body_hash
stringlengths 64
64
| body
stringlengths 23
109k
| docstring
stringlengths 1
57k
| path
stringlengths 4
198
| name
stringlengths 1
115
| repository_name
stringlengths 7
111
| repository_stars
float64 0
191k
| lang
stringclasses 1
value | body_without_docstring
stringlengths 14
108k
| unified
stringlengths 45
133k
|
|---|---|---|---|---|---|---|---|---|---|
7b3b156b65ea9e2a096ef8fbc33275f8a80977cfa0323b7b098f1525ea56e03e | @property
def title(self):
'Obtain the title of the Relat'
return self.story.title | Obtain the title of the Relat | relaty/relat.py | title | PaPablo/relaty | 0 | python | @property
def title(self):
return self.story.title | @property
def title(self):
return self.story.title<|docstring|>Obtain the title of the Relat<|endoftext|> |
61f008f0e7e284c8897781d197f3610923a240a5470b807e96622b2271d15cb7 | @property
def screens(self):
'Access the initial screens of the Relat'
return self.story.screens | Access the initial screens of the Relat | relaty/relat.py | screens | PaPablo/relaty | 0 | python | @property
def screens(self):
return self.story.screens | @property
def screens(self):
return self.story.screens<|docstring|>Access the initial screens of the Relat<|endoftext|> |
9e3e796b0edd68765413f3b4bda387a238fe4773a9e064e4da969ea32dd2fb0d | @property
def options(self):
'Access the root-level options of the Relat'
return self.story.options | Access the root-level options of the Relat | relaty/relat.py | options | PaPablo/relaty | 0 | python | @property
def options(self):
return self.story.options | @property
def options(self):
return self.story.options<|docstring|>Access the root-level options of the Relat<|endoftext|> |
831909f851d1b315835f0d6b7953774bf7d4aabdd82dc5a290f6558f8638b595 | def add_screen(self, screen: str):
'Adds a screen at the end of the initial screens'
self.story.add_screen(screen) | Adds a screen at the end of the initial screens | relaty/relat.py | add_screen | PaPablo/relaty | 0 | python | def add_screen(self, screen: str):
self.story.add_screen(screen) | def add_screen(self, screen: str):
self.story.add_screen(screen)<|docstring|>Adds a screen at the end of the initial screens<|endoftext|> |
a4b2c7f0a5ae118945db0c1eaa0a4f74a1c88611ccec59ce96a3ac41fdf9e673 | def add_option(self, option: Story):
'Adds and option to the root-level options of the Relat'
self.story.add_option(option) | Adds and option to the root-level options of the Relat | relaty/relat.py | add_option | PaPablo/relaty | 0 | python | def add_option(self, option: Story):
self.story.add_option(option) | def add_option(self, option: Story):
self.story.add_option(option)<|docstring|>Adds and option to the root-level options of the Relat<|endoftext|> |
6c1ad624ff806bdd60f3246a9f02e8daa071a3f7f95dcb2d2cf4dcac1399c64d | def navigate(self, path):
'Returns the story at the path'
return self.story.navigate(path) | Returns the story at the path | relaty/relat.py | navigate | PaPablo/relaty | 0 | python | def navigate(self, path):
return self.story.navigate(path) | def navigate(self, path):
return self.story.navigate(path)<|docstring|>Returns the story at the path<|endoftext|> |
c641290b1e028a60b37075fbc8aa6d09947b7d941ac474b87a701d4d1b71d8c8 | def play(self):
'Play the story in cli mode\n\n When this method is invoked, the story can be played in the terminal.\n It shows every screen and ask for confirmation to continue.\n\n Then displays each options and asks the user to choose one\n\n '
self.story.play() | Play the story in cli mode
When this method is invoked, the story can be played in the terminal.
It shows every screen and ask for confirmation to continue.
Then displays each options and asks the user to choose one | relaty/relat.py | play | PaPablo/relaty | 0 | python | def play(self):
'Play the story in cli mode\n\n When this method is invoked, the story can be played in the terminal.\n It shows every screen and ask for confirmation to continue.\n\n Then displays each options and asks the user to choose one\n\n '
self.story.play() | def play(self):
'Play the story in cli mode\n\n When this method is invoked, the story can be played in the terminal.\n It shows every screen and ask for confirmation to continue.\n\n Then displays each options and asks the user to choose one\n\n '
self.story.play()<|docstring|>Play the story in cli mode
When this method is invoked, the story can be played in the terminal.
It shows every screen and ask for confirmation to continue.
Then displays each options and asks the user to choose one<|endoftext|> |
ece596ba1c7b99b0c62774c28793226bf9151b81a97a15a90852681e2c91fbd4 | @abstractmethod
def resolve_target(self, node_task, target, results_dir, node_paths):
'Resolve a NodePackage target.' | Resolve a NodePackage target. | contrib/node/src/python/pants/contrib/node/subsystems/resolvers/node_resolver_base.py | resolve_target | mosesn/pants | 0 | python | @abstractmethod
def resolve_target(self, node_task, target, results_dir, node_paths):
| @abstractmethod
def resolve_target(self, node_task, target, results_dir, node_paths):
<|docstring|>Resolve a NodePackage target.<|endoftext|> |
94eef45eea416e61e589e1a1dbb7a38d7ca8f4e7bf723a5b87ed435feaca4a73 | def _copy_sources(self, target, results_dir):
'Copy sources from a target to a results directory.\n\n :param NodePackage target: A subclass of NodePackage\n :param string results_dir: The results directory\n '
buildroot = get_buildroot()
source_relative_to = target.address.spec_path
for source in target.sources_relative_to_buildroot():
dest = os.path.join(results_dir, os.path.relpath(source, source_relative_to))
safe_mkdir(os.path.dirname(dest))
shutil.copyfile(os.path.join(buildroot, source), dest) | Copy sources from a target to a results directory.
:param NodePackage target: A subclass of NodePackage
:param string results_dir: The results directory | contrib/node/src/python/pants/contrib/node/subsystems/resolvers/node_resolver_base.py | _copy_sources | mosesn/pants | 0 | python | def _copy_sources(self, target, results_dir):
'Copy sources from a target to a results directory.\n\n :param NodePackage target: A subclass of NodePackage\n :param string results_dir: The results directory\n '
buildroot = get_buildroot()
source_relative_to = target.address.spec_path
for source in target.sources_relative_to_buildroot():
dest = os.path.join(results_dir, os.path.relpath(source, source_relative_to))
safe_mkdir(os.path.dirname(dest))
shutil.copyfile(os.path.join(buildroot, source), dest) | def _copy_sources(self, target, results_dir):
'Copy sources from a target to a results directory.\n\n :param NodePackage target: A subclass of NodePackage\n :param string results_dir: The results directory\n '
buildroot = get_buildroot()
source_relative_to = target.address.spec_path
for source in target.sources_relative_to_buildroot():
dest = os.path.join(results_dir, os.path.relpath(source, source_relative_to))
safe_mkdir(os.path.dirname(dest))
shutil.copyfile(os.path.join(buildroot, source), dest)<|docstring|>Copy sources from a target to a results directory.
:param NodePackage target: A subclass of NodePackage
:param string results_dir: The results directory<|endoftext|> |
f84b4d7ad5d34be62d157fe854bb5b6d7242298c11f1d5c54ab873267d257096 | def mean_square_error(y_true: np.ndarray, y_pred: np.ndarray) -> float:
'\n Calculate MSE loss\n\n Parameters\n ----------\n y_true: ndarray of shape (n_samples, )\n True response values\n y_pred: ndarray of shape (n_samples, )\n Predicted response values\n\n Returns\n -------\n MSE of given predictions\n '
raise NotImplementedError() | Calculate MSE loss
Parameters
----------
y_true: ndarray of shape (n_samples, )
True response values
y_pred: ndarray of shape (n_samples, )
Predicted response values
Returns
-------
MSE of given predictions | IMLearn/metrics/loss_functions.py | mean_square_error | tehilaogen/IML.HUJI | 2 | python | def mean_square_error(y_true: np.ndarray, y_pred: np.ndarray) -> float:
'\n Calculate MSE loss\n\n Parameters\n ----------\n y_true: ndarray of shape (n_samples, )\n True response values\n y_pred: ndarray of shape (n_samples, )\n Predicted response values\n\n Returns\n -------\n MSE of given predictions\n '
raise NotImplementedError() | def mean_square_error(y_true: np.ndarray, y_pred: np.ndarray) -> float:
'\n Calculate MSE loss\n\n Parameters\n ----------\n y_true: ndarray of shape (n_samples, )\n True response values\n y_pred: ndarray of shape (n_samples, )\n Predicted response values\n\n Returns\n -------\n MSE of given predictions\n '
raise NotImplementedError()<|docstring|>Calculate MSE loss
Parameters
----------
y_true: ndarray of shape (n_samples, )
True response values
y_pred: ndarray of shape (n_samples, )
Predicted response values
Returns
-------
MSE of given predictions<|endoftext|> |
a23e1e56b2c8d5b2977464e228867ad24e498a70272bf0ad10d84a7cd2a27919 | def misclassification_error(y_true: np.ndarray, y_pred: np.ndarray, normalize: bool=True) -> float:
'\n Calculate misclassification loss\n\n Parameters\n ----------\n y_true: ndarray of shape (n_samples, )\n True response values\n y_pred: ndarray of shape (n_samples, )\n Predicted response values\n normalize: bool, default = True\n Normalize by number of samples or not\n\n Returns\n -------\n Misclassification of given predictions\n '
raise NotImplementedError() | Calculate misclassification loss
Parameters
----------
y_true: ndarray of shape (n_samples, )
True response values
y_pred: ndarray of shape (n_samples, )
Predicted response values
normalize: bool, default = True
Normalize by number of samples or not
Returns
-------
Misclassification of given predictions | IMLearn/metrics/loss_functions.py | misclassification_error | tehilaogen/IML.HUJI | 2 | python | def misclassification_error(y_true: np.ndarray, y_pred: np.ndarray, normalize: bool=True) -> float:
'\n Calculate misclassification loss\n\n Parameters\n ----------\n y_true: ndarray of shape (n_samples, )\n True response values\n y_pred: ndarray of shape (n_samples, )\n Predicted response values\n normalize: bool, default = True\n Normalize by number of samples or not\n\n Returns\n -------\n Misclassification of given predictions\n '
raise NotImplementedError() | def misclassification_error(y_true: np.ndarray, y_pred: np.ndarray, normalize: bool=True) -> float:
'\n Calculate misclassification loss\n\n Parameters\n ----------\n y_true: ndarray of shape (n_samples, )\n True response values\n y_pred: ndarray of shape (n_samples, )\n Predicted response values\n normalize: bool, default = True\n Normalize by number of samples or not\n\n Returns\n -------\n Misclassification of given predictions\n '
raise NotImplementedError()<|docstring|>Calculate misclassification loss
Parameters
----------
y_true: ndarray of shape (n_samples, )
True response values
y_pred: ndarray of shape (n_samples, )
Predicted response values
normalize: bool, default = True
Normalize by number of samples or not
Returns
-------
Misclassification of given predictions<|endoftext|> |
2d96a9c4f48ee4f5db257f711deb452779af720c26a6f2748fcc0fea13b7b69b | def accuracy(y_true: np.ndarray, y_pred: np.ndarray) -> float:
'\n Calculate accuracy of given predictions\n\n Parameters\n ----------\n y_true: ndarray of shape (n_samples, )\n True response values\n y_pred: ndarray of shape (n_samples, )\n Predicted response values\n\n Returns\n -------\n Accuracy of given predictions\n '
raise NotImplementedError() | Calculate accuracy of given predictions
Parameters
----------
y_true: ndarray of shape (n_samples, )
True response values
y_pred: ndarray of shape (n_samples, )
Predicted response values
Returns
-------
Accuracy of given predictions | IMLearn/metrics/loss_functions.py | accuracy | tehilaogen/IML.HUJI | 2 | python | def accuracy(y_true: np.ndarray, y_pred: np.ndarray) -> float:
'\n Calculate accuracy of given predictions\n\n Parameters\n ----------\n y_true: ndarray of shape (n_samples, )\n True response values\n y_pred: ndarray of shape (n_samples, )\n Predicted response values\n\n Returns\n -------\n Accuracy of given predictions\n '
raise NotImplementedError() | def accuracy(y_true: np.ndarray, y_pred: np.ndarray) -> float:
'\n Calculate accuracy of given predictions\n\n Parameters\n ----------\n y_true: ndarray of shape (n_samples, )\n True response values\n y_pred: ndarray of shape (n_samples, )\n Predicted response values\n\n Returns\n -------\n Accuracy of given predictions\n '
raise NotImplementedError()<|docstring|>Calculate accuracy of given predictions
Parameters
----------
y_true: ndarray of shape (n_samples, )
True response values
y_pred: ndarray of shape (n_samples, )
Predicted response values
Returns
-------
Accuracy of given predictions<|endoftext|> |
dd104679bf0fff585019c379fe84f5f2fd7b3841c9d44ce818fe2765d194e0d9 | def cross_entropy(y_true: np.ndarray, y_pred: np.ndarray) -> float:
'\n Calculate the cross entropy of given predictions\n\n Parameters\n ----------\n y_true: ndarray of shape (n_samples, )\n True response values\n y_pred: ndarray of shape (n_samples, )\n Predicted response values\n\n Returns\n -------\n Cross entropy of given predictions\n '
raise NotImplementedError() | Calculate the cross entropy of given predictions
Parameters
----------
y_true: ndarray of shape (n_samples, )
True response values
y_pred: ndarray of shape (n_samples, )
Predicted response values
Returns
-------
Cross entropy of given predictions | IMLearn/metrics/loss_functions.py | cross_entropy | tehilaogen/IML.HUJI | 2 | python | def cross_entropy(y_true: np.ndarray, y_pred: np.ndarray) -> float:
'\n Calculate the cross entropy of given predictions\n\n Parameters\n ----------\n y_true: ndarray of shape (n_samples, )\n True response values\n y_pred: ndarray of shape (n_samples, )\n Predicted response values\n\n Returns\n -------\n Cross entropy of given predictions\n '
raise NotImplementedError() | def cross_entropy(y_true: np.ndarray, y_pred: np.ndarray) -> float:
'\n Calculate the cross entropy of given predictions\n\n Parameters\n ----------\n y_true: ndarray of shape (n_samples, )\n True response values\n y_pred: ndarray of shape (n_samples, )\n Predicted response values\n\n Returns\n -------\n Cross entropy of given predictions\n '
raise NotImplementedError()<|docstring|>Calculate the cross entropy of given predictions
Parameters
----------
y_true: ndarray of shape (n_samples, )
True response values
y_pred: ndarray of shape (n_samples, )
Predicted response values
Returns
-------
Cross entropy of given predictions<|endoftext|> |
a44d3704b26bfb796b3e0faba587844a7e20b2c329e57a822d7754fa58a32059 | def test_old_files_redirect(self):
"pre-2.0 'files/' prefixed links are properly redirected"
nbdir = self.notebook_dir.name
base = self.base_url()
os.mkdir(pjoin(nbdir, 'files'))
os.makedirs(pjoin(nbdir, 'sub', 'files'))
for prefix in ('', 'sub'):
with open(pjoin(nbdir, prefix, 'files', 'f1.txt'), 'w') as f:
f.write((prefix + '/files/f1'))
with open(pjoin(nbdir, prefix, 'files', 'f2.txt'), 'w') as f:
f.write((prefix + '/files/f2'))
with open(pjoin(nbdir, prefix, 'f2.txt'), 'w') as f:
f.write((prefix + '/f2'))
with open(pjoin(nbdir, prefix, 'f3.txt'), 'w') as f:
f.write((prefix + '/f3'))
url = url_path_join(base, 'notebooks', prefix, 'files', 'f1.txt')
r = requests.get(url)
self.assertEqual(r.status_code, 200)
self.assertEqual(r.text, (prefix + '/files/f1'))
url = url_path_join(base, 'notebooks', prefix, 'files', 'f2.txt')
r = requests.get(url)
self.assertEqual(r.status_code, 200)
self.assertEqual(r.text, (prefix + '/files/f2'))
url = url_path_join(base, 'notebooks', prefix, 'files', 'f3.txt')
r = requests.get(url)
self.assertEqual(r.status_code, 200)
self.assertEqual(r.text, (prefix + '/f3')) | pre-2.0 'files/' prefixed links are properly redirected | IPython/html/tests/test_files.py | test_old_files_redirect | mineo/ipython | 2 | python | def test_old_files_redirect(self):
nbdir = self.notebook_dir.name
base = self.base_url()
os.mkdir(pjoin(nbdir, 'files'))
os.makedirs(pjoin(nbdir, 'sub', 'files'))
for prefix in (, 'sub'):
with open(pjoin(nbdir, prefix, 'files', 'f1.txt'), 'w') as f:
f.write((prefix + '/files/f1'))
with open(pjoin(nbdir, prefix, 'files', 'f2.txt'), 'w') as f:
f.write((prefix + '/files/f2'))
with open(pjoin(nbdir, prefix, 'f2.txt'), 'w') as f:
f.write((prefix + '/f2'))
with open(pjoin(nbdir, prefix, 'f3.txt'), 'w') as f:
f.write((prefix + '/f3'))
url = url_path_join(base, 'notebooks', prefix, 'files', 'f1.txt')
r = requests.get(url)
self.assertEqual(r.status_code, 200)
self.assertEqual(r.text, (prefix + '/files/f1'))
url = url_path_join(base, 'notebooks', prefix, 'files', 'f2.txt')
r = requests.get(url)
self.assertEqual(r.status_code, 200)
self.assertEqual(r.text, (prefix + '/files/f2'))
url = url_path_join(base, 'notebooks', prefix, 'files', 'f3.txt')
r = requests.get(url)
self.assertEqual(r.status_code, 200)
self.assertEqual(r.text, (prefix + '/f3')) | def test_old_files_redirect(self):
nbdir = self.notebook_dir.name
base = self.base_url()
os.mkdir(pjoin(nbdir, 'files'))
os.makedirs(pjoin(nbdir, 'sub', 'files'))
for prefix in (, 'sub'):
with open(pjoin(nbdir, prefix, 'files', 'f1.txt'), 'w') as f:
f.write((prefix + '/files/f1'))
with open(pjoin(nbdir, prefix, 'files', 'f2.txt'), 'w') as f:
f.write((prefix + '/files/f2'))
with open(pjoin(nbdir, prefix, 'f2.txt'), 'w') as f:
f.write((prefix + '/f2'))
with open(pjoin(nbdir, prefix, 'f3.txt'), 'w') as f:
f.write((prefix + '/f3'))
url = url_path_join(base, 'notebooks', prefix, 'files', 'f1.txt')
r = requests.get(url)
self.assertEqual(r.status_code, 200)
self.assertEqual(r.text, (prefix + '/files/f1'))
url = url_path_join(base, 'notebooks', prefix, 'files', 'f2.txt')
r = requests.get(url)
self.assertEqual(r.status_code, 200)
self.assertEqual(r.text, (prefix + '/files/f2'))
url = url_path_join(base, 'notebooks', prefix, 'files', 'f3.txt')
r = requests.get(url)
self.assertEqual(r.status_code, 200)
self.assertEqual(r.text, (prefix + '/f3'))<|docstring|>pre-2.0 'files/' prefixed links are properly redirected<|endoftext|> |
af60f25473b318acb147040ea2e3ea6931670f7e6662c6cd0f5bd482df2d395a | def distance(point1, point2):
'\n Calculate distance between two points\n\n Parameters\n ---------\n point1 : array_like\n point2 : array_like\n\n Return:\n --------\n float\n The distance between point1 and point2.\n '
point1 = np.asarray(point1)
point2 = np.asarray(point2)
return np.linalg.norm((point1 - point2)) | Calculate distance between two points
Parameters
---------
point1 : array_like
point2 : array_like
Return:
--------
float
The distance between point1 and point2. | molpy/util.py | distance | yonghui-cc/molpy | 0 | python | def distance(point1, point2):
'\n Calculate distance between two points\n\n Parameters\n ---------\n point1 : array_like\n point2 : array_like\n\n Return:\n --------\n float\n The distance between point1 and point2.\n '
point1 = np.asarray(point1)
point2 = np.asarray(point2)
return np.linalg.norm((point1 - point2)) | def distance(point1, point2):
'\n Calculate distance between two points\n\n Parameters\n ---------\n point1 : array_like\n point2 : array_like\n\n Return:\n --------\n float\n The distance between point1 and point2.\n '
point1 = np.asarray(point1)
point2 = np.asarray(point2)
return np.linalg.norm((point1 - point2))<|docstring|>Calculate distance between two points
Parameters
---------
point1 : array_like
point2 : array_like
Return:
--------
float
The distance between point1 and point2.<|endoftext|> |
0cdd53378489b4b40209194800ca3e37a19bb23364b5dddd59e19cd6b5fab125 | def read_xyz(filename):
'\n Read the molecule\n \n Parameters\n ----------\n filename : str\n name of the molecule.xyz\n \n Return\n ------\n symbols :\n coords :\n '
with open(filename, 'r') as handle:
data = handle.readlines()
data = data[2:]
data = [x.split() for x in data]
symbols = [x[0] for x in data]
xyz = []
for line in data:
xyz.append([float(line[1]), float(line[2]), float(line[3])])
return {'symbols': np.array(symbols), 'geometry': xyz} | Read the molecule
Parameters
----------
filename : str
name of the molecule.xyz
Return
------
symbols :
coords : | molpy/util.py | read_xyz | yonghui-cc/molpy | 0 | python | def read_xyz(filename):
'\n Read the molecule\n \n Parameters\n ----------\n filename : str\n name of the molecule.xyz\n \n Return\n ------\n symbols :\n coords :\n '
with open(filename, 'r') as handle:
data = handle.readlines()
data = data[2:]
data = [x.split() for x in data]
symbols = [x[0] for x in data]
xyz = []
for line in data:
xyz.append([float(line[1]), float(line[2]), float(line[3])])
return {'symbols': np.array(symbols), 'geometry': xyz} | def read_xyz(filename):
'\n Read the molecule\n \n Parameters\n ----------\n filename : str\n name of the molecule.xyz\n \n Return\n ------\n symbols :\n coords :\n '
with open(filename, 'r') as handle:
data = handle.readlines()
data = data[2:]
data = [x.split() for x in data]
symbols = [x[0] for x in data]
xyz = []
for line in data:
xyz.append([float(line[1]), float(line[2]), float(line[3])])
return {'symbols': np.array(symbols), 'geometry': xyz}<|docstring|>Read the molecule
Parameters
----------
filename : str
name of the molecule.xyz
Return
------
symbols :
coords :<|endoftext|> |
def4b486df7c3d23d57753243c346548ca8babf54c2ad0b9a4600700dd921a7e | def check_already_mounted(mountpoint):
'Check that the mount device is mounted on the specific mount point.\n\n :param devpath: The path of mount deivce.\n :param mountpoint: The path of mount point.\n :rtype: bool\n '
mounts = Mounter().read_mounts()
for m in mounts:
if (mountpoint == m.mountpoint):
return True
return False | Check that the mount device is mounted on the specific mount point.
:param devpath: The path of mount deivce.
:param mountpoint: The path of mount point.
:rtype: bool | zun/common/mount.py | check_already_mounted | hualingson/zun | 83 | python | def check_already_mounted(mountpoint):
'Check that the mount device is mounted on the specific mount point.\n\n :param devpath: The path of mount deivce.\n :param mountpoint: The path of mount point.\n :rtype: bool\n '
mounts = Mounter().read_mounts()
for m in mounts:
if (mountpoint == m.mountpoint):
return True
return False | def check_already_mounted(mountpoint):
'Check that the mount device is mounted on the specific mount point.\n\n :param devpath: The path of mount deivce.\n :param mountpoint: The path of mount point.\n :rtype: bool\n '
mounts = Mounter().read_mounts()
for m in mounts:
if (mountpoint == m.mountpoint):
return True
return False<|docstring|>Check that the mount device is mounted on the specific mount point.
:param devpath: The path of mount deivce.
:param mountpoint: The path of mount point.
:rtype: bool<|endoftext|> |
27c904860568762a86f9f462f0d1850e947315114e7115029e8fd8e83fbe2654 | def do_mount(devpath, mountpoint, fstype):
'Execute device mount operation.\n\n :param devpath: The path of mount device.\n :param mountpoint: The path of mount point.\n :param fstype: The file system type.\n '
if check_already_mounted(mountpoint):
return
mounter = Mounter()
try:
mounter.mount(devpath, mountpoint, fstype)
except exception.MountException:
try:
mounter.make_filesystem(devpath, fstype)
mounter.mount(devpath, mountpoint, fstype)
except exception.ZunException as e:
with excutils.save_and_reraise_exception():
LOG.error(e.message) | Execute device mount operation.
:param devpath: The path of mount device.
:param mountpoint: The path of mount point.
:param fstype: The file system type. | zun/common/mount.py | do_mount | hualingson/zun | 83 | python | def do_mount(devpath, mountpoint, fstype):
'Execute device mount operation.\n\n :param devpath: The path of mount device.\n :param mountpoint: The path of mount point.\n :param fstype: The file system type.\n '
if check_already_mounted(mountpoint):
return
mounter = Mounter()
try:
mounter.mount(devpath, mountpoint, fstype)
except exception.MountException:
try:
mounter.make_filesystem(devpath, fstype)
mounter.mount(devpath, mountpoint, fstype)
except exception.ZunException as e:
with excutils.save_and_reraise_exception():
LOG.error(e.message) | def do_mount(devpath, mountpoint, fstype):
'Execute device mount operation.\n\n :param devpath: The path of mount device.\n :param mountpoint: The path of mount point.\n :param fstype: The file system type.\n '
if check_already_mounted(mountpoint):
return
mounter = Mounter()
try:
mounter.mount(devpath, mountpoint, fstype)
except exception.MountException:
try:
mounter.make_filesystem(devpath, fstype)
mounter.mount(devpath, mountpoint, fstype)
except exception.ZunException as e:
with excutils.save_and_reraise_exception():
LOG.error(e.message)<|docstring|>Execute device mount operation.
:param devpath: The path of mount device.
:param mountpoint: The path of mount point.
:param fstype: The file system type.<|endoftext|> |
72780002e500d1b95526faec74054058b0c76626d5246559973080424e7fcaab | def read_mounts(self, filter_device=None, filter_fstype=None):
'Read all mounted filesystems.\n\n Read all mounted filesystems except filtered option.\n\n :param filter_device: Filter for device, the result will not contain\n the mounts whose device argument in it.\n :param filter_fstype: Filter for mount point.\n :return: All mounts.\n '
if (filter_device is None):
filter_device = ()
if (filter_fstype is None):
filter_fstype = ()
try:
(out, err) = utils.execute('cat', PROC_MOUNTS_PATH, check_exit_code=0)
except exception.CommandError:
msg = _('Failed to read mounts.')
raise exception.FileNotFound(msg)
lines = out.split('\n')
mounts = []
for line in lines:
if (not line):
continue
tokens = line.split()
if (len(tokens) < 4):
continue
if ((tokens[0] in filter_device) or (tokens[1] in filter_fstype)):
continue
mounts.append(MountInfo(device=tokens[0], mountpoint=tokens[1], fstype=tokens[2], opts=tokens[3]))
return mounts | Read all mounted filesystems.
Read all mounted filesystems except filtered option.
:param filter_device: Filter for device, the result will not contain
the mounts whose device argument in it.
:param filter_fstype: Filter for mount point.
:return: All mounts. | zun/common/mount.py | read_mounts | hualingson/zun | 83 | python | def read_mounts(self, filter_device=None, filter_fstype=None):
'Read all mounted filesystems.\n\n Read all mounted filesystems except filtered option.\n\n :param filter_device: Filter for device, the result will not contain\n the mounts whose device argument in it.\n :param filter_fstype: Filter for mount point.\n :return: All mounts.\n '
if (filter_device is None):
filter_device = ()
if (filter_fstype is None):
filter_fstype = ()
try:
(out, err) = utils.execute('cat', PROC_MOUNTS_PATH, check_exit_code=0)
except exception.CommandError:
msg = _('Failed to read mounts.')
raise exception.FileNotFound(msg)
lines = out.split('\n')
mounts = []
for line in lines:
if (not line):
continue
tokens = line.split()
if (len(tokens) < 4):
continue
if ((tokens[0] in filter_device) or (tokens[1] in filter_fstype)):
continue
mounts.append(MountInfo(device=tokens[0], mountpoint=tokens[1], fstype=tokens[2], opts=tokens[3]))
return mounts | def read_mounts(self, filter_device=None, filter_fstype=None):
'Read all mounted filesystems.\n\n Read all mounted filesystems except filtered option.\n\n :param filter_device: Filter for device, the result will not contain\n the mounts whose device argument in it.\n :param filter_fstype: Filter for mount point.\n :return: All mounts.\n '
if (filter_device is None):
filter_device = ()
if (filter_fstype is None):
filter_fstype = ()
try:
(out, err) = utils.execute('cat', PROC_MOUNTS_PATH, check_exit_code=0)
except exception.CommandError:
msg = _('Failed to read mounts.')
raise exception.FileNotFound(msg)
lines = out.split('\n')
mounts = []
for line in lines:
if (not line):
continue
tokens = line.split()
if (len(tokens) < 4):
continue
if ((tokens[0] in filter_device) or (tokens[1] in filter_fstype)):
continue
mounts.append(MountInfo(device=tokens[0], mountpoint=tokens[1], fstype=tokens[2], opts=tokens[3]))
return mounts<|docstring|>Read all mounted filesystems.
Read all mounted filesystems except filtered option.
:param filter_device: Filter for device, the result will not contain
the mounts whose device argument in it.
:param filter_fstype: Filter for mount point.
:return: All mounts.<|endoftext|> |
0e133461a19dd005a67d8a9cdbfa3e1f12d33c4dfe74f2c52597abd525c3da6f | def get_mps_by_device(self, devpath):
'Get all mountpoints that device mounted on.\n\n :param devpath: The path of mount device.\n :return: All mountpoints.\n '
mps = []
mounts = self.read_mounts()
for m in mounts:
if (devpath == m.device):
mps.append(m.mountpoint)
return mps | Get all mountpoints that device mounted on.
:param devpath: The path of mount device.
:return: All mountpoints. | zun/common/mount.py | get_mps_by_device | hualingson/zun | 83 | python | def get_mps_by_device(self, devpath):
'Get all mountpoints that device mounted on.\n\n :param devpath: The path of mount device.\n :return: All mountpoints.\n '
mps = []
mounts = self.read_mounts()
for m in mounts:
if (devpath == m.device):
mps.append(m.mountpoint)
return mps | def get_mps_by_device(self, devpath):
'Get all mountpoints that device mounted on.\n\n :param devpath: The path of mount device.\n :return: All mountpoints.\n '
mps = []
mounts = self.read_mounts()
for m in mounts:
if (devpath == m.device):
mps.append(m.mountpoint)
return mps<|docstring|>Get all mountpoints that device mounted on.
:param devpath: The path of mount device.
:return: All mountpoints.<|endoftext|> |
63d70a89e3fabfe06aa3cd2d39f3e8f7babc1fc4675238ca91978303cbfa27bb | def establecer_destino_archivo_ubicacion(instance, filename):
'\n Establece la ruta de destino para el archivo de ubicación cargado a la instancia.\n '
ruta_archivos_ubicacion = 'app_reservas/ubicaciones/aulas/'
extension_archivo = (filename.split('.')[(- 1)] if ('.' in filename) else '')
nombre_archivo = '{0!s}.{1!s}'.format(slugify(str(instance)), extension_archivo)
return os.path.join(ruta_archivos_ubicacion, nombre_archivo) | Establece la ruta de destino para el archivo de ubicación cargado a la instancia. | app_reservas/models/aula.py | establecer_destino_archivo_ubicacion | fedegallar/reservas | 1 | python | def establecer_destino_archivo_ubicacion(instance, filename):
'\n \n '
ruta_archivos_ubicacion = 'app_reservas/ubicaciones/aulas/'
extension_archivo = (filename.split('.')[(- 1)] if ('.' in filename) else )
nombre_archivo = '{0!s}.{1!s}'.format(slugify(str(instance)), extension_archivo)
return os.path.join(ruta_archivos_ubicacion, nombre_archivo) | def establecer_destino_archivo_ubicacion(instance, filename):
'\n \n '
ruta_archivos_ubicacion = 'app_reservas/ubicaciones/aulas/'
extension_archivo = (filename.split('.')[(- 1)] if ('.' in filename) else )
nombre_archivo = '{0!s}.{1!s}'.format(slugify(str(instance)), extension_archivo)
return os.path.join(ruta_archivos_ubicacion, nombre_archivo)<|docstring|>Establece la ruta de destino para el archivo de ubicación cargado a la instancia.<|endoftext|> |
e038ffa3155b2d52e37fad36ab5e48535889c9cd1c6910939fb60be651e4608a | def __str__(self):
'\n Representación de la instancia.\n '
return '{0!s} - {1!s}'.format(self.get_nombre_corto(), self.nivel) | Representación de la instancia. | app_reservas/models/aula.py | __str__ | fedegallar/reservas | 1 | python | def __str__(self):
'\n \n '
return '{0!s} - {1!s}'.format(self.get_nombre_corto(), self.nivel) | def __str__(self):
'\n \n '
return '{0!s} - {1!s}'.format(self.get_nombre_corto(), self.nivel)<|docstring|>Representación de la instancia.<|endoftext|> |
89b26bb84642638e4f6cca58e1c5430bcb13dd70a35a9e61642bd48cbd341ecf | def get_nombre_corto(self):
'\n Retorna el nombre corto de la instancia.\n '
nombre_corto = (self.nombre or 'Aula {0:d}'.format(self.numero))
return nombre_corto | Retorna el nombre corto de la instancia. | app_reservas/models/aula.py | get_nombre_corto | fedegallar/reservas | 1 | python | def get_nombre_corto(self):
'\n \n '
nombre_corto = (self.nombre or 'Aula {0:d}'.format(self.numero))
return nombre_corto | def get_nombre_corto(self):
'\n \n '
nombre_corto = (self.nombre or 'Aula {0:d}'.format(self.numero))
return nombre_corto<|docstring|>Retorna el nombre corto de la instancia.<|endoftext|> |
1c31b7a82570f37344bb71c4f58764ca3581ebf00ddf61c6311bea96c7a649c2 | def get_identificador_url(self):
'\n Retorna el identificador utilizado para acceder a la URL de detalle de\n la instancia.\n '
return str(self.id) | Retorna el identificador utilizado para acceder a la URL de detalle de
la instancia. | app_reservas/models/aula.py | get_identificador_url | fedegallar/reservas | 1 | python | def get_identificador_url(self):
'\n Retorna el identificador utilizado para acceder a la URL de detalle de\n la instancia.\n '
return str(self.id) | def get_identificador_url(self):
'\n Retorna el identificador utilizado para acceder a la URL de detalle de\n la instancia.\n '
return str(self.id)<|docstring|>Retorna el identificador utilizado para acceder a la URL de detalle de
la instancia.<|endoftext|> |
011b2dd5617deb83ac8c3f9b81463149a25f2a9f2b41c324d07a04160dac4161 | @exp_factory.register_config_factory('panoptic_maskrcnn_resnetfpn_coco')
def panoptic_maskrcnn_resnetfpn_coco() -> cfg.ExperimentConfig:
'COCO panoptic segmentation with Panoptic Mask R-CNN.'
train_batch_size = 64
eval_batch_size = 8
steps_per_epoch = (_COCO_TRAIN_EXAMPLES // train_batch_size)
validation_steps = (_COCO_VAL_EXAMPLES // eval_batch_size)
config = cfg.ExperimentConfig(runtime=cfg.RuntimeConfig(mixed_precision_dtype='bfloat16'), task=PanopticMaskRCNNTask(init_checkpoint='gs://cloud-tpu-checkpoints/vision-2.0/resnet50_imagenet/ckpt-28080', init_checkpoint_modules=['backbone'], model=PanopticMaskRCNN(num_classes=91, input_size=[1024, 1024, 3], segmentation_model=SEGMENTATION_MODEL(num_classes=91, head=SEGMENTATION_HEAD(level=3))), losses=Losses(l2_weight_decay=4e-05), train_data=DataConfig(input_path=os.path.join(_COCO_INPUT_PATH_BASE, 'train*'), is_training=True, global_batch_size=train_batch_size, parser=Parser(aug_rand_hflip=True, aug_scale_min=0.8, aug_scale_max=1.25)), validation_data=DataConfig(input_path=os.path.join(_COCO_INPUT_PATH_BASE, 'val*'), is_training=False, global_batch_size=eval_batch_size, drop_remainder=False), annotation_file=os.path.join(_COCO_INPUT_PATH_BASE, 'instances_val2017.json')), trainer=cfg.TrainerConfig(train_steps=22500, validation_steps=validation_steps, validation_interval=steps_per_epoch, steps_per_loop=steps_per_epoch, summary_interval=steps_per_epoch, checkpoint_interval=steps_per_epoch, optimizer_config=optimization.OptimizationConfig({'optimizer': {'type': 'sgd', 'sgd': {'momentum': 0.9}}, 'learning_rate': {'type': 'stepwise', 'stepwise': {'boundaries': [15000, 20000], 'values': [0.12, 0.012, 0.0012]}}, 'warmup': {'type': 'linear', 'linear': {'warmup_steps': 500, 'warmup_learning_rate': 0.0067}}})), restrictions=['task.train_data.is_training != None', 'task.validation_data.is_training != None'])
return config | COCO panoptic segmentation with Panoptic Mask R-CNN. | official/vision/beta/projects/panoptic_maskrcnn/configs/panoptic_maskrcnn.py | panoptic_maskrcnn_resnetfpn_coco | kisna-aryan/models | 3 | python | @exp_factory.register_config_factory('panoptic_maskrcnn_resnetfpn_coco')
def panoptic_maskrcnn_resnetfpn_coco() -> cfg.ExperimentConfig:
train_batch_size = 64
eval_batch_size = 8
steps_per_epoch = (_COCO_TRAIN_EXAMPLES // train_batch_size)
validation_steps = (_COCO_VAL_EXAMPLES // eval_batch_size)
config = cfg.ExperimentConfig(runtime=cfg.RuntimeConfig(mixed_precision_dtype='bfloat16'), task=PanopticMaskRCNNTask(init_checkpoint='gs://cloud-tpu-checkpoints/vision-2.0/resnet50_imagenet/ckpt-28080', init_checkpoint_modules=['backbone'], model=PanopticMaskRCNN(num_classes=91, input_size=[1024, 1024, 3], segmentation_model=SEGMENTATION_MODEL(num_classes=91, head=SEGMENTATION_HEAD(level=3))), losses=Losses(l2_weight_decay=4e-05), train_data=DataConfig(input_path=os.path.join(_COCO_INPUT_PATH_BASE, 'train*'), is_training=True, global_batch_size=train_batch_size, parser=Parser(aug_rand_hflip=True, aug_scale_min=0.8, aug_scale_max=1.25)), validation_data=DataConfig(input_path=os.path.join(_COCO_INPUT_PATH_BASE, 'val*'), is_training=False, global_batch_size=eval_batch_size, drop_remainder=False), annotation_file=os.path.join(_COCO_INPUT_PATH_BASE, 'instances_val2017.json')), trainer=cfg.TrainerConfig(train_steps=22500, validation_steps=validation_steps, validation_interval=steps_per_epoch, steps_per_loop=steps_per_epoch, summary_interval=steps_per_epoch, checkpoint_interval=steps_per_epoch, optimizer_config=optimization.OptimizationConfig({'optimizer': {'type': 'sgd', 'sgd': {'momentum': 0.9}}, 'learning_rate': {'type': 'stepwise', 'stepwise': {'boundaries': [15000, 20000], 'values': [0.12, 0.012, 0.0012]}}, 'warmup': {'type': 'linear', 'linear': {'warmup_steps': 500, 'warmup_learning_rate': 0.0067}}})), restrictions=['task.train_data.is_training != None', 'task.validation_data.is_training != None'])
return config | @exp_factory.register_config_factory('panoptic_maskrcnn_resnetfpn_coco')
def panoptic_maskrcnn_resnetfpn_coco() -> cfg.ExperimentConfig:
train_batch_size = 64
eval_batch_size = 8
steps_per_epoch = (_COCO_TRAIN_EXAMPLES // train_batch_size)
validation_steps = (_COCO_VAL_EXAMPLES // eval_batch_size)
config = cfg.ExperimentConfig(runtime=cfg.RuntimeConfig(mixed_precision_dtype='bfloat16'), task=PanopticMaskRCNNTask(init_checkpoint='gs://cloud-tpu-checkpoints/vision-2.0/resnet50_imagenet/ckpt-28080', init_checkpoint_modules=['backbone'], model=PanopticMaskRCNN(num_classes=91, input_size=[1024, 1024, 3], segmentation_model=SEGMENTATION_MODEL(num_classes=91, head=SEGMENTATION_HEAD(level=3))), losses=Losses(l2_weight_decay=4e-05), train_data=DataConfig(input_path=os.path.join(_COCO_INPUT_PATH_BASE, 'train*'), is_training=True, global_batch_size=train_batch_size, parser=Parser(aug_rand_hflip=True, aug_scale_min=0.8, aug_scale_max=1.25)), validation_data=DataConfig(input_path=os.path.join(_COCO_INPUT_PATH_BASE, 'val*'), is_training=False, global_batch_size=eval_batch_size, drop_remainder=False), annotation_file=os.path.join(_COCO_INPUT_PATH_BASE, 'instances_val2017.json')), trainer=cfg.TrainerConfig(train_steps=22500, validation_steps=validation_steps, validation_interval=steps_per_epoch, steps_per_loop=steps_per_epoch, summary_interval=steps_per_epoch, checkpoint_interval=steps_per_epoch, optimizer_config=optimization.OptimizationConfig({'optimizer': {'type': 'sgd', 'sgd': {'momentum': 0.9}}, 'learning_rate': {'type': 'stepwise', 'stepwise': {'boundaries': [15000, 20000], 'values': [0.12, 0.012, 0.0012]}}, 'warmup': {'type': 'linear', 'linear': {'warmup_steps': 500, 'warmup_learning_rate': 0.0067}}})), restrictions=['task.train_data.is_training != None', 'task.validation_data.is_training != None'])
return config<|docstring|>COCO panoptic segmentation with Panoptic Mask R-CNN.<|endoftext|> |
989bbf46ca19bed3b3ff5ed423eaaf2aa94442bd68e66286470da59909591fd3 | def store_initial_buy(self, coin_pair, buy_order_uuid):
"\n Used to place an initial trade in the database\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n :param buy_order_uuid: The buy order's UUID\n :type buy_order_uuid: str\n "
if (coin_pair in self.trades['trackedCoinPairs']):
return logger.warning('Trying to buy on the {} market which is already tracked.'.format(coin_pair))
new_buy_object = {'coinPair': coin_pair, 'quantity': 0, 'buy': {'orderUuid': buy_order_uuid}}
self.trades['trackedCoinPairs'].append(coin_pair)
self.trades['trades'].append(new_buy_object)
write_json_to_file(self.trades_file_string, self.trades) | Used to place an initial trade in the database
:param coin_pair: String literal for the market (ex: BTC-LTC)
:type coin_pair: str
:param buy_order_uuid: The buy order's UUID
:type buy_order_uuid: str | src/database.py | store_initial_buy | CryptoRye/Crypto-Trading-Bot | 301 | python | def store_initial_buy(self, coin_pair, buy_order_uuid):
"\n Used to place an initial trade in the database\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n :param buy_order_uuid: The buy order's UUID\n :type buy_order_uuid: str\n "
if (coin_pair in self.trades['trackedCoinPairs']):
return logger.warning('Trying to buy on the {} market which is already tracked.'.format(coin_pair))
new_buy_object = {'coinPair': coin_pair, 'quantity': 0, 'buy': {'orderUuid': buy_order_uuid}}
self.trades['trackedCoinPairs'].append(coin_pair)
self.trades['trades'].append(new_buy_object)
write_json_to_file(self.trades_file_string, self.trades) | def store_initial_buy(self, coin_pair, buy_order_uuid):
"\n Used to place an initial trade in the database\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n :param buy_order_uuid: The buy order's UUID\n :type buy_order_uuid: str\n "
if (coin_pair in self.trades['trackedCoinPairs']):
return logger.warning('Trying to buy on the {} market which is already tracked.'.format(coin_pair))
new_buy_object = {'coinPair': coin_pair, 'quantity': 0, 'buy': {'orderUuid': buy_order_uuid}}
self.trades['trackedCoinPairs'].append(coin_pair)
self.trades['trades'].append(new_buy_object)
write_json_to_file(self.trades_file_string, self.trades)<|docstring|>Used to place an initial trade in the database
:param coin_pair: String literal for the market (ex: BTC-LTC)
:type coin_pair: str
:param buy_order_uuid: The buy order's UUID
:type buy_order_uuid: str<|endoftext|> |
903758e4bd0424c92feaf725c1c4096d9c533db2bacc72349b271a94be5bad2e | def store_buy(self, bittrex_order, stats):
'\n Used to place a buy trade in the database\n\n :param bittrex_order: Bittrex buy order object\n :type bittrex_order: dict\n :param stats: The buy stats to store\n :type stats: dict\n '
if (bittrex_order['Exchange'] not in self.trades['trackedCoinPairs']):
return logger.warning('Trying to buy on the {} market without an initial buy object.'.format(bittrex_order['Exchange']))
order = self.convert_bittrex_order_object(bittrex_order, stats)
trade = self.get_open_trade(bittrex_order['Exchange'])
trade['quantity'] = round((bittrex_order['Quantity'] - bittrex_order['QuantityRemaining']), 8)
trade['buy'] = order
write_json_to_file(self.trades_file_string, self.trades) | Used to place a buy trade in the database
:param bittrex_order: Bittrex buy order object
:type bittrex_order: dict
:param stats: The buy stats to store
:type stats: dict | src/database.py | store_buy | CryptoRye/Crypto-Trading-Bot | 301 | python | def store_buy(self, bittrex_order, stats):
'\n Used to place a buy trade in the database\n\n :param bittrex_order: Bittrex buy order object\n :type bittrex_order: dict\n :param stats: The buy stats to store\n :type stats: dict\n '
if (bittrex_order['Exchange'] not in self.trades['trackedCoinPairs']):
return logger.warning('Trying to buy on the {} market without an initial buy object.'.format(bittrex_order['Exchange']))
order = self.convert_bittrex_order_object(bittrex_order, stats)
trade = self.get_open_trade(bittrex_order['Exchange'])
trade['quantity'] = round((bittrex_order['Quantity'] - bittrex_order['QuantityRemaining']), 8)
trade['buy'] = order
write_json_to_file(self.trades_file_string, self.trades) | def store_buy(self, bittrex_order, stats):
'\n Used to place a buy trade in the database\n\n :param bittrex_order: Bittrex buy order object\n :type bittrex_order: dict\n :param stats: The buy stats to store\n :type stats: dict\n '
if (bittrex_order['Exchange'] not in self.trades['trackedCoinPairs']):
return logger.warning('Trying to buy on the {} market without an initial buy object.'.format(bittrex_order['Exchange']))
order = self.convert_bittrex_order_object(bittrex_order, stats)
trade = self.get_open_trade(bittrex_order['Exchange'])
trade['quantity'] = round((bittrex_order['Quantity'] - bittrex_order['QuantityRemaining']), 8)
trade['buy'] = order
write_json_to_file(self.trades_file_string, self.trades)<|docstring|>Used to place a buy trade in the database
:param bittrex_order: Bittrex buy order object
:type bittrex_order: dict
:param stats: The buy stats to store
:type stats: dict<|endoftext|> |
80d4a3e997d75162b19ea8cf770aab11a18322628bdc0925ae1a3e48b879f854 | def store_sell(self, bittrex_order, stats):
'\n Used to place a sell trade in the database\n\n :param bittrex_order: Bittrex sell order object\n :type bittrex_order: dict\n :param stats: The sell stats to store\n :type stats: dict\n '
if (bittrex_order['Exchange'] not in self.trades['trackedCoinPairs']):
return logger.warning('Trying to sell on the {} market which is not tracked.'.format(bittrex_order['Exchange']))
order = self.convert_bittrex_order_object(bittrex_order, stats)
trade = self.get_open_trade(bittrex_order['Exchange'])
trade['sell'] = order
self.trades['trackedCoinPairs'].remove(bittrex_order['Exchange'])
write_json_to_file(self.trades_file_string, self.trades) | Used to place a sell trade in the database
:param bittrex_order: Bittrex sell order object
:type bittrex_order: dict
:param stats: The sell stats to store
:type stats: dict | src/database.py | store_sell | CryptoRye/Crypto-Trading-Bot | 301 | python | def store_sell(self, bittrex_order, stats):
'\n Used to place a sell trade in the database\n\n :param bittrex_order: Bittrex sell order object\n :type bittrex_order: dict\n :param stats: The sell stats to store\n :type stats: dict\n '
if (bittrex_order['Exchange'] not in self.trades['trackedCoinPairs']):
return logger.warning('Trying to sell on the {} market which is not tracked.'.format(bittrex_order['Exchange']))
order = self.convert_bittrex_order_object(bittrex_order, stats)
trade = self.get_open_trade(bittrex_order['Exchange'])
trade['sell'] = order
self.trades['trackedCoinPairs'].remove(bittrex_order['Exchange'])
write_json_to_file(self.trades_file_string, self.trades) | def store_sell(self, bittrex_order, stats):
'\n Used to place a sell trade in the database\n\n :param bittrex_order: Bittrex sell order object\n :type bittrex_order: dict\n :param stats: The sell stats to store\n :type stats: dict\n '
if (bittrex_order['Exchange'] not in self.trades['trackedCoinPairs']):
return logger.warning('Trying to sell on the {} market which is not tracked.'.format(bittrex_order['Exchange']))
order = self.convert_bittrex_order_object(bittrex_order, stats)
trade = self.get_open_trade(bittrex_order['Exchange'])
trade['sell'] = order
self.trades['trackedCoinPairs'].remove(bittrex_order['Exchange'])
write_json_to_file(self.trades_file_string, self.trades)<|docstring|>Used to place a sell trade in the database
:param bittrex_order: Bittrex sell order object
:type bittrex_order: dict
:param stats: The sell stats to store
:type stats: dict<|endoftext|> |
1a64e2c53f3877270a9027513abafc90543ab0768e5d22274ec5fd47fc0e7618 | def pause_buy(self, coin_pair):
'\n Used to pause buy tracking on the coin pair\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n '
self.app_data['coinPairs'].remove(coin_pair)
write_json_to_file(self.app_data_file_string, self.app_data) | Used to pause buy tracking on the coin pair
:param coin_pair: String literal for the market (ex: BTC-LTC)
:type coin_pair: str | src/database.py | pause_buy | CryptoRye/Crypto-Trading-Bot | 301 | python | def pause_buy(self, coin_pair):
'\n Used to pause buy tracking on the coin pair\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n '
self.app_data['coinPairs'].remove(coin_pair)
write_json_to_file(self.app_data_file_string, self.app_data) | def pause_buy(self, coin_pair):
'\n Used to pause buy tracking on the coin pair\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n '
self.app_data['coinPairs'].remove(coin_pair)
write_json_to_file(self.app_data_file_string, self.app_data)<|docstring|>Used to pause buy tracking on the coin pair
:param coin_pair: String literal for the market (ex: BTC-LTC)
:type coin_pair: str<|endoftext|> |
fc9c8af9c9adf658f4209ec3c6a15e4f57b09a693f7df164b89cd39980581db0 | def pause_sell(self, coin_pair):
'\n Used to pause sell tracking on the coin pair and set the sell pause time\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n '
if (coin_pair in self.app_data['pausedTrackedCoinPairs']):
return
self.app_data['pausedTrackedCoinPairs'].append(coin_pair)
if (self.app_data['pauseTime']['sell'] is None):
self.app_data['pauseTime']['sell'] = time.time()
write_json_to_file(self.app_data_file_string, self.app_data) | Used to pause sell tracking on the coin pair and set the sell pause time
:param coin_pair: String literal for the market (ex: BTC-LTC)
:type coin_pair: str | src/database.py | pause_sell | CryptoRye/Crypto-Trading-Bot | 301 | python | def pause_sell(self, coin_pair):
'\n Used to pause sell tracking on the coin pair and set the sell pause time\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n '
if (coin_pair in self.app_data['pausedTrackedCoinPairs']):
return
self.app_data['pausedTrackedCoinPairs'].append(coin_pair)
if (self.app_data['pauseTime']['sell'] is None):
self.app_data['pauseTime']['sell'] = time.time()
write_json_to_file(self.app_data_file_string, self.app_data) | def pause_sell(self, coin_pair):
'\n Used to pause sell tracking on the coin pair and set the sell pause time\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n '
if (coin_pair in self.app_data['pausedTrackedCoinPairs']):
return
self.app_data['pausedTrackedCoinPairs'].append(coin_pair)
if (self.app_data['pauseTime']['sell'] is None):
self.app_data['pauseTime']['sell'] = time.time()
write_json_to_file(self.app_data_file_string, self.app_data)<|docstring|>Used to pause sell tracking on the coin pair and set the sell pause time
:param coin_pair: String literal for the market (ex: BTC-LTC)
:type coin_pair: str<|endoftext|> |
5bf64e57241d2cda0e97690e6e8ffa652b368c9fb71bfc27e094bda83870e182 | def store_coin_pairs(self, btc_coin_pairs):
'\n Used to store the latest Bittrex available markets and update the buy pause time\n\n :param btc_coin_pairs: String list of market pairs\n :type btc_coin_pairs: list\n '
self.app_data['coinPairs'] = btc_coin_pairs
self.app_data['pauseTime']['buy'] = time.time()
write_json_to_file(self.app_data_file_string, self.app_data) | Used to store the latest Bittrex available markets and update the buy pause time
:param btc_coin_pairs: String list of market pairs
:type btc_coin_pairs: list | src/database.py | store_coin_pairs | CryptoRye/Crypto-Trading-Bot | 301 | python | def store_coin_pairs(self, btc_coin_pairs):
'\n Used to store the latest Bittrex available markets and update the buy pause time\n\n :param btc_coin_pairs: String list of market pairs\n :type btc_coin_pairs: list\n '
self.app_data['coinPairs'] = btc_coin_pairs
self.app_data['pauseTime']['buy'] = time.time()
write_json_to_file(self.app_data_file_string, self.app_data) | def store_coin_pairs(self, btc_coin_pairs):
'\n Used to store the latest Bittrex available markets and update the buy pause time\n\n :param btc_coin_pairs: String list of market pairs\n :type btc_coin_pairs: list\n '
self.app_data['coinPairs'] = btc_coin_pairs
self.app_data['pauseTime']['buy'] = time.time()
write_json_to_file(self.app_data_file_string, self.app_data)<|docstring|>Used to store the latest Bittrex available markets and update the buy pause time
:param btc_coin_pairs: String list of market pairs
:type btc_coin_pairs: list<|endoftext|> |
0a9e3684894f70a4b6c9dab4476216fe4438af329edd8829b01d8ae4dd84c218 | def resume_sells(self):
'\n Used to resume all paused sells and reset the sell pause time\n '
if (len(self.app_data['pausedTrackedCoinPairs']) < 1):
return
self.app_data['pausedTrackedCoinPairs'] = []
self.app_data['pauseTime']['sell'] = None
write_json_to_file(self.app_data_file_string, self.app_data) | Used to resume all paused sells and reset the sell pause time | src/database.py | resume_sells | CryptoRye/Crypto-Trading-Bot | 301 | python | def resume_sells(self):
'\n \n '
if (len(self.app_data['pausedTrackedCoinPairs']) < 1):
return
self.app_data['pausedTrackedCoinPairs'] = []
self.app_data['pauseTime']['sell'] = None
write_json_to_file(self.app_data_file_string, self.app_data) | def resume_sells(self):
'\n \n '
if (len(self.app_data['pausedTrackedCoinPairs']) < 1):
return
self.app_data['pausedTrackedCoinPairs'] = []
self.app_data['pauseTime']['sell'] = None
write_json_to_file(self.app_data_file_string, self.app_data)<|docstring|>Used to resume all paused sells and reset the sell pause time<|endoftext|> |
5a1dc90a743a83db235a2cc50718a8266d531c8fde7815d6d6fb608cb683a93f | def reset_balance_notifier(self, current_balance=None):
"\n Used to reset the balance notifier pause time\n\n :param current_balance: The current total balance's BTC value\n :type current_balance: float\n "
if (current_balance is not None):
self.app_data['previousBalance'] = current_balance
self.app_data['pauseTime']['balance'] = time.time()
write_json_to_file(self.app_data_file_string, self.app_data) | Used to reset the balance notifier pause time
:param current_balance: The current total balance's BTC value
:type current_balance: float | src/database.py | reset_balance_notifier | CryptoRye/Crypto-Trading-Bot | 301 | python | def reset_balance_notifier(self, current_balance=None):
"\n Used to reset the balance notifier pause time\n\n :param current_balance: The current total balance's BTC value\n :type current_balance: float\n "
if (current_balance is not None):
self.app_data['previousBalance'] = current_balance
self.app_data['pauseTime']['balance'] = time.time()
write_json_to_file(self.app_data_file_string, self.app_data) | def reset_balance_notifier(self, current_balance=None):
"\n Used to reset the balance notifier pause time\n\n :param current_balance: The current total balance's BTC value\n :type current_balance: float\n "
if (current_balance is not None):
self.app_data['previousBalance'] = current_balance
self.app_data['pauseTime']['balance'] = time.time()
write_json_to_file(self.app_data_file_string, self.app_data)<|docstring|>Used to reset the balance notifier pause time
:param current_balance: The current total balance's BTC value
:type current_balance: float<|endoftext|> |
40efb7a20e8fd48eea70594f5ef8b058dc9c890f97c21160732098bad3a76f02 | def check_resume(self, pause_time, pause_type):
"\n Used to check if the pause type can be un-paused\n\n :param pause_time: The amount of minutes tracking should be paused\n :type pause_time: int\n :param pause_type: The pause type to check (one of: 'buy', 'sell', 'balance)\n :type pause_type: str\n "
if (self.app_data['pauseTime'][pause_type] is None):
if (pause_type == 'balance'):
self.reset_balance_notifier()
return True
return False
return ((time.time() - self.app_data['pauseTime'][pause_type]) >= (pause_time * 60)) | Used to check if the pause type can be un-paused
:param pause_time: The amount of minutes tracking should be paused
:type pause_time: int
:param pause_type: The pause type to check (one of: 'buy', 'sell', 'balance)
:type pause_type: str | src/database.py | check_resume | CryptoRye/Crypto-Trading-Bot | 301 | python | def check_resume(self, pause_time, pause_type):
"\n Used to check if the pause type can be un-paused\n\n :param pause_time: The amount of minutes tracking should be paused\n :type pause_time: int\n :param pause_type: The pause type to check (one of: 'buy', 'sell', 'balance)\n :type pause_type: str\n "
if (self.app_data['pauseTime'][pause_type] is None):
if (pause_type == 'balance'):
self.reset_balance_notifier()
return True
return False
return ((time.time() - self.app_data['pauseTime'][pause_type]) >= (pause_time * 60)) | def check_resume(self, pause_time, pause_type):
"\n Used to check if the pause type can be un-paused\n\n :param pause_time: The amount of minutes tracking should be paused\n :type pause_time: int\n :param pause_type: The pause type to check (one of: 'buy', 'sell', 'balance)\n :type pause_type: str\n "
if (self.app_data['pauseTime'][pause_type] is None):
if (pause_type == 'balance'):
self.reset_balance_notifier()
return True
return False
return ((time.time() - self.app_data['pauseTime'][pause_type]) >= (pause_time * 60))<|docstring|>Used to check if the pause type can be un-paused
:param pause_time: The amount of minutes tracking should be paused
:type pause_time: int
:param pause_type: The pause type to check (one of: 'buy', 'sell', 'balance)
:type pause_type: str<|endoftext|> |
485773d1b64e84241c62c3ee0eb2c001a94a01f8fc200ac0c6ecafbaaece5d34 | def get_open_trade(self, coin_pair):
"\n Used to get the coin pair's unsold trade in the database\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n\n :return: The open trade object\n :rtype: dict\n "
trade_index = py_.find_index(self.trades['trades'], (lambda trade: ((trade['coinPair'] == coin_pair) and ('sell' not in trade))))
if (trade_index == (- 1)):
logger.error('Could not find open trade for {} coin pair'.format(coin_pair))
return None
return self.trades['trades'][trade_index] | Used to get the coin pair's unsold trade in the database
:param coin_pair: String literal for the market (ex: BTC-LTC)
:type coin_pair: str
:return: The open trade object
:rtype: dict | src/database.py | get_open_trade | CryptoRye/Crypto-Trading-Bot | 301 | python | def get_open_trade(self, coin_pair):
"\n Used to get the coin pair's unsold trade in the database\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n\n :return: The open trade object\n :rtype: dict\n "
trade_index = py_.find_index(self.trades['trades'], (lambda trade: ((trade['coinPair'] == coin_pair) and ('sell' not in trade))))
if (trade_index == (- 1)):
logger.error('Could not find open trade for {} coin pair'.format(coin_pair))
return None
return self.trades['trades'][trade_index] | def get_open_trade(self, coin_pair):
"\n Used to get the coin pair's unsold trade in the database\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n\n :return: The open trade object\n :rtype: dict\n "
trade_index = py_.find_index(self.trades['trades'], (lambda trade: ((trade['coinPair'] == coin_pair) and ('sell' not in trade))))
if (trade_index == (- 1)):
logger.error('Could not find open trade for {} coin pair'.format(coin_pair))
return None
return self.trades['trades'][trade_index]<|docstring|>Used to get the coin pair's unsold trade in the database
:param coin_pair: String literal for the market (ex: BTC-LTC)
:type coin_pair: str
:return: The open trade object
:rtype: dict<|endoftext|> |
50e4bf0f1117435ec0691233ebc1a1c1af4faad8c26e64789c985100a053b492 | def get_profit_margin(self, coin_pair, current_price, trade=None):
'\n Used to get the profit margin for a coin pair"s trade\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n :param current_price: Market"s current price\n :type current_price: float\n :param trade: The trade to calculate the profit margin on\n Not required. If not passed in the function will go find it\n :type trade: dict\n\n :return: Profit margin\n :rtype: float\n '
if (trade is None):
trade = self.get_open_trade(coin_pair)
buy_btc_quantity = round((trade['buy']['price'] / (1 - bittrex_trade_commission)), 8)
sell_btc_quantity = round(((trade['quantity'] * current_price) * (1 - bittrex_trade_commission)), 8)
profit_margin = ((100 * (sell_btc_quantity - buy_btc_quantity)) / buy_btc_quantity)
return profit_margin | Used to get the profit margin for a coin pair"s trade
:param coin_pair: String literal for the market (ex: BTC-LTC)
:type coin_pair: str
:param current_price: Market"s current price
:type current_price: float
:param trade: The trade to calculate the profit margin on
Not required. If not passed in the function will go find it
:type trade: dict
:return: Profit margin
:rtype: float | src/database.py | get_profit_margin | CryptoRye/Crypto-Trading-Bot | 301 | python | def get_profit_margin(self, coin_pair, current_price, trade=None):
'\n Used to get the profit margin for a coin pair"s trade\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n :param current_price: Market"s current price\n :type current_price: float\n :param trade: The trade to calculate the profit margin on\n Not required. If not passed in the function will go find it\n :type trade: dict\n\n :return: Profit margin\n :rtype: float\n '
if (trade is None):
trade = self.get_open_trade(coin_pair)
buy_btc_quantity = round((trade['buy']['price'] / (1 - bittrex_trade_commission)), 8)
sell_btc_quantity = round(((trade['quantity'] * current_price) * (1 - bittrex_trade_commission)), 8)
profit_margin = ((100 * (sell_btc_quantity - buy_btc_quantity)) / buy_btc_quantity)
return profit_margin | def get_profit_margin(self, coin_pair, current_price, trade=None):
'\n Used to get the profit margin for a coin pair"s trade\n\n :param coin_pair: String literal for the market (ex: BTC-LTC)\n :type coin_pair: str\n :param current_price: Market"s current price\n :type current_price: float\n :param trade: The trade to calculate the profit margin on\n Not required. If not passed in the function will go find it\n :type trade: dict\n\n :return: Profit margin\n :rtype: float\n '
if (trade is None):
trade = self.get_open_trade(coin_pair)
buy_btc_quantity = round((trade['buy']['price'] / (1 - bittrex_trade_commission)), 8)
sell_btc_quantity = round(((trade['quantity'] * current_price) * (1 - bittrex_trade_commission)), 8)
profit_margin = ((100 * (sell_btc_quantity - buy_btc_quantity)) / buy_btc_quantity)
return profit_margin<|docstring|>Used to get the profit margin for a coin pair"s trade
:param coin_pair: String literal for the market (ex: BTC-LTC)
:type coin_pair: str
:param current_price: Market"s current price
:type current_price: float
:param trade: The trade to calculate the profit margin on
Not required. If not passed in the function will go find it
:type trade: dict
:return: Profit margin
:rtype: float<|endoftext|> |
e72644979290ae1fc00a5f64fc36eb9415dc301dc5853d6a78818810ae6dcd20 | def get_previous_total_balance(self):
'\n Used to get the previous total balance\n\n :return: Previous total balance\n :rtype: float\n '
if (('previousBalance' not in self.app_data) or (self.app_data['previousBalance'] == 0)):
return None
return self.app_data['previousBalance'] | Used to get the previous total balance
:return: Previous total balance
:rtype: float | src/database.py | get_previous_total_balance | CryptoRye/Crypto-Trading-Bot | 301 | python | def get_previous_total_balance(self):
'\n Used to get the previous total balance\n\n :return: Previous total balance\n :rtype: float\n '
if (('previousBalance' not in self.app_data) or (self.app_data['previousBalance'] == 0)):
return None
return self.app_data['previousBalance'] | def get_previous_total_balance(self):
'\n Used to get the previous total balance\n\n :return: Previous total balance\n :rtype: float\n '
if (('previousBalance' not in self.app_data) or (self.app_data['previousBalance'] == 0)):
return None
return self.app_data['previousBalance']<|docstring|>Used to get the previous total balance
:return: Previous total balance
:rtype: float<|endoftext|> |
004166a47a543804b705baa25a26267344a796f6d2efd8fe279a1e5350085567 | @staticmethod
def convert_bittrex_order_object(bittrex_order, stats=None):
'\n Used to convert a Bittrex order object to a database buy object\n and add stats to it of they are provided.\n\n :param bittrex_order: Bittrex buy order object\n :type bittrex_order: dict\n :param stats: The buy stats to store\n :type stats: dict\n '
database_order = {'orderUuid': bittrex_order['OrderUuid'], 'dateOpened': bittrex_order['Opened'], 'dateClosed': bittrex_order['Closed'], 'price': bittrex_order['Price'], 'unitPrice': bittrex_order['PricePerUnit'], 'commissionPaid': bittrex_order['CommissionPaid']}
if (stats is not None):
database_order['stats'] = stats
return database_order | Used to convert a Bittrex order object to a database buy object
and add stats to it of they are provided.
:param bittrex_order: Bittrex buy order object
:type bittrex_order: dict
:param stats: The buy stats to store
:type stats: dict | src/database.py | convert_bittrex_order_object | CryptoRye/Crypto-Trading-Bot | 301 | python | @staticmethod
def convert_bittrex_order_object(bittrex_order, stats=None):
'\n Used to convert a Bittrex order object to a database buy object\n and add stats to it of they are provided.\n\n :param bittrex_order: Bittrex buy order object\n :type bittrex_order: dict\n :param stats: The buy stats to store\n :type stats: dict\n '
database_order = {'orderUuid': bittrex_order['OrderUuid'], 'dateOpened': bittrex_order['Opened'], 'dateClosed': bittrex_order['Closed'], 'price': bittrex_order['Price'], 'unitPrice': bittrex_order['PricePerUnit'], 'commissionPaid': bittrex_order['CommissionPaid']}
if (stats is not None):
database_order['stats'] = stats
return database_order | @staticmethod
def convert_bittrex_order_object(bittrex_order, stats=None):
'\n Used to convert a Bittrex order object to a database buy object\n and add stats to it of they are provided.\n\n :param bittrex_order: Bittrex buy order object\n :type bittrex_order: dict\n :param stats: The buy stats to store\n :type stats: dict\n '
database_order = {'orderUuid': bittrex_order['OrderUuid'], 'dateOpened': bittrex_order['Opened'], 'dateClosed': bittrex_order['Closed'], 'price': bittrex_order['Price'], 'unitPrice': bittrex_order['PricePerUnit'], 'commissionPaid': bittrex_order['CommissionPaid']}
if (stats is not None):
database_order['stats'] = stats
return database_order<|docstring|>Used to convert a Bittrex order object to a database buy object
and add stats to it of they are provided.
:param bittrex_order: Bittrex buy order object
:type bittrex_order: dict
:param stats: The buy stats to store
:type stats: dict<|endoftext|> |
dfb8c2941339752acaeaa072aeceffcc295712c55b7a68ca2d9310509ad1a23c | def get_objective(self, coeff=1):
'\n Objective function of the Photovoltaic.\n\n Return the objective function of the photovoltaic weighted\n with `coeff`. Depending on `self.force_renewables` leave objective\n function empty or build quadratic objective function to minimize\n discrepancy between available power and produced power.\n\n Parameters\n ----------\n coeff : float, optional\n Coefficient for the objective function.\n\n Returns\n -------\n ExpressionBase :\n Objective function.\n '
m = self.model
s = pyomo.sum_product(m.p_el_vars, m.p_el_vars)
s += ((- 2) * pyomo.sum_product(self.p_el_supply[self.op_slice], m.p_el_vars))
return (coeff * s) | Objective function of the Photovoltaic.
Return the objective function of the photovoltaic weighted
with `coeff`. Depending on `self.force_renewables` leave objective
function empty or build quadratic objective function to minimize
discrepancy between available power and produced power.
Parameters
----------
coeff : float, optional
Coefficient for the objective function.
Returns
-------
ExpressionBase :
Objective function. | src/pycity_scheduling/classes/photovoltaic.py | get_objective | ElsevierSoftwareX/SOFTX-D-20-00087 | 4 | python | def get_objective(self, coeff=1):
'\n Objective function of the Photovoltaic.\n\n Return the objective function of the photovoltaic weighted\n with `coeff`. Depending on `self.force_renewables` leave objective\n function empty or build quadratic objective function to minimize\n discrepancy between available power and produced power.\n\n Parameters\n ----------\n coeff : float, optional\n Coefficient for the objective function.\n\n Returns\n -------\n ExpressionBase :\n Objective function.\n '
m = self.model
s = pyomo.sum_product(m.p_el_vars, m.p_el_vars)
s += ((- 2) * pyomo.sum_product(self.p_el_supply[self.op_slice], m.p_el_vars))
return (coeff * s) | def get_objective(self, coeff=1):
'\n Objective function of the Photovoltaic.\n\n Return the objective function of the photovoltaic weighted\n with `coeff`. Depending on `self.force_renewables` leave objective\n function empty or build quadratic objective function to minimize\n discrepancy between available power and produced power.\n\n Parameters\n ----------\n coeff : float, optional\n Coefficient for the objective function.\n\n Returns\n -------\n ExpressionBase :\n Objective function.\n '
m = self.model
s = pyomo.sum_product(m.p_el_vars, m.p_el_vars)
s += ((- 2) * pyomo.sum_product(self.p_el_supply[self.op_slice], m.p_el_vars))
return (coeff * s)<|docstring|>Objective function of the Photovoltaic.
Return the objective function of the photovoltaic weighted
with `coeff`. Depending on `self.force_renewables` leave objective
function empty or build quadratic objective function to minimize
discrepancy between available power and produced power.
Parameters
----------
coeff : float, optional
Coefficient for the objective function.
Returns
-------
ExpressionBase :
Objective function.<|endoftext|> |
4409a517bf63efae1ed77ffee6be90da4727a89545fa0e0063e7918769d1b9c0 | def commit_file(self, file_name, content):
'\n Commits a file specified by the file name and its content. If the file \n already exists, its content will be overwritten.\n\n The changes will be committed, thereby, a new SHA will be generated.\n \n :return: Itself (the branch)\n '
self._files.set_file_content(file_name, content)
self._commit()
return self | Commits a file specified by the file name and its content. If the file
already exists, its content will be overwritten.
The changes will be committed, thereby, a new SHA will be generated.
:return: Itself (the branch) | src/cicd_sim/git/branch.py | commit_file | Software-Natives-OSS/cicd_sim | 0 | python | def commit_file(self, file_name, content):
'\n Commits a file specified by the file name and its content. If the file \n already exists, its content will be overwritten.\n\n The changes will be committed, thereby, a new SHA will be generated.\n \n :return: Itself (the branch)\n '
self._files.set_file_content(file_name, content)
self._commit()
return self | def commit_file(self, file_name, content):
'\n Commits a file specified by the file name and its content. If the file \n already exists, its content will be overwritten.\n\n The changes will be committed, thereby, a new SHA will be generated.\n \n :return: Itself (the branch)\n '
self._files.set_file_content(file_name, content)
self._commit()
return self<|docstring|>Commits a file specified by the file name and its content. If the file
already exists, its content will be overwritten.
The changes will be committed, thereby, a new SHA will be generated.
:return: Itself (the branch)<|endoftext|> |
752997ced248a84e6e9adb9f8d76961558884b2f1c94b2a1aeb05cbf3cde93ba | def set_version(self, version):
"Set the project version\n\n :version: A string denoting a semver.org version. E.g. '1.2.3-pre.0+20200313'\n \n Technically, this function commits a file named 'VERSION' as this CICD\n simulator expects an according file to determine the project version.\n "
self.commit_file('VERSION', version) | Set the project version
:version: A string denoting a semver.org version. E.g. '1.2.3-pre.0+20200313'
Technically, this function commits a file named 'VERSION' as this CICD
simulator expects an according file to determine the project version. | src/cicd_sim/git/branch.py | set_version | Software-Natives-OSS/cicd_sim | 0 | python | def set_version(self, version):
"Set the project version\n\n :version: A string denoting a semver.org version. E.g. '1.2.3-pre.0+20200313'\n \n Technically, this function commits a file named 'VERSION' as this CICD\n simulator expects an according file to determine the project version.\n "
self.commit_file('VERSION', version) | def set_version(self, version):
"Set the project version\n\n :version: A string denoting a semver.org version. E.g. '1.2.3-pre.0+20200313'\n \n Technically, this function commits a file named 'VERSION' as this CICD\n simulator expects an according file to determine the project version.\n "
self.commit_file('VERSION', version)<|docstring|>Set the project version
:version: A string denoting a semver.org version. E.g. '1.2.3-pre.0+20200313'
Technically, this function commits a file named 'VERSION' as this CICD
simulator expects an according file to determine the project version.<|endoftext|> |
134a17aeb54535959183d7d614740558988f98c40a2ab161fc78019915fb2f29 | def set_requires(self, requires):
"Set the project requires (AKA dependencies)\n\n :requires: A string composed of the required package and the required \n semver version or version range delimited by a slash ('/'). \n E.g. 'lib/1.2.4', 'libA/1.x' or even 'lib/>1.0.0.0-0 <2.0.0'\n \n Technically, this function commits a file named 'REQUIRES' as this CICD\n simulator expects an according file to determine the projects \n requirements.\n "
self.commit_file('REQUIRES', requires) | Set the project requires (AKA dependencies)
:requires: A string composed of the required package and the required
semver version or version range delimited by a slash ('/').
E.g. 'lib/1.2.4', 'libA/1.x' or even 'lib/>1.0.0.0-0 <2.0.0'
Technically, this function commits a file named 'REQUIRES' as this CICD
simulator expects an according file to determine the projects
requirements. | src/cicd_sim/git/branch.py | set_requires | Software-Natives-OSS/cicd_sim | 0 | python | def set_requires(self, requires):
"Set the project requires (AKA dependencies)\n\n :requires: A string composed of the required package and the required \n semver version or version range delimited by a slash ('/'). \n E.g. 'lib/1.2.4', 'libA/1.x' or even 'lib/>1.0.0.0-0 <2.0.0'\n \n Technically, this function commits a file named 'REQUIRES' as this CICD\n simulator expects an according file to determine the projects \n requirements.\n "
self.commit_file('REQUIRES', requires) | def set_requires(self, requires):
"Set the project requires (AKA dependencies)\n\n :requires: A string composed of the required package and the required \n semver version or version range delimited by a slash ('/'). \n E.g. 'lib/1.2.4', 'libA/1.x' or even 'lib/>1.0.0.0-0 <2.0.0'\n \n Technically, this function commits a file named 'REQUIRES' as this CICD\n simulator expects an according file to determine the projects \n requirements.\n "
self.commit_file('REQUIRES', requires)<|docstring|>Set the project requires (AKA dependencies)
:requires: A string composed of the required package and the required
semver version or version range delimited by a slash ('/').
E.g. 'lib/1.2.4', 'libA/1.x' or even 'lib/>1.0.0.0-0 <2.0.0'
Technically, this function commits a file named 'REQUIRES' as this CICD
simulator expects an according file to determine the projects
requirements.<|endoftext|> |
13b21a67cbfc4eeeb9a689d2f2b566c094695ca12a2853c23a96bcce57d34e24 | def __init__(self):
'Capability - a model defined in Swagger'
self.discriminator = None | Capability - a model defined in Swagger | vtpl_api/models/capability.py | __init__ | vtpl1/videonetics_api | 0 | python | def __init__(self):
self.discriminator = None | def __init__(self):
self.discriminator = None<|docstring|>Capability - a model defined in Swagger<|endoftext|> |
7d0220f1bd8b5050af2a8f4e507bde8aa569c4e58583a1e463192c83aeaaf671 | def to_dict(self):
'Returns the model properties as a dict'
result = {}
for (attr, _) in six.iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map((lambda item: ((item[0], item[1].to_dict()) if hasattr(item[1], 'to_dict') else item)), value.items()))
else:
result[attr] = value
if issubclass(Capability, dict):
for (key, value) in self.items():
result[key] = value
return result | Returns the model properties as a dict | vtpl_api/models/capability.py | to_dict | vtpl1/videonetics_api | 0 | python | def to_dict(self):
result = {}
for (attr, _) in six.iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map((lambda item: ((item[0], item[1].to_dict()) if hasattr(item[1], 'to_dict') else item)), value.items()))
else:
result[attr] = value
if issubclass(Capability, dict):
for (key, value) in self.items():
result[key] = value
return result | def to_dict(self):
result = {}
for (attr, _) in six.iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map((lambda item: ((item[0], item[1].to_dict()) if hasattr(item[1], 'to_dict') else item)), value.items()))
else:
result[attr] = value
if issubclass(Capability, dict):
for (key, value) in self.items():
result[key] = value
return result<|docstring|>Returns the model properties as a dict<|endoftext|> |
cbb19eaa2fc8a113d9e32f924ef280a7e97563f8915f94f65dab438997af2e99 | def to_str(self):
'Returns the string representation of the model'
return pprint.pformat(self.to_dict()) | Returns the string representation of the model | vtpl_api/models/capability.py | to_str | vtpl1/videonetics_api | 0 | python | def to_str(self):
return pprint.pformat(self.to_dict()) | def to_str(self):
return pprint.pformat(self.to_dict())<|docstring|>Returns the string representation of the model<|endoftext|> |
772243a2c2b3261a9b954d07aaf295e3c1242a579a495e2d6a5679c677861703 | def __repr__(self):
'For `print` and `pprint`'
return self.to_str() | For `print` and `pprint` | vtpl_api/models/capability.py | __repr__ | vtpl1/videonetics_api | 0 | python | def __repr__(self):
return self.to_str() | def __repr__(self):
return self.to_str()<|docstring|>For `print` and `pprint`<|endoftext|> |
2a58b1f67871e4f170f1ca8cfdf3701648ca338cc86d4032fe908c2e9db7cacb | def __eq__(self, other):
'Returns true if both objects are equal'
if (not isinstance(other, Capability)):
return False
return (self.__dict__ == other.__dict__) | Returns true if both objects are equal | vtpl_api/models/capability.py | __eq__ | vtpl1/videonetics_api | 0 | python | def __eq__(self, other):
if (not isinstance(other, Capability)):
return False
return (self.__dict__ == other.__dict__) | def __eq__(self, other):
if (not isinstance(other, Capability)):
return False
return (self.__dict__ == other.__dict__)<|docstring|>Returns true if both objects are equal<|endoftext|> |
43dc6740163eb9fc1161d09cb2208a64c7ad0cc8d9c8637ac3264522d3ec7e42 | def __ne__(self, other):
'Returns true if both objects are not equal'
return (not (self == other)) | Returns true if both objects are not equal | vtpl_api/models/capability.py | __ne__ | vtpl1/videonetics_api | 0 | python | def __ne__(self, other):
return (not (self == other)) | def __ne__(self, other):
return (not (self == other))<|docstring|>Returns true if both objects are not equal<|endoftext|> |
909bf60d6b8c4295f5bf849bcf5e78546f338fe4fa1af75ad961cea576959557 | def test_run_with_save_version_as_run_id(self, mocker, dummy_context, dummy_dataframe, caplog):
'Test that the default behaviour, with run_id set to None,\n creates a journal record with the run_id the same as save_version.\n '
save_version = '2020-01-01T00.00.00.000Z'
mocked_get_save_version = mocker.patch.object(dummy_context, '_get_save_version', return_value=save_version)
dummy_context.catalog.save('cars', dummy_dataframe)
dummy_context.run(load_versions={'boats': save_version})
mocked_get_save_version.assert_called_once_with()
log_msg = next((record.getMessage() for record in caplog.records if (record.name == 'kedro.journal')))
assert (json.loads(log_msg)['run_id'] == save_version) | Test that the default behaviour, with run_id set to None,
creates a journal record with the run_id the same as save_version. | tests/framework/context/test_context.py | test_run_with_save_version_as_run_id | juan-carlos-calvo/kedro | 4,923 | python | def test_run_with_save_version_as_run_id(self, mocker, dummy_context, dummy_dataframe, caplog):
'Test that the default behaviour, with run_id set to None,\n creates a journal record with the run_id the same as save_version.\n '
save_version = '2020-01-01T00.00.00.000Z'
mocked_get_save_version = mocker.patch.object(dummy_context, '_get_save_version', return_value=save_version)
dummy_context.catalog.save('cars', dummy_dataframe)
dummy_context.run(load_versions={'boats': save_version})
mocked_get_save_version.assert_called_once_with()
log_msg = next((record.getMessage() for record in caplog.records if (record.name == 'kedro.journal')))
assert (json.loads(log_msg)['run_id'] == save_version) | def test_run_with_save_version_as_run_id(self, mocker, dummy_context, dummy_dataframe, caplog):
'Test that the default behaviour, with run_id set to None,\n creates a journal record with the run_id the same as save_version.\n '
save_version = '2020-01-01T00.00.00.000Z'
mocked_get_save_version = mocker.patch.object(dummy_context, '_get_save_version', return_value=save_version)
dummy_context.catalog.save('cars', dummy_dataframe)
dummy_context.run(load_versions={'boats': save_version})
mocked_get_save_version.assert_called_once_with()
log_msg = next((record.getMessage() for record in caplog.records if (record.name == 'kedro.journal')))
assert (json.loads(log_msg)['run_id'] == save_version)<|docstring|>Test that the default behaviour, with run_id set to None,
creates a journal record with the run_id the same as save_version.<|endoftext|> |
cd05a349769a26a012100fc223198819acfe9a7c9e112e2ec048e201f9cecb94 | def pad_omni_image(image, pad_size, image_dims=None):
'\n Pad an omni-directional image with the correct image wrapping at the edges.\n\n :param image: Image to perform the padding on *[batch_shape,h,w,d]*\n :type image: array\n :param pad_size: Number of pixels to pad.\n :type pad_size: int\n :param image_dims: Image dimensions. Inferred from Inputs if None.\n :type image_dims: sequence of ints, optional\n :return: New padded omni-directional image *[batch_shape,h+ps,w+ps,d]*\n '
if (image_dims is None):
image_dims = image.shape[(- 3):(- 1)]
top_left = image[(..., 0:pad_size, int((image_dims[1] / 2)):, :)]
top_right = image[(..., 0:pad_size, 0:int((image_dims[1] / 2)), :)]
top_border = _ivy.flip(_ivy.concatenate((top_left, top_right), (- 2)), (- 3))
bottom_left = image[(..., (- pad_size):, int((image_dims[1] / 2)):, :)]
bottom_right = image[(..., (- pad_size):, 0:int((image_dims[1] / 2)), :)]
bottom_border = _ivy.flip(_ivy.concatenate((bottom_left, bottom_right), (- 2)), (- 3))
image_expanded = _ivy.concatenate((top_border, image, bottom_border), (- 3))
left_border = image_expanded[(..., (- pad_size):, :)]
right_border = image_expanded[(..., 0:pad_size, :)]
return _ivy.concatenate((left_border, image_expanded, right_border), (- 2)) | Pad an omni-directional image with the correct image wrapping at the edges.
:param image: Image to perform the padding on *[batch_shape,h,w,d]*
:type image: array
:param pad_size: Number of pixels to pad.
:type pad_size: int
:param image_dims: Image dimensions. Inferred from Inputs if None.
:type image_dims: sequence of ints, optional
:return: New padded omni-directional image *[batch_shape,h+ps,w+ps,d]* | ivy_vision/padding.py | pad_omni_image | ivy-dl/vision | 35 | python | def pad_omni_image(image, pad_size, image_dims=None):
'\n Pad an omni-directional image with the correct image wrapping at the edges.\n\n :param image: Image to perform the padding on *[batch_shape,h,w,d]*\n :type image: array\n :param pad_size: Number of pixels to pad.\n :type pad_size: int\n :param image_dims: Image dimensions. Inferred from Inputs if None.\n :type image_dims: sequence of ints, optional\n :return: New padded omni-directional image *[batch_shape,h+ps,w+ps,d]*\n '
if (image_dims is None):
image_dims = image.shape[(- 3):(- 1)]
top_left = image[(..., 0:pad_size, int((image_dims[1] / 2)):, :)]
top_right = image[(..., 0:pad_size, 0:int((image_dims[1] / 2)), :)]
top_border = _ivy.flip(_ivy.concatenate((top_left, top_right), (- 2)), (- 3))
bottom_left = image[(..., (- pad_size):, int((image_dims[1] / 2)):, :)]
bottom_right = image[(..., (- pad_size):, 0:int((image_dims[1] / 2)), :)]
bottom_border = _ivy.flip(_ivy.concatenate((bottom_left, bottom_right), (- 2)), (- 3))
image_expanded = _ivy.concatenate((top_border, image, bottom_border), (- 3))
left_border = image_expanded[(..., (- pad_size):, :)]
right_border = image_expanded[(..., 0:pad_size, :)]
return _ivy.concatenate((left_border, image_expanded, right_border), (- 2)) | def pad_omni_image(image, pad_size, image_dims=None):
'\n Pad an omni-directional image with the correct image wrapping at the edges.\n\n :param image: Image to perform the padding on *[batch_shape,h,w,d]*\n :type image: array\n :param pad_size: Number of pixels to pad.\n :type pad_size: int\n :param image_dims: Image dimensions. Inferred from Inputs if None.\n :type image_dims: sequence of ints, optional\n :return: New padded omni-directional image *[batch_shape,h+ps,w+ps,d]*\n '
if (image_dims is None):
image_dims = image.shape[(- 3):(- 1)]
top_left = image[(..., 0:pad_size, int((image_dims[1] / 2)):, :)]
top_right = image[(..., 0:pad_size, 0:int((image_dims[1] / 2)), :)]
top_border = _ivy.flip(_ivy.concatenate((top_left, top_right), (- 2)), (- 3))
bottom_left = image[(..., (- pad_size):, int((image_dims[1] / 2)):, :)]
bottom_right = image[(..., (- pad_size):, 0:int((image_dims[1] / 2)), :)]
bottom_border = _ivy.flip(_ivy.concatenate((bottom_left, bottom_right), (- 2)), (- 3))
image_expanded = _ivy.concatenate((top_border, image, bottom_border), (- 3))
left_border = image_expanded[(..., (- pad_size):, :)]
right_border = image_expanded[(..., 0:pad_size, :)]
return _ivy.concatenate((left_border, image_expanded, right_border), (- 2))<|docstring|>Pad an omni-directional image with the correct image wrapping at the edges.
:param image: Image to perform the padding on *[batch_shape,h,w,d]*
:type image: array
:param pad_size: Number of pixels to pad.
:type pad_size: int
:param image_dims: Image dimensions. Inferred from Inputs if None.
:type image_dims: sequence of ints, optional
:return: New padded omni-directional image *[batch_shape,h+ps,w+ps,d]*<|endoftext|> |
c160ad1c266e099415edd7f0d3c5d94053e7f71c853734de8142ea639b52af94 | def clones(module, N):
'Produce N identical layers.'
return nn.ModuleList([copy.deepcopy(module) for _ in range(N)]) | Produce N identical layers. | Model_Transformer/train_utils.py | clones | AnubhavGupta3377/Text-Classification-Models | 481 | python | def clones(module, N):
return nn.ModuleList([copy.deepcopy(module) for _ in range(N)]) | def clones(module, N):
return nn.ModuleList([copy.deepcopy(module) for _ in range(N)])<|docstring|>Produce N identical layers.<|endoftext|> |
ded32b216ffa5b61c215a606ee2b3cc1ba4bee532555b3430df520d520590fc6 | @staticmethod
def taking_int_input_from_user(msg_to_user):
'\n [summary]\n Taking an int input from the user (checks if legal input -> num: int)\n\n Arguments:\n msg_to_user {[str]} -- [message to print to the user]\n '
is_correct = False
while (not is_correct):
try:
num_from_user = int(input(msg_to_user))
if (num_from_user <= 0):
raise ValueError
is_correct = True
except:
print('Please enter a LEGAL number (an integer).')
is_correct = False
return num_from_user | [summary]
Taking an int input from the user (checks if legal input -> num: int)
Arguments:
msg_to_user {[str]} -- [message to print to the user] | BlackJackGame/BlackJackGame.py | taking_int_input_from_user | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def taking_int_input_from_user(msg_to_user):
'\n [summary]\n Taking an int input from the user (checks if legal input -> num: int)\n\n Arguments:\n msg_to_user {[str]} -- [message to print to the user]\n '
is_correct = False
while (not is_correct):
try:
num_from_user = int(input(msg_to_user))
if (num_from_user <= 0):
raise ValueError
is_correct = True
except:
print('Please enter a LEGAL number (an integer).')
is_correct = False
return num_from_user | @staticmethod
def taking_int_input_from_user(msg_to_user):
'\n [summary]\n Taking an int input from the user (checks if legal input -> num: int)\n\n Arguments:\n msg_to_user {[str]} -- [message to print to the user]\n '
is_correct = False
while (not is_correct):
try:
num_from_user = int(input(msg_to_user))
if (num_from_user <= 0):
raise ValueError
is_correct = True
except:
print('Please enter a LEGAL number (an integer).')
is_correct = False
return num_from_user<|docstring|>[summary]
Taking an int input from the user (checks if legal input -> num: int)
Arguments:
msg_to_user {[str]} -- [message to print to the user]<|endoftext|> |
d44e214cf43e21dfd42296a5a32ae6641af15e75cc8e441cfdde6f60083223a8 | @staticmethod
def take_bet_from_player(player):
"\n [summary]\n Taking an input (int) from player. The input is the player's bet (with chips)\n\n Arguments:\n player {[Player]} -- [a reference to the player object, to check if the input is legal (if the player has enough chips)]\n "
is_correct = False
while (not is_correct):
try:
chips_to_bet = Game.taking_int_input_from_user('Please enter your bet (chips [integer]), considering your current chips balance: ')
if (chips_to_bet > player.chips.total_chips):
raise ValueError
else:
player.chips.make_bet(chips_to_bet)
is_correct = True
except:
print(f"You don't have enought chips, your have: ({player.chips.count_total_chips()}). Please enter a legal number of chips.")
is_correct = False
return chips_to_bet | [summary]
Taking an input (int) from player. The input is the player's bet (with chips)
Arguments:
player {[Player]} -- [a reference to the player object, to check if the input is legal (if the player has enough chips)] | BlackJackGame/BlackJackGame.py | take_bet_from_player | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def take_bet_from_player(player):
"\n [summary]\n Taking an input (int) from player. The input is the player's bet (with chips)\n\n Arguments:\n player {[Player]} -- [a reference to the player object, to check if the input is legal (if the player has enough chips)]\n "
is_correct = False
while (not is_correct):
try:
chips_to_bet = Game.taking_int_input_from_user('Please enter your bet (chips [integer]), considering your current chips balance: ')
if (chips_to_bet > player.chips.total_chips):
raise ValueError
else:
player.chips.make_bet(chips_to_bet)
is_correct = True
except:
print(f"You don't have enought chips, your have: ({player.chips.count_total_chips()}). Please enter a legal number of chips.")
is_correct = False
return chips_to_bet | @staticmethod
def take_bet_from_player(player):
"\n [summary]\n Taking an input (int) from player. The input is the player's bet (with chips)\n\n Arguments:\n player {[Player]} -- [a reference to the player object, to check if the input is legal (if the player has enough chips)]\n "
is_correct = False
while (not is_correct):
try:
chips_to_bet = Game.taking_int_input_from_user('Please enter your bet (chips [integer]), considering your current chips balance: ')
if (chips_to_bet > player.chips.total_chips):
raise ValueError
else:
player.chips.make_bet(chips_to_bet)
is_correct = True
except:
print(f"You don't have enought chips, your have: ({player.chips.count_total_chips()}). Please enter a legal number of chips.")
is_correct = False
return chips_to_bet<|docstring|>[summary]
Taking an input (int) from player. The input is the player's bet (with chips)
Arguments:
player {[Player]} -- [a reference to the player object, to check if the input is legal (if the player has enough chips)]<|endoftext|> |
ff1bf5b21705f43998530eed38566febecd30f831fcacf64af952d6eb070d369 | @staticmethod
def player_hit(player, dealer):
"\n [summary]\n Hitting (adding) new card to the player's hand from the dealer's deck\n\n Arguments:\n player {[Player]} -- [a reference to a player object, to add the card to his hand]\n dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to the player from his deck]\n "
player.hand.add_new_card(dealer)
player.hand.adjust_for_ace() | [summary]
Hitting (adding) new card to the player's hand from the dealer's deck
Arguments:
player {[Player]} -- [a reference to a player object, to add the card to his hand]
dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to the player from his deck] | BlackJackGame/BlackJackGame.py | player_hit | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def player_hit(player, dealer):
"\n [summary]\n Hitting (adding) new card to the player's hand from the dealer's deck\n\n Arguments:\n player {[Player]} -- [a reference to a player object, to add the card to his hand]\n dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to the player from his deck]\n "
player.hand.add_new_card(dealer)
player.hand.adjust_for_ace() | @staticmethod
def player_hit(player, dealer):
"\n [summary]\n Hitting (adding) new card to the player's hand from the dealer's deck\n\n Arguments:\n player {[Player]} -- [a reference to a player object, to add the card to his hand]\n dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to the player from his deck]\n "
player.hand.add_new_card(dealer)
player.hand.adjust_for_ace()<|docstring|>[summary]
Hitting (adding) new card to the player's hand from the dealer's deck
Arguments:
player {[Player]} -- [a reference to a player object, to add the card to his hand]
dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to the player from his deck]<|endoftext|> |
254ae775eb2c85da216c9c36e2ea25a9d408cd780e87bbc67d81214120f4cec9 | @staticmethod
def dealer_hit(dealer):
"\n [summary]\n Hitting (adding) new card to the dealer's hand from its deck\n\n Arguments:\n dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to its hand from its deck]\n "
dealer.hand.add_new_card(dealer)
dealer.hand.adjust_for_ace() | [summary]
Hitting (adding) new card to the dealer's hand from its deck
Arguments:
dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to its hand from its deck] | BlackJackGame/BlackJackGame.py | dealer_hit | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def dealer_hit(dealer):
"\n [summary]\n Hitting (adding) new card to the dealer's hand from its deck\n\n Arguments:\n dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to its hand from its deck]\n "
dealer.hand.add_new_card(dealer)
dealer.hand.adjust_for_ace() | @staticmethod
def dealer_hit(dealer):
"\n [summary]\n Hitting (adding) new card to the dealer's hand from its deck\n\n Arguments:\n dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to its hand from its deck]\n "
dealer.hand.add_new_card(dealer)
dealer.hand.adjust_for_ace()<|docstring|>[summary]
Hitting (adding) new card to the dealer's hand from its deck
Arguments:
dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to its hand from its deck]<|endoftext|> |
c15a82612a7137167a7c8748d82d3219b1531119cb5eed97e700ca8dbbe29d17 | @staticmethod
def player_hit_or_stand(player, dealer):
'\n [summary]\n Ask the player to choose between Hit or Stand (Hit -> add new card to his hand, Stand -> stand with his cards)\n If the player choose to Hit -> using player_hit() method with the references of the player and the dealer\n\n Arguments:\n player {[Player]} -- [a reference to a player object, to add the card to his hand - if the player choose to hit]\n dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to the player from his deck if the player choose to hit]\n '
print('Please enter your next move: ')
is_correct = False
while (not is_correct):
try:
answer_from_user = input("Do you want to Hit or Stand? Enter 'H'/'h' to Hit, or 'S'/'s' to Stand: ")
if ((answer_from_user == 'H') or 'h' or 'S' or 's'):
if ((answer_from_user == 'H') or 'h'):
print(f'{player} Hits!')
player_hit(player, dealer)
is_correct = True
elif ((answer_from_user == 'S') or 's'):
print(f'''{player} Stands.
The Dealer's Turn.''')
Game.is_player_turn = False
is_correct = True
else:
raise ValueError
except:
print('Wrong input, please try again.')
is_correct = False | [summary]
Ask the player to choose between Hit or Stand (Hit -> add new card to his hand, Stand -> stand with his cards)
If the player choose to Hit -> using player_hit() method with the references of the player and the dealer
Arguments:
player {[Player]} -- [a reference to a player object, to add the card to his hand - if the player choose to hit]
dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to the player from his deck if the player choose to hit] | BlackJackGame/BlackJackGame.py | player_hit_or_stand | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def player_hit_or_stand(player, dealer):
'\n [summary]\n Ask the player to choose between Hit or Stand (Hit -> add new card to his hand, Stand -> stand with his cards)\n If the player choose to Hit -> using player_hit() method with the references of the player and the dealer\n\n Arguments:\n player {[Player]} -- [a reference to a player object, to add the card to his hand - if the player choose to hit]\n dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to the player from his deck if the player choose to hit]\n '
print('Please enter your next move: ')
is_correct = False
while (not is_correct):
try:
answer_from_user = input("Do you want to Hit or Stand? Enter 'H'/'h' to Hit, or 'S'/'s' to Stand: ")
if ((answer_from_user == 'H') or 'h' or 'S' or 's'):
if ((answer_from_user == 'H') or 'h'):
print(f'{player} Hits!')
player_hit(player, dealer)
is_correct = True
elif ((answer_from_user == 'S') or 's'):
print(f'{player} Stands.
The Dealer's Turn.')
Game.is_player_turn = False
is_correct = True
else:
raise ValueError
except:
print('Wrong input, please try again.')
is_correct = False | @staticmethod
def player_hit_or_stand(player, dealer):
'\n [summary]\n Ask the player to choose between Hit or Stand (Hit -> add new card to his hand, Stand -> stand with his cards)\n If the player choose to Hit -> using player_hit() method with the references of the player and the dealer\n\n Arguments:\n player {[Player]} -- [a reference to a player object, to add the card to his hand - if the player choose to hit]\n dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to the player from his deck if the player choose to hit]\n '
print('Please enter your next move: ')
is_correct = False
while (not is_correct):
try:
answer_from_user = input("Do you want to Hit or Stand? Enter 'H'/'h' to Hit, or 'S'/'s' to Stand: ")
if ((answer_from_user == 'H') or 'h' or 'S' or 's'):
if ((answer_from_user == 'H') or 'h'):
print(f'{player} Hits!')
player_hit(player, dealer)
is_correct = True
elif ((answer_from_user == 'S') or 's'):
print(f'{player} Stands.
The Dealer's Turn.')
Game.is_player_turn = False
is_correct = True
else:
raise ValueError
except:
print('Wrong input, please try again.')
is_correct = False<|docstring|>[summary]
Ask the player to choose between Hit or Stand (Hit -> add new card to his hand, Stand -> stand with his cards)
If the player choose to Hit -> using player_hit() method with the references of the player and the dealer
Arguments:
player {[Player]} -- [a reference to a player object, to add the card to his hand - if the player choose to hit]
dealer {[ComputerDealer]} -- [a reference to a dealer object, to add the card to the player from his deck if the player choose to hit]<|endoftext|> |
3658dea471c192ee45f8b7c3b7329bef4d2116014623c6e642e8dd465aa64259 | @staticmethod
def player_bust(player):
'\n [summary]\n The player busted -> have to decrease his chips that was in the current bet (because of the lose)\n\n Arguments:\n player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]\n '
print(f'{player} BUST!')
player.chips.losing_bet() | [summary]
The player busted -> have to decrease his chips that was in the current bet (because of the lose)
Arguments:
player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it] | BlackJackGame/BlackJackGame.py | player_bust | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def player_bust(player):
'\n [summary]\n The player busted -> have to decrease his chips that was in the current bet (because of the lose)\n\n Arguments:\n player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]\n '
print(f'{player} BUST!')
player.chips.losing_bet() | @staticmethod
def player_bust(player):
'\n [summary]\n The player busted -> have to decrease his chips that was in the current bet (because of the lose)\n\n Arguments:\n player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]\n '
print(f'{player} BUST!')
player.chips.losing_bet()<|docstring|>[summary]
The player busted -> have to decrease his chips that was in the current bet (because of the lose)
Arguments:
player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]<|endoftext|> |
7e30cdcaed3e44503e4142e321c5aae58f5646a0a626edc681f4603a5fd77ae1 | @staticmethod
def player_wins(player):
'\n [summary]\n The player wins -> have to increase his chips that was in the current bet (because of the win)\n\n Arguments:\n player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]\n '
print(f'{player} WINS!')
player.chips.winning_bet() | [summary]
The player wins -> have to increase his chips that was in the current bet (because of the win)
Arguments:
player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it] | BlackJackGame/BlackJackGame.py | player_wins | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def player_wins(player):
'\n [summary]\n The player wins -> have to increase his chips that was in the current bet (because of the win)\n\n Arguments:\n player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]\n '
print(f'{player} WINS!')
player.chips.winning_bet() | @staticmethod
def player_wins(player):
'\n [summary]\n The player wins -> have to increase his chips that was in the current bet (because of the win)\n\n Arguments:\n player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]\n '
print(f'{player} WINS!')
player.chips.winning_bet()<|docstring|>[summary]
The player wins -> have to increase his chips that was in the current bet (because of the win)
Arguments:
player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]<|endoftext|> |
c51da68ec4999cb2e13559df5a4079a15b596c0a8e4cdcf74a2c1e51686d0e8c | @staticmethod
def dealer_bust(player, dealer):
"\n [summary]\n The dealer bust so the player wins -> have to increase the player's chips that was in the current bet (because of the lose of the dealer)\n\n Arguments:\n player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]\n dealer {[ComputerDealer]} -- [a reference to the dealer to use its name]\n "
print(f'''{player} WINS!
{dealer} BUSTED!''')
player.chips.winning_bet() | [summary]
The dealer bust so the player wins -> have to increase the player's chips that was in the current bet (because of the lose of the dealer)
Arguments:
player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]
dealer {[ComputerDealer]} -- [a reference to the dealer to use its name] | BlackJackGame/BlackJackGame.py | dealer_bust | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def dealer_bust(player, dealer):
"\n [summary]\n The dealer bust so the player wins -> have to increase the player's chips that was in the current bet (because of the lose of the dealer)\n\n Arguments:\n player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]\n dealer {[ComputerDealer]} -- [a reference to the dealer to use its name]\n "
print(f'{player} WINS!
{dealer} BUSTED!')
player.chips.winning_bet() | @staticmethod
def dealer_bust(player, dealer):
"\n [summary]\n The dealer bust so the player wins -> have to increase the player's chips that was in the current bet (because of the lose of the dealer)\n\n Arguments:\n player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]\n dealer {[ComputerDealer]} -- [a reference to the dealer to use its name]\n "
print(f'{player} WINS!
{dealer} BUSTED!')
player.chips.winning_bet()<|docstring|>[summary]
The dealer bust so the player wins -> have to increase the player's chips that was in the current bet (because of the lose of the dealer)
Arguments:
player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]
dealer {[ComputerDealer]} -- [a reference to the dealer to use its name]<|endoftext|> |
af6891c743e836141d52f0eb41278661c77cc855794ee21210f4c4ad7518f4f1 | @staticmethod
def dealer_wins(player, dealer):
"\n [summary]\n The dealer wins so the player loses -> have to decrease the player's chips that was in the current bet (because of the win of the dealer)\n\n Arguments:\n player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]\n dealer {[ComputerDealer]} -- [a reference to the dealer to use its name]\n "
print(f'{dealer} WINS!')
player.chips.losing_bet() | [summary]
The dealer wins so the player loses -> have to decrease the player's chips that was in the current bet (because of the win of the dealer)
Arguments:
player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]
dealer {[ComputerDealer]} -- [a reference to the dealer to use its name] | BlackJackGame/BlackJackGame.py | dealer_wins | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def dealer_wins(player, dealer):
"\n [summary]\n The dealer wins so the player loses -> have to decrease the player's chips that was in the current bet (because of the win of the dealer)\n\n Arguments:\n player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]\n dealer {[ComputerDealer]} -- [a reference to the dealer to use its name]\n "
print(f'{dealer} WINS!')
player.chips.losing_bet() | @staticmethod
def dealer_wins(player, dealer):
"\n [summary]\n The dealer wins so the player loses -> have to decrease the player's chips that was in the current bet (because of the win of the dealer)\n\n Arguments:\n player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]\n dealer {[ComputerDealer]} -- [a reference to the dealer to use its name]\n "
print(f'{dealer} WINS!')
player.chips.losing_bet()<|docstring|>[summary]
The dealer wins so the player loses -> have to decrease the player's chips that was in the current bet (because of the win of the dealer)
Arguments:
player {[Player]} -- [a reference to the player (using its name) and to the chips object inside it]
dealer {[ComputerDealer]} -- [a reference to the dealer to use its name]<|endoftext|> |
2aa5c1485ada29951a20315351768c003ea11c2d6d7af3d98f7f19f6bc8286f6 | @staticmethod
def push(player, dealer):
'\n [summary]\n The player and the dealer tie -> push\n\n Arguments:\n player {[Player]} -- [a reference to the player to use its name]\n dealer {[ComputerDealer]} -- [a reference to the dealer to use its name]\n '
print(f'{player} and {dealer} tie! PUSH!') | [summary]
The player and the dealer tie -> push
Arguments:
player {[Player]} -- [a reference to the player to use its name]
dealer {[ComputerDealer]} -- [a reference to the dealer to use its name] | BlackJackGame/BlackJackGame.py | push | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def push(player, dealer):
'\n [summary]\n The player and the dealer tie -> push\n\n Arguments:\n player {[Player]} -- [a reference to the player to use its name]\n dealer {[ComputerDealer]} -- [a reference to the dealer to use its name]\n '
print(f'{player} and {dealer} tie! PUSH!') | @staticmethod
def push(player, dealer):
'\n [summary]\n The player and the dealer tie -> push\n\n Arguments:\n player {[Player]} -- [a reference to the player to use its name]\n dealer {[ComputerDealer]} -- [a reference to the dealer to use its name]\n '
print(f'{player} and {dealer} tie! PUSH!')<|docstring|>[summary]
The player and the dealer tie -> push
Arguments:
player {[Player]} -- [a reference to the player to use its name]
dealer {[ComputerDealer]} -- [a reference to the dealer to use its name]<|endoftext|> |
be8212d3074d0d182cf49979052a2223259f71a33666877f2cea438af2a78937 | @staticmethod
def ask_for_new_round():
'\n [summary]\n Asking the player to have a new round (with the same state as before [after the change in its chips at the end of the previous round])\n '
print('Please enter your choice: ')
is_correct = False
while (not is_correct):
try:
answer_from_user = input("Do you want to play another round (with the current chips you already have)? Enter 'Y'/'y' for 'Yes', or 'N'/'n' for 'No': ")
if ((answer_from_user == 'Y') or 'y' or 'N' or 'n'):
if ((answer_from_user == 'Y') or 'y'):
print('New round! \nGet ready!')
Game.game_state = True
is_correct = True
elif ((answer_from_user == 'N') or 'n'):
print('Thanks for playing!')
Game.game_state = False
is_correct = True
else:
raise ValueError
except:
print('Wrong input, please try again.')
is_correct = False | [summary]
Asking the player to have a new round (with the same state as before [after the change in its chips at the end of the previous round]) | BlackJackGame/BlackJackGame.py | ask_for_new_round | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def ask_for_new_round():
'\n [summary]\n Asking the player to have a new round (with the same state as before [after the change in its chips at the end of the previous round])\n '
print('Please enter your choice: ')
is_correct = False
while (not is_correct):
try:
answer_from_user = input("Do you want to play another round (with the current chips you already have)? Enter 'Y'/'y' for 'Yes', or 'N'/'n' for 'No': ")
if ((answer_from_user == 'Y') or 'y' or 'N' or 'n'):
if ((answer_from_user == 'Y') or 'y'):
print('New round! \nGet ready!')
Game.game_state = True
is_correct = True
elif ((answer_from_user == 'N') or 'n'):
print('Thanks for playing!')
Game.game_state = False
is_correct = True
else:
raise ValueError
except:
print('Wrong input, please try again.')
is_correct = False | @staticmethod
def ask_for_new_round():
'\n [summary]\n Asking the player to have a new round (with the same state as before [after the change in its chips at the end of the previous round])\n '
print('Please enter your choice: ')
is_correct = False
while (not is_correct):
try:
answer_from_user = input("Do you want to play another round (with the current chips you already have)? Enter 'Y'/'y' for 'Yes', or 'N'/'n' for 'No': ")
if ((answer_from_user == 'Y') or 'y' or 'N' or 'n'):
if ((answer_from_user == 'Y') or 'y'):
print('New round! \nGet ready!')
Game.game_state = True
is_correct = True
elif ((answer_from_user == 'N') or 'n'):
print('Thanks for playing!')
Game.game_state = False
is_correct = True
else:
raise ValueError
except:
print('Wrong input, please try again.')
is_correct = False<|docstring|>[summary]
Asking the player to have a new round (with the same state as before [after the change in its chips at the end of the previous round])<|endoftext|> |
e24db54b10d44aeb525e4090e3d507dc92963f083a3be236ba27837a1d085f71 | @staticmethod
def ask_to_restart_the_whole_game():
'\n [summary]\n Asking the player to restart the whole game (running Game.run() method again)\n '
print('Please enter your choice: ')
is_correct = False
while (not is_correct):
try:
answer_from_user = input("Would you like to restart the whole game? Enter 'Y'/'y' for 'Yes', or 'N'/'n' for 'No': ")
if ((answer_from_user == 'Y') or 'y' or 'N' or 'n'):
if ((answer_from_user == 'Y') or 'y'):
Game.game_state = True
is_correct = True
Game.run()
elif ((answer_from_user == 'N') or 'n'):
Game.game_state = False
is_correct = True
else:
raise ValueError
except:
print('Wrong input, please try again.')
is_correct = False | [summary]
Asking the player to restart the whole game (running Game.run() method again) | BlackJackGame/BlackJackGame.py | ask_to_restart_the_whole_game | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def ask_to_restart_the_whole_game():
'\n [summary]\n Asking the player to restart the whole game (running Game.run() method again)\n '
print('Please enter your choice: ')
is_correct = False
while (not is_correct):
try:
answer_from_user = input("Would you like to restart the whole game? Enter 'Y'/'y' for 'Yes', or 'N'/'n' for 'No': ")
if ((answer_from_user == 'Y') or 'y' or 'N' or 'n'):
if ((answer_from_user == 'Y') or 'y'):
Game.game_state = True
is_correct = True
Game.run()
elif ((answer_from_user == 'N') or 'n'):
Game.game_state = False
is_correct = True
else:
raise ValueError
except:
print('Wrong input, please try again.')
is_correct = False | @staticmethod
def ask_to_restart_the_whole_game():
'\n [summary]\n Asking the player to restart the whole game (running Game.run() method again)\n '
print('Please enter your choice: ')
is_correct = False
while (not is_correct):
try:
answer_from_user = input("Would you like to restart the whole game? Enter 'Y'/'y' for 'Yes', or 'N'/'n' for 'No': ")
if ((answer_from_user == 'Y') or 'y' or 'N' or 'n'):
if ((answer_from_user == 'Y') or 'y'):
Game.game_state = True
is_correct = True
Game.run()
elif ((answer_from_user == 'N') or 'n'):
Game.game_state = False
is_correct = True
else:
raise ValueError
except:
print('Wrong input, please try again.')
is_correct = False<|docstring|>[summary]
Asking the player to restart the whole game (running Game.run() method again)<|endoftext|> |
3d8cca51dad3daa86fde598b1f724dbbe00d41719b74f676d0abccf213d7fd0a | @staticmethod
def run():
'\n [summary]\n The main flow method of the game (Static class method -> No need Game() instance)\n '
print('This is a Console UI BlackJack Game.')
print('\n')
print("You are going to play against a Computer - 'The Dealer'.")
print('What is you name?')
name_of_player = str(input('Please enter you name: '))
print(f'Hello {name_of_player}!')
starting_chips = Game.taking_int_input_from_user('With how many chips do you want to start the game? ')
print('\n')
player = BlackJackGameBuilders.PlayerBuilder.build_player(name_of_player, starting_chips)
dealer = BlackJackGameBuilders.ComputerDealerBuilder.build_dealer()
dealer.deck.shuffle()
player.set_new_hand()
player.current_hand.add_new_card(dealer)
player.current_hand.add_new_card(dealer)
dealer.set_new_hand()
dealer.current_hand.add_new_card(dealer)
dealer.current_hand.add_new_card(dealer)
print(f'''Finally.....GAME IS ON!
Good Luck {player}!''')
while Game.game_state:
Game.is_player_turn = True
print(('\n' * 3))
current_player_bet = Game.take_bet_from_player(player)
print(f'Your bet is: {current_player_bet}.')
print('\n')
print(f'{player} has: ')
print(player.show_hand())
print('\n')
print(f'{dealer} has: ')
print(dealer.show_dealer_one_card())
while Game.is_player_turn:
Game.player_hit_or_stand(player, dealer)
print(f'{player} has: ')
print(player.show_hand())
print('\n')
print(f'{dealer} has: ')
print(dealer.show_dealer_one_card())
if (player.current_hand.value_of_cards_in_hand > 21):
Game.player_bust(player)
break
if (player.current_hand.value_of_cards_in_hand <= 21):
while (dealer.current_hand.value_of_cards_in_hand < 17):
Game.dealer_hit(dealer)
print(f'{player} has: ')
print(player.show_hand())
print('\n')
print(f'{dealer} has: ')
print(dealer.show_hand())
if (dealer.current_hand.value_of_cards_in_hand > 21):
Game.dealer_bust(player, dealer)
elif (dealer.current_hand.value_of_cards_in_hand > player.current_hand.value_of_cards_in_hand):
Game.dealer_wins(player, dealer)
elif (dealer.current_hand.value_of_cards_in_hand < player.current_hand.value_of_cards_in_hand):
Game.player_wins(player)
elif (dealer.current_hand.value_of_cards_in_hand == player.current_hand.value_of_cards_in_hand):
Game.push(player, dealer)
print('\n')
print(f'''
{player}'s {player.chips.count_total_chips}''')
if (player.chips.total_chips > 0):
Game.ask_for_new_round()
else:
Game.game_state = False
Game.ask_to_restart_the_whole_game() | [summary]
The main flow method of the game (Static class method -> No need Game() instance) | BlackJackGame/BlackJackGame.py | run | NatanMeirov/PythonMiniProjects | 0 | python | @staticmethod
def run():
'\n [summary]\n The main flow method of the game (Static class method -> No need Game() instance)\n '
print('This is a Console UI BlackJack Game.')
print('\n')
print("You are going to play against a Computer - 'The Dealer'.")
print('What is you name?')
name_of_player = str(input('Please enter you name: '))
print(f'Hello {name_of_player}!')
starting_chips = Game.taking_int_input_from_user('With how many chips do you want to start the game? ')
print('\n')
player = BlackJackGameBuilders.PlayerBuilder.build_player(name_of_player, starting_chips)
dealer = BlackJackGameBuilders.ComputerDealerBuilder.build_dealer()
dealer.deck.shuffle()
player.set_new_hand()
player.current_hand.add_new_card(dealer)
player.current_hand.add_new_card(dealer)
dealer.set_new_hand()
dealer.current_hand.add_new_card(dealer)
dealer.current_hand.add_new_card(dealer)
print(f'Finally.....GAME IS ON!
Good Luck {player}!')
while Game.game_state:
Game.is_player_turn = True
print(('\n' * 3))
current_player_bet = Game.take_bet_from_player(player)
print(f'Your bet is: {current_player_bet}.')
print('\n')
print(f'{player} has: ')
print(player.show_hand())
print('\n')
print(f'{dealer} has: ')
print(dealer.show_dealer_one_card())
while Game.is_player_turn:
Game.player_hit_or_stand(player, dealer)
print(f'{player} has: ')
print(player.show_hand())
print('\n')
print(f'{dealer} has: ')
print(dealer.show_dealer_one_card())
if (player.current_hand.value_of_cards_in_hand > 21):
Game.player_bust(player)
break
if (player.current_hand.value_of_cards_in_hand <= 21):
while (dealer.current_hand.value_of_cards_in_hand < 17):
Game.dealer_hit(dealer)
print(f'{player} has: ')
print(player.show_hand())
print('\n')
print(f'{dealer} has: ')
print(dealer.show_hand())
if (dealer.current_hand.value_of_cards_in_hand > 21):
Game.dealer_bust(player, dealer)
elif (dealer.current_hand.value_of_cards_in_hand > player.current_hand.value_of_cards_in_hand):
Game.dealer_wins(player, dealer)
elif (dealer.current_hand.value_of_cards_in_hand < player.current_hand.value_of_cards_in_hand):
Game.player_wins(player)
elif (dealer.current_hand.value_of_cards_in_hand == player.current_hand.value_of_cards_in_hand):
Game.push(player, dealer)
print('\n')
print(f'
{player}'s {player.chips.count_total_chips}')
if (player.chips.total_chips > 0):
Game.ask_for_new_round()
else:
Game.game_state = False
Game.ask_to_restart_the_whole_game() | @staticmethod
def run():
'\n [summary]\n The main flow method of the game (Static class method -> No need Game() instance)\n '
print('This is a Console UI BlackJack Game.')
print('\n')
print("You are going to play against a Computer - 'The Dealer'.")
print('What is you name?')
name_of_player = str(input('Please enter you name: '))
print(f'Hello {name_of_player}!')
starting_chips = Game.taking_int_input_from_user('With how many chips do you want to start the game? ')
print('\n')
player = BlackJackGameBuilders.PlayerBuilder.build_player(name_of_player, starting_chips)
dealer = BlackJackGameBuilders.ComputerDealerBuilder.build_dealer()
dealer.deck.shuffle()
player.set_new_hand()
player.current_hand.add_new_card(dealer)
player.current_hand.add_new_card(dealer)
dealer.set_new_hand()
dealer.current_hand.add_new_card(dealer)
dealer.current_hand.add_new_card(dealer)
print(f'Finally.....GAME IS ON!
Good Luck {player}!')
while Game.game_state:
Game.is_player_turn = True
print(('\n' * 3))
current_player_bet = Game.take_bet_from_player(player)
print(f'Your bet is: {current_player_bet}.')
print('\n')
print(f'{player} has: ')
print(player.show_hand())
print('\n')
print(f'{dealer} has: ')
print(dealer.show_dealer_one_card())
while Game.is_player_turn:
Game.player_hit_or_stand(player, dealer)
print(f'{player} has: ')
print(player.show_hand())
print('\n')
print(f'{dealer} has: ')
print(dealer.show_dealer_one_card())
if (player.current_hand.value_of_cards_in_hand > 21):
Game.player_bust(player)
break
if (player.current_hand.value_of_cards_in_hand <= 21):
while (dealer.current_hand.value_of_cards_in_hand < 17):
Game.dealer_hit(dealer)
print(f'{player} has: ')
print(player.show_hand())
print('\n')
print(f'{dealer} has: ')
print(dealer.show_hand())
if (dealer.current_hand.value_of_cards_in_hand > 21):
Game.dealer_bust(player, dealer)
elif (dealer.current_hand.value_of_cards_in_hand > player.current_hand.value_of_cards_in_hand):
Game.dealer_wins(player, dealer)
elif (dealer.current_hand.value_of_cards_in_hand < player.current_hand.value_of_cards_in_hand):
Game.player_wins(player)
elif (dealer.current_hand.value_of_cards_in_hand == player.current_hand.value_of_cards_in_hand):
Game.push(player, dealer)
print('\n')
print(f'
{player}'s {player.chips.count_total_chips}')
if (player.chips.total_chips > 0):
Game.ask_for_new_round()
else:
Game.game_state = False
Game.ask_to_restart_the_whole_game()<|docstring|>[summary]
The main flow method of the game (Static class method -> No need Game() instance)<|endoftext|> |
cb3003656826937e67faf1d69a2326d699572f016195ab6d6a27a5138ddbd1e6 | def response_content(self, url, request):
' Fake HTTP responses for use with HTTMock in tests.\n '
(scheme, host, path, _, query, _) = urlparse(url.geturl())
tests_dirname = dirname(__file__)
if (host == 'fake-cwd.local'):
with open((tests_dirname + path), 'rb') as file:
(type, _) = mimetypes.guess_type(file.name)
return httmock.response(200, file.read(), headers={'Content-Type': type})
elif ((host, path) == ('www.ci.berkeley.ca.us', '/uploadedFiles/IT/GIS/Parcels.zip')):
with open(join(tests_dirname, 'data', 'us-ca-berkeley-excerpt.zip'), 'rb') as file:
return httmock.response(200, file.read(), headers={'Content-Type': 'application/octet-stream'})
elif ((host, path) == ('data.sfgov.org', '/download/kvej-w5kb/ZIPPED%20SHAPEFILE')):
return httmock.response(302, '', headers={'Location': 'http://apps.sfgov.org/datafiles/view.php?file=sfgis/eas_addresses_with_units.zip'})
elif ((host, path, query) == ('apps.sfgov.org', '/datafiles/view.php', 'file=sfgis/eas_addresses_with_units.zip')):
with open(join(tests_dirname, 'data', 'us-ca-san_francisco-excerpt.zip'), 'rb') as file:
return httmock.response(200, file.read(), headers={'Content-Type': 'application/download', 'Content-Disposition': 'attachment; filename=eas_addresses_with_units.zip;'})
elif ((host, path, query) == ('dcatlas.dcgis.dc.gov', '/catalog/download.asp', 'downloadID=2182&downloadTYPE=ESRI')):
return httmock.response(200, (b'FAKE' * 99), headers={'Content-Type': 'application/x-zip-compressed'})
elif ((host, path, query) == ('data.northcowichan.ca', '/DataBrowser/DownloadCsv', 'container=mncowichan&entitySet=PropertyReport&filter=NOFILTER')):
return httmock.response(200, (b'FAKE,FAKE\n' * 99), headers={'Content-Type': 'text/csv', 'Content-Disposition': 'attachment; filename=PropertyReport.csv'})
raise NotImplementedError(url.geturl()) | Fake HTTP responses for use with HTTMock in tests. | openaddr/tests/cache.py | response_content | geobrando/machine | 101 | python | def response_content(self, url, request):
' \n '
(scheme, host, path, _, query, _) = urlparse(url.geturl())
tests_dirname = dirname(__file__)
if (host == 'fake-cwd.local'):
with open((tests_dirname + path), 'rb') as file:
(type, _) = mimetypes.guess_type(file.name)
return httmock.response(200, file.read(), headers={'Content-Type': type})
elif ((host, path) == ('www.ci.berkeley.ca.us', '/uploadedFiles/IT/GIS/Parcels.zip')):
with open(join(tests_dirname, 'data', 'us-ca-berkeley-excerpt.zip'), 'rb') as file:
return httmock.response(200, file.read(), headers={'Content-Type': 'application/octet-stream'})
elif ((host, path) == ('data.sfgov.org', '/download/kvej-w5kb/ZIPPED%20SHAPEFILE')):
return httmock.response(302, , headers={'Location': 'http://apps.sfgov.org/datafiles/view.php?file=sfgis/eas_addresses_with_units.zip'})
elif ((host, path, query) == ('apps.sfgov.org', '/datafiles/view.php', 'file=sfgis/eas_addresses_with_units.zip')):
with open(join(tests_dirname, 'data', 'us-ca-san_francisco-excerpt.zip'), 'rb') as file:
return httmock.response(200, file.read(), headers={'Content-Type': 'application/download', 'Content-Disposition': 'attachment; filename=eas_addresses_with_units.zip;'})
elif ((host, path, query) == ('dcatlas.dcgis.dc.gov', '/catalog/download.asp', 'downloadID=2182&downloadTYPE=ESRI')):
return httmock.response(200, (b'FAKE' * 99), headers={'Content-Type': 'application/x-zip-compressed'})
elif ((host, path, query) == ('data.northcowichan.ca', '/DataBrowser/DownloadCsv', 'container=mncowichan&entitySet=PropertyReport&filter=NOFILTER')):
return httmock.response(200, (b'FAKE,FAKE\n' * 99), headers={'Content-Type': 'text/csv', 'Content-Disposition': 'attachment; filename=PropertyReport.csv'})
raise NotImplementedError(url.geturl()) | def response_content(self, url, request):
' \n '
(scheme, host, path, _, query, _) = urlparse(url.geturl())
tests_dirname = dirname(__file__)
if (host == 'fake-cwd.local'):
with open((tests_dirname + path), 'rb') as file:
(type, _) = mimetypes.guess_type(file.name)
return httmock.response(200, file.read(), headers={'Content-Type': type})
elif ((host, path) == ('www.ci.berkeley.ca.us', '/uploadedFiles/IT/GIS/Parcels.zip')):
with open(join(tests_dirname, 'data', 'us-ca-berkeley-excerpt.zip'), 'rb') as file:
return httmock.response(200, file.read(), headers={'Content-Type': 'application/octet-stream'})
elif ((host, path) == ('data.sfgov.org', '/download/kvej-w5kb/ZIPPED%20SHAPEFILE')):
return httmock.response(302, , headers={'Location': 'http://apps.sfgov.org/datafiles/view.php?file=sfgis/eas_addresses_with_units.zip'})
elif ((host, path, query) == ('apps.sfgov.org', '/datafiles/view.php', 'file=sfgis/eas_addresses_with_units.zip')):
with open(join(tests_dirname, 'data', 'us-ca-san_francisco-excerpt.zip'), 'rb') as file:
return httmock.response(200, file.read(), headers={'Content-Type': 'application/download', 'Content-Disposition': 'attachment; filename=eas_addresses_with_units.zip;'})
elif ((host, path, query) == ('dcatlas.dcgis.dc.gov', '/catalog/download.asp', 'downloadID=2182&downloadTYPE=ESRI')):
return httmock.response(200, (b'FAKE' * 99), headers={'Content-Type': 'application/x-zip-compressed'})
elif ((host, path, query) == ('data.northcowichan.ca', '/DataBrowser/DownloadCsv', 'container=mncowichan&entitySet=PropertyReport&filter=NOFILTER')):
return httmock.response(200, (b'FAKE,FAKE\n' * 99), headers={'Content-Type': 'text/csv', 'Content-Disposition': 'attachment; filename=PropertyReport.csv'})
raise NotImplementedError(url.geturl())<|docstring|>Fake HTTP responses for use with HTTMock in tests.<|endoftext|> |
4b770d385a0af55f1020caa0ea6cd131c16804d90b2a6e12e436f6b14291bf50 | def setUp(self):
' Prepare a clean temporary directory, and work there.\n '
self.workdir = tempfile.mkdtemp(prefix='testCache-') | Prepare a clean temporary directory, and work there. | openaddr/tests/cache.py | setUp | geobrando/machine | 101 | python | def setUp(self):
' \n '
self.workdir = tempfile.mkdtemp(prefix='testCache-') | def setUp(self):
' \n '
self.workdir = tempfile.mkdtemp(prefix='testCache-')<|docstring|>Prepare a clean temporary directory, and work there.<|endoftext|> |
cf820a4c99a948104dd66adba35425bdb5294bbc95a761897910664c4c283909 | def test_download_with_conform(self):
' ESRI Caching Will Request With The Minimum Fields Required '
conforms = ((None, None), (['a', 'b', 'c'], {'type': 'csv', 'street': ['a', 'b'], 'number': 'c'}), (['a'], {'type': 'csv', 'street': {'function': 'regexp', 'field': 'a'}, 'number': {'function': 'regexp', 'field': 'a'}}))
task = EsriRestDownloadTask('us-fl-palmbeach')
for (expected, conform) in conforms:
actual = task.field_names_to_request(conform)
self.assertEqual(expected, actual) | ESRI Caching Will Request With The Minimum Fields Required | openaddr/tests/cache.py | test_download_with_conform | geobrando/machine | 101 | python | def test_download_with_conform(self):
' '
conforms = ((None, None), (['a', 'b', 'c'], {'type': 'csv', 'street': ['a', 'b'], 'number': 'c'}), (['a'], {'type': 'csv', 'street': {'function': 'regexp', 'field': 'a'}, 'number': {'function': 'regexp', 'field': 'a'}}))
task = EsriRestDownloadTask('us-fl-palmbeach')
for (expected, conform) in conforms:
actual = task.field_names_to_request(conform)
self.assertEqual(expected, actual) | def test_download_with_conform(self):
' '
conforms = ((None, None), (['a', 'b', 'c'], {'type': 'csv', 'street': ['a', 'b'], 'number': 'c'}), (['a'], {'type': 'csv', 'street': {'function': 'regexp', 'field': 'a'}, 'number': {'function': 'regexp', 'field': 'a'}}))
task = EsriRestDownloadTask('us-fl-palmbeach')
for (expected, conform) in conforms:
actual = task.field_names_to_request(conform)
self.assertEqual(expected, actual)<|docstring|>ESRI Caching Will Request With The Minimum Fields Required<|endoftext|> |
5dd38d5cef8dbb880c7a94fd2da5c194db7e467e169a3db5424366b1e1516dea | def test_download_handles_no_count(self):
' ESRI Caching Will Handle A Server Without returnCountOnly Support '
task = EsriRestDownloadTask('us-fl-palmbeach')
with patch('esridump.EsriDumper.get_metadata') as metadata_patch:
metadata_patch.return_value = {'fields': []}
with patch('esridump.EsriDumper.get_feature_count') as feature_patch:
feature_patch.side_effect = EsriDownloadError("Server doesn't support returnCountOnly")
with self.assertRaises(EsriDownloadError) as e:
task.download(['http://example.com/'], self.workdir)
self.assertEqual(e.message, 'Could not find object ID field name for deduplication') | ESRI Caching Will Handle A Server Without returnCountOnly Support | openaddr/tests/cache.py | test_download_handles_no_count | geobrando/machine | 101 | python | def test_download_handles_no_count(self):
' '
task = EsriRestDownloadTask('us-fl-palmbeach')
with patch('esridump.EsriDumper.get_metadata') as metadata_patch:
metadata_patch.return_value = {'fields': []}
with patch('esridump.EsriDumper.get_feature_count') as feature_patch:
feature_patch.side_effect = EsriDownloadError("Server doesn't support returnCountOnly")
with self.assertRaises(EsriDownloadError) as e:
task.download(['http://example.com/'], self.workdir)
self.assertEqual(e.message, 'Could not find object ID field name for deduplication') | def test_download_handles_no_count(self):
' '
task = EsriRestDownloadTask('us-fl-palmbeach')
with patch('esridump.EsriDumper.get_metadata') as metadata_patch:
metadata_patch.return_value = {'fields': []}
with patch('esridump.EsriDumper.get_feature_count') as feature_patch:
feature_patch.side_effect = EsriDownloadError("Server doesn't support returnCountOnly")
with self.assertRaises(EsriDownloadError) as e:
task.download(['http://example.com/'], self.workdir)
self.assertEqual(e.message, 'Could not find object ID field name for deduplication')<|docstring|>ESRI Caching Will Handle A Server Without returnCountOnly Support<|endoftext|> |
754634a45f03f82829820a48e33acea283dce00969db0d5d5ad0f6117babfa61 | @override_settings(USE_I18N=True, MIDDLEWARE=['django.middleware.locale.LocaleMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware'])
def test_translation(self):
'\n An invalid request is rejected with a localized error message.\n '
response = self.client.post('/')
self.assertContains(response, 'Forbidden', status_code=403)
self.assertContains(response, 'CSRF verification failed. Request aborted.', status_code=403)
with self.settings(LANGUAGE_CODE='nl'), override('en-us'):
response = self.client.post('/')
self.assertContains(response, 'Verboden', status_code=403)
self.assertContains(response, 'CSRF-verificatie mislukt. Verzoek afgebroken.', status_code=403) | An invalid request is rejected with a localized error message. | tests/view_tests/tests/test_csrf.py | test_translation | jonashaag/django-1.1-python-3.7 | 5,079 | python | @override_settings(USE_I18N=True, MIDDLEWARE=['django.middleware.locale.LocaleMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware'])
def test_translation(self):
'\n \n '
response = self.client.post('/')
self.assertContains(response, 'Forbidden', status_code=403)
self.assertContains(response, 'CSRF verification failed. Request aborted.', status_code=403)
with self.settings(LANGUAGE_CODE='nl'), override('en-us'):
response = self.client.post('/')
self.assertContains(response, 'Verboden', status_code=403)
self.assertContains(response, 'CSRF-verificatie mislukt. Verzoek afgebroken.', status_code=403) | @override_settings(USE_I18N=True, MIDDLEWARE=['django.middleware.locale.LocaleMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware'])
def test_translation(self):
'\n \n '
response = self.client.post('/')
self.assertContains(response, 'Forbidden', status_code=403)
self.assertContains(response, 'CSRF verification failed. Request aborted.', status_code=403)
with self.settings(LANGUAGE_CODE='nl'), override('en-us'):
response = self.client.post('/')
self.assertContains(response, 'Verboden', status_code=403)
self.assertContains(response, 'CSRF-verificatie mislukt. Verzoek afgebroken.', status_code=403)<|docstring|>An invalid request is rejected with a localized error message.<|endoftext|> |
7f74ec487eb0cc6479581abb3cfb7460bde400ffab73736450c07665552b6f08 | @ignore_warnings(category=RemovedInDjango20Warning)
@override_settings(USE_I18N=True, MIDDLEWARE=None, MIDDLEWARE_CLASSES=['django.middleware.locale.LocaleMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware'])
def test_translation_middleware_classes(self):
'\n An invalid request is rejected with a localized error message.\n '
response = self.client.post('/')
self.assertContains(response, 'Forbidden', status_code=403)
self.assertContains(response, 'CSRF verification failed. Request aborted.', status_code=403)
with self.settings(LANGUAGE_CODE='nl'), override('en-us'):
response = self.client.post('/')
self.assertContains(response, 'Verboden', status_code=403)
self.assertContains(response, 'CSRF-verificatie mislukt. Verzoek afgebroken.', status_code=403) | An invalid request is rejected with a localized error message. | tests/view_tests/tests/test_csrf.py | test_translation_middleware_classes | jonashaag/django-1.1-python-3.7 | 5,079 | python | @ignore_warnings(category=RemovedInDjango20Warning)
@override_settings(USE_I18N=True, MIDDLEWARE=None, MIDDLEWARE_CLASSES=['django.middleware.locale.LocaleMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware'])
def test_translation_middleware_classes(self):
'\n \n '
response = self.client.post('/')
self.assertContains(response, 'Forbidden', status_code=403)
self.assertContains(response, 'CSRF verification failed. Request aborted.', status_code=403)
with self.settings(LANGUAGE_CODE='nl'), override('en-us'):
response = self.client.post('/')
self.assertContains(response, 'Verboden', status_code=403)
self.assertContains(response, 'CSRF-verificatie mislukt. Verzoek afgebroken.', status_code=403) | @ignore_warnings(category=RemovedInDjango20Warning)
@override_settings(USE_I18N=True, MIDDLEWARE=None, MIDDLEWARE_CLASSES=['django.middleware.locale.LocaleMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware'])
def test_translation_middleware_classes(self):
'\n \n '
response = self.client.post('/')
self.assertContains(response, 'Forbidden', status_code=403)
self.assertContains(response, 'CSRF verification failed. Request aborted.', status_code=403)
with self.settings(LANGUAGE_CODE='nl'), override('en-us'):
response = self.client.post('/')
self.assertContains(response, 'Verboden', status_code=403)
self.assertContains(response, 'CSRF-verificatie mislukt. Verzoek afgebroken.', status_code=403)<|docstring|>An invalid request is rejected with a localized error message.<|endoftext|> |
7a7e18871b8bab77475ae3512181bf49c8b848b73c89a62e80fcdc77b7b0fb06 | @override_settings(SECURE_PROXY_SSL_HEADER=('HTTP_X_FORWARDED_PROTO', 'https'))
def test_no_referer(self):
'\n Referer header is strictly checked for POST over HTTPS. Trigger the\n exception by sending an incorrect referer.\n '
response = self.client.post('/', HTTP_X_FORWARDED_PROTO='https')
self.assertContains(response, 'You are seeing this message because this HTTPS site requires a 'Referer header' to be sent by your Web browser, but none was sent.', status_code=403) | Referer header is strictly checked for POST over HTTPS. Trigger the
exception by sending an incorrect referer. | tests/view_tests/tests/test_csrf.py | test_no_referer | jonashaag/django-1.1-python-3.7 | 5,079 | python | @override_settings(SECURE_PROXY_SSL_HEADER=('HTTP_X_FORWARDED_PROTO', 'https'))
def test_no_referer(self):
'\n Referer header is strictly checked for POST over HTTPS. Trigger the\n exception by sending an incorrect referer.\n '
response = self.client.post('/', HTTP_X_FORWARDED_PROTO='https')
self.assertContains(response, 'You are seeing this message because this HTTPS site requires a 'Referer header' to be sent by your Web browser, but none was sent.', status_code=403) | @override_settings(SECURE_PROXY_SSL_HEADER=('HTTP_X_FORWARDED_PROTO', 'https'))
def test_no_referer(self):
'\n Referer header is strictly checked for POST over HTTPS. Trigger the\n exception by sending an incorrect referer.\n '
response = self.client.post('/', HTTP_X_FORWARDED_PROTO='https')
self.assertContains(response, 'You are seeing this message because this HTTPS site requires a 'Referer header' to be sent by your Web browser, but none was sent.', status_code=403)<|docstring|>Referer header is strictly checked for POST over HTTPS. Trigger the
exception by sending an incorrect referer.<|endoftext|> |
ca0a0d62502ece27abf05271d3373cded400df606689ff158ee6e93c110b437d | def test_no_cookies(self):
'\n The CSRF cookie is checked for POST. Failure to send this cookie should\n provide a nice error message.\n '
response = self.client.post('/')
self.assertContains(response, 'You are seeing this message because this site requires a CSRF cookie when submitting forms. This cookie is required for security reasons, to ensure that your browser is not being hijacked by third parties.', status_code=403) | The CSRF cookie is checked for POST. Failure to send this cookie should
provide a nice error message. | tests/view_tests/tests/test_csrf.py | test_no_cookies | jonashaag/django-1.1-python-3.7 | 5,079 | python | def test_no_cookies(self):
'\n The CSRF cookie is checked for POST. Failure to send this cookie should\n provide a nice error message.\n '
response = self.client.post('/')
self.assertContains(response, 'You are seeing this message because this site requires a CSRF cookie when submitting forms. This cookie is required for security reasons, to ensure that your browser is not being hijacked by third parties.', status_code=403) | def test_no_cookies(self):
'\n The CSRF cookie is checked for POST. Failure to send this cookie should\n provide a nice error message.\n '
response = self.client.post('/')
self.assertContains(response, 'You are seeing this message because this site requires a CSRF cookie when submitting forms. This cookie is required for security reasons, to ensure that your browser is not being hijacked by third parties.', status_code=403)<|docstring|>The CSRF cookie is checked for POST. Failure to send this cookie should
provide a nice error message.<|endoftext|> |
95985cc0381098dcf3c35d248e5fb602615a9d0e705670a175c769e6a887ef0e | @override_settings(TEMPLATES=[])
def test_no_django_template_engine(self):
"\n The CSRF view doesn't depend on the TEMPLATES configuration (#24388).\n "
response = self.client.post('/')
self.assertContains(response, 'Forbidden', status_code=403) | The CSRF view doesn't depend on the TEMPLATES configuration (#24388). | tests/view_tests/tests/test_csrf.py | test_no_django_template_engine | jonashaag/django-1.1-python-3.7 | 5,079 | python | @override_settings(TEMPLATES=[])
def test_no_django_template_engine(self):
"\n \n "
response = self.client.post('/')
self.assertContains(response, 'Forbidden', status_code=403) | @override_settings(TEMPLATES=[])
def test_no_django_template_engine(self):
"\n \n "
response = self.client.post('/')
self.assertContains(response, 'Forbidden', status_code=403)<|docstring|>The CSRF view doesn't depend on the TEMPLATES configuration (#24388).<|endoftext|> |
7d605b2a247e58fad6479d6f8a707bb3d60faffe937d76357f82a0c4a898d0d9 | @override_settings(TEMPLATES=[{'BACKEND': 'django.template.backends.django.DjangoTemplates', 'OPTIONS': {'loaders': [('django.template.loaders.locmem.Loader', {CSRF_FAILURE_TEMPLATE_NAME: 'Test template for CSRF failure'})]}}])
def test_custom_template(self):
'\n A custom CSRF_FAILURE_TEMPLATE_NAME is used.\n '
response = self.client.post('/')
self.assertContains(response, 'Test template for CSRF failure', status_code=403) | A custom CSRF_FAILURE_TEMPLATE_NAME is used. | tests/view_tests/tests/test_csrf.py | test_custom_template | jonashaag/django-1.1-python-3.7 | 5,079 | python | @override_settings(TEMPLATES=[{'BACKEND': 'django.template.backends.django.DjangoTemplates', 'OPTIONS': {'loaders': [('django.template.loaders.locmem.Loader', {CSRF_FAILURE_TEMPLATE_NAME: 'Test template for CSRF failure'})]}}])
def test_custom_template(self):
'\n \n '
response = self.client.post('/')
self.assertContains(response, 'Test template for CSRF failure', status_code=403) | @override_settings(TEMPLATES=[{'BACKEND': 'django.template.backends.django.DjangoTemplates', 'OPTIONS': {'loaders': [('django.template.loaders.locmem.Loader', {CSRF_FAILURE_TEMPLATE_NAME: 'Test template for CSRF failure'})]}}])
def test_custom_template(self):
'\n \n '
response = self.client.post('/')
self.assertContains(response, 'Test template for CSRF failure', status_code=403)<|docstring|>A custom CSRF_FAILURE_TEMPLATE_NAME is used.<|endoftext|> |
18778544a8cf6d22b2257172499452785df23230c01bd9f66250465565c7b17c | def test_custom_template_does_not_exist(self):
'\n An exception is raised if a nonexistent template is supplied.\n '
factory = RequestFactory()
request = factory.post('/')
with self.assertRaises(TemplateDoesNotExist):
csrf_failure(request, template_name='nonexistent.html') | An exception is raised if a nonexistent template is supplied. | tests/view_tests/tests/test_csrf.py | test_custom_template_does_not_exist | jonashaag/django-1.1-python-3.7 | 5,079 | python | def test_custom_template_does_not_exist(self):
'\n \n '
factory = RequestFactory()
request = factory.post('/')
with self.assertRaises(TemplateDoesNotExist):
csrf_failure(request, template_name='nonexistent.html') | def test_custom_template_does_not_exist(self):
'\n \n '
factory = RequestFactory()
request = factory.post('/')
with self.assertRaises(TemplateDoesNotExist):
csrf_failure(request, template_name='nonexistent.html')<|docstring|>An exception is raised if a nonexistent template is supplied.<|endoftext|> |
4e82464926c0ee651e1826f5d2d0480788ca26cb50cba26db00b1da768e32d6a | def parse_type(t):
'Returns the Ibis datatype from source type.'
t = t.lower()
if (t in _impala_to_ibis_type):
return _impala_to_ibis_type[t]
elif (('varchar' in t) or ('char' in t)):
return 'string'
elif ('decimal' in t):
result = dt.dtype(t)
if result:
return t
else:
return ValueError(t)
elif (('struct' in t) or ('array' in t) or ('map' in t)):
return t.replace('int', 'int32')
else:
raise Exception(t) | Returns the Ibis datatype from source type. | third_party/ibis/ibis_impala/api.py | parse_type | ajw0100/professional-services-data-validator | 167 | python | def parse_type(t):
t = t.lower()
if (t in _impala_to_ibis_type):
return _impala_to_ibis_type[t]
elif (('varchar' in t) or ('char' in t)):
return 'string'
elif ('decimal' in t):
result = dt.dtype(t)
if result:
return t
else:
return ValueError(t)
elif (('struct' in t) or ('array' in t) or ('map' in t)):
return t.replace('int', 'int32')
else:
raise Exception(t) | def parse_type(t):
t = t.lower()
if (t in _impala_to_ibis_type):
return _impala_to_ibis_type[t]
elif (('varchar' in t) or ('char' in t)):
return 'string'
elif ('decimal' in t):
result = dt.dtype(t)
if result:
return t
else:
return ValueError(t)
elif (('struct' in t) or ('array' in t) or ('map' in t)):
return t.replace('int', 'int32')
else:
raise Exception(t)<|docstring|>Returns the Ibis datatype from source type.<|endoftext|> |
8a403d3e8144965847bfc7a2c5e116cecd5cc88f5bee3ccb37c9a8a9623e63f5 | def ISM_filter(dict_freq, threshold):
'\n collapse low frequency ISMs into "OTHER" per location\n Parameters\n ----------\n dict_freq: dictionary\n ISM frequency of a location of interest\n threshold: float\n ISMs lower than this threshold will be collapsed into "OTHER"\n Returns\n -------\n res_dict: dictionary\n filtered ISM frequency of a location of interest\n '
res_dict = {'OTHER': [0, 0]}
total = sum([int(dict_freq[ISM][1]) for ISM in dict_freq])
for ISM in dict_freq:
if ((int(dict_freq[ISM][1]) / total) < threshold):
res_dict['OTHER'] = [0, (res_dict['OTHER'][1] + int(dict_freq[ISM][1]))]
else:
res_dict[ISM] = [dict_freq[ISM][0], (int(dict_freq[ISM][1]) + res_dict.get(ISM, [0, 0])[1])]
if (res_dict['OTHER'][1] == 0):
del res_dict['OTHER']
return res_dict | collapse low frequency ISMs into "OTHER" per location
Parameters
----------
dict_freq: dictionary
ISM frequency of a location of interest
threshold: float
ISMs lower than this threshold will be collapsed into "OTHER"
Returns
-------
res_dict: dictionary
filtered ISM frequency of a location of interest | ncov_ism/_visualization.py | ISM_filter | EESI/ncov_ism | 1 | python | def ISM_filter(dict_freq, threshold):
'\n collapse low frequency ISMs into "OTHER" per location\n Parameters\n ----------\n dict_freq: dictionary\n ISM frequency of a location of interest\n threshold: float\n ISMs lower than this threshold will be collapsed into "OTHER"\n Returns\n -------\n res_dict: dictionary\n filtered ISM frequency of a location of interest\n '
res_dict = {'OTHER': [0, 0]}
total = sum([int(dict_freq[ISM][1]) for ISM in dict_freq])
for ISM in dict_freq:
if ((int(dict_freq[ISM][1]) / total) < threshold):
res_dict['OTHER'] = [0, (res_dict['OTHER'][1] + int(dict_freq[ISM][1]))]
else:
res_dict[ISM] = [dict_freq[ISM][0], (int(dict_freq[ISM][1]) + res_dict.get(ISM, [0, 0])[1])]
if (res_dict['OTHER'][1] == 0):
del res_dict['OTHER']
return res_dict | def ISM_filter(dict_freq, threshold):
'\n collapse low frequency ISMs into "OTHER" per location\n Parameters\n ----------\n dict_freq: dictionary\n ISM frequency of a location of interest\n threshold: float\n ISMs lower than this threshold will be collapsed into "OTHER"\n Returns\n -------\n res_dict: dictionary\n filtered ISM frequency of a location of interest\n '
res_dict = {'OTHER': [0, 0]}
total = sum([int(dict_freq[ISM][1]) for ISM in dict_freq])
for ISM in dict_freq:
if ((int(dict_freq[ISM][1]) / total) < threshold):
res_dict['OTHER'] = [0, (res_dict['OTHER'][1] + int(dict_freq[ISM][1]))]
else:
res_dict[ISM] = [dict_freq[ISM][0], (int(dict_freq[ISM][1]) + res_dict.get(ISM, [0, 0])[1])]
if (res_dict['OTHER'][1] == 0):
del res_dict['OTHER']
return res_dict<|docstring|>collapse low frequency ISMs into "OTHER" per location
Parameters
----------
dict_freq: dictionary
ISM frequency of a location of interest
threshold: float
ISMs lower than this threshold will be collapsed into "OTHER"
Returns
-------
res_dict: dictionary
filtered ISM frequency of a location of interest<|endoftext|> |
e56815b5cda99685cb34f19ddd83a695c12f93b608b4c7be62af725839210985 | def ISM_time_series_filter(dict_freq, threshold):
'\n collapse low frequency ISMs into "OTHER" per location\n Parameters\n ----------\n dict_freq: dictionary\n ISM frequency of a location of interest\n threshold: float\n ISMs lower than this threshold will be collapsed into "OTHER"\n Returns\n -------\n res_dict: dictionary\n filtered ISM frequency of a location of interest\n '
res_dict = {'OTHER': [0, 0]}
total = sum([int(dict_freq[ISM]) for ISM in dict_freq])
for ISM in dict_freq:
if ((int(dict_freq[ISM]) / total) < threshold):
res_dict['OTHER'] = [0, (res_dict['OTHER'][1] + int(dict_freq[ISM]))]
else:
res_dict[ISM] = [dict_freq[ISM], (int(dict_freq[ISM]) + res_dict.get(ISM, [0, 0])[1])]
if (res_dict['OTHER'][1] == 0):
del res_dict['OTHER']
return res_dict | collapse low frequency ISMs into "OTHER" per location
Parameters
----------
dict_freq: dictionary
ISM frequency of a location of interest
threshold: float
ISMs lower than this threshold will be collapsed into "OTHER"
Returns
-------
res_dict: dictionary
filtered ISM frequency of a location of interest | ncov_ism/_visualization.py | ISM_time_series_filter | EESI/ncov_ism | 1 | python | def ISM_time_series_filter(dict_freq, threshold):
'\n collapse low frequency ISMs into "OTHER" per location\n Parameters\n ----------\n dict_freq: dictionary\n ISM frequency of a location of interest\n threshold: float\n ISMs lower than this threshold will be collapsed into "OTHER"\n Returns\n -------\n res_dict: dictionary\n filtered ISM frequency of a location of interest\n '
res_dict = {'OTHER': [0, 0]}
total = sum([int(dict_freq[ISM]) for ISM in dict_freq])
for ISM in dict_freq:
if ((int(dict_freq[ISM]) / total) < threshold):
res_dict['OTHER'] = [0, (res_dict['OTHER'][1] + int(dict_freq[ISM]))]
else:
res_dict[ISM] = [dict_freq[ISM], (int(dict_freq[ISM]) + res_dict.get(ISM, [0, 0])[1])]
if (res_dict['OTHER'][1] == 0):
del res_dict['OTHER']
return res_dict | def ISM_time_series_filter(dict_freq, threshold):
'\n collapse low frequency ISMs into "OTHER" per location\n Parameters\n ----------\n dict_freq: dictionary\n ISM frequency of a location of interest\n threshold: float\n ISMs lower than this threshold will be collapsed into "OTHER"\n Returns\n -------\n res_dict: dictionary\n filtered ISM frequency of a location of interest\n '
res_dict = {'OTHER': [0, 0]}
total = sum([int(dict_freq[ISM]) for ISM in dict_freq])
for ISM in dict_freq:
if ((int(dict_freq[ISM]) / total) < threshold):
res_dict['OTHER'] = [0, (res_dict['OTHER'][1] + int(dict_freq[ISM]))]
else:
res_dict[ISM] = [dict_freq[ISM], (int(dict_freq[ISM]) + res_dict.get(ISM, [0, 0])[1])]
if (res_dict['OTHER'][1] == 0):
del res_dict['OTHER']
return res_dict<|docstring|>collapse low frequency ISMs into "OTHER" per location
Parameters
----------
dict_freq: dictionary
ISM frequency of a location of interest
threshold: float
ISMs lower than this threshold will be collapsed into "OTHER"
Returns
-------
res_dict: dictionary
filtered ISM frequency of a location of interest<|endoftext|> |
c6d9c9ea9e76e3f4cb21671dc77f6ef6b8e42590684bf20ea1f463671767416a | def ISM_visualization(region_raw_count, state_raw_count, count_dict, region_list, state_list, time_series_region_list, output_folder, ISM_FILTER_THRESHOLD=0.05, ISM_TIME_SERIES_FILTER_THRESHOLD=0.025):
'\n Informative Subtype Marker analysis visualization\n Parameters\n ----------\n region_raw_count: dictionary\n ISM frequency per region\n state_raw_count: dictionary\n ISM frequency per state\n count_dict: dictionary\n ISM frequency time series per region\n region_list: list\n regions of interest\n state_list: list\n states of interest\n time_series_region_list: list\n regions of interest for time series analysis\n output_folder: str\n path to the output folder\n ISM_FILTER_THRESHOLD: float\n ISM filter threshold\n ISM_TIME_SERIES_FILTER_THRESHOLD: float\n ISM filter threshold for time series\n Returns\n -------\n Objects for downstream visualization\n '
ISM_set = set([])
region_pie_chart = {}
for (idx, region) in enumerate(region_list):
dict_freq_filtered = ISM_filter(region_raw_count[region], ISM_FILTER_THRESHOLD)
region_pie_chart[region] = dict_freq_filtered
ISM_set.update(dict_freq_filtered.keys())
state_pie_chart = {}
for (idx, state) in enumerate(state_list):
dict_freq_filtered = ISM_filter(state_raw_count[state], ISM_FILTER_THRESHOLD)
state_pie_chart[state] = dict_freq_filtered
ISM_set.update(dict_freq_filtered.keys())
count_list = []
date_list = []
sorted_date = sorted(count_dict.keys())
for date in sorted_date:
dict_freq = {}
for region in time_series_region_list:
regional_dict_freq = count_dict[date][region]
dict_freq_filtered = ISM_time_series_filter(regional_dict_freq, ISM_TIME_SERIES_FILTER_THRESHOLD)
ISM_set.update(list(dict_freq_filtered.keys()))
dict_freq[region] = dict_freq_filtered
count_list.append(dict_freq)
date_list.append(date)
return (ISM_set, region_pie_chart, state_pie_chart, count_list, date_list) | Informative Subtype Marker analysis visualization
Parameters
----------
region_raw_count: dictionary
ISM frequency per region
state_raw_count: dictionary
ISM frequency per state
count_dict: dictionary
ISM frequency time series per region
region_list: list
regions of interest
state_list: list
states of interest
time_series_region_list: list
regions of interest for time series analysis
output_folder: str
path to the output folder
ISM_FILTER_THRESHOLD: float
ISM filter threshold
ISM_TIME_SERIES_FILTER_THRESHOLD: float
ISM filter threshold for time series
Returns
-------
Objects for downstream visualization | ncov_ism/_visualization.py | ISM_visualization | EESI/ncov_ism | 1 | python | def ISM_visualization(region_raw_count, state_raw_count, count_dict, region_list, state_list, time_series_region_list, output_folder, ISM_FILTER_THRESHOLD=0.05, ISM_TIME_SERIES_FILTER_THRESHOLD=0.025):
'\n Informative Subtype Marker analysis visualization\n Parameters\n ----------\n region_raw_count: dictionary\n ISM frequency per region\n state_raw_count: dictionary\n ISM frequency per state\n count_dict: dictionary\n ISM frequency time series per region\n region_list: list\n regions of interest\n state_list: list\n states of interest\n time_series_region_list: list\n regions of interest for time series analysis\n output_folder: str\n path to the output folder\n ISM_FILTER_THRESHOLD: float\n ISM filter threshold\n ISM_TIME_SERIES_FILTER_THRESHOLD: float\n ISM filter threshold for time series\n Returns\n -------\n Objects for downstream visualization\n '
ISM_set = set([])
region_pie_chart = {}
for (idx, region) in enumerate(region_list):
dict_freq_filtered = ISM_filter(region_raw_count[region], ISM_FILTER_THRESHOLD)
region_pie_chart[region] = dict_freq_filtered
ISM_set.update(dict_freq_filtered.keys())
state_pie_chart = {}
for (idx, state) in enumerate(state_list):
dict_freq_filtered = ISM_filter(state_raw_count[state], ISM_FILTER_THRESHOLD)
state_pie_chart[state] = dict_freq_filtered
ISM_set.update(dict_freq_filtered.keys())
count_list = []
date_list = []
sorted_date = sorted(count_dict.keys())
for date in sorted_date:
dict_freq = {}
for region in time_series_region_list:
regional_dict_freq = count_dict[date][region]
dict_freq_filtered = ISM_time_series_filter(regional_dict_freq, ISM_TIME_SERIES_FILTER_THRESHOLD)
ISM_set.update(list(dict_freq_filtered.keys()))
dict_freq[region] = dict_freq_filtered
count_list.append(dict_freq)
date_list.append(date)
return (ISM_set, region_pie_chart, state_pie_chart, count_list, date_list) | def ISM_visualization(region_raw_count, state_raw_count, count_dict, region_list, state_list, time_series_region_list, output_folder, ISM_FILTER_THRESHOLD=0.05, ISM_TIME_SERIES_FILTER_THRESHOLD=0.025):
'\n Informative Subtype Marker analysis visualization\n Parameters\n ----------\n region_raw_count: dictionary\n ISM frequency per region\n state_raw_count: dictionary\n ISM frequency per state\n count_dict: dictionary\n ISM frequency time series per region\n region_list: list\n regions of interest\n state_list: list\n states of interest\n time_series_region_list: list\n regions of interest for time series analysis\n output_folder: str\n path to the output folder\n ISM_FILTER_THRESHOLD: float\n ISM filter threshold\n ISM_TIME_SERIES_FILTER_THRESHOLD: float\n ISM filter threshold for time series\n Returns\n -------\n Objects for downstream visualization\n '
ISM_set = set([])
region_pie_chart = {}
for (idx, region) in enumerate(region_list):
dict_freq_filtered = ISM_filter(region_raw_count[region], ISM_FILTER_THRESHOLD)
region_pie_chart[region] = dict_freq_filtered
ISM_set.update(dict_freq_filtered.keys())
state_pie_chart = {}
for (idx, state) in enumerate(state_list):
dict_freq_filtered = ISM_filter(state_raw_count[state], ISM_FILTER_THRESHOLD)
state_pie_chart[state] = dict_freq_filtered
ISM_set.update(dict_freq_filtered.keys())
count_list = []
date_list = []
sorted_date = sorted(count_dict.keys())
for date in sorted_date:
dict_freq = {}
for region in time_series_region_list:
regional_dict_freq = count_dict[date][region]
dict_freq_filtered = ISM_time_series_filter(regional_dict_freq, ISM_TIME_SERIES_FILTER_THRESHOLD)
ISM_set.update(list(dict_freq_filtered.keys()))
dict_freq[region] = dict_freq_filtered
count_list.append(dict_freq)
date_list.append(date)
return (ISM_set, region_pie_chart, state_pie_chart, count_list, date_list)<|docstring|>Informative Subtype Marker analysis visualization
Parameters
----------
region_raw_count: dictionary
ISM frequency per region
state_raw_count: dictionary
ISM frequency per state
count_dict: dictionary
ISM frequency time series per region
region_list: list
regions of interest
state_list: list
states of interest
time_series_region_list: list
regions of interest for time series analysis
output_folder: str
path to the output folder
ISM_FILTER_THRESHOLD: float
ISM filter threshold
ISM_TIME_SERIES_FILTER_THRESHOLD: float
ISM filter threshold for time series
Returns
-------
Objects for downstream visualization<|endoftext|> |
d544ecde11119dff11e755213b08f1a3d96132231d40d9b3ee84b0979a570f40 | def customized_ISM_visualization(region_raw_count, count_dict, region_list, output_folder, ISM_FILTER_THRESHOLD=0.05, ISM_TIME_SERIES_FILTER_THRESHOLD=0.025):
'\n Informative Subtype Marker analysis visualization\n Parameters\n ----------\n region_raw_count: dictionary\n ISM frequency per region\n state_raw_count: dictionary\n ISM frequency per state\n count_dict: dictionary\n ISM frequency time series per region\n region_list: list\n regions of interest\n state_list: list\n states of interest\n time_series_region_list: list\n regions of interest for time series analysis\n output_folder: str\n path to the output folder\n ISM_FILTER_THRESHOLD: float\n ISM filter threshold\n ISM_TIME_SERIES_FILTER_THRESHOLD: float\n ISM filter threshold for time series\n Returns\n -------\n Objects for downstream visualization\n '
ISM_set = set([])
region_pie_chart = {}
for (idx, region) in enumerate(region_list):
dict_freq_filtered = ISM_filter(region_raw_count[region], ISM_FILTER_THRESHOLD)
region_pie_chart[region] = dict_freq_filtered
ISM_set.update(dict_freq_filtered.keys())
count_list = []
date_list = []
sorted_date = sorted(count_dict.keys())
for date in sorted_date:
dict_freq = {}
for region in region_list:
regional_dict_freq = count_dict[date][region]
dict_freq_filtered = ISM_time_series_filter(regional_dict_freq, ISM_TIME_SERIES_FILTER_THRESHOLD)
ISM_set.update(list(dict_freq_filtered.keys()))
dict_freq[region] = dict_freq_filtered
count_list.append(dict_freq)
date_list.append(date)
return (ISM_set, region_pie_chart, count_list, date_list) | Informative Subtype Marker analysis visualization
Parameters
----------
region_raw_count: dictionary
ISM frequency per region
state_raw_count: dictionary
ISM frequency per state
count_dict: dictionary
ISM frequency time series per region
region_list: list
regions of interest
state_list: list
states of interest
time_series_region_list: list
regions of interest for time series analysis
output_folder: str
path to the output folder
ISM_FILTER_THRESHOLD: float
ISM filter threshold
ISM_TIME_SERIES_FILTER_THRESHOLD: float
ISM filter threshold for time series
Returns
-------
Objects for downstream visualization | ncov_ism/_visualization.py | customized_ISM_visualization | EESI/ncov_ism | 1 | python | def customized_ISM_visualization(region_raw_count, count_dict, region_list, output_folder, ISM_FILTER_THRESHOLD=0.05, ISM_TIME_SERIES_FILTER_THRESHOLD=0.025):
'\n Informative Subtype Marker analysis visualization\n Parameters\n ----------\n region_raw_count: dictionary\n ISM frequency per region\n state_raw_count: dictionary\n ISM frequency per state\n count_dict: dictionary\n ISM frequency time series per region\n region_list: list\n regions of interest\n state_list: list\n states of interest\n time_series_region_list: list\n regions of interest for time series analysis\n output_folder: str\n path to the output folder\n ISM_FILTER_THRESHOLD: float\n ISM filter threshold\n ISM_TIME_SERIES_FILTER_THRESHOLD: float\n ISM filter threshold for time series\n Returns\n -------\n Objects for downstream visualization\n '
ISM_set = set([])
region_pie_chart = {}
for (idx, region) in enumerate(region_list):
dict_freq_filtered = ISM_filter(region_raw_count[region], ISM_FILTER_THRESHOLD)
region_pie_chart[region] = dict_freq_filtered
ISM_set.update(dict_freq_filtered.keys())
count_list = []
date_list = []
sorted_date = sorted(count_dict.keys())
for date in sorted_date:
dict_freq = {}
for region in region_list:
regional_dict_freq = count_dict[date][region]
dict_freq_filtered = ISM_time_series_filter(regional_dict_freq, ISM_TIME_SERIES_FILTER_THRESHOLD)
ISM_set.update(list(dict_freq_filtered.keys()))
dict_freq[region] = dict_freq_filtered
count_list.append(dict_freq)
date_list.append(date)
return (ISM_set, region_pie_chart, count_list, date_list) | def customized_ISM_visualization(region_raw_count, count_dict, region_list, output_folder, ISM_FILTER_THRESHOLD=0.05, ISM_TIME_SERIES_FILTER_THRESHOLD=0.025):
'\n Informative Subtype Marker analysis visualization\n Parameters\n ----------\n region_raw_count: dictionary\n ISM frequency per region\n state_raw_count: dictionary\n ISM frequency per state\n count_dict: dictionary\n ISM frequency time series per region\n region_list: list\n regions of interest\n state_list: list\n states of interest\n time_series_region_list: list\n regions of interest for time series analysis\n output_folder: str\n path to the output folder\n ISM_FILTER_THRESHOLD: float\n ISM filter threshold\n ISM_TIME_SERIES_FILTER_THRESHOLD: float\n ISM filter threshold for time series\n Returns\n -------\n Objects for downstream visualization\n '
ISM_set = set([])
region_pie_chart = {}
for (idx, region) in enumerate(region_list):
dict_freq_filtered = ISM_filter(region_raw_count[region], ISM_FILTER_THRESHOLD)
region_pie_chart[region] = dict_freq_filtered
ISM_set.update(dict_freq_filtered.keys())
count_list = []
date_list = []
sorted_date = sorted(count_dict.keys())
for date in sorted_date:
dict_freq = {}
for region in region_list:
regional_dict_freq = count_dict[date][region]
dict_freq_filtered = ISM_time_series_filter(regional_dict_freq, ISM_TIME_SERIES_FILTER_THRESHOLD)
ISM_set.update(list(dict_freq_filtered.keys()))
dict_freq[region] = dict_freq_filtered
count_list.append(dict_freq)
date_list.append(date)
return (ISM_set, region_pie_chart, count_list, date_list)<|docstring|>Informative Subtype Marker analysis visualization
Parameters
----------
region_raw_count: dictionary
ISM frequency per region
state_raw_count: dictionary
ISM frequency per state
count_dict: dictionary
ISM frequency time series per region
region_list: list
regions of interest
state_list: list
states of interest
time_series_region_list: list
regions of interest for time series analysis
output_folder: str
path to the output folder
ISM_FILTER_THRESHOLD: float
ISM filter threshold
ISM_TIME_SERIES_FILTER_THRESHOLD: float
ISM filter threshold for time series
Returns
-------
Objects for downstream visualization<|endoftext|> |
5f2c980a3a26ffefe4e89402bb77b12ba6cba009ec3d69dc7efec839ed278142 | def get_color_names(CSS4_COLORS, num_colors):
'\n Prepare colors for each ISM.\n '
bad_colors = set(['seashell', 'linen', 'ivory', 'oldlace', 'floralwhite', 'lightyellow', 'lightgoldenrodyellow', 'honeydew', 'mintcream', 'azure', 'lightcyan', 'aliceblue', 'ghostwhite', 'lavenderblush'])
by_hsv = sorted(((tuple(mcolors.rgb_to_hsv(mcolors.to_rgb(color))), name) for (name, color) in CSS4_COLORS.items()))
names = [name for (hsv, name) in by_hsv][14:]
prime_names = ['red', 'orange', 'green', 'blue', 'gold', 'lightskyblue', 'brown', 'black', 'pink', 'yellow']
OTHER = 'gray'
name_list = [name for name in names if ((name not in prime_names) and (name != OTHER) and (name not in bad_colors))]
if (num_colors > (len(name_list) - 10)):
logging.info('NOTE: Repetitive colors for different ISMs (inadequate distinctive colors)')
name_list = (name_list + (ceil((num_colors / len(name_list))) * name_list))
if (num_colors > len(prime_names)):
ind_list = np.linspace(0, len(name_list), (num_colors - 10), dtype=int, endpoint=False).tolist()
color_names = (prime_names + [name_list[ind] for ind in ind_list])
else:
color_names = prime_names[:num_colors]
return color_names | Prepare colors for each ISM. | ncov_ism/_visualization.py | get_color_names | EESI/ncov_ism | 1 | python | def get_color_names(CSS4_COLORS, num_colors):
'\n \n '
bad_colors = set(['seashell', 'linen', 'ivory', 'oldlace', 'floralwhite', 'lightyellow', 'lightgoldenrodyellow', 'honeydew', 'mintcream', 'azure', 'lightcyan', 'aliceblue', 'ghostwhite', 'lavenderblush'])
by_hsv = sorted(((tuple(mcolors.rgb_to_hsv(mcolors.to_rgb(color))), name) for (name, color) in CSS4_COLORS.items()))
names = [name for (hsv, name) in by_hsv][14:]
prime_names = ['red', 'orange', 'green', 'blue', 'gold', 'lightskyblue', 'brown', 'black', 'pink', 'yellow']
OTHER = 'gray'
name_list = [name for name in names if ((name not in prime_names) and (name != OTHER) and (name not in bad_colors))]
if (num_colors > (len(name_list) - 10)):
logging.info('NOTE: Repetitive colors for different ISMs (inadequate distinctive colors)')
name_list = (name_list + (ceil((num_colors / len(name_list))) * name_list))
if (num_colors > len(prime_names)):
ind_list = np.linspace(0, len(name_list), (num_colors - 10), dtype=int, endpoint=False).tolist()
color_names = (prime_names + [name_list[ind] for ind in ind_list])
else:
color_names = prime_names[:num_colors]
return color_names | def get_color_names(CSS4_COLORS, num_colors):
'\n \n '
bad_colors = set(['seashell', 'linen', 'ivory', 'oldlace', 'floralwhite', 'lightyellow', 'lightgoldenrodyellow', 'honeydew', 'mintcream', 'azure', 'lightcyan', 'aliceblue', 'ghostwhite', 'lavenderblush'])
by_hsv = sorted(((tuple(mcolors.rgb_to_hsv(mcolors.to_rgb(color))), name) for (name, color) in CSS4_COLORS.items()))
names = [name for (hsv, name) in by_hsv][14:]
prime_names = ['red', 'orange', 'green', 'blue', 'gold', 'lightskyblue', 'brown', 'black', 'pink', 'yellow']
OTHER = 'gray'
name_list = [name for name in names if ((name not in prime_names) and (name != OTHER) and (name not in bad_colors))]
if (num_colors > (len(name_list) - 10)):
logging.info('NOTE: Repetitive colors for different ISMs (inadequate distinctive colors)')
name_list = (name_list + (ceil((num_colors / len(name_list))) * name_list))
if (num_colors > len(prime_names)):
ind_list = np.linspace(0, len(name_list), (num_colors - 10), dtype=int, endpoint=False).tolist()
color_names = (prime_names + [name_list[ind] for ind in ind_list])
else:
color_names = prime_names[:num_colors]
return color_names<|docstring|>Prepare colors for each ISM.<|endoftext|> |
37929257d6f8f9592684408e66b39ad28ed46e6a70f82b254ebb0450e02a637a | def global_color_map(COLOR_DICT, ISM_list, out_dir):
'\n Plot color-ISM map for reference.\n Adapted from https://matplotlib.org/3.1.0/gallery/color/named_colors.html\n '
ncols = 3
n = len(COLOR_DICT)
nrows = ((n // ncols) + int(((n % ncols) > 0)))
cell_width = 1300
cell_height = 100
swatch_width = 180
margin = 30
topmargin = 40
width = ((cell_width * 3) + (2 * margin))
height = (((cell_height * nrows) + margin) + topmargin)
dpi = 300
(fig, ax) = plt.subplots(figsize=((width / dpi), (height / dpi)), dpi=dpi)
fig.subplots_adjust((margin / width), (margin / height), ((width - margin) / width), ((height - topmargin) / height))
ax.set_xlim(0, (cell_width * 4))
ax.set_ylim((cell_height * (nrows - 0.5)), ((- cell_height) / 2.0))
ax.yaxis.set_visible(False)
ax.xaxis.set_visible(False)
ax.set_axis_off()
ISM_list.append('OTHER')
for (i, name) in enumerate(ISM_list):
row = (i % nrows)
col = (i // nrows)
y = (row * cell_height)
swatch_start_x = (cell_width * col)
swatch_end_x = ((cell_width * col) + swatch_width)
text_pos_x = (((cell_width * col) + swatch_width) + 50)
ax.text(text_pos_x, y, name, fontsize=14, fontname='monospace', horizontalalignment='left', verticalalignment='center')
ax.hlines(y, swatch_start_x, swatch_end_x, color=COLOR_DICT[name], linewidth=18)
plt.savefig('{}/COLOR_MAP.png'.format(out_dir), bbox_inches='tight', dpi=dpi)
plt.close(fig) | Plot color-ISM map for reference.
Adapted from https://matplotlib.org/3.1.0/gallery/color/named_colors.html | ncov_ism/_visualization.py | global_color_map | EESI/ncov_ism | 1 | python | def global_color_map(COLOR_DICT, ISM_list, out_dir):
'\n Plot color-ISM map for reference.\n Adapted from https://matplotlib.org/3.1.0/gallery/color/named_colors.html\n '
ncols = 3
n = len(COLOR_DICT)
nrows = ((n // ncols) + int(((n % ncols) > 0)))
cell_width = 1300
cell_height = 100
swatch_width = 180
margin = 30
topmargin = 40
width = ((cell_width * 3) + (2 * margin))
height = (((cell_height * nrows) + margin) + topmargin)
dpi = 300
(fig, ax) = plt.subplots(figsize=((width / dpi), (height / dpi)), dpi=dpi)
fig.subplots_adjust((margin / width), (margin / height), ((width - margin) / width), ((height - topmargin) / height))
ax.set_xlim(0, (cell_width * 4))
ax.set_ylim((cell_height * (nrows - 0.5)), ((- cell_height) / 2.0))
ax.yaxis.set_visible(False)
ax.xaxis.set_visible(False)
ax.set_axis_off()
ISM_list.append('OTHER')
for (i, name) in enumerate(ISM_list):
row = (i % nrows)
col = (i // nrows)
y = (row * cell_height)
swatch_start_x = (cell_width * col)
swatch_end_x = ((cell_width * col) + swatch_width)
text_pos_x = (((cell_width * col) + swatch_width) + 50)
ax.text(text_pos_x, y, name, fontsize=14, fontname='monospace', horizontalalignment='left', verticalalignment='center')
ax.hlines(y, swatch_start_x, swatch_end_x, color=COLOR_DICT[name], linewidth=18)
plt.savefig('{}/COLOR_MAP.png'.format(out_dir), bbox_inches='tight', dpi=dpi)
plt.close(fig) | def global_color_map(COLOR_DICT, ISM_list, out_dir):
'\n Plot color-ISM map for reference.\n Adapted from https://matplotlib.org/3.1.0/gallery/color/named_colors.html\n '
ncols = 3
n = len(COLOR_DICT)
nrows = ((n // ncols) + int(((n % ncols) > 0)))
cell_width = 1300
cell_height = 100
swatch_width = 180
margin = 30
topmargin = 40
width = ((cell_width * 3) + (2 * margin))
height = (((cell_height * nrows) + margin) + topmargin)
dpi = 300
(fig, ax) = plt.subplots(figsize=((width / dpi), (height / dpi)), dpi=dpi)
fig.subplots_adjust((margin / width), (margin / height), ((width - margin) / width), ((height - topmargin) / height))
ax.set_xlim(0, (cell_width * 4))
ax.set_ylim((cell_height * (nrows - 0.5)), ((- cell_height) / 2.0))
ax.yaxis.set_visible(False)
ax.xaxis.set_visible(False)
ax.set_axis_off()
ISM_list.append('OTHER')
for (i, name) in enumerate(ISM_list):
row = (i % nrows)
col = (i // nrows)
y = (row * cell_height)
swatch_start_x = (cell_width * col)
swatch_end_x = ((cell_width * col) + swatch_width)
text_pos_x = (((cell_width * col) + swatch_width) + 50)
ax.text(text_pos_x, y, name, fontsize=14, fontname='monospace', horizontalalignment='left', verticalalignment='center')
ax.hlines(y, swatch_start_x, swatch_end_x, color=COLOR_DICT[name], linewidth=18)
plt.savefig('{}/COLOR_MAP.png'.format(out_dir), bbox_inches='tight', dpi=dpi)
plt.close(fig)<|docstring|>Plot color-ISM map for reference.
Adapted from https://matplotlib.org/3.1.0/gallery/color/named_colors.html<|endoftext|> |
322885f1718605efb901f8a58ed16f49cff0fa47ce62f95834a3364dfb3979e4 | def func(pct, allvals):
'\n covert to absolute value for pie chart plot.\n '
absolute = int(round(((pct / 100.0) * np.sum(allvals))))
return '{:d}'.format(absolute) | covert to absolute value for pie chart plot. | ncov_ism/_visualization.py | func | EESI/ncov_ism | 1 | python | def func(pct, allvals):
'\n \n '
absolute = int(round(((pct / 100.0) * np.sum(allvals))))
return '{:d}'.format(absolute) | def func(pct, allvals):
'\n \n '
absolute = int(round(((pct / 100.0) * np.sum(allvals))))
return '{:d}'.format(absolute)<|docstring|>covert to absolute value for pie chart plot.<|endoftext|> |
d435675463f2857358d6331f3c6f548d7b22d724ea9da202b1e7513df1905a49 | def plot_pie_chart(sizes, labels, colors, ax):
'\n plot pie chart\n Adapted from https://matplotlib.org/3.1.1/gallery/pie_and_polar_charts/pie_and_donut_labels.html#sphx-glr-gallery-pie-and-polar-charts-pie-and-donut-labels-py\n '
(wedges, texts, autotexts) = ax.pie(sizes, autopct=(lambda pct: func(pct, sizes)), colors=colors, textprops=dict(color='w'))
time_labels = [('-' if (label == 'OTHER') else label.split(' ')[1]) for label in labels]
ax.legend(wedges, time_labels, loc='lower left', bbox_to_anchor=(0.8, 0, 0.5, 1))
ax.axis('equal')
return (wedges, labels) | plot pie chart
Adapted from https://matplotlib.org/3.1.1/gallery/pie_and_polar_charts/pie_and_donut_labels.html#sphx-glr-gallery-pie-and-polar-charts-pie-and-donut-labels-py | ncov_ism/_visualization.py | plot_pie_chart | EESI/ncov_ism | 1 | python | def plot_pie_chart(sizes, labels, colors, ax):
'\n plot pie chart\n Adapted from https://matplotlib.org/3.1.1/gallery/pie_and_polar_charts/pie_and_donut_labels.html#sphx-glr-gallery-pie-and-polar-charts-pie-and-donut-labels-py\n '
(wedges, texts, autotexts) = ax.pie(sizes, autopct=(lambda pct: func(pct, sizes)), colors=colors, textprops=dict(color='w'))
time_labels = [('-' if (label == 'OTHER') else label.split(' ')[1]) for label in labels]
ax.legend(wedges, time_labels, loc='lower left', bbox_to_anchor=(0.8, 0, 0.5, 1))
ax.axis('equal')
return (wedges, labels) | def plot_pie_chart(sizes, labels, colors, ax):
'\n plot pie chart\n Adapted from https://matplotlib.org/3.1.1/gallery/pie_and_polar_charts/pie_and_donut_labels.html#sphx-glr-gallery-pie-and-polar-charts-pie-and-donut-labels-py\n '
(wedges, texts, autotexts) = ax.pie(sizes, autopct=(lambda pct: func(pct, sizes)), colors=colors, textprops=dict(color='w'))
time_labels = [('-' if (label == 'OTHER') else label.split(' ')[1]) for label in labels]
ax.legend(wedges, time_labels, loc='lower left', bbox_to_anchor=(0.8, 0, 0.5, 1))
ax.axis('equal')
return (wedges, labels)<|docstring|>plot pie chart
Adapted from https://matplotlib.org/3.1.1/gallery/pie_and_polar_charts/pie_and_donut_labels.html#sphx-glr-gallery-pie-and-polar-charts-pie-and-donut-labels-py<|endoftext|> |
b62972ad7758bcdc0d9935b23cb03feb7e2ce74346b09d6740a6ee87bc9961d1 | def regional_growth_plot(region, ISM_df, REFERENCE_date, count_list, date_list, COLOR_DICT, OUTPUT_FOLDER):
'\n time series plot for a region of interest\n '
xlim_len = (ISM_df[(ISM_df['country/region'] == region)]['date'].max().date() - REFERENCE_date).days
fig = plt.figure(figsize=(30, 15))
n = 4
ax = plt.subplot(1, 1, 1)
regional_total = []
ISM_regional_set = set([])
for i in range(len(count_list)):
regional_dict_freq = count_list[i][region]
regional_total.append(sum([regional_dict_freq[ISM][1] for ISM in regional_dict_freq]))
ISM_regional_set.update(regional_dict_freq.keys())
ISM_regional_list = []
for ISM in ISM_regional_set:
if (ISM != 'OTHER'):
ISM_regional_list.append(ISM)
NONOTHER = len(ISM_regional_list)
if ('OTHER' in ISM_regional_set):
ISM_regional_list.append('OTHER')
to_plot = []
ISM_to_plot_list = []
for ISM in ISM_regional_list:
ISM_regional_growth = []
for i in range(len(count_list)):
regional_dict_freq = count_list[i][region]
if ((ISM in regional_dict_freq) and (regional_dict_freq[ISM][1] != 0)):
ISM_regional_growth.append((regional_dict_freq[ISM][1] / regional_total[i]))
elif (ISM == 'OTHER'):
other_count = sum([regional_dict_freq[ISM][1] for ISM in regional_dict_freq if (ISM not in ISM_regional_set)])
if (regional_total[i] != 0):
ISM_regional_growth.append((other_count / regional_total[i]))
else:
ISM_regional_growth.append(0)
else:
ISM_regional_growth.append(0)
to_plot.append(ISM_regional_growth)
ISM_to_plot_list.append(ISM)
to_plot = np.row_stack(to_plot)
y_stack = np.cumsum(to_plot, axis=0)
x = np.arange(y_stack.shape[1])
for i in range(y_stack.shape[0]):
ISM = ISM_to_plot_list[i]
if (i == 0):
ax.fill_between(x, 0, y_stack[(i, :)], facecolor=COLOR_DICT[ISM], alpha=0.5, label=ISM)
else:
ax.fill_between(x, y_stack[(i - 1)], y_stack[(i, :)], facecolor=COLOR_DICT[ISM], alpha=0.5, label=ISM)
major_ticks = np.arange(0, len(date_list), 5)
minor_ticks = np.arange(0, len(date_list))
major_label = []
for i in major_ticks.tolist():
major_label.append(str(date_list[i]))
ax.set_xticks(minor_ticks, minor=True)
ax.set_xticks(major_ticks)
ax.set_xticklabels(major_label)
plt.setp(ax.get_xticklabels(), rotation=90)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
plt.legend(loc='lower left', bbox_to_anchor=(1, 0, 0.5, 1), prop={'family': monospace_font['fontname']})
plt.xlim([(- 1), xlim_len])
plt.ylabel('Relative abundance')
ax.grid(which='minor', alpha=0.3, linestyle='--')
ax.grid(which='major', alpha=0.8)
plt.savefig('{}/3_ISM_growth_{}.png'.format(OUTPUT_FOLDER, region), bbox_inches='tight')
plt.close(fig) | time series plot for a region of interest | ncov_ism/_visualization.py | regional_growth_plot | EESI/ncov_ism | 1 | python | def regional_growth_plot(region, ISM_df, REFERENCE_date, count_list, date_list, COLOR_DICT, OUTPUT_FOLDER):
'\n \n '
xlim_len = (ISM_df[(ISM_df['country/region'] == region)]['date'].max().date() - REFERENCE_date).days
fig = plt.figure(figsize=(30, 15))
n = 4
ax = plt.subplot(1, 1, 1)
regional_total = []
ISM_regional_set = set([])
for i in range(len(count_list)):
regional_dict_freq = count_list[i][region]
regional_total.append(sum([regional_dict_freq[ISM][1] for ISM in regional_dict_freq]))
ISM_regional_set.update(regional_dict_freq.keys())
ISM_regional_list = []
for ISM in ISM_regional_set:
if (ISM != 'OTHER'):
ISM_regional_list.append(ISM)
NONOTHER = len(ISM_regional_list)
if ('OTHER' in ISM_regional_set):
ISM_regional_list.append('OTHER')
to_plot = []
ISM_to_plot_list = []
for ISM in ISM_regional_list:
ISM_regional_growth = []
for i in range(len(count_list)):
regional_dict_freq = count_list[i][region]
if ((ISM in regional_dict_freq) and (regional_dict_freq[ISM][1] != 0)):
ISM_regional_growth.append((regional_dict_freq[ISM][1] / regional_total[i]))
elif (ISM == 'OTHER'):
other_count = sum([regional_dict_freq[ISM][1] for ISM in regional_dict_freq if (ISM not in ISM_regional_set)])
if (regional_total[i] != 0):
ISM_regional_growth.append((other_count / regional_total[i]))
else:
ISM_regional_growth.append(0)
else:
ISM_regional_growth.append(0)
to_plot.append(ISM_regional_growth)
ISM_to_plot_list.append(ISM)
to_plot = np.row_stack(to_plot)
y_stack = np.cumsum(to_plot, axis=0)
x = np.arange(y_stack.shape[1])
for i in range(y_stack.shape[0]):
ISM = ISM_to_plot_list[i]
if (i == 0):
ax.fill_between(x, 0, y_stack[(i, :)], facecolor=COLOR_DICT[ISM], alpha=0.5, label=ISM)
else:
ax.fill_between(x, y_stack[(i - 1)], y_stack[(i, :)], facecolor=COLOR_DICT[ISM], alpha=0.5, label=ISM)
major_ticks = np.arange(0, len(date_list), 5)
minor_ticks = np.arange(0, len(date_list))
major_label = []
for i in major_ticks.tolist():
major_label.append(str(date_list[i]))
ax.set_xticks(minor_ticks, minor=True)
ax.set_xticks(major_ticks)
ax.set_xticklabels(major_label)
plt.setp(ax.get_xticklabels(), rotation=90)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
plt.legend(loc='lower left', bbox_to_anchor=(1, 0, 0.5, 1), prop={'family': monospace_font['fontname']})
plt.xlim([(- 1), xlim_len])
plt.ylabel('Relative abundance')
ax.grid(which='minor', alpha=0.3, linestyle='--')
ax.grid(which='major', alpha=0.8)
plt.savefig('{}/3_ISM_growth_{}.png'.format(OUTPUT_FOLDER, region), bbox_inches='tight')
plt.close(fig) | def regional_growth_plot(region, ISM_df, REFERENCE_date, count_list, date_list, COLOR_DICT, OUTPUT_FOLDER):
'\n \n '
xlim_len = (ISM_df[(ISM_df['country/region'] == region)]['date'].max().date() - REFERENCE_date).days
fig = plt.figure(figsize=(30, 15))
n = 4
ax = plt.subplot(1, 1, 1)
regional_total = []
ISM_regional_set = set([])
for i in range(len(count_list)):
regional_dict_freq = count_list[i][region]
regional_total.append(sum([regional_dict_freq[ISM][1] for ISM in regional_dict_freq]))
ISM_regional_set.update(regional_dict_freq.keys())
ISM_regional_list = []
for ISM in ISM_regional_set:
if (ISM != 'OTHER'):
ISM_regional_list.append(ISM)
NONOTHER = len(ISM_regional_list)
if ('OTHER' in ISM_regional_set):
ISM_regional_list.append('OTHER')
to_plot = []
ISM_to_plot_list = []
for ISM in ISM_regional_list:
ISM_regional_growth = []
for i in range(len(count_list)):
regional_dict_freq = count_list[i][region]
if ((ISM in regional_dict_freq) and (regional_dict_freq[ISM][1] != 0)):
ISM_regional_growth.append((regional_dict_freq[ISM][1] / regional_total[i]))
elif (ISM == 'OTHER'):
other_count = sum([regional_dict_freq[ISM][1] for ISM in regional_dict_freq if (ISM not in ISM_regional_set)])
if (regional_total[i] != 0):
ISM_regional_growth.append((other_count / regional_total[i]))
else:
ISM_regional_growth.append(0)
else:
ISM_regional_growth.append(0)
to_plot.append(ISM_regional_growth)
ISM_to_plot_list.append(ISM)
to_plot = np.row_stack(to_plot)
y_stack = np.cumsum(to_plot, axis=0)
x = np.arange(y_stack.shape[1])
for i in range(y_stack.shape[0]):
ISM = ISM_to_plot_list[i]
if (i == 0):
ax.fill_between(x, 0, y_stack[(i, :)], facecolor=COLOR_DICT[ISM], alpha=0.5, label=ISM)
else:
ax.fill_between(x, y_stack[(i - 1)], y_stack[(i, :)], facecolor=COLOR_DICT[ISM], alpha=0.5, label=ISM)
major_ticks = np.arange(0, len(date_list), 5)
minor_ticks = np.arange(0, len(date_list))
major_label = []
for i in major_ticks.tolist():
major_label.append(str(date_list[i]))
ax.set_xticks(minor_ticks, minor=True)
ax.set_xticks(major_ticks)
ax.set_xticklabels(major_label)
plt.setp(ax.get_xticklabels(), rotation=90)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
plt.legend(loc='lower left', bbox_to_anchor=(1, 0, 0.5, 1), prop={'family': monospace_font['fontname']})
plt.xlim([(- 1), xlim_len])
plt.ylabel('Relative abundance')
ax.grid(which='minor', alpha=0.3, linestyle='--')
ax.grid(which='major', alpha=0.8)
plt.savefig('{}/3_ISM_growth_{}.png'.format(OUTPUT_FOLDER, region), bbox_inches='tight')
plt.close(fig)<|docstring|>time series plot for a region of interest<|endoftext|> |
52fe005bf3f19ce8d5466ed0bf1d8c4497c829ae8302ee76e4242e3e69589cb3 | def ISM_plot(ISM_df, ISM_set, region_list, region_pie_chart, state_list, state_pie_chart, REFERENCE_date, time_series_region_list, count_list, date_list, OUTPUT_FOLDER):
'\n Generate figures for ISM analysis.\n '
ISM_index = {}
idx = 0
for (ISM, counts) in ISM_df['ISM'].value_counts().items():
ISM_index[ISM] = idx
idx += 1
logging.info('{} ISMs will show up in the visualizations'.format(len(ISM_set)))
ISM_list = []
for ISM in ISM_set:
if (ISM == 'OTHER'):
continue
ISM_list.append((ISM, ISM_index[ISM]))
ISM_list = sorted(ISM_list, key=(lambda x: x[1]))
ISM_list = [item[0] for item in ISM_list]
color_map = get_color_names(CSS4_COLORS, len(ISM_list))
COLOR_DICT = {}
for (idx, ISM) in enumerate(ISM_list):
COLOR_DICT[ISM] = color_map[idx]
COLOR_DICT['OTHER'] = 'gray'
pickle.dump(COLOR_DICT, open('COLOR_DICT.pkl', 'wb'))
global_color_map(COLOR_DICT, ISM_list, OUTPUT_FOLDER)
DPI = 100
fig = plt.figure(figsize=(25, 15))
wedges_list = []
for (idx, region) in enumerate(region_list):
dict_freq = region_pie_chart[region]
total = sum([dict_freq[ISM][1] for ISM in dict_freq])
labels = []
sizes = []
colors = []
for ISM in dict_freq:
if (ISM == 'OTHER'):
continue
labels.append('{}: {}'.format(ISM, dict_freq[ISM][0]))
colors.append(COLOR_DICT[ISM])
sizes.append(dict_freq[ISM][1])
if ('OTHER' in dict_freq):
labels.append('OTHER')
colors.append(COLOR_DICT['OTHER'])
sizes.append(dict_freq['OTHER'][1])
ax = plt.subplot(5, 5, (idx + 1))
(wedges, labels) = plot_pie_chart(sizes, labels, colors, ax)
ax.set_title(region)
wedges_list.append((wedges, labels))
labels_handles = {}
handles_OTHER = None
for (wedges, labels) in wedges_list:
for (idx, label) in enumerate(labels):
label = label.split(':')[0]
if (label == 'OTHER'):
handles_OTHER = [wedges[idx], label]
continue
if (label not in labels_handles):
labels_handles[label] = wedges[idx]
if handles_OTHER:
handles_list = (list(labels_handles.values()) + [handles_OTHER[0]])
labels_list = (list(labels_handles.keys()) + [handles_OTHER[1]])
fig.legend(handles_list, labels_list, bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
else:
fig.legend(labels_handles.values(), labels_handles.keys(), bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
plt.savefig('{}/1_regional_ISM.png'.format(OUTPUT_FOLDER), bbox_inches='tight', dpi=DPI, transparent=True)
plt.close(fig)
fig = plt.figure(figsize=(25, 20))
subplot_y = int(np.sqrt(len(state_list)))
subplot_x = (int(np.sqrt(len(state_list))) + 1)
if ((subplot_x * subplot_y) < len(state_list)):
subplot_y = subplot_x
wedges_list = []
for (idx, state) in enumerate(state_list):
dict_freq = state_pie_chart[state]
total = sum([dict_freq[ISM][1] for ISM in dict_freq])
labels = []
sizes = []
colors = []
for ISM in dict_freq:
if (ISM == 'OTHER'):
continue
labels.append('{}: {}'.format(ISM, dict_freq[ISM][0]))
colors.append(COLOR_DICT[ISM])
sizes.append(dict_freq[ISM][1])
if ('OTHER' in dict_freq):
labels.append('OTHER')
colors.append(COLOR_DICT['OTHER'])
sizes.append(dict_freq['OTHER'][1])
ax = plt.subplot(subplot_x, subplot_y, (idx + 1))
(wedges, labels) = plot_pie_chart(sizes, labels, colors, ax)
ax.set_title(state)
wedges_list.append((wedges, labels))
labels_handles = {}
handles_OTHER = None
for (wedges, labels) in wedges_list:
for (idx, label) in enumerate(labels):
label = label.split(':')[0]
if (label == 'OTHER'):
handles_OTHER = [wedges[idx], label]
continue
if (label not in labels_handles):
labels_handles[label] = wedges[idx]
if handles_OTHER:
handles_list = (list(labels_handles.values()) + [handles_OTHER[0]])
labels_list = (list(labels_handles.keys()) + [handles_OTHER[1]])
fig.legend(handles_list, labels_list, bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
else:
fig.legend(labels_handles.values(), labels_handles.keys(), bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
plt.savefig('{}/2_intra-US_ISM.png'.format(OUTPUT_FOLDER), bbox_inches='tight', dpi=DPI, transparent=True)
plt.close(fig)
font = {'family': 'sans-serif', 'size': 25}
matplotlib.rc('font', **font)
for region in time_series_region_list:
regional_growth_plot(region, ISM_df, REFERENCE_date, count_list, date_list, COLOR_DICT, OUTPUT_FOLDER) | Generate figures for ISM analysis. | ncov_ism/_visualization.py | ISM_plot | EESI/ncov_ism | 1 | python | def ISM_plot(ISM_df, ISM_set, region_list, region_pie_chart, state_list, state_pie_chart, REFERENCE_date, time_series_region_list, count_list, date_list, OUTPUT_FOLDER):
'\n \n '
ISM_index = {}
idx = 0
for (ISM, counts) in ISM_df['ISM'].value_counts().items():
ISM_index[ISM] = idx
idx += 1
logging.info('{} ISMs will show up in the visualizations'.format(len(ISM_set)))
ISM_list = []
for ISM in ISM_set:
if (ISM == 'OTHER'):
continue
ISM_list.append((ISM, ISM_index[ISM]))
ISM_list = sorted(ISM_list, key=(lambda x: x[1]))
ISM_list = [item[0] for item in ISM_list]
color_map = get_color_names(CSS4_COLORS, len(ISM_list))
COLOR_DICT = {}
for (idx, ISM) in enumerate(ISM_list):
COLOR_DICT[ISM] = color_map[idx]
COLOR_DICT['OTHER'] = 'gray'
pickle.dump(COLOR_DICT, open('COLOR_DICT.pkl', 'wb'))
global_color_map(COLOR_DICT, ISM_list, OUTPUT_FOLDER)
DPI = 100
fig = plt.figure(figsize=(25, 15))
wedges_list = []
for (idx, region) in enumerate(region_list):
dict_freq = region_pie_chart[region]
total = sum([dict_freq[ISM][1] for ISM in dict_freq])
labels = []
sizes = []
colors = []
for ISM in dict_freq:
if (ISM == 'OTHER'):
continue
labels.append('{}: {}'.format(ISM, dict_freq[ISM][0]))
colors.append(COLOR_DICT[ISM])
sizes.append(dict_freq[ISM][1])
if ('OTHER' in dict_freq):
labels.append('OTHER')
colors.append(COLOR_DICT['OTHER'])
sizes.append(dict_freq['OTHER'][1])
ax = plt.subplot(5, 5, (idx + 1))
(wedges, labels) = plot_pie_chart(sizes, labels, colors, ax)
ax.set_title(region)
wedges_list.append((wedges, labels))
labels_handles = {}
handles_OTHER = None
for (wedges, labels) in wedges_list:
for (idx, label) in enumerate(labels):
label = label.split(':')[0]
if (label == 'OTHER'):
handles_OTHER = [wedges[idx], label]
continue
if (label not in labels_handles):
labels_handles[label] = wedges[idx]
if handles_OTHER:
handles_list = (list(labels_handles.values()) + [handles_OTHER[0]])
labels_list = (list(labels_handles.keys()) + [handles_OTHER[1]])
fig.legend(handles_list, labels_list, bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
else:
fig.legend(labels_handles.values(), labels_handles.keys(), bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
plt.savefig('{}/1_regional_ISM.png'.format(OUTPUT_FOLDER), bbox_inches='tight', dpi=DPI, transparent=True)
plt.close(fig)
fig = plt.figure(figsize=(25, 20))
subplot_y = int(np.sqrt(len(state_list)))
subplot_x = (int(np.sqrt(len(state_list))) + 1)
if ((subplot_x * subplot_y) < len(state_list)):
subplot_y = subplot_x
wedges_list = []
for (idx, state) in enumerate(state_list):
dict_freq = state_pie_chart[state]
total = sum([dict_freq[ISM][1] for ISM in dict_freq])
labels = []
sizes = []
colors = []
for ISM in dict_freq:
if (ISM == 'OTHER'):
continue
labels.append('{}: {}'.format(ISM, dict_freq[ISM][0]))
colors.append(COLOR_DICT[ISM])
sizes.append(dict_freq[ISM][1])
if ('OTHER' in dict_freq):
labels.append('OTHER')
colors.append(COLOR_DICT['OTHER'])
sizes.append(dict_freq['OTHER'][1])
ax = plt.subplot(subplot_x, subplot_y, (idx + 1))
(wedges, labels) = plot_pie_chart(sizes, labels, colors, ax)
ax.set_title(state)
wedges_list.append((wedges, labels))
labels_handles = {}
handles_OTHER = None
for (wedges, labels) in wedges_list:
for (idx, label) in enumerate(labels):
label = label.split(':')[0]
if (label == 'OTHER'):
handles_OTHER = [wedges[idx], label]
continue
if (label not in labels_handles):
labels_handles[label] = wedges[idx]
if handles_OTHER:
handles_list = (list(labels_handles.values()) + [handles_OTHER[0]])
labels_list = (list(labels_handles.keys()) + [handles_OTHER[1]])
fig.legend(handles_list, labels_list, bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
else:
fig.legend(labels_handles.values(), labels_handles.keys(), bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
plt.savefig('{}/2_intra-US_ISM.png'.format(OUTPUT_FOLDER), bbox_inches='tight', dpi=DPI, transparent=True)
plt.close(fig)
font = {'family': 'sans-serif', 'size': 25}
matplotlib.rc('font', **font)
for region in time_series_region_list:
regional_growth_plot(region, ISM_df, REFERENCE_date, count_list, date_list, COLOR_DICT, OUTPUT_FOLDER) | def ISM_plot(ISM_df, ISM_set, region_list, region_pie_chart, state_list, state_pie_chart, REFERENCE_date, time_series_region_list, count_list, date_list, OUTPUT_FOLDER):
'\n \n '
ISM_index = {}
idx = 0
for (ISM, counts) in ISM_df['ISM'].value_counts().items():
ISM_index[ISM] = idx
idx += 1
logging.info('{} ISMs will show up in the visualizations'.format(len(ISM_set)))
ISM_list = []
for ISM in ISM_set:
if (ISM == 'OTHER'):
continue
ISM_list.append((ISM, ISM_index[ISM]))
ISM_list = sorted(ISM_list, key=(lambda x: x[1]))
ISM_list = [item[0] for item in ISM_list]
color_map = get_color_names(CSS4_COLORS, len(ISM_list))
COLOR_DICT = {}
for (idx, ISM) in enumerate(ISM_list):
COLOR_DICT[ISM] = color_map[idx]
COLOR_DICT['OTHER'] = 'gray'
pickle.dump(COLOR_DICT, open('COLOR_DICT.pkl', 'wb'))
global_color_map(COLOR_DICT, ISM_list, OUTPUT_FOLDER)
DPI = 100
fig = plt.figure(figsize=(25, 15))
wedges_list = []
for (idx, region) in enumerate(region_list):
dict_freq = region_pie_chart[region]
total = sum([dict_freq[ISM][1] for ISM in dict_freq])
labels = []
sizes = []
colors = []
for ISM in dict_freq:
if (ISM == 'OTHER'):
continue
labels.append('{}: {}'.format(ISM, dict_freq[ISM][0]))
colors.append(COLOR_DICT[ISM])
sizes.append(dict_freq[ISM][1])
if ('OTHER' in dict_freq):
labels.append('OTHER')
colors.append(COLOR_DICT['OTHER'])
sizes.append(dict_freq['OTHER'][1])
ax = plt.subplot(5, 5, (idx + 1))
(wedges, labels) = plot_pie_chart(sizes, labels, colors, ax)
ax.set_title(region)
wedges_list.append((wedges, labels))
labels_handles = {}
handles_OTHER = None
for (wedges, labels) in wedges_list:
for (idx, label) in enumerate(labels):
label = label.split(':')[0]
if (label == 'OTHER'):
handles_OTHER = [wedges[idx], label]
continue
if (label not in labels_handles):
labels_handles[label] = wedges[idx]
if handles_OTHER:
handles_list = (list(labels_handles.values()) + [handles_OTHER[0]])
labels_list = (list(labels_handles.keys()) + [handles_OTHER[1]])
fig.legend(handles_list, labels_list, bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
else:
fig.legend(labels_handles.values(), labels_handles.keys(), bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
plt.savefig('{}/1_regional_ISM.png'.format(OUTPUT_FOLDER), bbox_inches='tight', dpi=DPI, transparent=True)
plt.close(fig)
fig = plt.figure(figsize=(25, 20))
subplot_y = int(np.sqrt(len(state_list)))
subplot_x = (int(np.sqrt(len(state_list))) + 1)
if ((subplot_x * subplot_y) < len(state_list)):
subplot_y = subplot_x
wedges_list = []
for (idx, state) in enumerate(state_list):
dict_freq = state_pie_chart[state]
total = sum([dict_freq[ISM][1] for ISM in dict_freq])
labels = []
sizes = []
colors = []
for ISM in dict_freq:
if (ISM == 'OTHER'):
continue
labels.append('{}: {}'.format(ISM, dict_freq[ISM][0]))
colors.append(COLOR_DICT[ISM])
sizes.append(dict_freq[ISM][1])
if ('OTHER' in dict_freq):
labels.append('OTHER')
colors.append(COLOR_DICT['OTHER'])
sizes.append(dict_freq['OTHER'][1])
ax = plt.subplot(subplot_x, subplot_y, (idx + 1))
(wedges, labels) = plot_pie_chart(sizes, labels, colors, ax)
ax.set_title(state)
wedges_list.append((wedges, labels))
labels_handles = {}
handles_OTHER = None
for (wedges, labels) in wedges_list:
for (idx, label) in enumerate(labels):
label = label.split(':')[0]
if (label == 'OTHER'):
handles_OTHER = [wedges[idx], label]
continue
if (label not in labels_handles):
labels_handles[label] = wedges[idx]
if handles_OTHER:
handles_list = (list(labels_handles.values()) + [handles_OTHER[0]])
labels_list = (list(labels_handles.keys()) + [handles_OTHER[1]])
fig.legend(handles_list, labels_list, bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
else:
fig.legend(labels_handles.values(), labels_handles.keys(), bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
plt.savefig('{}/2_intra-US_ISM.png'.format(OUTPUT_FOLDER), bbox_inches='tight', dpi=DPI, transparent=True)
plt.close(fig)
font = {'family': 'sans-serif', 'size': 25}
matplotlib.rc('font', **font)
for region in time_series_region_list:
regional_growth_plot(region, ISM_df, REFERENCE_date, count_list, date_list, COLOR_DICT, OUTPUT_FOLDER)<|docstring|>Generate figures for ISM analysis.<|endoftext|> |
d1808d47d6b6ec6e78b583adb72990c0ad7e26902599c77abaae4cd293e92a6f | def customized_ISM_plot(ISM_df, ISM_set, region_list, region_pie_chart, REFERENCE_date, count_list, date_list, OUTPUT_FOLDER):
'\n Generate figures for ISM analysis.\n '
ISM_index = {}
idx = 0
for (ISM, counts) in ISM_df['ISM'].value_counts().items():
ISM_index[ISM] = idx
idx += 1
logging.info('{} ISMs will show up in the visualizations'.format(len(ISM_set)))
ISM_list = []
for ISM in ISM_set:
if (ISM == 'OTHER'):
continue
ISM_list.append((ISM, ISM_index[ISM]))
ISM_list = sorted(ISM_list, key=(lambda x: x[1]))
ISM_list = [item[0] for item in ISM_list]
color_map = get_color_names(CSS4_COLORS, len(ISM_list))
COLOR_DICT = {}
for (idx, ISM) in enumerate(ISM_list):
COLOR_DICT[ISM] = color_map[idx]
COLOR_DICT['OTHER'] = 'gray'
pickle.dump(COLOR_DICT, open('COLOR_DICT.pkl', 'wb'))
global_color_map(COLOR_DICT, ISM_list, OUTPUT_FOLDER)
DPI = 100
fig = plt.figure(figsize=(25, 15))
wedges_list = []
for (idx, region) in enumerate(region_list):
dict_freq = region_pie_chart[region]
total = sum([dict_freq[ISM][1] for ISM in dict_freq])
labels = []
sizes = []
colors = []
for ISM in dict_freq:
if (ISM == 'OTHER'):
continue
labels.append('{}: {}'.format(ISM, dict_freq[ISM][0]))
colors.append(COLOR_DICT[ISM])
sizes.append(dict_freq[ISM][1])
if ('OTHER' in dict_freq):
labels.append('OTHER')
colors.append(COLOR_DICT['OTHER'])
sizes.append(dict_freq['OTHER'][1])
ax = plt.subplot(5, 5, (idx + 1))
(wedges, labels) = plot_pie_chart(sizes, labels, colors, ax)
ax.set_title(region)
wedges_list.append((wedges, labels))
labels_handles = {}
handles_OTHER = None
for (wedges, labels) in wedges_list:
for (idx, label) in enumerate(labels):
label = label.split(':')[0]
if (label == 'OTHER'):
handles_OTHER = [wedges[idx], label]
continue
if (label not in labels_handles):
labels_handles[label] = wedges[idx]
if handles_OTHER:
handles_list = (list(labels_handles.values()) + [handles_OTHER[0]])
labels_list = (list(labels_handles.keys()) + [handles_OTHER[1]])
fig.legend(handles_list, labels_list, bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
else:
fig.legend(labels_handles.values(), labels_handles.keys(), bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
plt.savefig('{}/1_regional_ISM.png'.format(OUTPUT_FOLDER), bbox_inches='tight', dpi=DPI, transparent=True)
plt.close(fig)
font = {'family': 'sans-serif', 'size': 25}
matplotlib.rc('font', **font)
for region in region_list:
regional_growth_plot(region, ISM_df, REFERENCE_date, count_list, date_list, COLOR_DICT, OUTPUT_FOLDER) | Generate figures for ISM analysis. | ncov_ism/_visualization.py | customized_ISM_plot | EESI/ncov_ism | 1 | python | def customized_ISM_plot(ISM_df, ISM_set, region_list, region_pie_chart, REFERENCE_date, count_list, date_list, OUTPUT_FOLDER):
'\n \n '
ISM_index = {}
idx = 0
for (ISM, counts) in ISM_df['ISM'].value_counts().items():
ISM_index[ISM] = idx
idx += 1
logging.info('{} ISMs will show up in the visualizations'.format(len(ISM_set)))
ISM_list = []
for ISM in ISM_set:
if (ISM == 'OTHER'):
continue
ISM_list.append((ISM, ISM_index[ISM]))
ISM_list = sorted(ISM_list, key=(lambda x: x[1]))
ISM_list = [item[0] for item in ISM_list]
color_map = get_color_names(CSS4_COLORS, len(ISM_list))
COLOR_DICT = {}
for (idx, ISM) in enumerate(ISM_list):
COLOR_DICT[ISM] = color_map[idx]
COLOR_DICT['OTHER'] = 'gray'
pickle.dump(COLOR_DICT, open('COLOR_DICT.pkl', 'wb'))
global_color_map(COLOR_DICT, ISM_list, OUTPUT_FOLDER)
DPI = 100
fig = plt.figure(figsize=(25, 15))
wedges_list = []
for (idx, region) in enumerate(region_list):
dict_freq = region_pie_chart[region]
total = sum([dict_freq[ISM][1] for ISM in dict_freq])
labels = []
sizes = []
colors = []
for ISM in dict_freq:
if (ISM == 'OTHER'):
continue
labels.append('{}: {}'.format(ISM, dict_freq[ISM][0]))
colors.append(COLOR_DICT[ISM])
sizes.append(dict_freq[ISM][1])
if ('OTHER' in dict_freq):
labels.append('OTHER')
colors.append(COLOR_DICT['OTHER'])
sizes.append(dict_freq['OTHER'][1])
ax = plt.subplot(5, 5, (idx + 1))
(wedges, labels) = plot_pie_chart(sizes, labels, colors, ax)
ax.set_title(region)
wedges_list.append((wedges, labels))
labels_handles = {}
handles_OTHER = None
for (wedges, labels) in wedges_list:
for (idx, label) in enumerate(labels):
label = label.split(':')[0]
if (label == 'OTHER'):
handles_OTHER = [wedges[idx], label]
continue
if (label not in labels_handles):
labels_handles[label] = wedges[idx]
if handles_OTHER:
handles_list = (list(labels_handles.values()) + [handles_OTHER[0]])
labels_list = (list(labels_handles.keys()) + [handles_OTHER[1]])
fig.legend(handles_list, labels_list, bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
else:
fig.legend(labels_handles.values(), labels_handles.keys(), bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
plt.savefig('{}/1_regional_ISM.png'.format(OUTPUT_FOLDER), bbox_inches='tight', dpi=DPI, transparent=True)
plt.close(fig)
font = {'family': 'sans-serif', 'size': 25}
matplotlib.rc('font', **font)
for region in region_list:
regional_growth_plot(region, ISM_df, REFERENCE_date, count_list, date_list, COLOR_DICT, OUTPUT_FOLDER) | def customized_ISM_plot(ISM_df, ISM_set, region_list, region_pie_chart, REFERENCE_date, count_list, date_list, OUTPUT_FOLDER):
'\n \n '
ISM_index = {}
idx = 0
for (ISM, counts) in ISM_df['ISM'].value_counts().items():
ISM_index[ISM] = idx
idx += 1
logging.info('{} ISMs will show up in the visualizations'.format(len(ISM_set)))
ISM_list = []
for ISM in ISM_set:
if (ISM == 'OTHER'):
continue
ISM_list.append((ISM, ISM_index[ISM]))
ISM_list = sorted(ISM_list, key=(lambda x: x[1]))
ISM_list = [item[0] for item in ISM_list]
color_map = get_color_names(CSS4_COLORS, len(ISM_list))
COLOR_DICT = {}
for (idx, ISM) in enumerate(ISM_list):
COLOR_DICT[ISM] = color_map[idx]
COLOR_DICT['OTHER'] = 'gray'
pickle.dump(COLOR_DICT, open('COLOR_DICT.pkl', 'wb'))
global_color_map(COLOR_DICT, ISM_list, OUTPUT_FOLDER)
DPI = 100
fig = plt.figure(figsize=(25, 15))
wedges_list = []
for (idx, region) in enumerate(region_list):
dict_freq = region_pie_chart[region]
total = sum([dict_freq[ISM][1] for ISM in dict_freq])
labels = []
sizes = []
colors = []
for ISM in dict_freq:
if (ISM == 'OTHER'):
continue
labels.append('{}: {}'.format(ISM, dict_freq[ISM][0]))
colors.append(COLOR_DICT[ISM])
sizes.append(dict_freq[ISM][1])
if ('OTHER' in dict_freq):
labels.append('OTHER')
colors.append(COLOR_DICT['OTHER'])
sizes.append(dict_freq['OTHER'][1])
ax = plt.subplot(5, 5, (idx + 1))
(wedges, labels) = plot_pie_chart(sizes, labels, colors, ax)
ax.set_title(region)
wedges_list.append((wedges, labels))
labels_handles = {}
handles_OTHER = None
for (wedges, labels) in wedges_list:
for (idx, label) in enumerate(labels):
label = label.split(':')[0]
if (label == 'OTHER'):
handles_OTHER = [wedges[idx], label]
continue
if (label not in labels_handles):
labels_handles[label] = wedges[idx]
if handles_OTHER:
handles_list = (list(labels_handles.values()) + [handles_OTHER[0]])
labels_list = (list(labels_handles.keys()) + [handles_OTHER[1]])
fig.legend(handles_list, labels_list, bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
else:
fig.legend(labels_handles.values(), labels_handles.keys(), bbox_to_anchor=(0.82, 0.25), bbox_transform=plt.gcf().transFigure, ncol=5, prop={'family': monospace_font['fontname']})
plt.savefig('{}/1_regional_ISM.png'.format(OUTPUT_FOLDER), bbox_inches='tight', dpi=DPI, transparent=True)
plt.close(fig)
font = {'family': 'sans-serif', 'size': 25}
matplotlib.rc('font', **font)
for region in region_list:
regional_growth_plot(region, ISM_df, REFERENCE_date, count_list, date_list, COLOR_DICT, OUTPUT_FOLDER)<|docstring|>Generate figures for ISM analysis.<|endoftext|> |
0ec1e52e95b27382268e418e714eaba844f2efe693f4f4bbfe3aa9b87a0680e6 | def apply_to_boxes(self, evaluation):
'System`MakeBoxes[System`CustomAtom, StandardForm|TraditionalForm|OutputForm|InputForm]'
return CustomBoxConstruct(evaluation=evaluation) | System`MakeBoxes[System`CustomAtom, StandardForm|TraditionalForm|OutputForm|InputForm] | test/test_custom_boxconstruct.py | apply_to_boxes | lambdaxymox/Mathics | 1,920 | python | def apply_to_boxes(self, evaluation):
return CustomBoxConstruct(evaluation=evaluation) | def apply_to_boxes(self, evaluation):
return CustomBoxConstruct(evaluation=evaluation)<|docstring|>System`MakeBoxes[System`CustomAtom, StandardForm|TraditionalForm|OutputForm|InputForm]<|endoftext|> |
005edf5b5a093f69043152a2f0c457ff45019dc62da85931c76e37780bf8eff6 | def apply_box(self, elems, evaluation, options):
'System`MakeBoxes[System`Graphics[elems_, System`OptionsPattern[System`Graphics]],\n System`StandardForm|System`TraditionalForm|System`OutputForm]'
instance = CustomGraphicsBox(*elems._leaves, evaluation=evaluation)
return instance | System`MakeBoxes[System`Graphics[elems_, System`OptionsPattern[System`Graphics]],
System`StandardForm|System`TraditionalForm|System`OutputForm] | test/test_custom_boxconstruct.py | apply_box | lambdaxymox/Mathics | 1,920 | python | def apply_box(self, elems, evaluation, options):
'System`MakeBoxes[System`Graphics[elems_, System`OptionsPattern[System`Graphics]],\n System`StandardForm|System`TraditionalForm|System`OutputForm]'
instance = CustomGraphicsBox(*elems._leaves, evaluation=evaluation)
return instance | def apply_box(self, elems, evaluation, options):
'System`MakeBoxes[System`Graphics[elems_, System`OptionsPattern[System`Graphics]],\n System`StandardForm|System`TraditionalForm|System`OutputForm]'
instance = CustomGraphicsBox(*elems._leaves, evaluation=evaluation)
return instance<|docstring|>System`MakeBoxes[System`Graphics[elems_, System`OptionsPattern[System`Graphics]],
System`StandardForm|System`TraditionalForm|System`OutputForm]<|endoftext|> |
f8d10f3cf870d4ee0165db2b53839a324cd1f7fa67a93d6158f09954abc56917 | def test_check_n_jobs():
'Test check_n_jobs function..\n '
n_jobs_valid = 1
n_jobs_safe = check_n_jobs(n_jobs_valid)
assert_equal(n_jobs_valid, n_jobs_safe)
n_jobs_large = 100000000
n_jobs_safe = check_n_jobs(n_jobs_large)
assert_true((n_jobs_safe < n_jobs_large))
assert_true((n_jobs_safe >= 1))
n_jobs_not_enough = (- 100000000)
n_jobs_safe = check_n_jobs(n_jobs_not_enough)
assert_equal(n_jobs_safe, 1)
n_jobs = 0
assert_raises(ValueError, check_n_jobs, n_jobs) | Test check_n_jobs function.. | nilearn_sandbox/tests/test_common_checks.py | test_check_n_jobs | KamalakerDadi/nilearn_sandbox | 1 | python | def test_check_n_jobs():
'\n '
n_jobs_valid = 1
n_jobs_safe = check_n_jobs(n_jobs_valid)
assert_equal(n_jobs_valid, n_jobs_safe)
n_jobs_large = 100000000
n_jobs_safe = check_n_jobs(n_jobs_large)
assert_true((n_jobs_safe < n_jobs_large))
assert_true((n_jobs_safe >= 1))
n_jobs_not_enough = (- 100000000)
n_jobs_safe = check_n_jobs(n_jobs_not_enough)
assert_equal(n_jobs_safe, 1)
n_jobs = 0
assert_raises(ValueError, check_n_jobs, n_jobs) | def test_check_n_jobs():
'\n '
n_jobs_valid = 1
n_jobs_safe = check_n_jobs(n_jobs_valid)
assert_equal(n_jobs_valid, n_jobs_safe)
n_jobs_large = 100000000
n_jobs_safe = check_n_jobs(n_jobs_large)
assert_true((n_jobs_safe < n_jobs_large))
assert_true((n_jobs_safe >= 1))
n_jobs_not_enough = (- 100000000)
n_jobs_safe = check_n_jobs(n_jobs_not_enough)
assert_equal(n_jobs_safe, 1)
n_jobs = 0
assert_raises(ValueError, check_n_jobs, n_jobs)<|docstring|>Test check_n_jobs function..<|endoftext|> |
bb796ebaff3587a5e5eeec0b88c78df8123e2cdef39cc8f123a8c2cf203d86a4 | def get_basename_root(path):
'Return the extensionless basename of the file described by ``path``.\n\n Example:\n name = get_basename_root("/path/to/file.json")\n name == "file" # true\n\n :param path: A file path.\n :type path: str\n :returns: str\n\n '
(name, _) = os.path.splitext(os.path.basename(path))
return name | Return the extensionless basename of the file described by ``path``.
Example:
name = get_basename_root("/path/to/file.json")
name == "file" # true
:param path: A file path.
:type path: str
:returns: str | integration_tests/steps/compilation.py | get_basename_root | Grindizer/ptolemy | 1 | python | def get_basename_root(path):
'Return the extensionless basename of the file described by ``path``.\n\n Example:\n name = get_basename_root("/path/to/file.json")\n name == "file" # true\n\n :param path: A file path.\n :type path: str\n :returns: str\n\n '
(name, _) = os.path.splitext(os.path.basename(path))
return name | def get_basename_root(path):
'Return the extensionless basename of the file described by ``path``.\n\n Example:\n name = get_basename_root("/path/to/file.json")\n name == "file" # true\n\n :param path: A file path.\n :type path: str\n :returns: str\n\n '
(name, _) = os.path.splitext(os.path.basename(path))
return name<|docstring|>Return the extensionless basename of the file described by ``path``.
Example:
name = get_basename_root("/path/to/file.json")
name == "file" # true
:param path: A file path.
:type path: str
:returns: str<|endoftext|> |
80907e49651d10629c51df6c63e9f0a208a22f7494928695a9699da955d658a7 | def __init__(self, networkSecurityGroupId=None, networkSecurityGroupName=None, description=None, vpcId=None, securityGroupRules=None, createdTime=None):
'\n :param networkSecurityGroupId: (Optional) 安全组ID\n :param networkSecurityGroupName: (Optional) 安全组名称\n :param description: (Optional) 安全组描述信息\n :param vpcId: (Optional) 安全组所在vpc的Id\n :param securityGroupRules: (Optional) 安全组规则信息\n :param createdTime: (Optional) 安全组创建时间\n '
self.networkSecurityGroupId = networkSecurityGroupId
self.networkSecurityGroupName = networkSecurityGroupName
self.description = description
self.vpcId = vpcId
self.securityGroupRules = securityGroupRules
self.createdTime = createdTime | :param networkSecurityGroupId: (Optional) 安全组ID
:param networkSecurityGroupName: (Optional) 安全组名称
:param description: (Optional) 安全组描述信息
:param vpcId: (Optional) 安全组所在vpc的Id
:param securityGroupRules: (Optional) 安全组规则信息
:param createdTime: (Optional) 安全组创建时间 | jdcloud_sdk/services/vpc/models/NetworkSecurityGroup.py | __init__ | lidaobing/jdcloud-sdk-python | 0 | python | def __init__(self, networkSecurityGroupId=None, networkSecurityGroupName=None, description=None, vpcId=None, securityGroupRules=None, createdTime=None):
'\n :param networkSecurityGroupId: (Optional) 安全组ID\n :param networkSecurityGroupName: (Optional) 安全组名称\n :param description: (Optional) 安全组描述信息\n :param vpcId: (Optional) 安全组所在vpc的Id\n :param securityGroupRules: (Optional) 安全组规则信息\n :param createdTime: (Optional) 安全组创建时间\n '
self.networkSecurityGroupId = networkSecurityGroupId
self.networkSecurityGroupName = networkSecurityGroupName
self.description = description
self.vpcId = vpcId
self.securityGroupRules = securityGroupRules
self.createdTime = createdTime | def __init__(self, networkSecurityGroupId=None, networkSecurityGroupName=None, description=None, vpcId=None, securityGroupRules=None, createdTime=None):
'\n :param networkSecurityGroupId: (Optional) 安全组ID\n :param networkSecurityGroupName: (Optional) 安全组名称\n :param description: (Optional) 安全组描述信息\n :param vpcId: (Optional) 安全组所在vpc的Id\n :param securityGroupRules: (Optional) 安全组规则信息\n :param createdTime: (Optional) 安全组创建时间\n '
self.networkSecurityGroupId = networkSecurityGroupId
self.networkSecurityGroupName = networkSecurityGroupName
self.description = description
self.vpcId = vpcId
self.securityGroupRules = securityGroupRules
self.createdTime = createdTime<|docstring|>:param networkSecurityGroupId: (Optional) 安全组ID
:param networkSecurityGroupName: (Optional) 安全组名称
:param description: (Optional) 安全组描述信息
:param vpcId: (Optional) 安全组所在vpc的Id
:param securityGroupRules: (Optional) 安全组规则信息
:param createdTime: (Optional) 安全组创建时间<|endoftext|> |
c72910a17eca28910f634d4599538017d05319539d0c66efe1d13109b813df50 | @patch('hc.api.management.commands.sendalerts.Command.handle_many')
def test_it_notifies_when_check_run_too_often(self, mock):
'\n Tests that a check is not too often i.e.\n it should not be run before the time left\n before its timeout period expires is\n less than or equal to its grace period\n '
self.client.get(('/ping/%s/' % self.check.code))
check = Check.objects.filter(name='Test 1').first()
self.assertEqual(check.runs_too_often, True)
result = Command().handle_many()
assert result, True | Tests that a check is not too often i.e.
it should not be run before the time left
before its timeout period expires is
less than or equal to its grace period | hc/api/tests/test_sendalerts_running_often.py | test_it_notifies_when_check_run_too_often | andela/hc-aces-kla- | 0 | python | @patch('hc.api.management.commands.sendalerts.Command.handle_many')
def test_it_notifies_when_check_run_too_often(self, mock):
'\n Tests that a check is not too often i.e.\n it should not be run before the time left\n before its timeout period expires is\n less than or equal to its grace period\n '
self.client.get(('/ping/%s/' % self.check.code))
check = Check.objects.filter(name='Test 1').first()
self.assertEqual(check.runs_too_often, True)
result = Command().handle_many()
assert result, True | @patch('hc.api.management.commands.sendalerts.Command.handle_many')
def test_it_notifies_when_check_run_too_often(self, mock):
'\n Tests that a check is not too often i.e.\n it should not be run before the time left\n before its timeout period expires is\n less than or equal to its grace period\n '
self.client.get(('/ping/%s/' % self.check.code))
check = Check.objects.filter(name='Test 1').first()
self.assertEqual(check.runs_too_often, True)
result = Command().handle_many()
assert result, True<|docstring|>Tests that a check is not too often i.e.
it should not be run before the time left
before its timeout period expires is
less than or equal to its grace period<|endoftext|> |
e4d01a37cbceccacc854c124e34bb45019dbbf40a78e6a796815bcb788f4dd83 | def _notify(self, to_return):
'\n if hasattr(to_return, "_observers") and hasattr(self, "_observers"):\n Subject._notify()\n else:\n print("Error! No observers found")\n '
if (to_return is not None):
if hasattr(self, '_observers'):
to_return._observers = self._observers
Subject._notify(self)
else:
Subject._notify(self) | if hasattr(to_return, "_observers") and hasattr(self, "_observers"):
Subject._notify()
else:
print("Error! No observers found") | Py3DViewer/utils/ObservableArray.py | _notify | alexus98/py3DViewer | 24 | python | def _notify(self, to_return):
'\n if hasattr(to_return, "_observers") and hasattr(self, "_observers"):\n Subject._notify()\n else:\n print("Error! No observers found")\n '
if (to_return is not None):
if hasattr(self, '_observers'):
to_return._observers = self._observers
Subject._notify(self)
else:
Subject._notify(self) | def _notify(self, to_return):
'\n if hasattr(to_return, "_observers") and hasattr(self, "_observers"):\n Subject._notify()\n else:\n print("Error! No observers found")\n '
if (to_return is not None):
if hasattr(self, '_observers'):
to_return._observers = self._observers
Subject._notify(self)
else:
Subject._notify(self)<|docstring|>if hasattr(to_return, "_observers") and hasattr(self, "_observers"):
Subject._notify()
else:
print("Error! No observers found")<|endoftext|> |
cedb5b7046e55b30067f4f0a42e5eb3fc01261927fc1216f4d200bf6f38f5b6a | def to_json(self):
'Take all model attributes and render them as JSON.'
return {'id': self.id, 'title': self.title, 'author': self.author, 'isbn': self.isbn, 'pub_date': (self.pub_date.strftime('%m/%d/%Y') if self.pub_date else None)} | Take all model attributes and render them as JSON. | book_api/models/book.py | to_json | musflood/zonar-book-api | 0 | python | def to_json(self):
return {'id': self.id, 'title': self.title, 'author': self.author, 'isbn': self.isbn, 'pub_date': (self.pub_date.strftime('%m/%d/%Y') if self.pub_date else None)} | def to_json(self):
return {'id': self.id, 'title': self.title, 'author': self.author, 'isbn': self.isbn, 'pub_date': (self.pub_date.strftime('%m/%d/%Y') if self.pub_date else None)}<|docstring|>Take all model attributes and render them as JSON.<|endoftext|> |
854a0ed7ee9e0d06cd7f807bd6e468bcfcd0586de3ba4c49c231b76b3c51e93f | def decode_binary_rle(data):
'\n decodes binary rle to integer list rle\n '
m = len(data)
cnts = ([0] * m)
h = 0
p = 0
while (p < m):
x = 0
k = 0
more = 1
while (more > 0):
c = (ord(data[p]) - 48)
x |= ((c & 31) << (5 * k))
more = (c & 32)
p = (p + 1)
k = (k + 1)
if ((more == 0) and ((c & 16) != 0)):
x |= ((- 1) << (5 * k))
if (h > 2):
x += cnts[(h - 2)]
cnts[h] = x
h += 1
return cnts[0:h] | decodes binary rle to integer list rle | darwin/importer/formats/coco.py | decode_binary_rle | sachasamama/darwin-py | 28 | python | def decode_binary_rle(data):
'\n \n '
m = len(data)
cnts = ([0] * m)
h = 0
p = 0
while (p < m):
x = 0
k = 0
more = 1
while (more > 0):
c = (ord(data[p]) - 48)
x |= ((c & 31) << (5 * k))
more = (c & 32)
p = (p + 1)
k = (k + 1)
if ((more == 0) and ((c & 16) != 0)):
x |= ((- 1) << (5 * k))
if (h > 2):
x += cnts[(h - 2)]
cnts[h] = x
h += 1
return cnts[0:h] | def decode_binary_rle(data):
'\n \n '
m = len(data)
cnts = ([0] * m)
h = 0
p = 0
while (p < m):
x = 0
k = 0
more = 1
while (more > 0):
c = (ord(data[p]) - 48)
x |= ((c & 31) << (5 * k))
more = (c & 32)
p = (p + 1)
k = (k + 1)
if ((more == 0) and ((c & 16) != 0)):
x |= ((- 1) << (5 * k))
if (h > 2):
x += cnts[(h - 2)]
cnts[h] = x
h += 1
return cnts[0:h]<|docstring|>decodes binary rle to integer list rle<|endoftext|> |
547e05a5d58fba96c04103700620e689b7ee1952d4daa8e48b353eec675a6f13 | def _apply_some_settings(self):
'\n Applies all settings that can be applied without re-opening the ide\n :return: None\n '
self._apply_tab_length_to_all_open_editors() | Applies all settings that can be applied without re-opening the ide
:return: None | ide/SettingsDialog.py | _apply_some_settings | bookofproofs/fpl | 4 | python | def _apply_some_settings(self):
'\n Applies all settings that can be applied without re-opening the ide\n :return: None\n '
self._apply_tab_length_to_all_open_editors() | def _apply_some_settings(self):
'\n Applies all settings that can be applied without re-opening the ide\n :return: None\n '
self._apply_tab_length_to_all_open_editors()<|docstring|>Applies all settings that can be applied without re-opening the ide
:return: None<|endoftext|> |
ddc689a529894cdb8da6dfce7adcbab914f30b5c2a6656f714230546ab7395d9 | def cluster_diffs(concepts, data, graph_location, file_length_map, occurrence_matrix, file_index_map, times, edges_kept=None, use_file_dist=True, use_call_distance=True, use_data=True, use_namespace=True, use_change_coupling=True):
"\n :param concepts: The number of concepts we wish to segment\n :param data: The initial diff-regions segmentation, each it's own group\n :param graph_location: The location of the dot file representing the deltaPDG of the file\n :param file_length_map: A map between filename and file line count\n :param occurrence_matrix: The matrix mapping commits to files and vice versa\n :param file_index_map: The map between filenames and occurrence_matrix indices\n :return: The proposed clustering of diff_regions\n "
deltaPDG = obj_dict_to_networkx(read_graph_from_dot(graph_location))
if (edges_kept is not None):
deltaPDG = remove_all_except(deltaPDG, edges_kept)
context = get_context_from_nxgraph(deltaPDG)
voters = [(file_distance(file_length_map) if use_file_dist else None), (call_graph_distance(deltaPDG, context) if use_call_distance else None), (data_dependency(deltaPDG) if use_data else None), (namespace_distance(deltaPDG, context) if use_namespace else None), (change_coupling(occurrence_matrix, file_index_map) if use_change_coupling else None)]
voters = [v for v in voters if (v is not None)]
n = len(data)
t0 = time.process_time()
for i in range(times):
(affinity, args) = generate_empty_affinity(n, voters)
with ThreadPool(processes=min((os.cpu_count() - 1), 6)) as wp:
for (k, value) in wp.imap_unordered((lambda i: (i[1], i[0](data[i[(- 1)][0]], data[i[(- 1)][1]]))), args):
affinity[k] += value
labels = cluster_from_voter_affinity(affinity, concepts)
t1 = time.process_time()
time_ = ((t1 - t0) / times)
return (labels, time_) | :param concepts: The number of concepts we wish to segment
:param data: The initial diff-regions segmentation, each it's own group
:param graph_location: The location of the dot file representing the deltaPDG of the file
:param file_length_map: A map between filename and file line count
:param occurrence_matrix: The matrix mapping commits to files and vice versa
:param file_index_map: The map between filenames and occurrence_matrix indices
:return: The proposed clustering of diff_regions | confidence_voters/confidence_voters.py | cluster_diffs | PPPI/Flexeme | 3 | python | def cluster_diffs(concepts, data, graph_location, file_length_map, occurrence_matrix, file_index_map, times, edges_kept=None, use_file_dist=True, use_call_distance=True, use_data=True, use_namespace=True, use_change_coupling=True):
"\n :param concepts: The number of concepts we wish to segment\n :param data: The initial diff-regions segmentation, each it's own group\n :param graph_location: The location of the dot file representing the deltaPDG of the file\n :param file_length_map: A map between filename and file line count\n :param occurrence_matrix: The matrix mapping commits to files and vice versa\n :param file_index_map: The map between filenames and occurrence_matrix indices\n :return: The proposed clustering of diff_regions\n "
deltaPDG = obj_dict_to_networkx(read_graph_from_dot(graph_location))
if (edges_kept is not None):
deltaPDG = remove_all_except(deltaPDG, edges_kept)
context = get_context_from_nxgraph(deltaPDG)
voters = [(file_distance(file_length_map) if use_file_dist else None), (call_graph_distance(deltaPDG, context) if use_call_distance else None), (data_dependency(deltaPDG) if use_data else None), (namespace_distance(deltaPDG, context) if use_namespace else None), (change_coupling(occurrence_matrix, file_index_map) if use_change_coupling else None)]
voters = [v for v in voters if (v is not None)]
n = len(data)
t0 = time.process_time()
for i in range(times):
(affinity, args) = generate_empty_affinity(n, voters)
with ThreadPool(processes=min((os.cpu_count() - 1), 6)) as wp:
for (k, value) in wp.imap_unordered((lambda i: (i[1], i[0](data[i[(- 1)][0]], data[i[(- 1)][1]]))), args):
affinity[k] += value
labels = cluster_from_voter_affinity(affinity, concepts)
t1 = time.process_time()
time_ = ((t1 - t0) / times)
return (labels, time_) | def cluster_diffs(concepts, data, graph_location, file_length_map, occurrence_matrix, file_index_map, times, edges_kept=None, use_file_dist=True, use_call_distance=True, use_data=True, use_namespace=True, use_change_coupling=True):
"\n :param concepts: The number of concepts we wish to segment\n :param data: The initial diff-regions segmentation, each it's own group\n :param graph_location: The location of the dot file representing the deltaPDG of the file\n :param file_length_map: A map between filename and file line count\n :param occurrence_matrix: The matrix mapping commits to files and vice versa\n :param file_index_map: The map between filenames and occurrence_matrix indices\n :return: The proposed clustering of diff_regions\n "
deltaPDG = obj_dict_to_networkx(read_graph_from_dot(graph_location))
if (edges_kept is not None):
deltaPDG = remove_all_except(deltaPDG, edges_kept)
context = get_context_from_nxgraph(deltaPDG)
voters = [(file_distance(file_length_map) if use_file_dist else None), (call_graph_distance(deltaPDG, context) if use_call_distance else None), (data_dependency(deltaPDG) if use_data else None), (namespace_distance(deltaPDG, context) if use_namespace else None), (change_coupling(occurrence_matrix, file_index_map) if use_change_coupling else None)]
voters = [v for v in voters if (v is not None)]
n = len(data)
t0 = time.process_time()
for i in range(times):
(affinity, args) = generate_empty_affinity(n, voters)
with ThreadPool(processes=min((os.cpu_count() - 1), 6)) as wp:
for (k, value) in wp.imap_unordered((lambda i: (i[1], i[0](data[i[(- 1)][0]], data[i[(- 1)][1]]))), args):
affinity[k] += value
labels = cluster_from_voter_affinity(affinity, concepts)
t1 = time.process_time()
time_ = ((t1 - t0) / times)
return (labels, time_)<|docstring|>:param concepts: The number of concepts we wish to segment
:param data: The initial diff-regions segmentation, each it's own group
:param graph_location: The location of the dot file representing the deltaPDG of the file
:param file_length_map: A map between filename and file line count
:param occurrence_matrix: The matrix mapping commits to files and vice versa
:param file_index_map: The map between filenames and occurrence_matrix indices
:return: The proposed clustering of diff_regions<|endoftext|> |
2b20e432207c763e3258096bf92924509ae8a6e197a256e401e2d4f8d8395627 | def calc_added_turbulence(self, dw_ijlk, cw_ijlk, D_src_il, ct_ilk, TI_ilk, **_):
' Calculate the added turbulence intensity at locations specified by\n downstream distances (dw_jl) and crosswind distances (cw_jl)\n caused by the wake of a turbine (diameter: D_src_l, thrust coefficient: Ct_lk).\n\n Returns\n -------\n TI_eff_ijlk: array:float\n Effective turbulence intensity [-]\n '
with np.warnings.catch_warnings():
np.warnings.filterwarnings('ignore', 'divide by zero encountered in true_divide')
np.warnings.filterwarnings('ignore', 'invalid value encountered in true_divide')
TI_add_ijlk = (1 / (1.5 + ((0.8 * (dw_ijlk / D_src_il[(:, na, :, na)])) / np.sqrt(ct_ilk)[(:, na)])))
TI_add_ijlk[np.isnan(TI_add_ijlk)] = 0
weights_ijlk = self.weight(dw_ijlk, cw_ijlk, D_src_il)
TI_add_ijlk = (weights_ijlk * (np.hypot(TI_add_ijlk, TI_ilk[(:, na)]) - TI_ilk[(:, na)]))
return TI_add_ijlk | Calculate the added turbulence intensity at locations specified by
downstream distances (dw_jl) and crosswind distances (cw_jl)
caused by the wake of a turbine (diameter: D_src_l, thrust coefficient: Ct_lk).
Returns
-------
TI_eff_ijlk: array:float
Effective turbulence intensity [-] | py_wake/turbulence_models/stf.py | calc_added_turbulence | hmharley/PyWake | 0 | python | def calc_added_turbulence(self, dw_ijlk, cw_ijlk, D_src_il, ct_ilk, TI_ilk, **_):
' Calculate the added turbulence intensity at locations specified by\n downstream distances (dw_jl) and crosswind distances (cw_jl)\n caused by the wake of a turbine (diameter: D_src_l, thrust coefficient: Ct_lk).\n\n Returns\n -------\n TI_eff_ijlk: array:float\n Effective turbulence intensity [-]\n '
with np.warnings.catch_warnings():
np.warnings.filterwarnings('ignore', 'divide by zero encountered in true_divide')
np.warnings.filterwarnings('ignore', 'invalid value encountered in true_divide')
TI_add_ijlk = (1 / (1.5 + ((0.8 * (dw_ijlk / D_src_il[(:, na, :, na)])) / np.sqrt(ct_ilk)[(:, na)])))
TI_add_ijlk[np.isnan(TI_add_ijlk)] = 0
weights_ijlk = self.weight(dw_ijlk, cw_ijlk, D_src_il)
TI_add_ijlk = (weights_ijlk * (np.hypot(TI_add_ijlk, TI_ilk[(:, na)]) - TI_ilk[(:, na)]))
return TI_add_ijlk | def calc_added_turbulence(self, dw_ijlk, cw_ijlk, D_src_il, ct_ilk, TI_ilk, **_):
' Calculate the added turbulence intensity at locations specified by\n downstream distances (dw_jl) and crosswind distances (cw_jl)\n caused by the wake of a turbine (diameter: D_src_l, thrust coefficient: Ct_lk).\n\n Returns\n -------\n TI_eff_ijlk: array:float\n Effective turbulence intensity [-]\n '
with np.warnings.catch_warnings():
np.warnings.filterwarnings('ignore', 'divide by zero encountered in true_divide')
np.warnings.filterwarnings('ignore', 'invalid value encountered in true_divide')
TI_add_ijlk = (1 / (1.5 + ((0.8 * (dw_ijlk / D_src_il[(:, na, :, na)])) / np.sqrt(ct_ilk)[(:, na)])))
TI_add_ijlk[np.isnan(TI_add_ijlk)] = 0
weights_ijlk = self.weight(dw_ijlk, cw_ijlk, D_src_il)
TI_add_ijlk = (weights_ijlk * (np.hypot(TI_add_ijlk, TI_ilk[(:, na)]) - TI_ilk[(:, na)]))
return TI_add_ijlk<|docstring|>Calculate the added turbulence intensity at locations specified by
downstream distances (dw_jl) and crosswind distances (cw_jl)
caused by the wake of a turbine (diameter: D_src_l, thrust coefficient: Ct_lk).
Returns
-------
TI_eff_ijlk: array:float
Effective turbulence intensity [-]<|endoftext|> |
78309a837be4ed3bd1478664c3758d4857fb1a57af5f1469b9e22167938370ed | def calc_added_turbulence(self, dw_ijlk, cw_ijlk, D_src_il, WS_ilk, TI_ilk, **_):
' Calculate the added turbulence intensity at locations specified by\n downstream distances (dw_jl) and crosswind distances (cw_jl)\n caused by the wake of a turbine (diameter: D_src_l, thrust coefficient: Ct_lk).\n\n Returns\n -------\n TI_eff_jlk: array:float\n Effective turbulence intensity [-]\n '
TI_maxadd_ijlk = (0.9 / (1.5 + ((0.3 * (dw_ijlk / D_src_il[(:, na, :, na)])) * np.sqrt(WS_ilk)[(:, na)])))
weights_ijlk = self.weight(dw_ijlk, cw_ijlk, D_src_il)
TI_add_ijlk = (weights_ijlk * (np.hypot(TI_maxadd_ijlk, TI_ilk[(:, na)]) - TI_ilk[(:, na)]))
return TI_add_ijlk | Calculate the added turbulence intensity at locations specified by
downstream distances (dw_jl) and crosswind distances (cw_jl)
caused by the wake of a turbine (diameter: D_src_l, thrust coefficient: Ct_lk).
Returns
-------
TI_eff_jlk: array:float
Effective turbulence intensity [-] | py_wake/turbulence_models/stf.py | calc_added_turbulence | hmharley/PyWake | 0 | python | def calc_added_turbulence(self, dw_ijlk, cw_ijlk, D_src_il, WS_ilk, TI_ilk, **_):
' Calculate the added turbulence intensity at locations specified by\n downstream distances (dw_jl) and crosswind distances (cw_jl)\n caused by the wake of a turbine (diameter: D_src_l, thrust coefficient: Ct_lk).\n\n Returns\n -------\n TI_eff_jlk: array:float\n Effective turbulence intensity [-]\n '
TI_maxadd_ijlk = (0.9 / (1.5 + ((0.3 * (dw_ijlk / D_src_il[(:, na, :, na)])) * np.sqrt(WS_ilk)[(:, na)])))
weights_ijlk = self.weight(dw_ijlk, cw_ijlk, D_src_il)
TI_add_ijlk = (weights_ijlk * (np.hypot(TI_maxadd_ijlk, TI_ilk[(:, na)]) - TI_ilk[(:, na)]))
return TI_add_ijlk | def calc_added_turbulence(self, dw_ijlk, cw_ijlk, D_src_il, WS_ilk, TI_ilk, **_):
' Calculate the added turbulence intensity at locations specified by\n downstream distances (dw_jl) and crosswind distances (cw_jl)\n caused by the wake of a turbine (diameter: D_src_l, thrust coefficient: Ct_lk).\n\n Returns\n -------\n TI_eff_jlk: array:float\n Effective turbulence intensity [-]\n '
TI_maxadd_ijlk = (0.9 / (1.5 + ((0.3 * (dw_ijlk / D_src_il[(:, na, :, na)])) * np.sqrt(WS_ilk)[(:, na)])))
weights_ijlk = self.weight(dw_ijlk, cw_ijlk, D_src_il)
TI_add_ijlk = (weights_ijlk * (np.hypot(TI_maxadd_ijlk, TI_ilk[(:, na)]) - TI_ilk[(:, na)]))
return TI_add_ijlk<|docstring|>Calculate the added turbulence intensity at locations specified by
downstream distances (dw_jl) and crosswind distances (cw_jl)
caused by the wake of a turbine (diameter: D_src_l, thrust coefficient: Ct_lk).
Returns
-------
TI_eff_jlk: array:float
Effective turbulence intensity [-]<|endoftext|> |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.