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9,221,803,474B
| docstring
stringlengths 1
16.8k
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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_image, 2)
return depth_image
| 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_image
|
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, interpolation=cv2.INTER_NEAREST)
| -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, cams)
else:
depth_image = scale_image(depth_image, scale=scale, interpolation='nearest')
return (images, cams, depth_image)
| 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 = scale_image(depth_image, scale=scale, interpolation='nearest')
return (images, cams, 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):
new_h = height
else:
new_h = int((math.floor((h / base_image_size)) * base_image_size))
if (new_w > width):
new_w = width
else:
new_w = int((math.floor((w / base_image_size)) * base_image_size))
start_h = int(math.floor(((h - new_h) / 2)))
start_w = int(math.floor(((w - new_w) / 2)))
finish_h = (start_h + new_h)
finish_w = (start_w + new_w)
images[view] = images[view][start_h:finish_h, start_w:finish_w]
cams[view][1][0][2] = (cams[view][1][0][2] - start_w)
cams[view][1][1][2] = (cams[view][1][1][2] - start_h)
if (not (depth_image is None)):
depth_image = depth_image[start_h:finish_h, start_w:finish_w]
return (images, cams, depth_image)
else:
return (images, cams)
| -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 / base_image_size)) * base_image_size))
if (new_w > width):
new_w = width
else:
new_w = int((math.floor((w / base_image_size)) * base_image_size))
start_h = int(math.floor(((h - new_h) / 2)))
start_w = int(math.floor(((w - new_w) / 2)))
finish_h = (start_h + new_h)
finish_w = (start_w + new_w)
images[view] = images[view][start_h:finish_h, start_w:finish_w]
cams[view][1][0][2] = (cams[view][1][0][2] - start_w)
cams[view][1][1][2] = (cams[view][1][1][2] - start_h)
if (not (depth_image is None)):
depth_image = depth_image[start_h:finish_h, start_w:finish_w]
return (images, cams, depth_image)
else:
return (images, cams)
|
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/EMA', 'conv1/W': 'conv0/W', 'conv1/b': 'conv0/b', 'fc1000/W': 'fc1000/W', 'fc1000/b': 'fc1000/b'}
if (caffe_layer_name in NAME_MAP):
return NAME_MAP[caffe_layer_name]
s = re.search('([a-z]+)([0-9]+)([a-z]+)_', caffe_layer_name)
if (s is None):
s = re.search('([a-z]+)([0-9]+)([a-z]+)([0-9]+)_', caffe_layer_name)
layer_block_part1 = s.group(3)
layer_block_part2 = s.group(4)
assert (layer_block_part1 in ['a', 'b'])
layer_block = (0 if (layer_block_part1 == 'a') else int(layer_block_part2))
else:
layer_block = (ord(s.group(3)) - ord('a'))
layer_type = s.group(1)
layer_group = s.group(2)
layer_branch = int(re.search('_branch([0-9])', caffe_layer_name).group(1))
assert (layer_branch in [1, 2])
if (layer_branch == 2):
layer_id = re.search('_branch[0-9]([a-z])/', caffe_layer_name).group(1)
layer_id = ((ord(layer_id) - ord('a')) + 1)
TYPE_DICT = {'res': 'conv', 'bn': 'bn'}
tf_name = caffe_layer_name[caffe_layer_name.index('/'):]
layer_type = (TYPE_DICT[layer_type] + (str(layer_id) if (layer_branch == 2) else 'shortcut'))
tf_name = ('group{}/block{}/{}'.format((int(layer_group) - 2), layer_block, layer_type) + tf_name)
return tf_name
| 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/EMA', 'conv1/W': 'conv0/W', 'conv1/b': 'conv0/b', 'fc1000/W': 'fc1000/W', 'fc1000/b': 'fc1000/b'}
if (caffe_layer_name in NAME_MAP):
return NAME_MAP[caffe_layer_name]
s = re.search('([a-z]+)([0-9]+)([a-z]+)_', caffe_layer_name)
if (s is None):
s = re.search('([a-z]+)([0-9]+)([a-z]+)([0-9]+)_', caffe_layer_name)
layer_block_part1 = s.group(3)
layer_block_part2 = s.group(4)
assert (layer_block_part1 in ['a', 'b'])
layer_block = (0 if (layer_block_part1 == 'a') else int(layer_block_part2))
else:
layer_block = (ord(s.group(3)) - ord('a'))
layer_type = s.group(1)
layer_group = s.group(2)
layer_branch = int(re.search('_branch([0-9])', caffe_layer_name).group(1))
assert (layer_branch in [1, 2])
if (layer_branch == 2):
layer_id = re.search('_branch[0-9]([a-z])/', caffe_layer_name).group(1)
layer_id = ((ord(layer_id) - ord('a')) + 1)
TYPE_DICT = {'res': 'conv', 'bn': 'bn'}
tf_name = caffe_layer_name[caffe_layer_name.index('/'):]
layer_type = (TYPE_DICT[layer_type] + (str(layer_id) if (layer_branch == 2) else 'shortcut'))
tf_name = ('group{}/block{}/{}'.format((int(layer_group) - 2), layer_block, layer_type) + tf_name)
return tf_name
|
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_CACHE):
data = USER_CACHE[key]
else:
data = current_app.remote.get('user')
if key:
USER_CACHE[key] = data
return data.data['data']
| 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_CACHE):
data = USER_CACHE[key]
else:
data = current_app.remote.get('user')
if key:
USER_CACHE[key] = data
return data.data['data']
|
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_ROLES)
| -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_ROLES)
|
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 is any of ``roles``, ``False`` otherwise\n '
try:
endpoint = get_endpoint(course=course)
for participation in get_user()['participations']:
if (roles and (participation['role'] not in roles)):
continue
if (participation['course']['offering'] != endpoint):
continue
return True
return False
except Exception as e:
print(e)
return False
| 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 is any of ``roles``, ``False`` otherwise\n '
try:
endpoint = get_endpoint(course=course)
for participation in get_user()['participations']:
if (roles and (participation['role'] not in roles)):
continue
if (participation['course']['offering'] != endpoint):
continue
return True
return False
except Exception as e:
print(e)
return False
|
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(netloc=get_host()).geturl()
return redirect(url_for('login'))
| 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(netloc=get_host()).geturl()
return redirect(url_for('login'))
|
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 receives the successful result\n of authentication, ``/api/user`` that acts as a test endpoint, and a\n :meth:`~flask_oauthlib.client.OAuthRemoteApp.tokengetter`.\n\n :param app: the app to add OAuth endpoints to\n :type app: ~flask.Flask\n\n :param consumer_key: the OAuth client consumer key\n :type consumer_key: str\n\n :param secret_key: the OAuth client secret, inferred using\n :func:`~common.rpc.secrets.get_secret` if omitted\n :type secret_key: str\n\n :param success_callback: an optional function to call upon login\n :type success_callback: func\n\n :param return_response: an optional function to send the OAuth response to\n :type return_response: func\n '
oauth = OAuth(app)
if (os.getenv('ENV') == 'prod'):
if (secret_key is None):
app.secret_key = get_secret(secret_name='OKPY_OAUTH_SECRET')
else:
app.secret_key = secret_key
else:
consumer_key = 'local-dev-all'
app.secret_key = 'kmSPJYPzKJglOOOmr7q0irMfBVMRFXN'
if (not app.debug):
app.config.update(SESSION_COOKIE_SECURE=True, SESSION_COOKIE_HTTPONLY=True, SESSION_COOKIE_SAMESITE='Lax')
remote = oauth.remote_app('ok-server', consumer_key=consumer_key, consumer_secret=app.secret_key, request_token_params={'scope': 'all', 'state': (lambda : security.gen_salt(10))}, base_url='https://okpy.org/api/v3/', request_token_url=None, access_token_method='POST', access_token_url='https://okpy.org/oauth/token', authorize_url='https://okpy.org/oauth/authorize')
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[4]))
query.update(params)
url_parts[4] = urllib.parse.urlencode(query)
uri = urllib.parse.urlunparse(url_parts)
return (uri, headers, body)
remote.pre_request = check_req
@app.route('/oauth/login')
def login():
if app.debug:
response = remote.authorize(callback=url_for('authorized', _external=True))
else:
response = remote.authorize(url_for('authorized', _external=True, _scheme='https'))
return response
@app.route('/oauth/authorized')
def authorized():
resp = remote.authorized_response()
if (resp is None):
return ('Access denied: error=%s' % request.args['error'])
if (isinstance(resp, dict) and ('access_token' in resp)):
session['access_token'] = (resp['access_token'], '')
if return_response:
return_response(resp)
if success_callback:
success_callback()
target = session.get(REDIRECT_KEY)
if target:
session.pop(REDIRECT_KEY)
return redirect(target)
return redirect(url_for('index'))
@app.route('/api/user', methods=['POST'])
def client_method():
if ('access_token' not in session):
abort(401)
token = session['access_token'][0]
r = requests.get('https://okpy.org/api/v3/user/?access_token={}'.format(token))
if (not r.ok):
abort(401)
return jsonify(r.json())
@remote.tokengetter
def get_oauth_token():
return session.get('access_token')
app.remote = remote
| -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.OAuthRemoteApp.tokengetter`.
:param app: the app to add OAuth endpoints to
:type app: ~flask.Flask
:param consumer_key: the OAuth client consumer key
:type consumer_key: str
:param secret_key: the OAuth client secret, inferred using
:func:`~common.rpc.secrets.get_secret` if omitted
:type secret_key: str
:param success_callback: an optional function to call upon login
:type success_callback: func
:param return_response: an optional function to send the OAuth response to
:type return_response: func
|
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 receives the successful result\n of authentication, ``/api/user`` that acts as a test endpoint, and a\n :meth:`~flask_oauthlib.client.OAuthRemoteApp.tokengetter`.\n\n :param app: the app to add OAuth endpoints to\n :type app: ~flask.Flask\n\n :param consumer_key: the OAuth client consumer key\n :type consumer_key: str\n\n :param secret_key: the OAuth client secret, inferred using\n :func:`~common.rpc.secrets.get_secret` if omitted\n :type secret_key: str\n\n :param success_callback: an optional function to call upon login\n :type success_callback: func\n\n :param return_response: an optional function to send the OAuth response to\n :type return_response: func\n '
oauth = OAuth(app)
if (os.getenv('ENV') == 'prod'):
if (secret_key is None):
app.secret_key = get_secret(secret_name='OKPY_OAUTH_SECRET')
else:
app.secret_key = secret_key
else:
consumer_key = 'local-dev-all'
app.secret_key = 'kmSPJYPzKJglOOOmr7q0irMfBVMRFXN'
if (not app.debug):
app.config.update(SESSION_COOKIE_SECURE=True, SESSION_COOKIE_HTTPONLY=True, SESSION_COOKIE_SAMESITE='Lax')
remote = oauth.remote_app('ok-server', consumer_key=consumer_key, consumer_secret=app.secret_key, request_token_params={'scope': 'all', 'state': (lambda : security.gen_salt(10))}, base_url='https://okpy.org/api/v3/', request_token_url=None, access_token_method='POST', access_token_url='https://okpy.org/oauth/token', authorize_url='https://okpy.org/oauth/authorize')
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[4]))
query.update(params)
url_parts[4] = urllib.parse.urlencode(query)
uri = urllib.parse.urlunparse(url_parts)
return (uri, headers, body)
remote.pre_request = check_req
@app.route('/oauth/login')
def login():
if app.debug:
response = remote.authorize(callback=url_for('authorized', _external=True))
else:
response = remote.authorize(url_for('authorized', _external=True, _scheme='https'))
return response
@app.route('/oauth/authorized')
def authorized():
resp = remote.authorized_response()
if (resp is None):
return ('Access denied: error=%s' % request.args['error'])
if (isinstance(resp, dict) and ('access_token' in resp)):
session['access_token'] = (resp['access_token'], )
if return_response:
return_response(resp)
if success_callback:
success_callback()
target = session.get(REDIRECT_KEY)
if target:
session.pop(REDIRECT_KEY)
return redirect(target)
return redirect(url_for('index'))
@app.route('/api/user', methods=['POST'])
def client_method():
if ('access_token' not in session):
abort(401)
token = session['access_token'][0]
r = requests.get('https://okpy.org/api/v3/user/?access_token={}'.format(token))
if (not r.ok):
abort(401)
return jsonify(r.json())
@remote.tokengetter
def get_oauth_token():
return session.get('access_token')
app.remote = remote
|
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[4]))
query.update(params)
url_parts[4] = urllib.parse.urlencode(query)
uri = urllib.parse.urlunparse(url_parts)
return (uri, headers, body)
| 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)
url_parts[4] = urllib.parse.urlencode(query)
uri = urllib.parse.urlunparse(url_parts)
return (uri, headers, body)
|
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 = (variance + 1)
X = ((util.randn(n, d, seed=seed) * np.sqrt(draw_variance)) + draw_mean)
dat = data.Data(X)
for J in [1, 3]:
sig2 = (util.meddistance(X, subsample=1000) ** 2)
k = kernel.KGauss(sig2)
V = util.fit_gaussian_draw(X, J, seed=(seed + 1))
null_sim = gof.FSSDH0SimCovObs(n_simulate=200, seed=3)
fssd = gof.FSSD(isonorm, k, V, null_sim=null_sim, alpha=alpha)
tresult = fssd.perform_test(dat, return_simulated_stats=True)
self.assertGreaterEqual(tresult['pvalue'], 0)
self.assertLessEqual(tresult['pvalue'], 1)
| 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, seed=seed) * np.sqrt(draw_variance)) + draw_mean)
dat = data.Data(X)
for J in [1, 3]:
sig2 = (util.meddistance(X, subsample=1000) ** 2)
k = kernel.KGauss(sig2)
V = util.fit_gaussian_draw(X, J, seed=(seed + 1))
null_sim = gof.FSSDH0SimCovObs(n_simulate=200, seed=3)
fssd = gof.FSSD(isonorm, k, V, null_sim=null_sim, alpha=alpha)
tresult = fssd.perform_test(dat, return_simulated_stats=True)
self.assertGreaterEqual(tresult['pvalue'], 0)
self.assertLessEqual(tresult['pvalue'], 1)
|
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), (variance + 0))
dat = ds.sample(n, seed=seed)
for J in [1, 4]:
opts = {'reg': 0.01, 'max_iter': 10, 'tol_fun': 0.001, 'disp': False}
(tr, te) = dat.split_tr_te(tr_proportion=0.3, seed=(seed + 1))
Xtr = tr.X
gwidth0 = (util.meddistance(Xtr, subsample=1000) ** 2)
V0 = util.fit_gaussian_draw(Xtr, J, seed=(seed + 1))
(V_opt, gw_opt, opt_result) = gof.GaussFSSD.optimize_locs_widths(p, tr, gwidth0, V0, **opts)
k_opt = kernel.KGauss(gw_opt)
null_sim = gof.FSSDH0SimCovObs(n_simulate=2000, seed=10)
fssd_opt = gof.FSSD(p, k_opt, V_opt, null_sim=null_sim, alpha=alpha)
fssd_opt_result = fssd_opt.perform_test(te, return_simulated_stats=True)
assert fssd_opt_result['h0_rejected']
| -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=seed)
for J in [1, 4]:
opts = {'reg': 0.01, 'max_iter': 10, 'tol_fun': 0.001, 'disp': False}
(tr, te) = dat.split_tr_te(tr_proportion=0.3, seed=(seed + 1))
Xtr = tr.X
gwidth0 = (util.meddistance(Xtr, subsample=1000) ** 2)
V0 = util.fit_gaussian_draw(Xtr, J, seed=(seed + 1))
(V_opt, gw_opt, opt_result) = gof.GaussFSSD.optimize_locs_widths(p, tr, gwidth0, V0, **opts)
k_opt = kernel.KGauss(gw_opt)
null_sim = gof.FSSDH0SimCovObs(n_simulate=2000, seed=10)
fssd_opt = gof.FSSD(p, k_opt, V_opt, null_sim=null_sim, alpha=alpha)
fssd_opt_result = fssd_opt.perform_test(te, return_simulated_stats=True)
assert fssd_opt_result['h0_rejected']
|
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.DSIsotropicNormal((mean + 4), (variance + 0))
dat = ds.sample(n, seed=seed)
for J in [1, 3]:
opts = {'reg': 0.01, 'max_iter': 10, 'tol_fun': 0.001, 'disp': False}
(tr, te) = dat.split_tr_te(tr_proportion=0.3, seed=(seed + 1))
(V_opt, gw_opt, opt_result) = gof.GaussFSSD.optimize_auto_init(p, tr, J, **opts)
k_opt = kernel.KGauss(gw_opt)
null_sim = gof.FSSDH0SimCovObs(n_simulate=2000, seed=10)
fssd_opt = gof.FSSD(p, k_opt, V_opt, null_sim=null_sim, alpha=alpha)
fssd_opt_result = fssd_opt.perform_test(te, return_simulated_stats=True)
assert fssd_opt_result['h0_rejected']
| 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, seed=seed)
for J in [1, 3]:
opts = {'reg': 0.01, 'max_iter': 10, 'tol_fun': 0.001, 'disp': False}
(tr, te) = dat.split_tr_te(tr_proportion=0.3, seed=(seed + 1))
(V_opt, gw_opt, opt_result) = gof.GaussFSSD.optimize_auto_init(p, tr, J, **opts)
k_opt = kernel.KGauss(gw_opt)
null_sim = gof.FSSDH0SimCovObs(n_simulate=2000, seed=10)
fssd_opt = gof.FSSD(p, k_opt, V_opt, null_sim=null_sim, alpha=alpha)
fssd_opt_result = fssd_opt.perform_test(te, return_simulated_stats=True)
assert fssd_opt_result['h0_rejected']
|
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['password'])
| 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['password'])
|
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_directory_names_only((brew_taps_path + ('/%s' % user)))
taps = (tap for tap in taps if tap.startswith('homebrew-'))
for tap in taps:
tap_cmd_path = (brew_taps_path + (TAP_CMD_PATH % (user, tap)))
if os.path.isdir(tap_cmd_path):
commands += (name.replace('brew-', '').replace('.rb', '') for name in os.listdir(tap_cmd_path) if _is_brew_tap_cmd_naming(name))
return commands
| 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_directory_names_only((brew_taps_path + ('/%s' % user)))
taps = (tap for tap in taps if tap.startswith('homebrew-'))
for tap in taps:
tap_cmd_path = (brew_taps_path + (TAP_CMD_PATH % (user, tap)))
if os.path.isdir(tap_cmd_path):
commands += (name.replace('brew-', ).replace('.rb', ) for name in os.listdir(tap_cmd_path) if _is_brew_tap_cmd_naming(name))
return commands
|
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):
AA = A3
AvAk = 7.75
if ((Av >= Av_me) and (Av < Av_hi)):
AA = A2
AvAk = 7.75
if ((Av >= Av_lo) and (Av < Av_me)):
AA = A2
AvAk = 7.75
if (Av < Av_lo):
AA = A1
AvAk = 9.03
AK_AV = (1.0 / AvAk)
Alambda_func = interp1d(awl, ((Av * AK_AV) * AA))
Alambda = Alambda_func(wl)
if mags:
return Alambda
else:
return (10.0 ** (0.4 * Alambda))
| 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 = A2
AvAk = 7.75
if ((Av >= Av_lo) and (Av < Av_me)):
AA = A2
AvAk = 7.75
if (Av < Av_lo):
AA = A1
AvAk = 9.03
AK_AV = (1.0 / AvAk)
Alambda_func = interp1d(awl, ((Av * AK_AV) * AA))
Alambda = Alambda_func(wl)
if mags:
return Alambda
else:
return (10.0 ** (0.4 * Alambda))
|
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), label='2.0 mags')
avs = av_points(wl)
ax.plot(wl, (10 ** (0.4 * avs)), 'k:', label='fiducial')
ax.legend(loc='upper right')
ax.set_xlabel('$\\lambda\\quad[\\AA]$')
ax.set_ylabel('$A_\\lambda$')
plt.savefig('redenning_curves.png')
| -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 = av_points(wl)
ax.plot(wl, (10 ** (0.4 * avs)), 'k:', label='fiducial')
ax.legend(loc='upper right')
ax.set_xlabel('$\\lambda\\quad[\\AA]$')
ax.set_ylabel('$A_\\lambda$')
plt.savefig('redenning_curves.png')
|
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
while (i < puzzle_x):
if ((crossword[j][i] == '-') or (((i + 1) < puzzle_x) and (crossword[j][i] == 'v') and (crossword[j][(i + 1)] == '-')) or (((j + 1) < puzzle_y) and (crossword[j][i] == 'h') and (crossword[(j + 1)][i] == '-'))):
if (crossword[j][i] != '-'):
cruces.append([sig, i, j])
crossword[j] = ((crossword[j][:i] + 'i') + crossword[j][(i + 1):])
pos[sig][0] = i
pos[sig][1] = j
sig += 1
iter_i = (i + 1)
iter_j = (j + 1)
while ((iter_i < puzzle_x) and ((crossword[j][iter_i] == '-') or (crossword[j][iter_i] == 'v'))):
pos[(sig - 1)][2] = 'h'
pos[(sig - 1)][3] += 1
if (crossword[j][iter_i] == 'v'):
crossword[j] = ((crossword[j][:iter_i] + 'x') + crossword[j][(iter_i + 1):])
cruces.append([(sig - 1), iter_i, j])
else:
crossword[j] = ((crossword[j][:iter_i] + 'h') + crossword[j][(iter_i + 1):])
iter_i += 1
while ((iter_j < puzzle_y) and ((crossword[iter_j][i] == '-') or (crossword[iter_j][i] == 'h'))):
pos[(sig - 1)][2] = 'v'
pos[(sig - 1)][3] += 1
if (crossword[iter_j][i] == 'h'):
crossword[iter_j] = ((crossword[iter_j][:i] + 'x') + crossword[iter_j][(i + 1):])
cruces.append([(sig - 1), i, iter_j])
else:
crossword[iter_j] = ((crossword[iter_j][:i] + 'v') + crossword[iter_j][(i + 1):])
iter_j += 1
i += 1
j += 1
for palabra_aux1 in pos:
posibles = []
for pal in palabras:
if (len(pal) == palabra_aux1[3]):
posibles.append(pal)
palabra_aux1.append(posibles)
for cruce in cruces:
i = 0
while (i < len(pos)):
if (pos[i][2] == 'h'):
if ((pos[i][0] <= cruce[1]) and ((pos[i][0] + pos[i][3]) >= cruce[1]) and (pos[i][1] == cruce[2])):
break
if (pos[i][2] == 'v'):
if ((pos[i][1] <= cruce[2]) and ((pos[i][1] + pos[i][3]) >= cruce[2]) and (pos[i][0] == cruce[1])):
break
i += 1
letra1 = abs((((cruce[1] - pos[i][0]) + cruce[2]) - pos[i][1]))
letra2 = abs((((pos[cruce[0]][0] - cruce[1]) + pos[cruce[0]][1]) - cruce[2]))
palabra_aux1 = ''
palabra_aux2 = ''
for palabra1 in pos[i][4]:
for palabra2 in pos[cruce[0]][4]:
if (palabra1[letra1] == palabra2[letra2]):
palabra_aux1 = palabra1
palabra_aux2 = palabra2
break
pos[i][4] = [palabra_aux1]
pos[cruce[0]][4] = [palabra_aux2]
for pal in pos:
if (pal[2] == 'h'):
crossword[pal[1]] = ((crossword[pal[1]][:pal[0]] + pal[4][0]) + crossword[pal[1]][(pal[0] + pal[3]):])
else:
i = 0
while (i < pal[3]):
crossword[(pal[1] + i)] = ((crossword[(pal[1] + i)][:pal[0]] + pal[4][0][i]) + crossword[(pal[1] + i)][(pal[0] + 1):])
i += 1
return crossword
| -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):
if ((crossword[j][i] == '-') or (((i + 1) < puzzle_x) and (crossword[j][i] == 'v') and (crossword[j][(i + 1)] == '-')) or (((j + 1) < puzzle_y) and (crossword[j][i] == 'h') and (crossword[(j + 1)][i] == '-'))):
if (crossword[j][i] != '-'):
cruces.append([sig, i, j])
crossword[j] = ((crossword[j][:i] + 'i') + crossword[j][(i + 1):])
pos[sig][0] = i
pos[sig][1] = j
sig += 1
iter_i = (i + 1)
iter_j = (j + 1)
while ((iter_i < puzzle_x) and ((crossword[j][iter_i] == '-') or (crossword[j][iter_i] == 'v'))):
pos[(sig - 1)][2] = 'h'
pos[(sig - 1)][3] += 1
if (crossword[j][iter_i] == 'v'):
crossword[j] = ((crossword[j][:iter_i] + 'x') + crossword[j][(iter_i + 1):])
cruces.append([(sig - 1), iter_i, j])
else:
crossword[j] = ((crossword[j][:iter_i] + 'h') + crossword[j][(iter_i + 1):])
iter_i += 1
while ((iter_j < puzzle_y) and ((crossword[iter_j][i] == '-') or (crossword[iter_j][i] == 'h'))):
pos[(sig - 1)][2] = 'v'
pos[(sig - 1)][3] += 1
if (crossword[iter_j][i] == 'h'):
crossword[iter_j] = ((crossword[iter_j][:i] + 'x') + crossword[iter_j][(i + 1):])
cruces.append([(sig - 1), i, iter_j])
else:
crossword[iter_j] = ((crossword[iter_j][:i] + 'v') + crossword[iter_j][(i + 1):])
iter_j += 1
i += 1
j += 1
for palabra_aux1 in pos:
posibles = []
for pal in palabras:
if (len(pal) == palabra_aux1[3]):
posibles.append(pal)
palabra_aux1.append(posibles)
for cruce in cruces:
i = 0
while (i < len(pos)):
if (pos[i][2] == 'h'):
if ((pos[i][0] <= cruce[1]) and ((pos[i][0] + pos[i][3]) >= cruce[1]) and (pos[i][1] == cruce[2])):
break
if (pos[i][2] == 'v'):
if ((pos[i][1] <= cruce[2]) and ((pos[i][1] + pos[i][3]) >= cruce[2]) and (pos[i][0] == cruce[1])):
break
i += 1
letra1 = abs((((cruce[1] - pos[i][0]) + cruce[2]) - pos[i][1]))
letra2 = abs((((pos[cruce[0]][0] - cruce[1]) + pos[cruce[0]][1]) - cruce[2]))
palabra_aux1 =
palabra_aux2 =
for palabra1 in pos[i][4]:
for palabra2 in pos[cruce[0]][4]:
if (palabra1[letra1] == palabra2[letra2]):
palabra_aux1 = palabra1
palabra_aux2 = palabra2
break
pos[i][4] = [palabra_aux1]
pos[cruce[0]][4] = [palabra_aux2]
for pal in pos:
if (pal[2] == 'h'):
crossword[pal[1]] = ((crossword[pal[1]][:pal[0]] + pal[4][0]) + crossword[pal[1]][(pal[0] + pal[3]):])
else:
i = 0
while (i < pal[3]):
crossword[(pal[1] + i)] = ((crossword[(pal[1] + i)][:pal[0]] + pal[4][0][i]) + crossword[(pal[1] + i)][(pal[0] + 1):])
i += 1
return crossword
|
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 SentenceTransformerModel\n '
self.model = model
self.examples = examples
self.label_type = (torch.long if isinstance(self.examples[0].label, int) else torch.float)
| -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 SentenceTransformerModel\n '
self.model = model
self.examples = examples
self.label_type = (torch.long if isinstance(self.examples[0].label, int) else torch.float)
|
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!")
self.page = page
self.title = page.title(as_link=True)
self.site = page.site
if (('%(' in self.message) and (')s' in self.message)):
super(PageRelatedError, self).__init__((self.message % self.__dict__))
else:
super(PageRelatedError, self).__init__((self.message % page))
| 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!")
self.page = page
self.title = page.title(as_link=True)
self.site = page.site
if (('%(' in self.message) and (')s' in self.message)):
super(PageRelatedError, self).__init__((self.message % self.__dict__))
else:
super(PageRelatedError, self).__init__((self.message % page))
|
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(InconsistentTitleReceived, self).__init__(page)
| 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(InconsistentTitleReceived, self).__init__(page)
|
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:
node.set(key, kv_map.get(key))
| 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:
node.set(key, kv_map.get(key))
|
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)):
parent_node.remove(child)
| 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)):
parent_node.remove(child)
|
@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 'autobinx' property must be specified as a bool\n (either True, or False)\n\n Returns\n -------\n bool\n "
return self['autobinx']
| 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
-------
bool
|
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 'autobinx' property must be specified as a bool\n (either True, or False)\n\n Returns\n -------\n bool\n "
return self['autobinx']
|
@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 'autobiny' property must be specified as a bool\n (either True, or False)\n\n Returns\n -------\n bool\n "
return self['autobiny']
| -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
-------
bool
|
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 'autobiny' property must be specified as a bool\n (either True, or False)\n\n Returns\n -------\n bool\n "
return self['autobiny']
|
@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 to whether numbers in the `color` array are all\n positive, all negative or mixed.\n\n The 'autocolorscale' property must be specified as a bool\n (either True, or False)\n\n Returns\n -------\n bool\n "
return self['autocolorscale']
| -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 'autocolorscale' property must be specified as a bool
(either True, or False)
Returns
-------
bool
|
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 to whether numbers in the `color` array are all\n positive, all negative or mixed.\n\n The 'autocolorscale' property must be specified as a bool\n (either True, or False)\n\n Returns\n -------\n bool\n "
return self['autocolorscale']
|
@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 must be specified as a bool\n (either True, or False)\n\n Returns\n -------\n bool\n "
return self['autocontour']
| 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 must be specified as a bool\n (either True, or False)\n\n Returns\n -------\n bool\n "
return self['autocontour']
|
@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 - A string\n - A number that will be converted to a string\n\n Returns\n -------\n str\n "
return self['bingroup']
| -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 - A string\n - A number that will be converted to a string\n\n Returns\n -------\n str\n "
return self['bingroup']
|
@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 Note that multiple color scales can be linked to the same color\n axis.\n\n The \'coloraxis\' property is an identifier of a particular\n subplot, of type \'coloraxis\', that may be specified as the string \'coloraxis\'\n optionally followed by an integer >= 1\n (e.g. \'coloraxis\', \'coloraxis1\', \'coloraxis2\', \'coloraxis3\', etc.)\n\n Returns\n -------\n str\n '
return self['coloraxis']
| -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 'coloraxis' property is an identifier of a particular
subplot, of type 'coloraxis', that may be specified as the string 'coloraxis'
optionally followed by an integer >= 1
(e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.)
Returns
-------
str
|
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 Note that multiple color scales can be linked to the same color\n axis.\n\n The \'coloraxis\' property is an identifier of a particular\n subplot, of type \'coloraxis\', that may be specified as the string \'coloraxis\'\n optionally followed by an integer >= 1\n (e.g. \'coloraxis\', \'coloraxis1\', \'coloraxis2\', \'coloraxis3\', etc.)\n\n Returns\n -------\n str\n '
return self['coloraxis']
|
@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 constructor\n\n Supported dict properties:\n\n bgcolor\n Sets the color of padded area.\n bordercolor\n Sets the axis line color.\n borderwidth\n Sets the width (in px) or the border enclosing\n this color bar.\n dtick\n Sets the step in-between ticks on this axis.\n Use with `tick0`. Must be a positive number, or\n special strings available to "log" and "date"\n axes. If the axis `type` is "log", then ticks\n are set every 10^(n*dtick) where n is the tick\n number. For example, to set a tick mark at 1,\n 10, 100, 1000, ... set dtick to 1. To set tick\n marks at 1, 100, 10000, ... set dtick to 2. To\n set tick marks at 1, 5, 25, 125, 625, 3125, ...\n set dtick to log_10(5), or 0.69897000433. "log"\n has several special values; "L<f>", where `f`\n is a positive number, gives ticks linearly\n spaced in value (but not position). For example\n `tick0` = 0.1, `dtick` = "L0.5" will put ticks\n at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10\n plus small digits between, use "D1" (all\n digits) or "D2" (only 2 and 5). `tick0` is\n ignored for "D1" and "D2". If the axis `type`\n is "date", then you must convert the time to\n milliseconds. For example, to set the interval\n between ticks to one day, set `dtick` to\n 86400000.0. "date" also has special values\n "M<n>" gives ticks spaced by a number of\n months. `n` must be a positive integer. To set\n ticks on the 15th of every third month, set\n `tick0` to "2000-01-15" and `dtick` to "M3". To\n set ticks every 4 years, set `dtick` to "M48"\n exponentformat\n Determines a formatting rule for the tick\n exponents. For example, consider the number\n 1,000,000,000. If "none", it appears as\n 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If\n "power", 1x10^9 (with 9 in a super script). If\n "SI", 1G. If "B", 1B.\n len\n Sets the length of the color bar This measure\n excludes the padding of both ends. That is, the\n color bar length is this length minus the\n padding on both ends.\n lenmode\n Determines whether this color bar\'s length\n (i.e. the measure in the color variation\n direction) is set in units of plot "fraction"\n or in *pixels. Use `len` to set the value.\n minexponent\n Hide SI prefix for 10^n if |n| is below this\n number. This only has an effect when\n `tickformat` is "SI" or "B".\n nticks\n Specifies the maximum number of ticks for the\n particular axis. The actual number of ticks\n will be chosen automatically to be less than or\n equal to `nticks`. Has an effect only if\n `tickmode` is set to "auto".\n orientation\n Sets the orientation of the colorbar.\n outlinecolor\n Sets the axis line color.\n outlinewidth\n Sets the width (in px) of the axis line.\n separatethousands\n If "true", even 4-digit integers are separated\n showexponent\n If "all", all exponents are shown besides their\n significands. If "first", only the exponent of\n the first tick is shown. If "last", only the\n exponent of the last tick is shown. If "none",\n no exponents appear.\n showticklabels\n Determines whether or not the tick labels are\n drawn.\n showtickprefix\n If "all", all tick labels are displayed with a\n prefix. If "first", only the first tick is\n displayed with a prefix. If "last", only the\n last tick is displayed with a suffix. If\n "none", tick prefixes are hidden.\n showticksuffix\n Same as `showtickprefix` but for tick suffixes.\n thickness\n Sets the thickness of the color bar This\n measure excludes the size of the padding, ticks\n and labels.\n thicknessmode\n Determines whether this color bar\'s thickness\n (i.e. the measure in the constant color\n direction) is set in units of plot "fraction"\n or in "pixels". Use `thickness` to set the\n value.\n tick0\n Sets the placement of the first tick on this\n axis. Use with `dtick`. If the axis `type` is\n "log", then you must take the log of your\n starting tick (e.g. to set the starting tick to\n 100, set the `tick0` to 2) except when\n `dtick`=*L<f>* (see `dtick` for more info). If\n the axis `type` is "date", it should be a date\n string, like date data. If the axis `type` is\n "category", it should be a number, using the\n scale where each category is assigned a serial\n number from zero in the order it appears.\n tickangle\n Sets the angle of the tick labels with respect\n to the horizontal. For example, a `tickangle`\n of -90 draws the tick labels vertically.\n tickcolor\n Sets the tick color.\n tickfont\n Sets the color bar\'s tick label font\n tickformat\n Sets the tick label formatting rule using d3\n formatting mini-languages which are very\n similar to those in Python. For numbers, see: h\n ttps://github.com/d3/d3-format/tree/v1.4.5#d3-f\n ormat. And for dates see:\n https://github.com/d3/d3-time-\n format/tree/v2.2.3#locale_format. We add two\n items to d3\'s date formatter: "%h" for half of\n the year as a decimal number as well as "%{n}f"\n for fractional seconds with n digits. For\n example, *2016-10-13 09:15:23.456* with\n tickformat "%H~%M~%S.%2f" would display\n "09~15~23.46"\n tickformatstops\n A tuple of :class:`plotly.graph_objects.histogr\n am2dcontour.colorbar.Tickformatstop` instances\n or dicts with compatible properties\n tickformatstopdefaults\n When used in a template (as layout.template.dat\n a.histogram2dcontour.colorbar.tickformatstopdef\n aults), sets the default property values to use\n for elements of\n histogram2dcontour.colorbar.tickformatstops\n ticklabeloverflow\n Determines how we handle tick labels that would\n overflow either the graph div or the domain of\n the axis. The default value for inside tick\n labels is *hide past domain*. In other cases\n the default is *hide past div*.\n ticklabelposition\n Determines where tick labels are drawn relative\n to the ticks. Left and right options are used\n when `orientation` is "h", top and bottom when\n `orientation` is "v".\n ticklabelstep\n Sets the spacing between tick labels as\n compared to the spacing between ticks. A value\n of 1 (default) means each tick gets a label. A\n value of 2 means shows every 2nd label. A\n larger value n means only every nth tick is\n labeled. `tick0` determines which labels are\n shown. Not implemented for axes with `type`\n "log" or "multicategory", or when `tickmode` is\n "array".\n ticklen\n Sets the tick length (in px).\n tickmode\n Sets the tick mode for this axis. If "auto",\n the number of ticks is set via `nticks`. If\n "linear", the placement of the ticks is\n determined by a starting position `tick0` and a\n tick step `dtick` ("linear" is the default\n value if `tick0` and `dtick` are provided). If\n "array", the placement of the ticks is set via\n `tickvals` and the tick text is `ticktext`.\n ("array" is the default value if `tickvals` is\n provided).\n tickprefix\n Sets a tick label prefix.\n ticks\n Determines whether ticks are drawn or not. If\n "", this axis\' ticks are not drawn. If\n "outside" ("inside"), this axis\' are drawn\n outside (inside) the axis lines.\n ticksuffix\n Sets a tick label suffix.\n ticktext\n Sets the text displayed at the ticks position\n via `tickvals`. Only has an effect if\n `tickmode` is set to "array". Used with\n `tickvals`.\n ticktextsrc\n Sets the source reference on Chart Studio Cloud\n for `ticktext`.\n tickvals\n Sets the values at which ticks on this axis\n appear. Only has an effect if `tickmode` is set\n to "array". Used with `ticktext`.\n tickvalssrc\n Sets the source reference on Chart Studio Cloud\n for `tickvals`.\n tickwidth\n Sets the tick width (in px).\n title\n :class:`plotly.graph_objects.histogram2dcontour\n .colorbar.Title` instance or dict with\n compatible properties\n titlefont\n Deprecated: Please use\n histogram2dcontour.colorbar.title.font instead.\n Sets this color bar\'s title font. Note that the\n title\'s font used to be set by the now\n deprecated `titlefont` attribute.\n titleside\n Deprecated: Please use\n histogram2dcontour.colorbar.title.side instead.\n Determines the location of color bar\'s title\n with respect to the color bar. Defaults to\n "top" when `orientation` if "v" and defaults\n to "right" when `orientation` if "h". Note that\n the title\'s location used to be set by the now\n deprecated `titleside` attribute.\n x\n Sets the x position of the color bar (in plot\n fraction). Defaults to 1.02 when `orientation`\n is "v" and 0.5 when `orientation` is "h".\n xanchor\n Sets this color bar\'s horizontal position\n anchor. This anchor binds the `x` position to\n the "left", "center" or "right" of the color\n bar. Defaults to "left" when `orientation` is\n "v" and "center" when `orientation` is "h".\n xpad\n Sets the amount of padding (in px) along the x\n direction.\n y\n Sets the y position of the color bar (in plot\n fraction). Defaults to 0.5 when `orientation`\n is "v" and 1.02 when `orientation` is "h".\n yanchor\n Sets this color bar\'s vertical position anchor\n This anchor binds the `y` position to the\n "top", "middle" or "bottom" of the color bar.\n Defaults to "middle" when `orientation` is "v"\n and "bottom" when `orientation` is "h".\n ypad\n Sets the amount of padding (in px) along the y\n direction.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.ColorBar\n '
return self['colorbar']
| 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 padded area.
bordercolor
Sets the axis line color.
borderwidth
Sets the width (in px) or the border enclosing
this color bar.
dtick
Sets the step in-between ticks on this axis.
Use with `tick0`. Must be a positive number, or
special strings available to "log" and "date"
axes. If the axis `type` is "log", then ticks
are set every 10^(n*dtick) where n is the tick
number. For example, to set a tick mark at 1,
10, 100, 1000, ... set dtick to 1. To set tick
marks at 1, 100, 10000, ... set dtick to 2. To
set tick marks at 1, 5, 25, 125, 625, 3125, ...
set dtick to log_10(5), or 0.69897000433. "log"
has several special values; "L<f>", where `f`
is a positive number, gives ticks linearly
spaced in value (but not position). For example
`tick0` = 0.1, `dtick` = "L0.5" will put ticks
at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10
plus small digits between, use "D1" (all
digits) or "D2" (only 2 and 5). `tick0` is
ignored for "D1" and "D2". If the axis `type`
is "date", then you must convert the time to
milliseconds. For example, to set the interval
between ticks to one day, set `dtick` to
86400000.0. "date" also has special values
"M<n>" gives ticks spaced by a number of
months. `n` must be a positive integer. To set
ticks on the 15th of every third month, set
`tick0` to "2000-01-15" and `dtick` to "M3". To
set ticks every 4 years, set `dtick` to "M48"
exponentformat
Determines a formatting rule for the tick
exponents. For example, consider the number
1,000,000,000. If "none", it appears as
1,000,000,000. If "e", 1e+9. If "E", 1E+9. If
"power", 1x10^9 (with 9 in a super script). If
"SI", 1G. If "B", 1B.
len
Sets the length of the color bar This measure
excludes the padding of both ends. That is, the
color bar length is this length minus the
padding on both ends.
lenmode
Determines whether this color bar's length
(i.e. the measure in the color variation
direction) is set in units of plot "fraction"
or in *pixels. Use `len` to set the value.
minexponent
Hide SI prefix for 10^n if |n| is below this
number. This only has an effect when
`tickformat` is "SI" or "B".
nticks
Specifies the maximum number of ticks for the
particular axis. The actual number of ticks
will be chosen automatically to be less than or
equal to `nticks`. Has an effect only if
`tickmode` is set to "auto".
orientation
Sets the orientation of the colorbar.
outlinecolor
Sets the axis line color.
outlinewidth
Sets the width (in px) of the axis line.
separatethousands
If "true", even 4-digit integers are separated
showexponent
If "all", all exponents are shown besides their
significands. If "first", only the exponent of
the first tick is shown. If "last", only the
exponent of the last tick is shown. If "none",
no exponents appear.
showticklabels
Determines whether or not the tick labels are
drawn.
showtickprefix
If "all", all tick labels are displayed with a
prefix. If "first", only the first tick is
displayed with a prefix. If "last", only the
last tick is displayed with a suffix. If
"none", tick prefixes are hidden.
showticksuffix
Same as `showtickprefix` but for tick suffixes.
thickness
Sets the thickness of the color bar This
measure excludes the size of the padding, ticks
and labels.
thicknessmode
Determines whether this color bar's thickness
(i.e. the measure in the constant color
direction) is set in units of plot "fraction"
or in "pixels". Use `thickness` to set the
value.
tick0
Sets the placement of the first tick on this
axis. Use with `dtick`. If the axis `type` is
"log", then you must take the log of your
starting tick (e.g. to set the starting tick to
100, set the `tick0` to 2) except when
`dtick`=*L<f>* (see `dtick` for more info). If
the axis `type` is "date", it should be a date
string, like date data. If the axis `type` is
"category", it should be a number, using the
scale where each category is assigned a serial
number from zero in the order it appears.
tickangle
Sets the angle of the tick labels with respect
to the horizontal. For example, a `tickangle`
of -90 draws the tick labels vertically.
tickcolor
Sets the tick color.
tickfont
Sets the color bar's tick label font
tickformat
Sets the tick label formatting rule using d3
formatting mini-languages which are very
similar to those in Python. For numbers, see: h
ttps://github.com/d3/d3-format/tree/v1.4.5#d3-f
ormat. 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: "%h" for half of
the year as a decimal number as well as "%{n}f"
for fractional seconds with n digits. For
example, *2016-10-13 09:15:23.456* with
tickformat "%H~%M~%S.%2f" would display
"09~15~23.46"
tickformatstops
A tuple of :class:`plotly.graph_objects.histogr
am2dcontour.colorbar.Tickformatstop` instances
or dicts with compatible properties
tickformatstopdefaults
When used in a template (as layout.template.dat
a.histogram2dcontour.colorbar.tickformatstopdef
aults), sets the default property values to use
for elements of
histogram2dcontour.colorbar.tickformatstops
ticklabeloverflow
Determines how we handle tick labels that would
overflow either the graph div or the domain of
the axis. The default value for inside tick
labels is *hide past domain*. In other cases
the default is *hide past div*.
ticklabelposition
Determines where tick labels are drawn relative
to the ticks. Left and right options are used
when `orientation` is "h", top and bottom when
`orientation` is "v".
ticklabelstep
Sets the spacing between tick labels as
compared to the spacing between ticks. A value
of 1 (default) means each tick gets a label. A
value of 2 means shows every 2nd label. A
larger value n means only every nth tick is
labeled. `tick0` determines which labels are
shown. Not implemented for axes with `type`
"log" or "multicategory", or when `tickmode` is
"array".
ticklen
Sets the tick length (in px).
tickmode
Sets the tick mode for this axis. If "auto",
the number of ticks is set via `nticks`. If
"linear", the placement of the ticks is
determined by a starting position `tick0` and a
tick step `dtick` ("linear" is the default
value if `tick0` and `dtick` are provided). If
"array", the placement of the ticks is set via
`tickvals` and the tick text is `ticktext`.
("array" is the default value if `tickvals` is
provided).
tickprefix
Sets a tick label prefix.
ticks
Determines whether ticks are drawn or not. If
"", this axis' ticks are not drawn. If
"outside" ("inside"), this axis' are drawn
outside (inside) the axis lines.
ticksuffix
Sets a tick label suffix.
ticktext
Sets the text displayed at the ticks position
via `tickvals`. Only has an effect if
`tickmode` is set to "array". Used with
`tickvals`.
ticktextsrc
Sets the source reference on Chart Studio Cloud
for `ticktext`.
tickvals
Sets the values at which ticks on this axis
appear. Only has an effect if `tickmode` is set
to "array". Used with `ticktext`.
tickvalssrc
Sets the source reference on Chart Studio Cloud
for `tickvals`.
tickwidth
Sets the tick width (in px).
title
:class:`plotly.graph_objects.histogram2dcontour
.colorbar.Title` instance or dict with
compatible properties
titlefont
Deprecated: Please use
histogram2dcontour.colorbar.title.font instead.
Sets this color bar's title font. Note that the
title's font used to be set by the now
deprecated `titlefont` attribute.
titleside
Deprecated: Please use
histogram2dcontour.colorbar.title.side instead.
Determines the location of color bar's title
with respect to the color bar. Defaults to
"top" when `orientation` if "v" and defaults
to "right" when `orientation` if "h". Note that
the title's location used to be set by the now
deprecated `titleside` attribute.
x
Sets the x position of the color bar (in plot
fraction). Defaults to 1.02 when `orientation`
is "v" and 0.5 when `orientation` is "h".
xanchor
Sets this color bar's horizontal position
anchor. This anchor binds the `x` position to
the "left", "center" or "right" of the color
bar. Defaults to "left" when `orientation` is
"v" and "center" when `orientation` is "h".
xpad
Sets the amount of padding (in px) along the x
direction.
y
Sets the y position of the color bar (in plot
fraction). Defaults to 0.5 when `orientation`
is "v" and 1.02 when `orientation` is "h".
yanchor
Sets this color bar's vertical position anchor
This anchor binds the `y` position to the
"top", "middle" or "bottom" of the color bar.
Defaults to "middle" when `orientation` is "v"
and "bottom" when `orientation` is "h".
ypad
Sets the amount of padding (in px) along the y
direction.
Returns
-------
plotly.graph_objs.histogram2dcontour.ColorBar
|
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 constructor\n\n Supported dict properties:\n\n bgcolor\n Sets the color of padded area.\n bordercolor\n Sets the axis line color.\n borderwidth\n Sets the width (in px) or the border enclosing\n this color bar.\n dtick\n Sets the step in-between ticks on this axis.\n Use with `tick0`. Must be a positive number, or\n special strings available to "log" and "date"\n axes. If the axis `type` is "log", then ticks\n are set every 10^(n*dtick) where n is the tick\n number. For example, to set a tick mark at 1,\n 10, 100, 1000, ... set dtick to 1. To set tick\n marks at 1, 100, 10000, ... set dtick to 2. To\n set tick marks at 1, 5, 25, 125, 625, 3125, ...\n set dtick to log_10(5), or 0.69897000433. "log"\n has several special values; "L<f>", where `f`\n is a positive number, gives ticks linearly\n spaced in value (but not position). For example\n `tick0` = 0.1, `dtick` = "L0.5" will put ticks\n at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10\n plus small digits between, use "D1" (all\n digits) or "D2" (only 2 and 5). `tick0` is\n ignored for "D1" and "D2". If the axis `type`\n is "date", then you must convert the time to\n milliseconds. For example, to set the interval\n between ticks to one day, set `dtick` to\n 86400000.0. "date" also has special values\n "M<n>" gives ticks spaced by a number of\n months. `n` must be a positive integer. To set\n ticks on the 15th of every third month, set\n `tick0` to "2000-01-15" and `dtick` to "M3". To\n set ticks every 4 years, set `dtick` to "M48"\n exponentformat\n Determines a formatting rule for the tick\n exponents. For example, consider the number\n 1,000,000,000. If "none", it appears as\n 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If\n "power", 1x10^9 (with 9 in a super script). If\n "SI", 1G. If "B", 1B.\n len\n Sets the length of the color bar This measure\n excludes the padding of both ends. That is, the\n color bar length is this length minus the\n padding on both ends.\n lenmode\n Determines whether this color bar\'s length\n (i.e. the measure in the color variation\n direction) is set in units of plot "fraction"\n or in *pixels. Use `len` to set the value.\n minexponent\n Hide SI prefix for 10^n if |n| is below this\n number. This only has an effect when\n `tickformat` is "SI" or "B".\n nticks\n Specifies the maximum number of ticks for the\n particular axis. The actual number of ticks\n will be chosen automatically to be less than or\n equal to `nticks`. Has an effect only if\n `tickmode` is set to "auto".\n orientation\n Sets the orientation of the colorbar.\n outlinecolor\n Sets the axis line color.\n outlinewidth\n Sets the width (in px) of the axis line.\n separatethousands\n If "true", even 4-digit integers are separated\n showexponent\n If "all", all exponents are shown besides their\n significands. If "first", only the exponent of\n the first tick is shown. If "last", only the\n exponent of the last tick is shown. If "none",\n no exponents appear.\n showticklabels\n Determines whether or not the tick labels are\n drawn.\n showtickprefix\n If "all", all tick labels are displayed with a\n prefix. If "first", only the first tick is\n displayed with a prefix. If "last", only the\n last tick is displayed with a suffix. If\n "none", tick prefixes are hidden.\n showticksuffix\n Same as `showtickprefix` but for tick suffixes.\n thickness\n Sets the thickness of the color bar This\n measure excludes the size of the padding, ticks\n and labels.\n thicknessmode\n Determines whether this color bar\'s thickness\n (i.e. the measure in the constant color\n direction) is set in units of plot "fraction"\n or in "pixels". Use `thickness` to set the\n value.\n tick0\n Sets the placement of the first tick on this\n axis. Use with `dtick`. If the axis `type` is\n "log", then you must take the log of your\n starting tick (e.g. to set the starting tick to\n 100, set the `tick0` to 2) except when\n `dtick`=*L<f>* (see `dtick` for more info). If\n the axis `type` is "date", it should be a date\n string, like date data. If the axis `type` is\n "category", it should be a number, using the\n scale where each category is assigned a serial\n number from zero in the order it appears.\n tickangle\n Sets the angle of the tick labels with respect\n to the horizontal. For example, a `tickangle`\n of -90 draws the tick labels vertically.\n tickcolor\n Sets the tick color.\n tickfont\n Sets the color bar\'s tick label font\n tickformat\n Sets the tick label formatting rule using d3\n formatting mini-languages which are very\n similar to those in Python. For numbers, see: h\n ttps://github.com/d3/d3-format/tree/v1.4.5#d3-f\n ormat. And for dates see:\n https://github.com/d3/d3-time-\n format/tree/v2.2.3#locale_format. We add two\n items to d3\'s date formatter: "%h" for half of\n the year as a decimal number as well as "%{n}f"\n for fractional seconds with n digits. For\n example, *2016-10-13 09:15:23.456* with\n tickformat "%H~%M~%S.%2f" would display\n "09~15~23.46"\n tickformatstops\n A tuple of :class:`plotly.graph_objects.histogr\n am2dcontour.colorbar.Tickformatstop` instances\n or dicts with compatible properties\n tickformatstopdefaults\n When used in a template (as layout.template.dat\n a.histogram2dcontour.colorbar.tickformatstopdef\n aults), sets the default property values to use\n for elements of\n histogram2dcontour.colorbar.tickformatstops\n ticklabeloverflow\n Determines how we handle tick labels that would\n overflow either the graph div or the domain of\n the axis. The default value for inside tick\n labels is *hide past domain*. In other cases\n the default is *hide past div*.\n ticklabelposition\n Determines where tick labels are drawn relative\n to the ticks. Left and right options are used\n when `orientation` is "h", top and bottom when\n `orientation` is "v".\n ticklabelstep\n Sets the spacing between tick labels as\n compared to the spacing between ticks. A value\n of 1 (default) means each tick gets a label. A\n value of 2 means shows every 2nd label. A\n larger value n means only every nth tick is\n labeled. `tick0` determines which labels are\n shown. Not implemented for axes with `type`\n "log" or "multicategory", or when `tickmode` is\n "array".\n ticklen\n Sets the tick length (in px).\n tickmode\n Sets the tick mode for this axis. If "auto",\n the number of ticks is set via `nticks`. If\n "linear", the placement of the ticks is\n determined by a starting position `tick0` and a\n tick step `dtick` ("linear" is the default\n value if `tick0` and `dtick` are provided). If\n "array", the placement of the ticks is set via\n `tickvals` and the tick text is `ticktext`.\n ("array" is the default value if `tickvals` is\n provided).\n tickprefix\n Sets a tick label prefix.\n ticks\n Determines whether ticks are drawn or not. If\n , this axis\' ticks are not drawn. If\n "outside" ("inside"), this axis\' are drawn\n outside (inside) the axis lines.\n ticksuffix\n Sets a tick label suffix.\n ticktext\n Sets the text displayed at the ticks position\n via `tickvals`. Only has an effect if\n `tickmode` is set to "array". Used with\n `tickvals`.\n ticktextsrc\n Sets the source reference on Chart Studio Cloud\n for `ticktext`.\n tickvals\n Sets the values at which ticks on this axis\n appear. Only has an effect if `tickmode` is set\n to "array". Used with `ticktext`.\n tickvalssrc\n Sets the source reference on Chart Studio Cloud\n for `tickvals`.\n tickwidth\n Sets the tick width (in px).\n title\n :class:`plotly.graph_objects.histogram2dcontour\n .colorbar.Title` instance or dict with\n compatible properties\n titlefont\n Deprecated: Please use\n histogram2dcontour.colorbar.title.font instead.\n Sets this color bar\'s title font. Note that the\n title\'s font used to be set by the now\n deprecated `titlefont` attribute.\n titleside\n Deprecated: Please use\n histogram2dcontour.colorbar.title.side instead.\n Determines the location of color bar\'s title\n with respect to the color bar. Defaults to\n "top" when `orientation` if "v" and defaults\n to "right" when `orientation` if "h". Note that\n the title\'s location used to be set by the now\n deprecated `titleside` attribute.\n x\n Sets the x position of the color bar (in plot\n fraction). Defaults to 1.02 when `orientation`\n is "v" and 0.5 when `orientation` is "h".\n xanchor\n Sets this color bar\'s horizontal position\n anchor. This anchor binds the `x` position to\n the "left", "center" or "right" of the color\n bar. Defaults to "left" when `orientation` is\n "v" and "center" when `orientation` is "h".\n xpad\n Sets the amount of padding (in px) along the x\n direction.\n y\n Sets the y position of the color bar (in plot\n fraction). Defaults to 0.5 when `orientation`\n is "v" and 1.02 when `orientation` is "h".\n yanchor\n Sets this color bar\'s vertical position anchor\n This anchor binds the `y` position to the\n "top", "middle" or "bottom" of the color bar.\n Defaults to "middle" when `orientation` is "v"\n and "bottom" when `orientation` is "h".\n ypad\n Sets the amount of padding (in px) along the y\n direction.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.ColorBar\n '
return self['colorbar']
|
@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 `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the\n bounds of the colorscale in color space, use `zmin` and `zmax`.\n Alternatively, `colorscale` may be a palette name string of the\n following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric,\n Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis,\n YlGnBu,YlOrRd.\n\n The 'colorscale' property is a colorscale and may be\n specified as:\n - A list of colors that will be spaced evenly to create the colorscale.\n Many predefined colorscale lists are included in the sequential, diverging,\n and cyclical modules in the plotly.colors package.\n - A list of 2-element lists where the first element is the\n normalized color level value (starting at 0 and ending at 1),\n and the second item is a valid color string.\n (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']])\n - One of the following named colorscales:\n ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance',\n 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg',\n 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl',\n 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric',\n 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys',\n 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet',\n 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges',\n 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl',\n 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn',\n 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu',\n 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar',\n 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn',\n 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid',\n 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr',\n 'ylorrd'].\n Appending '_r' to a named colorscale reverses it.\n\n Returns\n -------\n str\n "
return self['colorscale']
| -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 colorscale in color space, use `zmin` and `zmax`.
Alternatively, `colorscale` may be a palette name string of the
following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric,
Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis,
YlGnBu,YlOrRd.
The 'colorscale' property is a colorscale and may be
specified as:
- A list of colors that will be spaced evenly to create the colorscale.
Many predefined colorscale lists are included in the sequential, diverging,
and cyclical modules in the plotly.colors package.
- A list of 2-element lists where the first element is the
normalized color level value (starting at 0 and ending at 1),
and the second item is a valid color string.
(e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']])
- One of the following named colorscales:
['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance',
'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg',
'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl',
'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric',
'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys',
'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet',
'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges',
'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl',
'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn',
'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu',
'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar',
'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn',
'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid',
'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr',
'ylorrd'].
Appending '_r' to a named colorscale reverses it.
Returns
-------
str
|
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 `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the\n bounds of the colorscale in color space, use `zmin` and `zmax`.\n Alternatively, `colorscale` may be a palette name string of the\n following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric,\n Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis,\n YlGnBu,YlOrRd.\n\n The 'colorscale' property is a colorscale and may be\n specified as:\n - A list of colors that will be spaced evenly to create the colorscale.\n Many predefined colorscale lists are included in the sequential, diverging,\n and cyclical modules in the plotly.colors package.\n - A list of 2-element lists where the first element is the\n normalized color level value (starting at 0 and ending at 1),\n and the second item is a valid color string.\n (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']])\n - One of the following named colorscales:\n ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance',\n 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg',\n 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl',\n 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric',\n 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys',\n 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet',\n 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges',\n 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl',\n 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn',\n 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu',\n 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar',\n 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn',\n 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid',\n 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr',\n 'ylorrd'].\n Appending '_r' to a named colorscale reverses it.\n\n Returns\n -------\n str\n "
return self['colorscale']
|
@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 constructor\n\n Supported dict properties:\n\n coloring\n Determines the coloring method showing the\n contour values. If "fill", coloring is done\n evenly between each contour level If "heatmap",\n a heatmap gradient coloring is applied between\n each contour level. If "lines", coloring is\n done on the contour lines. If "none", no\n coloring is applied on this trace.\n end\n Sets the end contour level value. Must be more\n than `contours.start`\n labelfont\n Sets the font used for labeling the contour\n levels. The default color comes from the lines,\n if shown. The default family and size come from\n `layout.font`.\n labelformat\n Sets the contour label formatting rule using d3\n formatting mini-languages which are very\n similar to those in Python. For numbers, see: h\n ttps://github.com/d3/d3-format/tree/v1.4.5#d3-f\n ormat.\n operation\n Sets the constraint operation. "=" keeps\n regions equal to `value` "<" and "<=" keep\n regions less than `value` ">" and ">=" keep\n regions greater than `value` "[]", "()", "[)",\n and "(]" keep regions inside `value[0]` to\n `value[1]` "][", ")(", "](", ")[" keep regions\n outside `value[0]` to value[1]` Open vs. closed\n intervals make no difference to constraint\n display, but all versions are allowed for\n consistency with filter transforms.\n showlabels\n Determines whether to label the contour lines\n with their values.\n showlines\n Determines whether or not the contour lines are\n drawn. Has an effect only if\n `contours.coloring` is set to "fill".\n size\n Sets the step between each contour level. Must\n be positive.\n start\n Sets the starting contour level value. Must be\n less than `contours.end`\n type\n If `levels`, the data is represented as a\n contour plot with multiple levels displayed. If\n `constraint`, the data is represented as\n constraints with the invalid region shaded as\n specified by the `operation` and `value`\n parameters.\n value\n Sets the value or values of the constraint\n boundary. When `operation` is set to one of the\n comparison values (=,<,>=,>,<=) "value" is\n expected to be a number. When `operation` is\n set to one of the interval values\n ([],(),[),(],][,)(,](,)[) "value" is expected\n to be an array of two numbers where the first\n is the lower bound and the second is the upper\n bound.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Contours\n '
return self['contours']
| -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 coloring method showing the
contour values. If "fill", coloring is done
evenly between each contour level If "heatmap",
a heatmap gradient coloring is applied between
each contour level. If "lines", coloring is
done on the contour lines. If "none", no
coloring is applied on this trace.
end
Sets the end contour level value. Must be more
than `contours.start`
labelfont
Sets the font used for labeling the contour
levels. The default color comes from the lines,
if shown. The default family and size come from
`layout.font`.
labelformat
Sets the contour label formatting rule using d3
formatting mini-languages which are very
similar to those in Python. For numbers, see: h
ttps://github.com/d3/d3-format/tree/v1.4.5#d3-f
ormat.
operation
Sets the constraint operation. "=" keeps
regions equal to `value` "<" and "<=" keep
regions less than `value` ">" and ">=" keep
regions greater than `value` "[]", "()", "[)",
and "(]" keep regions inside `value[0]` to
`value[1]` "][", ")(", "](", ")[" keep regions
outside `value[0]` to value[1]` Open vs. closed
intervals make no difference to constraint
display, but all versions are allowed for
consistency with filter transforms.
showlabels
Determines whether to label the contour lines
with their values.
showlines
Determines whether or not the contour lines are
drawn. Has an effect only if
`contours.coloring` is set to "fill".
size
Sets the step between each contour level. Must
be positive.
start
Sets the starting contour level value. Must be
less than `contours.end`
type
If `levels`, the data is represented as a
contour plot with multiple levels displayed. If
`constraint`, the data is represented as
constraints with the invalid region shaded as
specified by the `operation` and `value`
parameters.
value
Sets the value or values of the constraint
boundary. When `operation` is set to one of the
comparison values (=,<,>=,>,<=) "value" is
expected to be a number. When `operation` is
set to one of the interval values
([],(),[),(],][,)(,](,)[) "value" is expected
to be an array of two numbers where the first
is the lower bound and the second is the upper
bound.
Returns
-------
plotly.graph_objs.histogram2dcontour.Contours
|
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 constructor\n\n Supported dict properties:\n\n coloring\n Determines the coloring method showing the\n contour values. If "fill", coloring is done\n evenly between each contour level If "heatmap",\n a heatmap gradient coloring is applied between\n each contour level. If "lines", coloring is\n done on the contour lines. If "none", no\n coloring is applied on this trace.\n end\n Sets the end contour level value. Must be more\n than `contours.start`\n labelfont\n Sets the font used for labeling the contour\n levels. The default color comes from the lines,\n if shown. The default family and size come from\n `layout.font`.\n labelformat\n Sets the contour label formatting rule using d3\n formatting mini-languages which are very\n similar to those in Python. For numbers, see: h\n ttps://github.com/d3/d3-format/tree/v1.4.5#d3-f\n ormat.\n operation\n Sets the constraint operation. "=" keeps\n regions equal to `value` "<" and "<=" keep\n regions less than `value` ">" and ">=" keep\n regions greater than `value` "[]", "()", "[)",\n and "(]" keep regions inside `value[0]` to\n `value[1]` "][", ")(", "](", ")[" keep regions\n outside `value[0]` to value[1]` Open vs. closed\n intervals make no difference to constraint\n display, but all versions are allowed for\n consistency with filter transforms.\n showlabels\n Determines whether to label the contour lines\n with their values.\n showlines\n Determines whether or not the contour lines are\n drawn. Has an effect only if\n `contours.coloring` is set to "fill".\n size\n Sets the step between each contour level. Must\n be positive.\n start\n Sets the starting contour level value. Must be\n less than `contours.end`\n type\n If `levels`, the data is represented as a\n contour plot with multiple levels displayed. If\n `constraint`, the data is represented as\n constraints with the invalid region shaded as\n specified by the `operation` and `value`\n parameters.\n value\n Sets the value or values of the constraint\n boundary. When `operation` is set to one of the\n comparison values (=,<,>=,>,<=) "value" is\n expected to be a number. When `operation` is\n set to one of the interval values\n ([],(),[),(],][,)(,](,)[) "value" is expected\n to be an array of two numbers where the first\n is the lower bound and the second is the upper\n bound.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Contours\n '
return self['contours']
|
@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 may be specified as a tuple,\n list, numpy array, or pandas Series\n\n Returns\n -------\n numpy.ndarray\n '
return self['customdata']
| 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.ndarray
|
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 may be specified as a tuple,\n list, numpy array, or pandas Series\n\n Returns\n -------\n numpy.ndarray\n '
return self['customdata']
|
@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['customdatasrc']
| 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['customdatasrc']
|
@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\n average, the minimum or the maximum of the values lying inside\n each bin respectively.\n\n The \'histfunc\' property is an enumeration that may be specified as:\n - One of the following enumeration values:\n [\'count\', \'sum\', \'avg\', \'min\', \'max\']\n\n Returns\n -------\n Any\n '
return self['histfunc']
| -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 respectively.
The 'histfunc' property is an enumeration that may be specified as:
- One of the following enumeration values:
['count', 'sum', 'avg', 'min', 'max']
Returns
-------
Any
|
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\n average, the minimum or the maximum of the values lying inside\n each bin respectively.\n\n The \'histfunc\' property is an enumeration that may be specified as:\n - One of the following enumeration values:\n [\'count\', \'sum\', \'avg\', \'min\', \'max\']\n\n Returns\n -------\n Any\n '
return self['histfunc']
|
@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 corresponds to the percentage / fraction of occurrences with\n respect to the total number of sample points (here, the sum of\n all bin HEIGHTS equals 100% / 1). If "density", the span of\n each bar corresponds to the number of occurrences in a bin\n divided by the size of the bin interval (here, the sum of all\n bin AREAS equals the total number of sample points). If\n *probability density*, the area of each bar corresponds to the\n probability that an event will fall into the corresponding bin\n (here, the sum of all bin AREAS equals 1).\n\n The \'histnorm\' property is an enumeration that may be specified as:\n - One of the following enumeration values:\n [\'\', \'percent\', \'probability\', \'density\', \'probability\n density\']\n\n Returns\n -------\n Any\n '
return self['histnorm']
| 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 total number of sample points (here, the sum of
all bin HEIGHTS equals 100% / 1). If "density", the span of
each bar corresponds to the number of occurrences in a bin
divided by the size of the bin interval (here, the sum of all
bin AREAS equals the total number of sample points). If
*probability density*, the area of each bar corresponds to the
probability that an event will fall into the corresponding bin
(here, the sum of all bin AREAS equals 1).
The 'histnorm' property is an enumeration that may be specified as:
- One of the following enumeration values:
['', 'percent', 'probability', 'density', 'probability
density']
Returns
-------
Any
|
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 corresponds to the percentage / fraction of occurrences with\n respect to the total number of sample points (here, the sum of\n all bin HEIGHTS equals 100% / 1). If "density", the span of\n each bar corresponds to the number of occurrences in a bin\n divided by the size of the bin interval (here, the sum of all\n bin AREAS equals the total number of sample points). If\n *probability density*, the area of each bar corresponds to the\n probability that an event will fall into the corresponding bin\n (here, the sum of all bin AREAS equals 1).\n\n The \'histnorm\' property is an enumeration that may be specified as:\n - One of the following enumeration values:\n [\'\', \'percent\', \'probability\', \'density\', \'probability\n density\']\n\n Returns\n -------\n Any\n '
return self['histnorm']
|
@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 specified\n as a string containing:\n - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters\n (e.g. 'x+y')\n OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip')\n - A list or array of the above\n\n Returns\n -------\n Any|numpy.ndarray\n "
return self['hoverinfo']
| 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', 'name'] joined with '+' characters
(e.g. 'x+y')
OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip')
- A list or array of the above
Returns
-------
Any|numpy.ndarray
|
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 specified\n as a string containing:\n - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters\n (e.g. 'x+y')\n OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip')\n - A list or array of the above\n\n Returns\n -------\n Any|numpy.ndarray\n "
return self['hoverinfo']
|
@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['hoverinfosrc']
| -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['hoverinfosrc']
|
@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 constructor\n\n Supported dict properties:\n\n align\n Sets the horizontal alignment of the text\n content within hover label box. Has an effect\n only if the hover label text spans more two or\n more lines\n alignsrc\n Sets the source reference on Chart Studio Cloud\n for `align`.\n bgcolor\n Sets the background color of the hover labels\n for this trace\n bgcolorsrc\n Sets the source reference on Chart Studio Cloud\n for `bgcolor`.\n bordercolor\n Sets the border color of the hover labels for\n this trace.\n bordercolorsrc\n Sets the source reference on Chart Studio Cloud\n for `bordercolor`.\n font\n Sets the font used in hover labels.\n namelength\n Sets the default length (in number of\n characters) of the trace name in the hover\n labels for all traces. -1 shows the whole name\n regardless of length. 0-3 shows the first 0-3\n characters, and an integer >3 will show the\n whole name if it is less than that many\n characters, but if it is longer, will truncate\n to `namelength - 3` characters and add an\n ellipsis.\n namelengthsrc\n Sets the source reference on Chart Studio Cloud\n for `namelength`.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Hoverlabel\n "
return self['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 horizontal alignment of the text
content within hover label box. Has an effect
only if the hover label text spans more two or
more lines
alignsrc
Sets the source reference on Chart Studio Cloud
for `align`.
bgcolor
Sets the background color of the hover labels
for this trace
bgcolorsrc
Sets the source reference on Chart Studio Cloud
for `bgcolor`.
bordercolor
Sets the border color of the hover labels for
this trace.
bordercolorsrc
Sets the source reference on Chart Studio Cloud
for `bordercolor`.
font
Sets the font used in hover labels.
namelength
Sets the default length (in number of
characters) of the trace name in the hover
labels for all traces. -1 shows the whole name
regardless of length. 0-3 shows the first 0-3
characters, and an integer >3 will show the
whole name if it is less than that many
characters, but if it is longer, will truncate
to `namelength - 3` characters and add an
ellipsis.
namelengthsrc
Sets the source reference on Chart Studio Cloud
for `namelength`.
Returns
-------
plotly.graph_objs.histogram2dcontour.Hoverlabel
|
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 constructor\n\n Supported dict properties:\n\n align\n Sets the horizontal alignment of the text\n content within hover label box. Has an effect\n only if the hover label text spans more two or\n more lines\n alignsrc\n Sets the source reference on Chart Studio Cloud\n for `align`.\n bgcolor\n Sets the background color of the hover labels\n for this trace\n bgcolorsrc\n Sets the source reference on Chart Studio Cloud\n for `bgcolor`.\n bordercolor\n Sets the border color of the hover labels for\n this trace.\n bordercolorsrc\n Sets the source reference on Chart Studio Cloud\n for `bordercolor`.\n font\n Sets the font used in hover labels.\n namelength\n Sets the default length (in number of\n characters) of the trace name in the hover\n labels for all traces. -1 shows the whole name\n regardless of length. 0-3 shows the first 0-3\n characters, and an integer >3 will show the\n whole name if it is less than that many\n characters, but if it is longer, will truncate\n to `namelength - 3` characters and add an\n ellipsis.\n namelengthsrc\n Sets the source reference on Chart Studio Cloud\n for `namelength`.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Hoverlabel\n "
return self['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_}. When\n showing info for several points, "xother" will be added to\n those with different x positions from the first point. An\n underscore before or after "(x|y)other" will add a space on\n that side, only when this field is shown. Numbers are formatted\n using d3-format\'s syntax %{variable:d3-format}, for example\n "Price: %{y:$.2f}".\n https://github.com/d3/d3-format/tree/v1.4.5#d3-format for\n details on the formatting syntax. Dates are formatted using\n d3-time-format\'s syntax %{variable|d3-time-format}, for example\n "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time-\n format/tree/v2.2.3#locale_format for details on the date\n formatting syntax. The variables available in `hovertemplate`\n are the ones emitted as event data described at this link\n https://plotly.com/javascript/plotlyjs-events/#event-data.\n Additionally, every attributes that can be specified per-point\n (the ones that are `arrayOk: true`) are available. variable `z`\n Anything contained in tag `<extra>` is displayed in the\n secondary box, for example "<extra>{fullData.name}</extra>". To\n hide the secondary box completely, use an empty tag\n `<extra></extra>`.\n\n The \'hovertemplate\' property is a string and must be specified as:\n - A string\n - A number that will be converted to a string\n - A tuple, list, or one-dimensional numpy array of the above\n\n Returns\n -------\n str|numpy.ndarray\n '
return self['hovertemplate']
| -4,780,456,981,960,301,000
|
Template string used for rendering the information that appear
on hover box. Note that this will override `hoverinfo`.
Variables are inserted using %{variable}, for example "y: %{y}"
as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When
showing info for several points, "xother" will be added to
those with different x positions from the first point. An
underscore before or after "(x|y)other" will add a space on
that side, only when this field is shown. Numbers are formatted
using d3-format's syntax %{variable:d3-format}, for example
"Price: %{y:$.2f}".
https://github.com/d3/d3-format/tree/v1.4.5#d3-format for
details on the formatting syntax. Dates are formatted using
d3-time-format's syntax %{variable|d3-time-format}, for example
"Day: %{2019-01-01|%A}". https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format for details on the date
formatting syntax. The variables available in `hovertemplate`
are the ones emitted as event data described at this link
https://plotly.com/javascript/plotlyjs-events/#event-data.
Additionally, every attributes that can be specified per-point
(the ones that are `arrayOk: true`) are available. variable `z`
Anything contained in tag `<extra>` is displayed in the
secondary box, for example "<extra>{fullData.name}</extra>". To
hide the secondary box completely, use an empty tag
`<extra></extra>`.
The 'hovertemplate' property is a string and must be specified as:
- A string
- A number that will be converted to a string
- A tuple, list, or one-dimensional numpy array of the above
Returns
-------
str|numpy.ndarray
|
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_}. When\n showing info for several points, "xother" will be added to\n those with different x positions from the first point. An\n underscore before or after "(x|y)other" will add a space on\n that side, only when this field is shown. Numbers are formatted\n using d3-format\'s syntax %{variable:d3-format}, for example\n "Price: %{y:$.2f}".\n https://github.com/d3/d3-format/tree/v1.4.5#d3-format for\n details on the formatting syntax. Dates are formatted using\n d3-time-format\'s syntax %{variable|d3-time-format}, for example\n "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time-\n format/tree/v2.2.3#locale_format for details on the date\n formatting syntax. The variables available in `hovertemplate`\n are the ones emitted as event data described at this link\n https://plotly.com/javascript/plotlyjs-events/#event-data.\n Additionally, every attributes that can be specified per-point\n (the ones that are `arrayOk: true`) are available. variable `z`\n Anything contained in tag `<extra>` is displayed in the\n secondary box, for example "<extra>{fullData.name}</extra>". To\n hide the secondary box completely, use an empty tag\n `<extra></extra>`.\n\n The \'hovertemplate\' property is a string and must be specified as:\n - A string\n - A number that will be converted to a string\n - A tuple, list, or one-dimensional numpy array of the above\n\n Returns\n -------\n str|numpy.ndarray\n '
return self['hovertemplate']
|
@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 "
return self['hovertemplatesrc']
| -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 "
return self['hovertemplatesrc']
|
@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, or pandas Series\n\n Returns\n -------\n numpy.ndarray\n "
return self['ids']
| 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, or pandas Series\n\n Returns\n -------\n numpy.ndarray\n "
return self['ids']
|
@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 will be converted to a string\n\n Returns\n -------\n str\n "
return self['legendgroup']
| -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 will be converted to a string\n\n Returns\n -------\n str\n "
return self['legendgroup']
|
@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 to the Legendgrouptitle constructor\n\n Supported dict properties:\n\n font\n Sets this legend group's title font.\n text\n Sets the title of the legend group.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Legendgrouptitle\n "
return self['legendgrouptitle']
| -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
Sets this legend group's title font.
text
Sets the title of the legend group.
Returns
-------
plotly.graph_objs.histogram2dcontour.Legendgrouptitle
|
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 to the Legendgrouptitle constructor\n\n Supported dict properties:\n\n font\n Sets this legend group's title font.\n text\n Sets the title of the legend group.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Legendgrouptitle\n "
return self['legendgrouptitle']
|
@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 than 1000 to place certain items before all unranked items, and\n ranks greater than 1000 to go after all unranked items.\n\n The 'legendrank' property is a number and may be specified as:\n - An int or float\n\n Returns\n -------\n int|float\n "
return self['legendrank']
| -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 than 1000 to go after all unranked items.
The 'legendrank' property is a number and may be specified as:
- An int or float
Returns
-------
int|float
|
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 than 1000 to place certain items before all unranked items, and\n ranks greater than 1000 to go after all unranked items.\n\n The 'legendrank' property is a number and may be specified as:\n - An int or float\n\n Returns\n -------\n int|float\n "
return self['legendrank']
|
@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 Supported dict properties:\n\n color\n Sets the color of the contour level. Has no\n effect if `contours.coloring` is set to\n "lines".\n dash\n Sets the dash style of lines. Set to a dash\n type string ("solid", "dot", "dash",\n "longdash", "dashdot", or "longdashdot") or a\n dash length list in px (eg "5px,10px,2px,2px").\n smoothing\n Sets the amount of smoothing for the contour\n lines, where 0 corresponds to no smoothing.\n width\n Sets the contour line width in (in px)\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Line\n '
return self['line']
| 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. Has no
effect if `contours.coloring` is set to
"lines".
dash
Sets the dash style of lines. Set to a dash
type string ("solid", "dot", "dash",
"longdash", "dashdot", or "longdashdot") or a
dash length list in px (eg "5px,10px,2px,2px").
smoothing
Sets the amount of smoothing for the contour
lines, where 0 corresponds to no smoothing.
width
Sets the contour line width in (in px)
Returns
-------
plotly.graph_objs.histogram2dcontour.Line
|
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 Supported dict properties:\n\n color\n Sets the color of the contour level. Has no\n effect if `contours.coloring` is set to\n "lines".\n dash\n Sets the dash style of lines. Set to a dash\n type string ("solid", "dot", "dash",\n "longdash", "dashdot", or "longdashdot") or a\n dash length list in px (eg "5px,10px,2px,2px").\n smoothing\n Sets the amount of smoothing for the contour\n lines, where 0 corresponds to no smoothing.\n width\n Sets the contour line width in (in px)\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Line\n '
return self['line']
|
@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 Supported dict properties:\n\n color\n Sets the aggregation data.\n colorsrc\n Sets the source reference on Chart Studio Cloud\n for `color`.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Marker\n "
return self['marker']
| 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.
colorsrc
Sets the source reference on Chart Studio Cloud
for `color`.
Returns
-------
plotly.graph_objs.histogram2dcontour.Marker
|
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 Supported dict properties:\n\n color\n Sets the aggregation data.\n colorsrc\n Sets the source reference on Chart Studio Cloud\n for `color`.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Marker\n "
return self['marker']
|
@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 text all support `meta`. To access the trace `meta` values in\n an attribute in the same trace, simply use `%{meta[i]}` where\n `i` is the index or key of the `meta` item in question. To\n access trace `meta` in layout attributes, use\n `%{data[n[.meta[i]}` where `i` is the index or key of the\n `meta` and `n` is the trace index.\n\n The 'meta' property accepts values of any type\n\n Returns\n -------\n Any|numpy.ndarray\n "
return self['meta']
| -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 attribute in the same trace, simply use `%{meta[i]}` where
`i` is the index or key of the `meta` item in question. To
access trace `meta` in layout attributes, use
`%{data[n[.meta[i]}` where `i` is the index or key of the
`meta` and `n` is the trace index.
The 'meta' property accepts values of any type
Returns
-------
Any|numpy.ndarray
|
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 text all support `meta`. To access the trace `meta` values in\n an attribute in the same trace, simply use `%{meta[i]}` where\n `i` is the index or key of the `meta` item in question. To\n access trace `meta` in layout attributes, use\n `%{data[n[.meta[i]}` where `i` is the index or key of the\n `meta` and `n` is the trace index.\n\n The 'meta' property accepts values of any type\n\n Returns\n -------\n Any|numpy.ndarray\n "
return self['meta']
|
@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 str\n "
return self['name']
| -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 str\n "
return self['name']
|
@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 'nbinsx' property is a integer and may be specified as:\n - An int (or float that will be cast to an int)\n in the interval [0, 9223372036854775807]\n\n Returns\n -------\n int\n "
return self['nbinsx']
| -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 will be cast to an int)
in the interval [0, 9223372036854775807]
Returns
-------
int
|
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 'nbinsx' property is a integer and may be specified as:\n - An int (or float that will be cast to an int)\n in the interval [0, 9223372036854775807]\n\n Returns\n -------\n int\n "
return self['nbinsx']
|
@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 'nbinsy' property is a integer and may be specified as:\n - An int (or float that will be cast to an int)\n in the interval [0, 9223372036854775807]\n\n Returns\n -------\n int\n "
return self['nbinsy']
| -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 will be cast to an int)
in the interval [0, 9223372036854775807]
Returns
-------
int
|
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 'nbinsy' property is a integer and may be specified as:\n - An int (or float that will be cast to an int)\n in the interval [0, 9223372036854775807]\n\n Returns\n -------\n int\n "
return self['nbinsy']
|
@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 The 'ncontours' property is a integer and may be specified as:\n - An int (or float that will be cast to an int)\n in the interval [1, 9223372036854775807]\n\n Returns\n -------\n int\n "
return self['ncontours']
| -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 that will be cast to an int)
in the interval [1, 9223372036854775807]
Returns
-------
int
|
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 The 'ncontours' property is a integer and may be specified as:\n - An int (or float that will be cast to an int)\n in the interval [1, 9223372036854775807]\n\n Returns\n -------\n int\n "
return self['ncontours']
|
@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 Returns\n -------\n bool\n "
return self['reversescale']
| 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 Returns\n -------\n bool\n "
return self['reversescale']
|
@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['showlegend']
| 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['showlegend']
|
@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 Supported dict properties:\n\n maxpoints\n Sets the maximum number of points to keep on\n the plots from an incoming stream. If\n `maxpoints` is set to 50, only the newest 50\n points will be displayed on the plot.\n token\n The stream id number links a data trace on a\n plot with a stream. See https://chart-\n studio.plotly.com/settings for more details.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Stream\n "
return self['stream']
| 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 of points to keep on
the plots from an incoming stream. If
`maxpoints` is set to 50, only the newest 50
points will be displayed on the plot.
token
The stream id number links a data trace on a
plot with a stream. See https://chart-
studio.plotly.com/settings for more details.
Returns
-------
plotly.graph_objs.histogram2dcontour.Stream
|
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 Supported dict properties:\n\n maxpoints\n Sets the maximum number of points to keep on\n the plots from an incoming stream. If\n `maxpoints` is set to 50, only the newest 50\n points will be displayed on the plot.\n token\n The stream id number links a data trace on a\n plot with a stream. See https://chart-\n studio.plotly.com/settings for more details.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Stream\n "
return self['stream']
|
@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.Textfont`\n - A dict of string/value properties that will be passed\n to the Textfont constructor\n\n Supported dict properties:\n\n color\n\n family\n HTML font family - the typeface that will be\n applied by the web browser. The web browser\n will only be able to apply a font if it is\n available on the system which it operates.\n Provide multiple font families, separated by\n commas, to indicate the preference in which to\n apply fonts if they aren\'t available on the\n system. The Chart Studio Cloud (at\n https://chart-studio.plotly.com or on-premise)\n generates images on a server, where only a\n select number of fonts are installed and\n supported. These include "Arial", "Balto",\n "Courier New", "Droid Sans",, "Droid Serif",\n "Droid Sans Mono", "Gravitas One", "Old\n Standard TT", "Open Sans", "Overpass", "PT Sans\n Narrow", "Raleway", "Times New Roman".\n size\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Textfont\n '
return self['textfont']
| 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 Textfont constructor
Supported dict properties:
color
family
HTML font family - the typeface that will be
applied by the web browser. The web browser
will only be able to apply a font if it is
available on the system which it operates.
Provide multiple font families, separated by
commas, to indicate the preference in which to
apply fonts if they aren't available on the
system. The Chart Studio Cloud (at
https://chart-studio.plotly.com or on-premise)
generates images on a server, where only a
select number of fonts are installed and
supported. These include "Arial", "Balto",
"Courier New", "Droid Sans",, "Droid Serif",
"Droid Sans Mono", "Gravitas One", "Old
Standard TT", "Open Sans", "Overpass", "PT Sans
Narrow", "Raleway", "Times New Roman".
size
Returns
-------
plotly.graph_objs.histogram2dcontour.Textfont
|
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.Textfont`\n - A dict of string/value properties that will be passed\n to the Textfont constructor\n\n Supported dict properties:\n\n color\n\n family\n HTML font family - the typeface that will be\n applied by the web browser. The web browser\n will only be able to apply a font if it is\n available on the system which it operates.\n Provide multiple font families, separated by\n commas, to indicate the preference in which to\n apply fonts if they aren\'t available on the\n system. The Chart Studio Cloud (at\n https://chart-studio.plotly.com or on-premise)\n generates images on a server, where only a\n select number of fonts are installed and\n supported. These include "Arial", "Balto",\n "Courier New", "Droid Sans",, "Droid Serif",\n "Droid Sans Mono", "Gravitas One", "Old\n Standard TT", "Open Sans", "Overpass", "PT Sans\n Narrow", "Raleway", "Times New Roman".\n size\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.Textfont\n '
return self['textfont']
|
@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 example "y: %{y}". Numbers are formatted using d3-format\'s\n syntax %{variable:d3-format}, for example "Price: %{y:$.2f}".\n https://github.com/d3/d3-format/tree/v1.4.5#d3-format for\n details on the formatting syntax. Dates are formatted using\n d3-time-format\'s syntax %{variable|d3-time-format}, for example\n "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time-\n format/tree/v2.2.3#locale_format for details on the date\n formatting syntax. Every attributes that can be specified per-\n point (the ones that are `arrayOk: true`) are available.\n variables `x`, `y`, `z` and `text`.\n\n The \'texttemplate\' 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 str\n '
return self['texttemplate']
| -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-format}, for example "Price: %{y:$.2f}".
https://github.com/d3/d3-format/tree/v1.4.5#d3-format for
details on the formatting syntax. Dates are formatted using
d3-time-format's syntax %{variable|d3-time-format}, for example
"Day: %{2019-01-01|%A}". https://github.com/d3/d3-time-
format/tree/v2.2.3#locale_format for details on the date
formatting syntax. Every attributes that can be specified per-
point (the ones that are `arrayOk: true`) are available.
variables `x`, `y`, `z` and `text`.
The 'texttemplate' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str
|
packages/python/plotly/plotly/graph_objs/_histogram2dcontour.py
|
texttemplate
|
labaran1/plotly.py
|
python
|
@property
def texttemplate(self):
'\n For this trace it only has an effect if `coloring` is set to\n "heatmap". Template string used for rendering the information\n text that appear on points. Note that this will override\n `textinfo`. Variables are inserted using %{variable}, for\n example "y: %{y}". Numbers are formatted using d3-format\'s\n syntax %{variable:d3-format}, for example "Price: %{y:$.2f}".\n https://github.com/d3/d3-format/tree/v1.4.5#d3-format for\n details on the formatting syntax. Dates are formatted using\n d3-time-format\'s syntax %{variable|d3-time-format}, for example\n "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time-\n format/tree/v2.2.3#locale_format for details on the date\n formatting syntax. Every attributes that can be specified per-\n point (the ones that are `arrayOk: true`) are available.\n variables `x`, `y`, `z` and `text`.\n\n The \'texttemplate\' 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 str\n '
return self['texttemplate']
|
@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 Returns\n -------\n str\n "
return self['uid']
| -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 Returns\n -------\n str\n "
return self['uid']
|
@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 user-driven trace attribute changes are controlled by\n `layout` attributes: `trace.visible` is controlled by\n `layout.legend.uirevision`, `selectedpoints` is controlled by\n `layout.selectionrevision`, and `colorbar.(x|y)` (accessible\n with `config: {editable: true}`) is controlled by\n `layout.editrevision`. Trace changes are tracked by `uid`,\n which only falls back on trace index if no `uid` is provided.\n So if your app can add/remove traces before the end of the\n `data` array, such that the same trace has a different index,\n you can still preserve user-driven changes if you give each\n trace a `uid` that stays with it as it moves.\n\n The 'uirevision' property accepts values of any type\n\n Returns\n -------\n Any\n "
return self['uirevision']
| 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.visible` is controlled by
`layout.legend.uirevision`, `selectedpoints` is controlled by
`layout.selectionrevision`, and `colorbar.(x|y)` (accessible
with `config: {editable: true}`) is controlled by
`layout.editrevision`. Trace changes are tracked by `uid`,
which only falls back on trace index if no `uid` is provided.
So if your app can add/remove traces before the end of the
`data` array, such that the same trace has a different index,
you can still preserve user-driven changes if you give each
trace a `uid` that stays with it as it moves.
The 'uirevision' property accepts values of any type
Returns
-------
Any
|
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 user-driven trace attribute changes are controlled by\n `layout` attributes: `trace.visible` is controlled by\n `layout.legend.uirevision`, `selectedpoints` is controlled by\n `layout.selectionrevision`, and `colorbar.(x|y)` (accessible\n with `config: {editable: true}`) is controlled by\n `layout.editrevision`. Trace changes are tracked by `uid`,\n which only falls back on trace index if no `uid` is provided.\n So if your app can add/remove traces before the end of the\n `data` array, such that the same trace has a different index,\n you can still preserve user-driven changes if you give each\n trace a `uid` that stays with it as it moves.\n\n The 'uirevision' property accepts values of any type\n\n Returns\n -------\n Any\n "
return self['uirevision']
|
@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 - One of the following enumeration values:\n [True, False, \'legendonly\']\n\n Returns\n -------\n Any\n '
return self['visible']
| 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']
Returns
-------
Any
|
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 - One of the following enumeration values:\n [True, False, \'legendonly\']\n\n Returns\n -------\n Any\n '
return self['visible']
|
@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 an identifier of a particular\n subplot, of type \'x\', that may be specified as the string \'x\'\n optionally followed by an integer >= 1\n (e.g. \'x\', \'x1\', \'x2\', \'x3\', etc.)\n\n Returns\n -------\n str\n '
return self['xaxis']
| -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 string 'x'
optionally followed by an integer >= 1
(e.g. 'x', 'x1', 'x2', 'x3', etc.)
Returns
-------
str
|
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 an identifier of a particular\n subplot, of type \'x\', that may be specified as the string \'x\'\n optionally followed by an integer >= 1\n (e.g. \'x\', \'x1\', \'x2\', \'x3\', etc.)\n\n Returns\n -------\n str\n '
return self['xaxis']
|
@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 value can be used to set (1D) histogram `bingroup`\n\n The 'xbingroup' 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 str\n "
return self['xbingroup']
| 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 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
|
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 value can be used to set (1D) histogram `bingroup`\n\n The 'xbingroup' 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 str\n "
return self['xbingroup']
|
@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 Supported dict properties:\n\n end\n Sets the end value for the x axis bins. The\n last bin may not end exactly at this value, we\n increment the bin edge by `size` from `start`\n until we reach or exceed `end`. Defaults to the\n maximum data value. Like `start`, for dates use\n a date string, and for category data `end` is\n based on the category serial numbers.\n size\n Sets the size of each x axis bin. Default\n behavior: If `nbinsx` is 0 or omitted, we\n choose a nice round bin size such that the\n number of bins is about the same as the typical\n number of samples in each bin. If `nbinsx` is\n provided, we choose a nice round bin size\n giving no more than that many bins. For date\n data, use milliseconds or "M<n>" for months, as\n in `axis.dtick`. For category data, the number\n of categories to bin together (always defaults\n to 1).\n start\n Sets the starting value for the x axis bins.\n Defaults to the minimum data value, shifted\n down if necessary to make nice round values and\n to remove ambiguous bin edges. For example, if\n most of the data is integers we shift the bin\n edges 0.5 down, so a `size` of 5 would have a\n default `start` of -0.5, so it is clear that\n 0-4 are in the first bin, 5-9 in the second,\n but continuous data gets a start of 0 and bins\n [0,5), [5,10) etc. Dates behave similarly, and\n `start` should be a date string. For category\n data, `start` is based on the category serial\n numbers, and defaults to -0.5.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.XBins\n '
return self['xbins']
| -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 bins. The
last bin may not end exactly at this value, we
increment the bin edge by `size` from `start`
until we reach or exceed `end`. Defaults to the
maximum data value. Like `start`, for dates use
a date string, and for category data `end` is
based on the category serial numbers.
size
Sets the size of each x axis bin. Default
behavior: If `nbinsx` is 0 or omitted, we
choose a nice round bin size such that the
number of bins is about the same as the typical
number of samples in each bin. If `nbinsx` is
provided, we choose a nice round bin size
giving no more than that many bins. For date
data, use milliseconds or "M<n>" for months, as
in `axis.dtick`. For category data, the number
of categories to bin together (always defaults
to 1).
start
Sets the starting value for the x axis bins.
Defaults to the minimum data value, shifted
down if necessary to make nice round values and
to remove ambiguous bin edges. For example, if
most of the data is integers we shift the bin
edges 0.5 down, so a `size` of 5 would have a
default `start` of -0.5, so it is clear that
0-4 are in the first bin, 5-9 in the second,
but continuous data gets a start of 0 and bins
[0,5), [5,10) etc. Dates behave similarly, and
`start` should be a date string. For category
data, `start` is based on the category serial
numbers, and defaults to -0.5.
Returns
-------
plotly.graph_objs.histogram2dcontour.XBins
|
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 Supported dict properties:\n\n end\n Sets the end value for the x axis bins. The\n last bin may not end exactly at this value, we\n increment the bin edge by `size` from `start`\n until we reach or exceed `end`. Defaults to the\n maximum data value. Like `start`, for dates use\n a date string, and for category data `end` is\n based on the category serial numbers.\n size\n Sets the size of each x axis bin. Default\n behavior: If `nbinsx` is 0 or omitted, we\n choose a nice round bin size such that the\n number of bins is about the same as the typical\n number of samples in each bin. If `nbinsx` is\n provided, we choose a nice round bin size\n giving no more than that many bins. For date\n data, use milliseconds or "M<n>" for months, as\n in `axis.dtick`. For category data, the number\n of categories to bin together (always defaults\n to 1).\n start\n Sets the starting value for the x axis bins.\n Defaults to the minimum data value, shifted\n down if necessary to make nice round values and\n to remove ambiguous bin edges. For example, if\n most of the data is integers we shift the bin\n edges 0.5 down, so a `size` of 5 would have a\n default `start` of -0.5, so it is clear that\n 0-4 are in the first bin, 5-9 in the second,\n but continuous data gets a start of 0 and bins\n [0,5), [5,10) etc. Dates behave similarly, and\n `start` should be a date string. For category\n data, `start` is based on the category serial\n numbers, and defaults to -0.5.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.XBins\n '
return self['xbins']
|
@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 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian',\n 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan',\n 'thai', 'ummalqura']\n\n Returns\n -------\n Any\n "
return self['xcalendar']
| -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', 'nepali', 'persian', 'taiwan',
'thai', 'ummalqura']
Returns
-------
Any
|
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 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian',\n 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan',\n 'thai', 'ummalqura']\n\n Returns\n -------\n Any\n "
return self['xcalendar']
|
@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/d3-time-\n format/tree/v2.2.3#locale_format. We add two items to d3\'s date\n formatter: "%h" for half of the year as a decimal number as\n well as "%{n}f" for fractional seconds with n digits. For\n example, *2016-10-13 09:15:23.456* with tickformat\n "%H~%M~%S.%2f" would display *09~15~23.46*By default the values\n are formatted using `xaxis.hoverformat`.\n\n The \'xhoverformat\' 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 str\n '
return self['xhoverformat']
| -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: "%h" for half of the year as a decimal number as
well as "%{n}f" for fractional seconds with n digits. For
example, *2016-10-13 09:15:23.456* with tickformat
"%H~%M~%S.%2f" would display *09~15~23.46*By default the values
are formatted using `xaxis.hoverformat`.
The 'xhoverformat' 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
|
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/d3-time-\n format/tree/v2.2.3#locale_format. We add two items to d3\'s date\n formatter: "%h" for half of the year as a decimal number as\n well as "%{n}f" for fractional seconds with n digits. For\n example, *2016-10-13 09:15:23.456* with tickformat\n "%H~%M~%S.%2f" would display *09~15~23.46*By default the values\n are formatted using `xaxis.hoverformat`.\n\n The \'xhoverformat\' 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 str\n '
return self['xhoverformat']
|
@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 an identifier of a particular\n subplot, of type \'y\', that may be specified as the string \'y\'\n optionally followed by an integer >= 1\n (e.g. \'y\', \'y1\', \'y2\', \'y3\', etc.)\n\n Returns\n -------\n str\n '
return self['yaxis']
| 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 string 'y'
optionally followed by an integer >= 1
(e.g. 'y', 'y1', 'y2', 'y3', etc.)
Returns
-------
str
|
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 an identifier of a particular\n subplot, of type \'y\', that may be specified as the string \'y\'\n optionally followed by an integer >= 1\n (e.g. \'y\', \'y1\', \'y2\', \'y3\', etc.)\n\n Returns\n -------\n str\n '
return self['yaxis']
|
@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 value can be used to set (1D) histogram `bingroup`\n\n The 'ybingroup' 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 str\n "
return self['ybingroup']
| -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 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
|
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 value can be used to set (1D) histogram `bingroup`\n\n The 'ybingroup' 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 str\n "
return self['ybingroup']
|
@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 Supported dict properties:\n\n end\n Sets the end value for the y axis bins. The\n last bin may not end exactly at this value, we\n increment the bin edge by `size` from `start`\n until we reach or exceed `end`. Defaults to the\n maximum data value. Like `start`, for dates use\n a date string, and for category data `end` is\n based on the category serial numbers.\n size\n Sets the size of each y axis bin. Default\n behavior: If `nbinsy` is 0 or omitted, we\n choose a nice round bin size such that the\n number of bins is about the same as the typical\n number of samples in each bin. If `nbinsy` is\n provided, we choose a nice round bin size\n giving no more than that many bins. For date\n data, use milliseconds or "M<n>" for months, as\n in `axis.dtick`. For category data, the number\n of categories to bin together (always defaults\n to 1).\n start\n Sets the starting value for the y axis bins.\n Defaults to the minimum data value, shifted\n down if necessary to make nice round values and\n to remove ambiguous bin edges. For example, if\n most of the data is integers we shift the bin\n edges 0.5 down, so a `size` of 5 would have a\n default `start` of -0.5, so it is clear that\n 0-4 are in the first bin, 5-9 in the second,\n but continuous data gets a start of 0 and bins\n [0,5), [5,10) etc. Dates behave similarly, and\n `start` should be a date string. For category\n data, `start` is based on the category serial\n numbers, and defaults to -0.5.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.YBins\n '
return self['ybins']
| -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 bins. The
last bin may not end exactly at this value, we
increment the bin edge by `size` from `start`
until we reach or exceed `end`. Defaults to the
maximum data value. Like `start`, for dates use
a date string, and for category data `end` is
based on the category serial numbers.
size
Sets the size of each y axis bin. Default
behavior: If `nbinsy` is 0 or omitted, we
choose a nice round bin size such that the
number of bins is about the same as the typical
number of samples in each bin. If `nbinsy` is
provided, we choose a nice round bin size
giving no more than that many bins. For date
data, use milliseconds or "M<n>" for months, as
in `axis.dtick`. For category data, the number
of categories to bin together (always defaults
to 1).
start
Sets the starting value for the y axis bins.
Defaults to the minimum data value, shifted
down if necessary to make nice round values and
to remove ambiguous bin edges. For example, if
most of the data is integers we shift the bin
edges 0.5 down, so a `size` of 5 would have a
default `start` of -0.5, so it is clear that
0-4 are in the first bin, 5-9 in the second,
but continuous data gets a start of 0 and bins
[0,5), [5,10) etc. Dates behave similarly, and
`start` should be a date string. For category
data, `start` is based on the category serial
numbers, and defaults to -0.5.
Returns
-------
plotly.graph_objs.histogram2dcontour.YBins
|
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 Supported dict properties:\n\n end\n Sets the end value for the y axis bins. The\n last bin may not end exactly at this value, we\n increment the bin edge by `size` from `start`\n until we reach or exceed `end`. Defaults to the\n maximum data value. Like `start`, for dates use\n a date string, and for category data `end` is\n based on the category serial numbers.\n size\n Sets the size of each y axis bin. Default\n behavior: If `nbinsy` is 0 or omitted, we\n choose a nice round bin size such that the\n number of bins is about the same as the typical\n number of samples in each bin. If `nbinsy` is\n provided, we choose a nice round bin size\n giving no more than that many bins. For date\n data, use milliseconds or "M<n>" for months, as\n in `axis.dtick`. For category data, the number\n of categories to bin together (always defaults\n to 1).\n start\n Sets the starting value for the y axis bins.\n Defaults to the minimum data value, shifted\n down if necessary to make nice round values and\n to remove ambiguous bin edges. For example, if\n most of the data is integers we shift the bin\n edges 0.5 down, so a `size` of 5 would have a\n default `start` of -0.5, so it is clear that\n 0-4 are in the first bin, 5-9 in the second,\n but continuous data gets a start of 0 and bins\n [0,5), [5,10) etc. Dates behave similarly, and\n `start` should be a date string. For category\n data, `start` is based on the category serial\n numbers, and defaults to -0.5.\n\n Returns\n -------\n plotly.graph_objs.histogram2dcontour.YBins\n '
return self['ybins']
|
@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 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian',\n 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan',\n 'thai', 'ummalqura']\n\n Returns\n -------\n Any\n "
return self['ycalendar']
| -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', 'nepali', 'persian', 'taiwan',
'thai', 'ummalqura']
Returns
-------
Any
|
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 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian',\n 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan',\n 'thai', 'ummalqura']\n\n Returns\n -------\n Any\n "
return self['ycalendar']
|
@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/d3-time-\n format/tree/v2.2.3#locale_format. We add two items to d3\'s date\n formatter: "%h" for half of the year as a decimal number as\n well as "%{n}f" for fractional seconds with n digits. For\n example, *2016-10-13 09:15:23.456* with tickformat\n "%H~%M~%S.%2f" would display *09~15~23.46*By default the values\n are formatted using `yaxis.hoverformat`.\n\n The \'yhoverformat\' 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 str\n '
return self['yhoverformat']
| -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: "%h" for half of the year as a decimal number as
well as "%{n}f" for fractional seconds with n digits. For
example, *2016-10-13 09:15:23.456* with tickformat
"%H~%M~%S.%2f" would display *09~15~23.46*By default the values
are formatted using `yaxis.hoverformat`.
The 'yhoverformat' 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
|
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/d3-time-\n format/tree/v2.2.3#locale_format. We add two items to d3\'s date\n formatter: "%h" for half of the year as a decimal number as\n well as "%{n}f" for fractional seconds with n digits. For\n example, *2016-10-13 09:15:23.456* with tickformat\n "%H~%M~%S.%2f" would display *09~15~23.46*By default the values\n are formatted using `yaxis.hoverformat`.\n\n The \'yhoverformat\' 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 str\n '
return self['yhoverformat']
|
@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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