used for rendering the information that appear
on hover box. Note that this will override `hoverinfo`.
Variables are inserted using %{variable}, for example "y: %{y}"
as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When
showing info for several points, "xother" will be added to
those with dif... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | hovertemplate | labaran1/plotly.py | python | @property
def hovertemplate(self):
'\n Template string used for rendering the information that appear\n on hover box. Note that this will override `hoverinfo`.\n Variables are inserted using %{variable}, for example "y: %{y}"\n as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. W... |
@property
def hovertemplatesrc(self):
"\n Sets the source reference on Chart Studio Cloud for\n `hovertemplate`.\n\n The 'hovertemplatesrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
retu... | -4,027,318,745,288,583,000 | Sets the source reference on Chart Studio Cloud for
`hovertemplate`.
The 'hovertemplatesrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | hovertemplatesrc | labaran1/plotly.py | python | @property
def hovertemplatesrc(self):
"\n Sets the source reference on Chart Studio Cloud for\n `hovertemplate`.\n\n The 'hovertemplatesrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
retu... |
@property
def ids(self):
"\n Assigns id labels to each datum. These ids for object constancy\n of data points during animation. Should be an array of strings,\n not numbers or any other type.\n\n The 'ids' property is an array that may be specified as a tuple,\n list, numpy array,... | 495,195,998,616,416,200 | Assigns id labels to each datum. These ids for object constancy
of data points during animation. Should be an array of strings,
not numbers or any other type.
The 'ids' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | ids | labaran1/plotly.py | python | @property
def ids(self):
"\n Assigns id labels to each datum. These ids for object constancy\n of data points during animation. Should be an array of strings,\n not numbers or any other type.\n\n The 'ids' property is an array that may be specified as a tuple,\n list, numpy array,... |
@property
def idssrc(self):
"\n Sets the source reference on Chart Studio Cloud for `ids`.\n\n The 'idssrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
return self['idssrc'] | 6,341,341,719,582,534,000 | Sets the source reference on Chart Studio Cloud for `ids`.
The 'idssrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | idssrc | labaran1/plotly.py | python | @property
def idssrc(self):
"\n Sets the source reference on Chart Studio Cloud for `ids`.\n\n The 'idssrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
return self['idssrc'] |
@property
def legendgroup(self):
"\n Sets the legend group for this trace. Traces part of the same\n legend group hide/show at the same time when toggling legend\n items.\n\n The 'legendgroup' property is a string and must be specified as:\n - A string\n - A number that... | -1,414,322,020,329,425,400 | Sets the legend group for this trace. Traces part of the same
legend group hide/show at the same time when toggling legend
items.
The 'legendgroup' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | legendgroup | labaran1/plotly.py | python | @property
def legendgroup(self):
"\n Sets the legend group for this trace. Traces part of the same\n legend group hide/show at the same time when toggling legend\n items.\n\n The 'legendgroup' property is a string and must be specified as:\n - A string\n - A number that... |
@property
def legendgrouptitle(self):
"\n The 'legendgrouptitle' property is an instance of Legendgrouptitle\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Legendgrouptitle`\n - A dict of string/value properties that will be passed\n ... | -8,161,286,107,835,697,000 | The 'legendgrouptitle' property is an instance of Legendgrouptitle
that may be specified as:
- An instance of :class:`plotly.graph_objs.histogram2dcontour.Legendgrouptitle`
- A dict of string/value properties that will be passed
to the Legendgrouptitle constructor
Supported dict properties:
font
... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | legendgrouptitle | labaran1/plotly.py | python | @property
def legendgrouptitle(self):
"\n The 'legendgrouptitle' property is an instance of Legendgrouptitle\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Legendgrouptitle`\n - A dict of string/value properties that will be passed\n ... |
@property
def legendrank(self):
"\n Sets the legend rank for this trace. Items and groups with\n smaller ranks are presented on top/left side while with\n `*reversed* `legend.traceorder` they are on bottom/right side.\n The default legendrank is 1000, so that you can use ranks less\n ... | -6,850,988,603,576,750,000 | Sets the legend rank for this trace. Items and groups with
smaller ranks are presented on top/left side while with
`*reversed* `legend.traceorder` they are on bottom/right side.
The default legendrank is 1000, so that you can use ranks less
than 1000 to place certain items before all unranked items, and
ranks greater t... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | legendrank | labaran1/plotly.py | python | @property
def legendrank(self):
"\n Sets the legend rank for this trace. Items and groups with\n smaller ranks are presented on top/left side while with\n `*reversed* `legend.traceorder` they are on bottom/right side.\n The default legendrank is 1000, so that you can use ranks less\n ... |
@property
def line(self):
'\n The \'line\' property is an instance of Line\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Line`\n - A dict of string/value properties that will be passed\n to the Line constructor\n\n S... | 877,410,188,773,463,200 | The 'line' property is an instance of Line
that may be specified as:
- An instance of :class:`plotly.graph_objs.histogram2dcontour.Line`
- A dict of string/value properties that will be passed
to the Line constructor
Supported dict properties:
color
Sets the color of the contour level.... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | line | labaran1/plotly.py | python | @property
def line(self):
'\n The \'line\' property is an instance of Line\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Line`\n - A dict of string/value properties that will be passed\n to the Line constructor\n\n S... |
@property
def marker(self):
"\n The 'marker' property is an instance of Marker\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Marker`\n - A dict of string/value properties that will be passed\n to the Marker constructor\n\n ... | 3,567,528,160,336,440,000 | The 'marker' property is an instance of Marker
that may be specified as:
- An instance of :class:`plotly.graph_objs.histogram2dcontour.Marker`
- A dict of string/value properties that will be passed
to the Marker constructor
Supported dict properties:
color
Sets the aggregation data.
... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | marker | labaran1/plotly.py | python | @property
def marker(self):
"\n The 'marker' property is an instance of Marker\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Marker`\n - A dict of string/value properties that will be passed\n to the Marker constructor\n\n ... |
@property
def meta(self):
"\n Assigns extra meta information associated with this trace that\n can be used in various text attributes. Attributes such as\n trace `name`, graph, axis and colorbar `title.text`, annotation\n `text` `rangeselector`, `updatemenues` and `sliders` `label`\n ... | -3,276,779,357,621,415,400 | Assigns extra meta information associated with this trace that
can be used in various text attributes. Attributes such as
trace `name`, graph, axis and colorbar `title.text`, annotation
`text` `rangeselector`, `updatemenues` and `sliders` `label`
text all support `meta`. To access the trace `meta` values in
an attribut... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | meta | labaran1/plotly.py | python | @property
def meta(self):
"\n Assigns extra meta information associated with this trace that\n can be used in various text attributes. Attributes such as\n trace `name`, graph, axis and colorbar `title.text`, annotation\n `text` `rangeselector`, `updatemenues` and `sliders` `label`\n ... |
@property
def metasrc(self):
"\n Sets the source reference on Chart Studio Cloud for `meta`.\n\n The 'metasrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
return self['metasrc'] | -3,793,176,597,983,288,000 | Sets the source reference on Chart Studio Cloud for `meta`.
The 'metasrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | metasrc | labaran1/plotly.py | python | @property
def metasrc(self):
"\n Sets the source reference on Chart Studio Cloud for `meta`.\n\n The 'metasrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
return self['metasrc'] |
@property
def name(self):
"\n Sets the trace name. The trace name appear as the legend item\n and on hover.\n\n The 'name' property is a string and must be specified as:\n - A string\n - A number that will be converted to a string\n\n Returns\n -------\n s... | -7,846,848,244,757,888,000 | Sets the trace name. The trace name appear as the legend item
and on hover.
The 'name' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | name | labaran1/plotly.py | python | @property
def name(self):
"\n Sets the trace name. The trace name appear as the legend item\n and on hover.\n\n The 'name' property is a string and must be specified as:\n - A string\n - A number that will be converted to a string\n\n Returns\n -------\n s... |
@property
def nbinsx(self):
"\n Specifies the maximum number of desired bins. This value will\n be used in an algorithm that will decide the optimal bin size\n such that the histogram best visualizes the distribution of the\n data. Ignored if `xbins.size` is provided.\n\n The 'nbi... | -1,433,460,423,653,042,400 | Specifies the maximum number of desired bins. This value will
be used in an algorithm that will decide the optimal bin size
such that the histogram best visualizes the distribution of the
data. Ignored if `xbins.size` is provided.
The 'nbinsx' property is a integer and may be specified as:
- An int (or float that wi... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | nbinsx | labaran1/plotly.py | python | @property
def nbinsx(self):
"\n Specifies the maximum number of desired bins. This value will\n be used in an algorithm that will decide the optimal bin size\n such that the histogram best visualizes the distribution of the\n data. Ignored if `xbins.size` is provided.\n\n The 'nbi... |
@property
def nbinsy(self):
"\n Specifies the maximum number of desired bins. This value will\n be used in an algorithm that will decide the optimal bin size\n such that the histogram best visualizes the distribution of the\n data. Ignored if `ybins.size` is provided.\n\n The 'nbi... | -1,830,005,275,288,606,000 | Specifies the maximum number of desired bins. This value will
be used in an algorithm that will decide the optimal bin size
such that the histogram best visualizes the distribution of the
data. Ignored if `ybins.size` is provided.
The 'nbinsy' property is a integer and may be specified as:
- An int (or float that wi... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | nbinsy | labaran1/plotly.py | python | @property
def nbinsy(self):
"\n Specifies the maximum number of desired bins. This value will\n be used in an algorithm that will decide the optimal bin size\n such that the histogram best visualizes the distribution of the\n data. Ignored if `ybins.size` is provided.\n\n The 'nbi... |
@property
def ncontours(self):
"\n Sets the maximum number of contour levels. The actual number of\n contours will be chosen automatically to be less than or equal\n to the value of `ncontours`. Has an effect only if\n `autocontour` is True or if `contours.size` is missing.\n\n Th... | -6,107,048,245,621,546,000 | Sets the maximum number of contour levels. The actual number of
contours will be chosen automatically to be less than or equal
to the value of `ncontours`. Has an effect only if
`autocontour` is True or if `contours.size` is missing.
The 'ncontours' property is a integer and may be specified as:
- An int (or float t... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | ncontours | labaran1/plotly.py | python | @property
def ncontours(self):
"\n Sets the maximum number of contour levels. The actual number of\n contours will be chosen automatically to be less than or equal\n to the value of `ncontours`. Has an effect only if\n `autocontour` is True or if `contours.size` is missing.\n\n Th... |
@property
def opacity(self):
"\n Sets the opacity of the trace.\n\n The 'opacity' property is a number and may be specified as:\n - An int or float in the interval [0, 1]\n\n Returns\n -------\n int|float\n "
return self['opacity'] | 7,831,924,921,999,790,000 | Sets the opacity of the trace.
The 'opacity' property is a number and may be specified as:
- An int or float in the interval [0, 1]
Returns
-------
int|float | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | opacity | labaran1/plotly.py | python | @property
def opacity(self):
"\n Sets the opacity of the trace.\n\n The 'opacity' property is a number and may be specified as:\n - An int or float in the interval [0, 1]\n\n Returns\n -------\n int|float\n "
return self['opacity'] |
@property
def reversescale(self):
"\n Reverses the color mapping if true. If true, `zmin` will\n correspond to the last color in the array and `zmax` will\n correspond to the first color.\n\n The 'reversescale' property must be specified as a bool\n (either True, or False)\n\n ... | 5,272,177,827,245,154,000 | Reverses the color mapping if true. If true, `zmin` will
correspond to the last color in the array and `zmax` will
correspond to the first color.
The 'reversescale' property must be specified as a bool
(either True, or False)
Returns
-------
bool | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | reversescale | labaran1/plotly.py | python | @property
def reversescale(self):
"\n Reverses the color mapping if true. If true, `zmin` will\n correspond to the last color in the array and `zmax` will\n correspond to the first color.\n\n The 'reversescale' property must be specified as a bool\n (either True, or False)\n\n ... |
@property
def showlegend(self):
"\n Determines whether or not an item corresponding to this trace\n is shown in the legend.\n\n The 'showlegend' property must be specified as a bool\n (either True, or False)\n\n Returns\n -------\n bool\n "
return self['sh... | 3,873,623,128,799,338,000 | Determines whether or not an item corresponding to this trace
is shown in the legend.
The 'showlegend' property must be specified as a bool
(either True, or False)
Returns
-------
bool | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | showlegend | labaran1/plotly.py | python | @property
def showlegend(self):
"\n Determines whether or not an item corresponding to this trace\n is shown in the legend.\n\n The 'showlegend' property must be specified as a bool\n (either True, or False)\n\n Returns\n -------\n bool\n "
return self['sh... |
@property
def showscale(self):
"\n Determines whether or not a colorbar is displayed for this\n trace.\n\n The 'showscale' property must be specified as a bool\n (either True, or False)\n\n Returns\n -------\n bool\n "
return self['showscale'] | -299,257,583,409,257,400 | Determines whether or not a colorbar is displayed for this
trace.
The 'showscale' property must be specified as a bool
(either True, or False)
Returns
-------
bool | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | showscale | labaran1/plotly.py | python | @property
def showscale(self):
"\n Determines whether or not a colorbar is displayed for this\n trace.\n\n The 'showscale' property must be specified as a bool\n (either True, or False)\n\n Returns\n -------\n bool\n "
return self['showscale'] |
@property
def stream(self):
"\n The 'stream' property is an instance of Stream\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Stream`\n - A dict of string/value properties that will be passed\n to the Stream constructor\n\n ... | 9,221,803,474,292,624,000 | The 'stream' property is an instance of Stream
that may be specified as:
- An instance of :class:`plotly.graph_objs.histogram2dcontour.Stream`
- A dict of string/value properties that will be passed
to the Stream constructor
Supported dict properties:
maxpoints
Sets the maximum number ... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | stream | labaran1/plotly.py | python | @property
def stream(self):
"\n The 'stream' property is an instance of Stream\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Stream`\n - A dict of string/value properties that will be passed\n to the Stream constructor\n\n ... |
@property
def textfont(self):
'\n For this trace it only has an effect if `coloring` is set to\n "heatmap". Sets the text font.\n\n The \'textfont\' property is an instance of Textfont\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Te... | 7,187,586,520,842,342,000 | For this trace it only has an effect if `coloring` is set to
"heatmap". Sets the text font.
The 'textfont' property is an instance of Textfont
that may be specified as:
- An instance of :class:`plotly.graph_objs.histogram2dcontour.Textfont`
- A dict of string/value properties that will be passed
to the Textfon... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | textfont | labaran1/plotly.py | python | @property
def textfont(self):
'\n For this trace it only has an effect if `coloring` is set to\n "heatmap". Sets the text font.\n\n The \'textfont\' property is an instance of Textfont\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.Te... |
@property
def texttemplate(self):
'\n For this trace it only has an effect if `coloring` is set to\n "heatmap". Template string used for rendering the information\n text that appear on points. Note that this will override\n `textinfo`. Variables are inserted using %{variable}, for\n ... | -7,959,166,855,973,472,000 | For this trace it only has an effect if `coloring` is set to
"heatmap". Template string used for rendering the information
text that appear on points. Note that this will override
`textinfo`. Variables are inserted using %{variable}, for
example "y: %{y}". Numbers are formatted using d3-format's
syntax %{variable:d3-fo... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | texttemplate | labaran1/plotly.py | python | @property
def texttemplate(self):
'\n For this trace it only has an effect if `coloring` is set to\n "heatmap". Template string used for rendering the information\n text that appear on points. Note that this will override\n `textinfo`. Variables are inserted using %{variable}, for\n ... |
@property
def uid(self):
"\n Assign an id to this trace, Use this to provide object\n constancy between traces during animations and transitions.\n\n The 'uid' property is a string and must be specified as:\n - A string\n - A number that will be converted to a string\n\n ... | -6,259,468,128,811,512,000 | Assign an id to this trace, Use this to provide object
constancy between traces during animations and transitions.
The 'uid' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | uid | labaran1/plotly.py | python | @property
def uid(self):
"\n Assign an id to this trace, Use this to provide object\n constancy between traces during animations and transitions.\n\n The 'uid' property is a string and must be specified as:\n - A string\n - A number that will be converted to a string\n\n ... |
@property
def uirevision(self):
"\n Controls persistence of some user-driven changes to the trace:\n `constraintrange` in `parcoords` traces, as well as some\n `editable: true` modifications such as `name` and\n `colorbar.title`. Defaults to `layout.uirevision`. Note that\n other ... | 4,750,175,976,540,109,000 | Controls persistence of some user-driven changes to the trace:
`constraintrange` in `parcoords` traces, as well as some
`editable: true` modifications such as `name` and
`colorbar.title`. Defaults to `layout.uirevision`. Note that
other user-driven trace attribute changes are controlled by
`layout` attributes: `trace.v... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | uirevision | labaran1/plotly.py | python | @property
def uirevision(self):
"\n Controls persistence of some user-driven changes to the trace:\n `constraintrange` in `parcoords` traces, as well as some\n `editable: true` modifications such as `name` and\n `colorbar.title`. Defaults to `layout.uirevision`. Note that\n other ... |
@property
def visible(self):
'\n Determines whether or not this trace is visible. If\n "legendonly", the trace is not drawn, but can appear as a\n legend item (provided that the legend itself is visible).\n\n The \'visible\' property is an enumeration that may be specified as:\n ... | 8,785,796,654,267,106,000 | Determines whether or not this trace is visible. If
"legendonly", the trace is not drawn, but can appear as a
legend item (provided that the legend itself is visible).
The 'visible' property is an enumeration that may be specified as:
- One of the following enumeration values:
[True, False, 'legendonly']
Re... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | visible | labaran1/plotly.py | python | @property
def visible(self):
'\n Determines whether or not this trace is visible. If\n "legendonly", the trace is not drawn, but can appear as a\n legend item (provided that the legend itself is visible).\n\n The \'visible\' property is an enumeration that may be specified as:\n ... |
@property
def x(self):
"\n Sets the sample data to be binned on the x axis.\n\n The 'x' property is an array that may be specified as a tuple,\n list, numpy array, or pandas Series\n\n Returns\n -------\n numpy.ndarray\n "
return self['x'] | -8,831,692,299,467,391,000 | Sets the sample data to be binned on the x axis.
The 'x' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | x | labaran1/plotly.py | python | @property
def x(self):
"\n Sets the sample data to be binned on the x axis.\n\n The 'x' property is an array that may be specified as a tuple,\n list, numpy array, or pandas Series\n\n Returns\n -------\n numpy.ndarray\n "
return self['x'] |
@property
def xaxis(self):
'\n Sets a reference between this trace\'s x coordinates and a 2D\n cartesian x axis. If "x" (the default value), the x coordinates\n refer to `layout.xaxis`. If "x2", the x coordinates refer to\n `layout.xaxis2`, and so on.\n\n The \'xaxis\' property is... | -6,077,734,735,450,253,000 | Sets a reference between this trace's x coordinates and a 2D
cartesian x axis. If "x" (the default value), the x coordinates
refer to `layout.xaxis`. If "x2", the x coordinates refer to
`layout.xaxis2`, and so on.
The 'xaxis' property is an identifier of a particular
subplot, of type 'x', that may be specified as the ... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | xaxis | labaran1/plotly.py | python | @property
def xaxis(self):
'\n Sets a reference between this trace\'s x coordinates and a 2D\n cartesian x axis. If "x" (the default value), the x coordinates\n refer to `layout.xaxis`. If "x2", the x coordinates refer to\n `layout.xaxis2`, and so on.\n\n The \'xaxis\' property is... |
@property
def xbingroup(self):
"\n Set a group of histogram traces which will have compatible\n x-bin settings. Using `xbingroup`, histogram2d and\n histogram2dcontour traces (on axes of the same axis type) can\n have compatible x-bin settings. Note that the same `xbingroup`\n va... | 659,657,411,388,869,000 | Set a group of histogram traces which will have compatible
x-bin settings. Using `xbingroup`, histogram2d and
histogram2dcontour traces (on axes of the same axis type) can
have compatible x-bin settings. Note that the same `xbingroup`
value can be used to set (1D) histogram `bingroup`
The 'xbingroup' property is a st... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | xbingroup | labaran1/plotly.py | python | @property
def xbingroup(self):
"\n Set a group of histogram traces which will have compatible\n x-bin settings. Using `xbingroup`, histogram2d and\n histogram2dcontour traces (on axes of the same axis type) can\n have compatible x-bin settings. Note that the same `xbingroup`\n va... |
@property
def xbins(self):
'\n The \'xbins\' property is an instance of XBins\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.XBins`\n - A dict of string/value properties that will be passed\n to the XBins constructor\n\n ... | -8,027,477,889,522,956,000 | The 'xbins' property is an instance of XBins
that may be specified as:
- An instance of :class:`plotly.graph_objs.histogram2dcontour.XBins`
- A dict of string/value properties that will be passed
to the XBins constructor
Supported dict properties:
end
Sets the end value for the x axis ... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | xbins | labaran1/plotly.py | python | @property
def xbins(self):
'\n The \'xbins\' property is an instance of XBins\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.XBins`\n - A dict of string/value properties that will be passed\n to the XBins constructor\n\n ... |
@property
def xcalendar(self):
"\n Sets the calendar system to use with `x` date data.\n\n The 'xcalendar' property is an enumeration that may be specified as:\n - One of the following enumeration values:\n ['chinese', 'coptic', 'discworld', 'ethiopian',\n 'grego... | -3,440,325,086,827,336,700 | Sets the calendar system to use with `x` date data.
The 'xcalendar' property is an enumeration that may be specified as:
- One of the following enumeration values:
['chinese', 'coptic', 'discworld', 'ethiopian',
'gregorian', 'hebrew', 'islamic', 'jalali', 'julian',
'mayan', 'nanakshahi', 'nep... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | xcalendar | labaran1/plotly.py | python | @property
def xcalendar(self):
"\n Sets the calendar system to use with `x` date data.\n\n The 'xcalendar' property is an enumeration that may be specified as:\n - One of the following enumeration values:\n ['chinese', 'coptic', 'discworld', 'ethiopian',\n 'grego... |
@property
def xhoverformat(self):
'\n Sets the hover text formatting rulefor `x` using d3 formatting\n mini-languages which are very similar to those in Python. For\n numbers, see:\n https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for\n dates see: https://github.com/d3... | -2,679,084,062,892,850,700 | Sets the hover text formatting rulefor `x` using d3 formatting
mini-languages which are very similar to those in Python. For
numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for
dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to d3's date
formatter: ... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | xhoverformat | labaran1/plotly.py | python | @property
def xhoverformat(self):
'\n Sets the hover text formatting rulefor `x` using d3 formatting\n mini-languages which are very similar to those in Python. For\n numbers, see:\n https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for\n dates see: https://github.com/d3... |
@property
def xsrc(self):
"\n Sets the source reference on Chart Studio Cloud for `x`.\n\n The 'xsrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
return self['xsrc'] | 8,029,645,459,233,492,000 | Sets the source reference on Chart Studio Cloud for `x`.
The 'xsrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | xsrc | labaran1/plotly.py | python | @property
def xsrc(self):
"\n Sets the source reference on Chart Studio Cloud for `x`.\n\n The 'xsrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
return self['xsrc'] |
@property
def y(self):
"\n Sets the sample data to be binned on the y axis.\n\n The 'y' property is an array that may be specified as a tuple,\n list, numpy array, or pandas Series\n\n Returns\n -------\n numpy.ndarray\n "
return self['y'] | -2,030,056,883,749,161,200 | Sets the sample data to be binned on the y axis.
The 'y' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | y | labaran1/plotly.py | python | @property
def y(self):
"\n Sets the sample data to be binned on the y axis.\n\n The 'y' property is an array that may be specified as a tuple,\n list, numpy array, or pandas Series\n\n Returns\n -------\n numpy.ndarray\n "
return self['y'] |
@property
def yaxis(self):
'\n Sets a reference between this trace\'s y coordinates and a 2D\n cartesian y axis. If "y" (the default value), the y coordinates\n refer to `layout.yaxis`. If "y2", the y coordinates refer to\n `layout.yaxis2`, and so on.\n\n The \'yaxis\' property is... | 4,010,060,130,903,161,300 | Sets a reference between this trace's y coordinates and a 2D
cartesian y axis. If "y" (the default value), the y coordinates
refer to `layout.yaxis`. If "y2", the y coordinates refer to
`layout.yaxis2`, and so on.
The 'yaxis' property is an identifier of a particular
subplot, of type 'y', that may be specified as the ... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | yaxis | labaran1/plotly.py | python | @property
def yaxis(self):
'\n Sets a reference between this trace\'s y coordinates and a 2D\n cartesian y axis. If "y" (the default value), the y coordinates\n refer to `layout.yaxis`. If "y2", the y coordinates refer to\n `layout.yaxis2`, and so on.\n\n The \'yaxis\' property is... |
@property
def ybingroup(self):
"\n Set a group of histogram traces which will have compatible\n y-bin settings. Using `ybingroup`, histogram2d and\n histogram2dcontour traces (on axes of the same axis type) can\n have compatible y-bin settings. Note that the same `ybingroup`\n va... | -7,875,643,609,555,250,000 | Set a group of histogram traces which will have compatible
y-bin settings. Using `ybingroup`, histogram2d and
histogram2dcontour traces (on axes of the same axis type) can
have compatible y-bin settings. Note that the same `ybingroup`
value can be used to set (1D) histogram `bingroup`
The 'ybingroup' property is a st... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | ybingroup | labaran1/plotly.py | python | @property
def ybingroup(self):
"\n Set a group of histogram traces which will have compatible\n y-bin settings. Using `ybingroup`, histogram2d and\n histogram2dcontour traces (on axes of the same axis type) can\n have compatible y-bin settings. Note that the same `ybingroup`\n va... |
@property
def ybins(self):
'\n The \'ybins\' property is an instance of YBins\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.YBins`\n - A dict of string/value properties that will be passed\n to the YBins constructor\n\n ... | -4,265,983,039,026,507,300 | The 'ybins' property is an instance of YBins
that may be specified as:
- An instance of :class:`plotly.graph_objs.histogram2dcontour.YBins`
- A dict of string/value properties that will be passed
to the YBins constructor
Supported dict properties:
end
Sets the end value for the y axis ... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | ybins | labaran1/plotly.py | python | @property
def ybins(self):
'\n The \'ybins\' property is an instance of YBins\n that may be specified as:\n - An instance of :class:`plotly.graph_objs.histogram2dcontour.YBins`\n - A dict of string/value properties that will be passed\n to the YBins constructor\n\n ... |
@property
def ycalendar(self):
"\n Sets the calendar system to use with `y` date data.\n\n The 'ycalendar' property is an enumeration that may be specified as:\n - One of the following enumeration values:\n ['chinese', 'coptic', 'discworld', 'ethiopian',\n 'grego... | -9,081,848,819,014,588,000 | Sets the calendar system to use with `y` date data.
The 'ycalendar' property is an enumeration that may be specified as:
- One of the following enumeration values:
['chinese', 'coptic', 'discworld', 'ethiopian',
'gregorian', 'hebrew', 'islamic', 'jalali', 'julian',
'mayan', 'nanakshahi', 'nep... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | ycalendar | labaran1/plotly.py | python | @property
def ycalendar(self):
"\n Sets the calendar system to use with `y` date data.\n\n The 'ycalendar' property is an enumeration that may be specified as:\n - One of the following enumeration values:\n ['chinese', 'coptic', 'discworld', 'ethiopian',\n 'grego... |
@property
def yhoverformat(self):
'\n Sets the hover text formatting rulefor `y` using d3 formatting\n mini-languages which are very similar to those in Python. For\n numbers, see:\n https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for\n dates see: https://github.com/d3... | -7,632,905,920,395,636,000 | Sets the hover text formatting rulefor `y` using d3 formatting
mini-languages which are very similar to those in Python. For
numbers, see:
https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for
dates see: https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format. We add two items to d3's date
formatter: ... | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | yhoverformat | labaran1/plotly.py | python | @property
def yhoverformat(self):
'\n Sets the hover text formatting rulefor `y` using d3 formatting\n mini-languages which are very similar to those in Python. For\n numbers, see:\n https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for\n dates see: https://github.com/d3... |
@property
def ysrc(self):
"\n Sets the source reference on Chart Studio Cloud for `y`.\n\n The 'ysrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
return self['ysrc'] | -2,617,352,206,358,118,000 | Sets the source reference on Chart Studio Cloud for `y`.
The 'ysrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str | packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py | ysrc | labaran1/plotly.py | python | @property
def ysrc(self):
"\n Sets the source reference on Chart Studio Cloud for `y`.\n\n The 'ysrc' property must be specified as a string or\n as a plotly.grid_objs.Column object\n\n Returns\n -------\n str\n "
return self['ysrc'] |
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