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e6dc51b7c0eac25e49ffee0983de262aaf26d68f151a7f3d6d698c6279fb1f13 | def read_unicode_csv_fileobj(fileobj, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL, lineterminator='\n', encoding='utf-8', skiprows=0):
'fileobj can be a StringIO in Py3, but should be a BytesIO in Py2.'
if (sys.version_info[0] >= 3):
csv_reader = csv.reader(fileobj, delimiter=delimiter, quotechar=quotechar, quoting=quoting, lineterminator=lineterminator)
for skip_ix in range(skiprows):
next(csv_reader)
for row in csv_reader:
(yield row)
else:
csv_reader = csv.reader(fileobj, delimiter=delimiter.encode(encoding), quotechar=quotechar.encode(encoding), quoting=quoting, lineterminator=lineterminator)
for skip_ix in range(skiprows):
next(csv_reader)
for row in csv_reader:
(yield [cell.decode(encoding) for cell in row]) | fileobj can be a StringIO in Py3, but should be a BytesIO in Py2. | indra/util/__init__.py | read_unicode_csv_fileobj | pupster90/indra | 0 | python | def read_unicode_csv_fileobj(fileobj, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL, lineterminator='\n', encoding='utf-8', skiprows=0):
if (sys.version_info[0] >= 3):
csv_reader = csv.reader(fileobj, delimiter=delimiter, quotechar=quotechar, quoting=quoting, lineterminator=lineterminator)
for skip_ix in range(skiprows):
next(csv_reader)
for row in csv_reader:
(yield row)
else:
csv_reader = csv.reader(fileobj, delimiter=delimiter.encode(encoding), quotechar=quotechar.encode(encoding), quoting=quoting, lineterminator=lineterminator)
for skip_ix in range(skiprows):
next(csv_reader)
for row in csv_reader:
(yield [cell.decode(encoding) for cell in row]) | def read_unicode_csv_fileobj(fileobj, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL, lineterminator='\n', encoding='utf-8', skiprows=0):
if (sys.version_info[0] >= 3):
csv_reader = csv.reader(fileobj, delimiter=delimiter, quotechar=quotechar, quoting=quoting, lineterminator=lineterminator)
for skip_ix in range(skiprows):
next(csv_reader)
for row in csv_reader:
(yield row)
else:
csv_reader = csv.reader(fileobj, delimiter=delimiter.encode(encoding), quotechar=quotechar.encode(encoding), quoting=quoting, lineterminator=lineterminator)
for skip_ix in range(skiprows):
next(csv_reader)
for row in csv_reader:
(yield [cell.decode(encoding) for cell in row])<|docstring|>fileobj can be a StringIO in Py3, but should be a BytesIO in Py2.<|endoftext|> |
b3149d1c76287116ce82ae7c62545b1856d4db0613b3be06406f869f4196b706 | def fast_deepcopy(obj):
'This is a faster implementation of deepcopy via pickle.\n\n It is meant primarily for sets of Statements with complex hierarchies\n but can be used for any object.\n '
with BytesIO() as buf:
pickle.dump(obj, buf)
buf.seek(0)
obj_new = pickle.load(buf)
return obj_new | This is a faster implementation of deepcopy via pickle.
It is meant primarily for sets of Statements with complex hierarchies
but can be used for any object. | indra/util/__init__.py | fast_deepcopy | pupster90/indra | 0 | python | def fast_deepcopy(obj):
'This is a faster implementation of deepcopy via pickle.\n\n It is meant primarily for sets of Statements with complex hierarchies\n but can be used for any object.\n '
with BytesIO() as buf:
pickle.dump(obj, buf)
buf.seek(0)
obj_new = pickle.load(buf)
return obj_new | def fast_deepcopy(obj):
'This is a faster implementation of deepcopy via pickle.\n\n It is meant primarily for sets of Statements with complex hierarchies\n but can be used for any object.\n '
with BytesIO() as buf:
pickle.dump(obj, buf)
buf.seek(0)
obj_new = pickle.load(buf)
return obj_new<|docstring|>This is a faster implementation of deepcopy via pickle.
It is meant primarily for sets of Statements with complex hierarchies
but can be used for any object.<|endoftext|> |
c78a8ea25b310168b46e9bbf1f397d1065e1413b6d9b5f525794abb7bfb4424e | def lmap(f, xs):
'A non-lazy version of map.'
return list(map(f, xs)) | A non-lazy version of map. | indra/util/__init__.py | lmap | pupster90/indra | 0 | python | def lmap(f, xs):
return list(map(f, xs)) | def lmap(f, xs):
return list(map(f, xs))<|docstring|>A non-lazy version of map.<|endoftext|> |
eb6f034f5f37f918633536f64523c73bd1ec6a5b3755fc0d968345680ab5fc59 | def flatten(l):
'Flatten a nested list.'
return (sum(map(flatten, l), []) if (isinstance(l, list) or isinstance(l, tuple)) else [l]) | Flatten a nested list. | indra/util/__init__.py | flatten | pupster90/indra | 0 | python | def flatten(l):
return (sum(map(flatten, l), []) if (isinstance(l, list) or isinstance(l, tuple)) else [l]) | def flatten(l):
return (sum(map(flatten, l), []) if (isinstance(l, list) or isinstance(l, tuple)) else [l])<|docstring|>Flatten a nested list.<|endoftext|> |
0aecee92b413b931514195548bdef79e5aa7588ca0b404c46676b412f4bdbd6a | def flatMap(f, xs):
'Map a function onto an iterable and flatten the result.'
return flatten(lmap(f, xs)) | Map a function onto an iterable and flatten the result. | indra/util/__init__.py | flatMap | pupster90/indra | 0 | python | def flatMap(f, xs):
return flatten(lmap(f, xs)) | def flatMap(f, xs):
return flatten(lmap(f, xs))<|docstring|>Map a function onto an iterable and flatten the result.<|endoftext|> |
5d5c899b4cef6f2714806dd23889f74f192168d1925d881fcfaf526cb7b02b34 | def get_list_arb():
'Run the arb finder\n\n Returns:\n List: List sorted by % of all arb opportunities found.\n '
dict_price_raw = get_raw_price_async()
dict_clean_price = get_clean_price(dict_price_raw)
list_arb_price = compute_arb_opportunities(dict_clean_price)
res = get_output(list_arb_price)
sorted_list_arb = sorted(res.items(), key=(lambda i: i[1]['%']), reverse=True)
pprint(sorted_list_arb)
return sorted_list_arb | Run the arb finder
Returns:
List: List sorted by % of all arb opportunities found. | examples/python/oracle_arb_finder/app.py | get_list_arb | edd34/OrFeed | 0 | python | def get_list_arb():
'Run the arb finder\n\n Returns:\n List: List sorted by % of all arb opportunities found.\n '
dict_price_raw = get_raw_price_async()
dict_clean_price = get_clean_price(dict_price_raw)
list_arb_price = compute_arb_opportunities(dict_clean_price)
res = get_output(list_arb_price)
sorted_list_arb = sorted(res.items(), key=(lambda i: i[1]['%']), reverse=True)
pprint(sorted_list_arb)
return sorted_list_arb | def get_list_arb():
'Run the arb finder\n\n Returns:\n List: List sorted by % of all arb opportunities found.\n '
dict_price_raw = get_raw_price_async()
dict_clean_price = get_clean_price(dict_price_raw)
list_arb_price = compute_arb_opportunities(dict_clean_price)
res = get_output(list_arb_price)
sorted_list_arb = sorted(res.items(), key=(lambda i: i[1]['%']), reverse=True)
pprint(sorted_list_arb)
return sorted_list_arb<|docstring|>Run the arb finder
Returns:
List: List sorted by % of all arb opportunities found.<|endoftext|> |
f52a7233349e3aad06943ba481ebfdf9ffb43ca04723a10073e6ae65ebbc1c91 | def knn_purity(data, labels: np.ndarray, n_neighbors=30):
'Computes KNN Purity for ``data`` given the labels.\n Parameters\n ----------\n data:\n Numpy ndarray of data\n labels\n Numpy ndarray of labels\n n_neighbors: int\n Number of nearest neighbors.\n Returns\n -------\n score: float\n KNN purity score. A float between 0 and 1.\n '
labels = LabelEncoder().fit_transform(labels.ravel())
nbrs = NearestNeighbors(n_neighbors=(n_neighbors + 1)).fit(data)
indices = nbrs.kneighbors(data, return_distance=False)[(:, 1:)]
neighbors_labels = np.vectorize((lambda i: labels[i]))(indices)
scores = ((neighbors_labels - labels.reshape((- 1), 1)) == 0).mean(axis=1)
res = [np.mean(scores[(labels == i)]) for i in np.unique(labels)]
return np.mean(res) | Computes KNN Purity for ``data`` given the labels.
Parameters
----------
data:
Numpy ndarray of data
labels
Numpy ndarray of labels
n_neighbors: int
Number of nearest neighbors.
Returns
-------
score: float
KNN purity score. A float between 0 and 1. | cpa/_metrics.py | knn_purity | theislab/CPA | 7 | python | def knn_purity(data, labels: np.ndarray, n_neighbors=30):
'Computes KNN Purity for ``data`` given the labels.\n Parameters\n ----------\n data:\n Numpy ndarray of data\n labels\n Numpy ndarray of labels\n n_neighbors: int\n Number of nearest neighbors.\n Returns\n -------\n score: float\n KNN purity score. A float between 0 and 1.\n '
labels = LabelEncoder().fit_transform(labels.ravel())
nbrs = NearestNeighbors(n_neighbors=(n_neighbors + 1)).fit(data)
indices = nbrs.kneighbors(data, return_distance=False)[(:, 1:)]
neighbors_labels = np.vectorize((lambda i: labels[i]))(indices)
scores = ((neighbors_labels - labels.reshape((- 1), 1)) == 0).mean(axis=1)
res = [np.mean(scores[(labels == i)]) for i in np.unique(labels)]
return np.mean(res) | def knn_purity(data, labels: np.ndarray, n_neighbors=30):
'Computes KNN Purity for ``data`` given the labels.\n Parameters\n ----------\n data:\n Numpy ndarray of data\n labels\n Numpy ndarray of labels\n n_neighbors: int\n Number of nearest neighbors.\n Returns\n -------\n score: float\n KNN purity score. A float between 0 and 1.\n '
labels = LabelEncoder().fit_transform(labels.ravel())
nbrs = NearestNeighbors(n_neighbors=(n_neighbors + 1)).fit(data)
indices = nbrs.kneighbors(data, return_distance=False)[(:, 1:)]
neighbors_labels = np.vectorize((lambda i: labels[i]))(indices)
scores = ((neighbors_labels - labels.reshape((- 1), 1)) == 0).mean(axis=1)
res = [np.mean(scores[(labels == i)]) for i in np.unique(labels)]
return np.mean(res)<|docstring|>Computes KNN Purity for ``data`` given the labels.
Parameters
----------
data:
Numpy ndarray of data
labels
Numpy ndarray of labels
n_neighbors: int
Number of nearest neighbors.
Returns
-------
score: float
KNN purity score. A float between 0 and 1.<|endoftext|> |
b59e8e0c164d108be9e45d4f226c2c6678a697427b918c1e9b0b38207dc252a2 | def entropy_batch_mixing(data, labels, n_neighbors=50, n_pools=50, n_samples_per_pool=100):
'Computes Entory of Batch mixing metric for ``adata`` given the batch column name.\n Parameters\n ----------\n data\n Numpy ndarray of data\n labels\n Numpy ndarray of labels\n n_neighbors: int\n Number of nearest neighbors.\n n_pools: int\n Number of EBM computation which will be averaged.\n n_samples_per_pool: int\n Number of samples to be used in each pool of execution.\n Returns\n -------\n score: float\n EBM score. A float between zero and one.\n '
def __entropy_from_indices(indices, n_cat):
return entropy(np.array(itemfreq(indices)[(:, 1)].astype(np.int32)), base=n_cat)
n_cat = len(np.unique(labels))
neighbors = NearestNeighbors(n_neighbors=(n_neighbors + 1)).fit(data)
indices = neighbors.kneighbors(data, return_distance=False)[(:, 1:)]
batch_indices = np.vectorize((lambda i: labels[i]))(indices)
entropies = np.apply_along_axis(__entropy_from_indices, axis=1, arr=batch_indices, n_cat=n_cat)
if (n_pools == 1):
score = np.mean(entropies)
else:
score = np.mean([np.mean(entropies[np.random.choice(len(entropies), size=n_samples_per_pool)]) for _ in range(n_pools)])
return score | Computes Entory of Batch mixing metric for ``adata`` given the batch column name.
Parameters
----------
data
Numpy ndarray of data
labels
Numpy ndarray of labels
n_neighbors: int
Number of nearest neighbors.
n_pools: int
Number of EBM computation which will be averaged.
n_samples_per_pool: int
Number of samples to be used in each pool of execution.
Returns
-------
score: float
EBM score. A float between zero and one. | cpa/_metrics.py | entropy_batch_mixing | theislab/CPA | 7 | python | def entropy_batch_mixing(data, labels, n_neighbors=50, n_pools=50, n_samples_per_pool=100):
'Computes Entory of Batch mixing metric for ``adata`` given the batch column name.\n Parameters\n ----------\n data\n Numpy ndarray of data\n labels\n Numpy ndarray of labels\n n_neighbors: int\n Number of nearest neighbors.\n n_pools: int\n Number of EBM computation which will be averaged.\n n_samples_per_pool: int\n Number of samples to be used in each pool of execution.\n Returns\n -------\n score: float\n EBM score. A float between zero and one.\n '
def __entropy_from_indices(indices, n_cat):
return entropy(np.array(itemfreq(indices)[(:, 1)].astype(np.int32)), base=n_cat)
n_cat = len(np.unique(labels))
neighbors = NearestNeighbors(n_neighbors=(n_neighbors + 1)).fit(data)
indices = neighbors.kneighbors(data, return_distance=False)[(:, 1:)]
batch_indices = np.vectorize((lambda i: labels[i]))(indices)
entropies = np.apply_along_axis(__entropy_from_indices, axis=1, arr=batch_indices, n_cat=n_cat)
if (n_pools == 1):
score = np.mean(entropies)
else:
score = np.mean([np.mean(entropies[np.random.choice(len(entropies), size=n_samples_per_pool)]) for _ in range(n_pools)])
return score | def entropy_batch_mixing(data, labels, n_neighbors=50, n_pools=50, n_samples_per_pool=100):
'Computes Entory of Batch mixing metric for ``adata`` given the batch column name.\n Parameters\n ----------\n data\n Numpy ndarray of data\n labels\n Numpy ndarray of labels\n n_neighbors: int\n Number of nearest neighbors.\n n_pools: int\n Number of EBM computation which will be averaged.\n n_samples_per_pool: int\n Number of samples to be used in each pool of execution.\n Returns\n -------\n score: float\n EBM score. A float between zero and one.\n '
def __entropy_from_indices(indices, n_cat):
return entropy(np.array(itemfreq(indices)[(:, 1)].astype(np.int32)), base=n_cat)
n_cat = len(np.unique(labels))
neighbors = NearestNeighbors(n_neighbors=(n_neighbors + 1)).fit(data)
indices = neighbors.kneighbors(data, return_distance=False)[(:, 1:)]
batch_indices = np.vectorize((lambda i: labels[i]))(indices)
entropies = np.apply_along_axis(__entropy_from_indices, axis=1, arr=batch_indices, n_cat=n_cat)
if (n_pools == 1):
score = np.mean(entropies)
else:
score = np.mean([np.mean(entropies[np.random.choice(len(entropies), size=n_samples_per_pool)]) for _ in range(n_pools)])
return score<|docstring|>Computes Entory of Batch mixing metric for ``adata`` given the batch column name.
Parameters
----------
data
Numpy ndarray of data
labels
Numpy ndarray of labels
n_neighbors: int
Number of nearest neighbors.
n_pools: int
Number of EBM computation which will be averaged.
n_samples_per_pool: int
Number of samples to be used in each pool of execution.
Returns
-------
score: float
EBM score. A float between zero and one.<|endoftext|> |
003c8d364a7eb5159af24d7b0055d5f3d71da622c5bf163c0a487d59c7305b26 | def __init__(self, parent, inet):
' Initialize Panel class '
self.inet = inet
wx.Panel.__init__(self, parent)
DEFAULT_FONT = wx.Font(12, wx.FONTFAMILY_DEFAULT, wx.FONTSTYLE_NORMAL, wx.FONTWEIGHT_NORMAL)
self.layout_main = wx.BoxSizer(wx.VERTICAL)
self.layout = [wx.BoxSizer(wx.HORIZONTAL) for i in range(4)]
label = wx.StaticText(self, id=wx.ID_ANY, label=u'Question : ')
label.SetFont(DEFAULT_FONT)
self.layout[0].Add(label, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.text_question = wx.TextCtrl(self, id=wx.ID_ANY, size=(400, 32))
self.text_question.SetFont(DEFAULT_FONT)
self.text_question.SetToolTipString(u'Qeustion')
self.layout[0].Add(self.text_question, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=0)
self.button_add = wx.Button(self, id=wx.ID_ANY, label=u'New', size=(128, 32))
self.button_add.SetFont(DEFAULT_FONT)
self.button_add.Bind(wx.EVT_BUTTON, self.new_choice)
self.layout[1].Add(self.button_add, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.button_delete = wx.Button(self, id=wx.ID_ANY, label=u'Delete', size=(128, 32))
self.button_delete.SetFont(DEFAULT_FONT)
self.button_delete.Bind(wx.EVT_BUTTON, self.delete_choice)
self.layout[1].Add(self.button_delete, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.button_clear = wx.Button(self, id=wx.ID_ANY, label=u'Clear All', size=(128, 32))
self.button_clear.SetFont(DEFAULT_FONT)
self.button_clear.Bind(wx.EVT_BUTTON, self.clear_choice)
self.layout[1].Add(self.button_clear, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.list_choice = wx.ListBox(self, wx.ID_ANY, choices=(), style=((wx.LB_SINGLE | wx.LB_HSCROLL) | wx.LB_NEEDED_SB))
self.list_choice.SetFont(DEFAULT_FONT)
self.layout[2].Add(self.list_choice, proportion=1, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.label_received = wx.StaticText(self, id=wx.ID_ANY, label='')
self.label_received.SetFont(DEFAULT_FONT)
self.layout[3].Add(self.label_received, flag=((wx.EXPAND | wx.ALIGN_RIGHT) | wx.ALL), border=8)
self.button_post = wx.Button(self, id=wx.ID_ANY, label=u'Post', size=(128, 32))
self.button_post.SetFont(DEFAULT_FONT)
self.button_post.Bind(wx.EVT_BUTTON, self.inet.post_questionnaire)
self.layout[3].Add(self.button_post, flag=((wx.EXPAND | wx.ALIGN_RIGHT) | wx.ALL), border=8)
self.layout_main.Add(self.layout[0], flag=wx.ALIGN_TOP)
self.layout_main.Add(self.layout[1], flag=wx.ALIGN_LEFT)
self.layout_main.Add(self.layout[2], proportion=1, flag=(wx.EXPAND | wx.ALIGN_CENTER))
self.layout_main.Add(self.layout[3], flag=(wx.ALIGN_BOTTOM | wx.ALIGN_RIGHT))
self.SetSizer(self.layout_main)
return | Initialize Panel class | src/ltkit/panel/server/questionnaire.py | __init__ | ptr-yudai/ltkit | 1 | python | def __init__(self, parent, inet):
' '
self.inet = inet
wx.Panel.__init__(self, parent)
DEFAULT_FONT = wx.Font(12, wx.FONTFAMILY_DEFAULT, wx.FONTSTYLE_NORMAL, wx.FONTWEIGHT_NORMAL)
self.layout_main = wx.BoxSizer(wx.VERTICAL)
self.layout = [wx.BoxSizer(wx.HORIZONTAL) for i in range(4)]
label = wx.StaticText(self, id=wx.ID_ANY, label=u'Question : ')
label.SetFont(DEFAULT_FONT)
self.layout[0].Add(label, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.text_question = wx.TextCtrl(self, id=wx.ID_ANY, size=(400, 32))
self.text_question.SetFont(DEFAULT_FONT)
self.text_question.SetToolTipString(u'Qeustion')
self.layout[0].Add(self.text_question, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=0)
self.button_add = wx.Button(self, id=wx.ID_ANY, label=u'New', size=(128, 32))
self.button_add.SetFont(DEFAULT_FONT)
self.button_add.Bind(wx.EVT_BUTTON, self.new_choice)
self.layout[1].Add(self.button_add, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.button_delete = wx.Button(self, id=wx.ID_ANY, label=u'Delete', size=(128, 32))
self.button_delete.SetFont(DEFAULT_FONT)
self.button_delete.Bind(wx.EVT_BUTTON, self.delete_choice)
self.layout[1].Add(self.button_delete, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.button_clear = wx.Button(self, id=wx.ID_ANY, label=u'Clear All', size=(128, 32))
self.button_clear.SetFont(DEFAULT_FONT)
self.button_clear.Bind(wx.EVT_BUTTON, self.clear_choice)
self.layout[1].Add(self.button_clear, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.list_choice = wx.ListBox(self, wx.ID_ANY, choices=(), style=((wx.LB_SINGLE | wx.LB_HSCROLL) | wx.LB_NEEDED_SB))
self.list_choice.SetFont(DEFAULT_FONT)
self.layout[2].Add(self.list_choice, proportion=1, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.label_received = wx.StaticText(self, id=wx.ID_ANY, label=)
self.label_received.SetFont(DEFAULT_FONT)
self.layout[3].Add(self.label_received, flag=((wx.EXPAND | wx.ALIGN_RIGHT) | wx.ALL), border=8)
self.button_post = wx.Button(self, id=wx.ID_ANY, label=u'Post', size=(128, 32))
self.button_post.SetFont(DEFAULT_FONT)
self.button_post.Bind(wx.EVT_BUTTON, self.inet.post_questionnaire)
self.layout[3].Add(self.button_post, flag=((wx.EXPAND | wx.ALIGN_RIGHT) | wx.ALL), border=8)
self.layout_main.Add(self.layout[0], flag=wx.ALIGN_TOP)
self.layout_main.Add(self.layout[1], flag=wx.ALIGN_LEFT)
self.layout_main.Add(self.layout[2], proportion=1, flag=(wx.EXPAND | wx.ALIGN_CENTER))
self.layout_main.Add(self.layout[3], flag=(wx.ALIGN_BOTTOM | wx.ALIGN_RIGHT))
self.SetSizer(self.layout_main)
return | def __init__(self, parent, inet):
' '
self.inet = inet
wx.Panel.__init__(self, parent)
DEFAULT_FONT = wx.Font(12, wx.FONTFAMILY_DEFAULT, wx.FONTSTYLE_NORMAL, wx.FONTWEIGHT_NORMAL)
self.layout_main = wx.BoxSizer(wx.VERTICAL)
self.layout = [wx.BoxSizer(wx.HORIZONTAL) for i in range(4)]
label = wx.StaticText(self, id=wx.ID_ANY, label=u'Question : ')
label.SetFont(DEFAULT_FONT)
self.layout[0].Add(label, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.text_question = wx.TextCtrl(self, id=wx.ID_ANY, size=(400, 32))
self.text_question.SetFont(DEFAULT_FONT)
self.text_question.SetToolTipString(u'Qeustion')
self.layout[0].Add(self.text_question, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=0)
self.button_add = wx.Button(self, id=wx.ID_ANY, label=u'New', size=(128, 32))
self.button_add.SetFont(DEFAULT_FONT)
self.button_add.Bind(wx.EVT_BUTTON, self.new_choice)
self.layout[1].Add(self.button_add, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.button_delete = wx.Button(self, id=wx.ID_ANY, label=u'Delete', size=(128, 32))
self.button_delete.SetFont(DEFAULT_FONT)
self.button_delete.Bind(wx.EVT_BUTTON, self.delete_choice)
self.layout[1].Add(self.button_delete, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.button_clear = wx.Button(self, id=wx.ID_ANY, label=u'Clear All', size=(128, 32))
self.button_clear.SetFont(DEFAULT_FONT)
self.button_clear.Bind(wx.EVT_BUTTON, self.clear_choice)
self.layout[1].Add(self.button_clear, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.list_choice = wx.ListBox(self, wx.ID_ANY, choices=(), style=((wx.LB_SINGLE | wx.LB_HSCROLL) | wx.LB_NEEDED_SB))
self.list_choice.SetFont(DEFAULT_FONT)
self.layout[2].Add(self.list_choice, proportion=1, flag=((wx.EXPAND | wx.ALIGN_LEFT) | wx.ALL), border=8)
self.label_received = wx.StaticText(self, id=wx.ID_ANY, label=)
self.label_received.SetFont(DEFAULT_FONT)
self.layout[3].Add(self.label_received, flag=((wx.EXPAND | wx.ALIGN_RIGHT) | wx.ALL), border=8)
self.button_post = wx.Button(self, id=wx.ID_ANY, label=u'Post', size=(128, 32))
self.button_post.SetFont(DEFAULT_FONT)
self.button_post.Bind(wx.EVT_BUTTON, self.inet.post_questionnaire)
self.layout[3].Add(self.button_post, flag=((wx.EXPAND | wx.ALIGN_RIGHT) | wx.ALL), border=8)
self.layout_main.Add(self.layout[0], flag=wx.ALIGN_TOP)
self.layout_main.Add(self.layout[1], flag=wx.ALIGN_LEFT)
self.layout_main.Add(self.layout[2], proportion=1, flag=(wx.EXPAND | wx.ALIGN_CENTER))
self.layout_main.Add(self.layout[3], flag=(wx.ALIGN_BOTTOM | wx.ALIGN_RIGHT))
self.SetSizer(self.layout_main)
return<|docstring|>Initialize Panel class<|endoftext|> |
c7bfb100ddcfe4e67e30978ff2476f2c47cbc48e5f416982cc93d0b34f1e8e97 | def new_choice(self, event):
' Add new choice '
dialog = wx.TextEntryDialog(self, message='Please enter the string of the choice.', caption='New choise')
if (dialog.ShowModal() != wx.ID_OK):
return
self.list_choice.Append(dialog.GetValue())
return | Add new choice | src/ltkit/panel/server/questionnaire.py | new_choice | ptr-yudai/ltkit | 1 | python | def new_choice(self, event):
' '
dialog = wx.TextEntryDialog(self, message='Please enter the string of the choice.', caption='New choise')
if (dialog.ShowModal() != wx.ID_OK):
return
self.list_choice.Append(dialog.GetValue())
return | def new_choice(self, event):
' '
dialog = wx.TextEntryDialog(self, message='Please enter the string of the choice.', caption='New choise')
if (dialog.ShowModal() != wx.ID_OK):
return
self.list_choice.Append(dialog.GetValue())
return<|docstring|>Add new choice<|endoftext|> |
51a90ec6259ecdf0681a86e9411c540799e79e958dd5c21eae57ca6b422fd159 | def delete_choice(self, event):
' Delete the selected choice '
index = self.list_choice.GetSelection()
if (index == wx.NOT_FOUND):
wx.MessageBox(u'Please select an item to remove from the choice.', u'LT Toolkit', style=(wx.OK | wx.ICON_ERROR))
return
self.list_choice.Delete(index)
return | Delete the selected choice | src/ltkit/panel/server/questionnaire.py | delete_choice | ptr-yudai/ltkit | 1 | python | def delete_choice(self, event):
' '
index = self.list_choice.GetSelection()
if (index == wx.NOT_FOUND):
wx.MessageBox(u'Please select an item to remove from the choice.', u'LT Toolkit', style=(wx.OK | wx.ICON_ERROR))
return
self.list_choice.Delete(index)
return | def delete_choice(self, event):
' '
index = self.list_choice.GetSelection()
if (index == wx.NOT_FOUND):
wx.MessageBox(u'Please select an item to remove from the choice.', u'LT Toolkit', style=(wx.OK | wx.ICON_ERROR))
return
self.list_choice.Delete(index)
return<|docstring|>Delete the selected choice<|endoftext|> |
cdb0e658a4c531738f999180b2b93d2c6d1c34bc2c97fa32b84ebca418d05c1e | def clear_choice(self, event):
' Clear all the choices '
dialog = wx.MessageDialog(None, 'Are you sure that you want to remove all the choices?', 'LT Toolkit', style=(wx.YES_NO | wx.ICON_QUESTION))
if (dialog.ShowModal() == wx.ID_YES):
self.list_choice.Clear()
return | Clear all the choices | src/ltkit/panel/server/questionnaire.py | clear_choice | ptr-yudai/ltkit | 1 | python | def clear_choice(self, event):
' '
dialog = wx.MessageDialog(None, 'Are you sure that you want to remove all the choices?', 'LT Toolkit', style=(wx.YES_NO | wx.ICON_QUESTION))
if (dialog.ShowModal() == wx.ID_YES):
self.list_choice.Clear()
return | def clear_choice(self, event):
' '
dialog = wx.MessageDialog(None, 'Are you sure that you want to remove all the choices?', 'LT Toolkit', style=(wx.YES_NO | wx.ICON_QUESTION))
if (dialog.ShowModal() == wx.ID_YES):
self.list_choice.Clear()
return<|docstring|>Clear all the choices<|endoftext|> |
2e12f0920869e39a99f32c311de3a38d3ad489f96765205a1f806ea65778ebf6 | def proc_new_answer(self, answer):
' Count up for new answer '
self.label_received.SetLabel('You have received {0} answer{1}.'.format(len(answer), ('s' if (len(answer) > 1) else '')))
self.layout[3].Layout()
self.layout_main.Layout()
return | Count up for new answer | src/ltkit/panel/server/questionnaire.py | proc_new_answer | ptr-yudai/ltkit | 1 | python | def proc_new_answer(self, answer):
' '
self.label_received.SetLabel('You have received {0} answer{1}.'.format(len(answer), ('s' if (len(answer) > 1) else )))
self.layout[3].Layout()
self.layout_main.Layout()
return | def proc_new_answer(self, answer):
' '
self.label_received.SetLabel('You have received {0} answer{1}.'.format(len(answer), ('s' if (len(answer) > 1) else )))
self.layout[3].Layout()
self.layout_main.Layout()
return<|docstring|>Count up for new answer<|endoftext|> |
0592c11cb5c7be69674ebd2804145d8c677ad00d78320a9cb5975ec396f39463 | def parse_line(line):
'parse a sentence with xml markup\n line - string from the file, contains the tab-separated sentence id, source sentence and target with error markup\n '
global cdec_home
line = line[:(- 1)].decode('utf-8')
chunks = line.split('\t')
if (np.size(chunks) != 3):
sys.stderr.write('Wrong format\n')
return ('', '', [], [])
sentence_id = chunks[0]
src = chunks[1]
trg = []
corrections = []
annotation = (('<?xml version="1.0" encoding="utf-8"?><mqm:translation xmlns:mqm="MQM">' + chunks[2].encode('utf-8')) + '</mqm:translation>')
try:
sentence = parseString(annotation)
except UnicodeEncodeError as e:
sys.stderr.write(("Sentence '%s' not parsed\n" % sentence_id))
print(e)
print(annotation)
return ('', '', [], [])
except:
print(sys.exc_info()[0])
print(annotation)
return ('', '', [], [])
if (not ('CDEC_HOME' in os.environ)):
cdec_home = '/home/varvara/software/cdec'
sys.stderr.write(('$CDEC_HOME variable not specified, using %s\n' % cdec_home))
else:
cdec_home = os.environ['CDEC_HOME']
FNULL = open(os.devnull, 'w')
p = Popen([(cdec_home + '/corpus/tokenize-anything.sh')], stdout=PIPE, stdin=PIPE, stderr=FNULL)
tok = p.communicate(input=src.encode('utf-8'))[0].strip()
src = tok.decode('utf-8')
FNULL.close()
curr_word = 0
opened_issues = {}
for elem in sentence.documentElement.childNodes:
if (elem.nodeType == 1):
try:
el_id = int(elem.attributes['id'].value)
if (elem.nodeName == 'mqm:startIssue'):
opened_issues[el_id] = (curr_word, elem.attributes['type'].value)
elif (elem.nodeName == 'mqm:endIssue'):
if (not opened_issues.has_key(el_id)):
sys.stderr.write(('Inconsistent error %d\n' % el_id))
return ('', '', [], [])
a_corr = Correction(opened_issues[el_id][0], curr_word, opened_issues[el_id][1], el_id)
corrections.append(a_corr)
del opened_issues[el_id]
except KeyError as e:
sys.stderr.write(('Missing attribute in sentence %s: %s\n' % (sentence_id, e.args[0])))
return ('', '', [], [])
except:
sys.stderr.write(sys.exc_info())
return ('', '', [], [])
elif (elem.nodeType == 3):
FNULL = open(os.devnull, 'w')
p = Popen([(cdec_home + '/corpus/tokenize-anything.sh')], stdout=PIPE, stdin=PIPE, stderr=FNULL)
tok = p.communicate(input=elem.nodeValue.encode('utf-8'))[0].strip()
FNULL.close()
words = [w.decode('utf-8') for w in tok.split()]
trg.extend(words)
curr_word += len(words)
if len(opened_issues):
sys.stderr.write(('Inconsistent error(s): %s\n' % ', '.join([str(x) for x in opened_issues.keys()])))
return ('', '', [], [])
return (sentence_id, src, np.array(trg, dtype=object), np.array(corrections, dtype=object)) | parse a sentence with xml markup
line - string from the file, contains the tab-separated sentence id, source sentence and target with error markup | marmot/preprocessing/parse_xml.py | parse_line | qe-team/marmot | 19 | python | def parse_line(line):
'parse a sentence with xml markup\n line - string from the file, contains the tab-separated sentence id, source sentence and target with error markup\n '
global cdec_home
line = line[:(- 1)].decode('utf-8')
chunks = line.split('\t')
if (np.size(chunks) != 3):
sys.stderr.write('Wrong format\n')
return (, , [], [])
sentence_id = chunks[0]
src = chunks[1]
trg = []
corrections = []
annotation = (('<?xml version="1.0" encoding="utf-8"?><mqm:translation xmlns:mqm="MQM">' + chunks[2].encode('utf-8')) + '</mqm:translation>')
try:
sentence = parseString(annotation)
except UnicodeEncodeError as e:
sys.stderr.write(("Sentence '%s' not parsed\n" % sentence_id))
print(e)
print(annotation)
return (, , [], [])
except:
print(sys.exc_info()[0])
print(annotation)
return (, , [], [])
if (not ('CDEC_HOME' in os.environ)):
cdec_home = '/home/varvara/software/cdec'
sys.stderr.write(('$CDEC_HOME variable not specified, using %s\n' % cdec_home))
else:
cdec_home = os.environ['CDEC_HOME']
FNULL = open(os.devnull, 'w')
p = Popen([(cdec_home + '/corpus/tokenize-anything.sh')], stdout=PIPE, stdin=PIPE, stderr=FNULL)
tok = p.communicate(input=src.encode('utf-8'))[0].strip()
src = tok.decode('utf-8')
FNULL.close()
curr_word = 0
opened_issues = {}
for elem in sentence.documentElement.childNodes:
if (elem.nodeType == 1):
try:
el_id = int(elem.attributes['id'].value)
if (elem.nodeName == 'mqm:startIssue'):
opened_issues[el_id] = (curr_word, elem.attributes['type'].value)
elif (elem.nodeName == 'mqm:endIssue'):
if (not opened_issues.has_key(el_id)):
sys.stderr.write(('Inconsistent error %d\n' % el_id))
return (, , [], [])
a_corr = Correction(opened_issues[el_id][0], curr_word, opened_issues[el_id][1], el_id)
corrections.append(a_corr)
del opened_issues[el_id]
except KeyError as e:
sys.stderr.write(('Missing attribute in sentence %s: %s\n' % (sentence_id, e.args[0])))
return (, , [], [])
except:
sys.stderr.write(sys.exc_info())
return (, , [], [])
elif (elem.nodeType == 3):
FNULL = open(os.devnull, 'w')
p = Popen([(cdec_home + '/corpus/tokenize-anything.sh')], stdout=PIPE, stdin=PIPE, stderr=FNULL)
tok = p.communicate(input=elem.nodeValue.encode('utf-8'))[0].strip()
FNULL.close()
words = [w.decode('utf-8') for w in tok.split()]
trg.extend(words)
curr_word += len(words)
if len(opened_issues):
sys.stderr.write(('Inconsistent error(s): %s\n' % ', '.join([str(x) for x in opened_issues.keys()])))
return (, , [], [])
return (sentence_id, src, np.array(trg, dtype=object), np.array(corrections, dtype=object)) | def parse_line(line):
'parse a sentence with xml markup\n line - string from the file, contains the tab-separated sentence id, source sentence and target with error markup\n '
global cdec_home
line = line[:(- 1)].decode('utf-8')
chunks = line.split('\t')
if (np.size(chunks) != 3):
sys.stderr.write('Wrong format\n')
return (, , [], [])
sentence_id = chunks[0]
src = chunks[1]
trg = []
corrections = []
annotation = (('<?xml version="1.0" encoding="utf-8"?><mqm:translation xmlns:mqm="MQM">' + chunks[2].encode('utf-8')) + '</mqm:translation>')
try:
sentence = parseString(annotation)
except UnicodeEncodeError as e:
sys.stderr.write(("Sentence '%s' not parsed\n" % sentence_id))
print(e)
print(annotation)
return (, , [], [])
except:
print(sys.exc_info()[0])
print(annotation)
return (, , [], [])
if (not ('CDEC_HOME' in os.environ)):
cdec_home = '/home/varvara/software/cdec'
sys.stderr.write(('$CDEC_HOME variable not specified, using %s\n' % cdec_home))
else:
cdec_home = os.environ['CDEC_HOME']
FNULL = open(os.devnull, 'w')
p = Popen([(cdec_home + '/corpus/tokenize-anything.sh')], stdout=PIPE, stdin=PIPE, stderr=FNULL)
tok = p.communicate(input=src.encode('utf-8'))[0].strip()
src = tok.decode('utf-8')
FNULL.close()
curr_word = 0
opened_issues = {}
for elem in sentence.documentElement.childNodes:
if (elem.nodeType == 1):
try:
el_id = int(elem.attributes['id'].value)
if (elem.nodeName == 'mqm:startIssue'):
opened_issues[el_id] = (curr_word, elem.attributes['type'].value)
elif (elem.nodeName == 'mqm:endIssue'):
if (not opened_issues.has_key(el_id)):
sys.stderr.write(('Inconsistent error %d\n' % el_id))
return (, , [], [])
a_corr = Correction(opened_issues[el_id][0], curr_word, opened_issues[el_id][1], el_id)
corrections.append(a_corr)
del opened_issues[el_id]
except KeyError as e:
sys.stderr.write(('Missing attribute in sentence %s: %s\n' % (sentence_id, e.args[0])))
return (, , [], [])
except:
sys.stderr.write(sys.exc_info())
return (, , [], [])
elif (elem.nodeType == 3):
FNULL = open(os.devnull, 'w')
p = Popen([(cdec_home + '/corpus/tokenize-anything.sh')], stdout=PIPE, stdin=PIPE, stderr=FNULL)
tok = p.communicate(input=elem.nodeValue.encode('utf-8'))[0].strip()
FNULL.close()
words = [w.decode('utf-8') for w in tok.split()]
trg.extend(words)
curr_word += len(words)
if len(opened_issues):
sys.stderr.write(('Inconsistent error(s): %s\n' % ', '.join([str(x) for x in opened_issues.keys()])))
return (, , [], [])
return (sentence_id, src, np.array(trg, dtype=object), np.array(corrections, dtype=object))<|docstring|>parse a sentence with xml markup
line - string from the file, contains the tab-separated sentence id, source sentence and target with error markup<|endoftext|> |
c7800ee8bfca49a4b174173e52b3edbbb0373625a5f5f7b589e0e2b8ad315e4a | async def open_connection_buffered(*args, get_buffer: GetBuffer=_get_buffer, loop=None, **kwargs) -> Tuple[(StreamReader, StreamWriter)]:
'\n Open stream using BufferedStreamProtocol.\n '
loop = (loop or asyncio.get_running_loop())
proto = BufferedStreamProtocol(loop, None, get_buffer)
(await loop.create_connection((lambda : proto), *args, **kwargs))
return (StreamReader(proto), StreamWriter(proto)) | Open stream using BufferedStreamProtocol. | fstream/__init__.py | open_connection_buffered | 33TU/fstream | 0 | python | async def open_connection_buffered(*args, get_buffer: GetBuffer=_get_buffer, loop=None, **kwargs) -> Tuple[(StreamReader, StreamWriter)]:
'\n \n '
loop = (loop or asyncio.get_running_loop())
proto = BufferedStreamProtocol(loop, None, get_buffer)
(await loop.create_connection((lambda : proto), *args, **kwargs))
return (StreamReader(proto), StreamWriter(proto)) | async def open_connection_buffered(*args, get_buffer: GetBuffer=_get_buffer, loop=None, **kwargs) -> Tuple[(StreamReader, StreamWriter)]:
'\n \n '
loop = (loop or asyncio.get_running_loop())
proto = BufferedStreamProtocol(loop, None, get_buffer)
(await loop.create_connection((lambda : proto), *args, **kwargs))
return (StreamReader(proto), StreamWriter(proto))<|docstring|>Open stream using BufferedStreamProtocol.<|endoftext|> |
672c4e4c1841478b70d334385dc18b780a3483c73d9881f49daadbeb8ff9f0cf | async def start_server_buffered(client_connected_cb: ConnectedCb, *args, get_buffer: GetBuffer=_get_buffer, loop=None, **kwargs) -> asyncio.AbstractServer:
'\n Start server which uses BufferedStreamProtocol.\n '
loop = (loop or asyncio.get_running_loop())
return (await loop.create_server((lambda : BufferedStreamProtocol(loop, client_connected_cb, get_buffer)), *args, **kwargs)) | Start server which uses BufferedStreamProtocol. | fstream/__init__.py | start_server_buffered | 33TU/fstream | 0 | python | async def start_server_buffered(client_connected_cb: ConnectedCb, *args, get_buffer: GetBuffer=_get_buffer, loop=None, **kwargs) -> asyncio.AbstractServer:
'\n \n '
loop = (loop or asyncio.get_running_loop())
return (await loop.create_server((lambda : BufferedStreamProtocol(loop, client_connected_cb, get_buffer)), *args, **kwargs)) | async def start_server_buffered(client_connected_cb: ConnectedCb, *args, get_buffer: GetBuffer=_get_buffer, loop=None, **kwargs) -> asyncio.AbstractServer:
'\n \n '
loop = (loop or asyncio.get_running_loop())
return (await loop.create_server((lambda : BufferedStreamProtocol(loop, client_connected_cb, get_buffer)), *args, **kwargs))<|docstring|>Start server which uses BufferedStreamProtocol.<|endoftext|> |
d192cf8e54b557c834df62a265a204fc75f1d4228b2604ed0cf7631e4e7df8ae | async def open_connection_chunked(*args, loop=None, **kwargs) -> Tuple[(StreamReader, StreamWriter)]:
'\n Open stream using ChunkedProtocol.\n '
loop = (loop or asyncio.get_running_loop())
proto = ChunkedStreamProtocol(loop, None)
(await loop.create_connection((lambda : proto), *args, **kwargs))
return (StreamReader(proto), StreamWriter(proto)) | Open stream using ChunkedProtocol. | fstream/__init__.py | open_connection_chunked | 33TU/fstream | 0 | python | async def open_connection_chunked(*args, loop=None, **kwargs) -> Tuple[(StreamReader, StreamWriter)]:
'\n \n '
loop = (loop or asyncio.get_running_loop())
proto = ChunkedStreamProtocol(loop, None)
(await loop.create_connection((lambda : proto), *args, **kwargs))
return (StreamReader(proto), StreamWriter(proto)) | async def open_connection_chunked(*args, loop=None, **kwargs) -> Tuple[(StreamReader, StreamWriter)]:
'\n \n '
loop = (loop or asyncio.get_running_loop())
proto = ChunkedStreamProtocol(loop, None)
(await loop.create_connection((lambda : proto), *args, **kwargs))
return (StreamReader(proto), StreamWriter(proto))<|docstring|>Open stream using ChunkedProtocol.<|endoftext|> |
edb8b714d3252470d03259c8b6445dc29c84ffb89d8b32079ac55a5608de130b | async def start_server_chunked(client_connected_cb: ConnectedCb, *args, loop=None, **kwargs) -> asyncio.AbstractServer:
'\n Start server which uses ChunkedStreamProtocol.\n '
loop = (loop or asyncio.get_running_loop())
return (await loop.create_server((lambda : ChunkedStreamProtocol(loop, client_connected_cb)), *args, **kwargs)) | Start server which uses ChunkedStreamProtocol. | fstream/__init__.py | start_server_chunked | 33TU/fstream | 0 | python | async def start_server_chunked(client_connected_cb: ConnectedCb, *args, loop=None, **kwargs) -> asyncio.AbstractServer:
'\n \n '
loop = (loop or asyncio.get_running_loop())
return (await loop.create_server((lambda : ChunkedStreamProtocol(loop, client_connected_cb)), *args, **kwargs)) | async def start_server_chunked(client_connected_cb: ConnectedCb, *args, loop=None, **kwargs) -> asyncio.AbstractServer:
'\n \n '
loop = (loop or asyncio.get_running_loop())
return (await loop.create_server((lambda : ChunkedStreamProtocol(loop, client_connected_cb)), *args, **kwargs))<|docstring|>Start server which uses ChunkedStreamProtocol.<|endoftext|> |
fdd675e6944ba2af15c7dfcb0611fe9aa6c94a47ae09e52b5d66136acbc1d576 | def get_index_node(self, vx):
' return the meta graph to implement index calculation\n from input @p vx '
raise NotImplementedError | return the meta graph to implement index calculation
from input @p vx | metalibm_core/core/indexing.py | get_index_node | kalray/metalibm | 27 | python | def get_index_node(self, vx):
' return the meta graph to implement index calculation\n from input @p vx '
raise NotImplementedError | def get_index_node(self, vx):
' return the meta graph to implement index calculation\n from input @p vx '
raise NotImplementedError<|docstring|>return the meta graph to implement index calculation
from input @p vx<|endoftext|> |
cd3025c65ad8b38a5915dee73d018646de6550da9e82c6e0472fa54c3bfa77cf | def get_sub_interval(self, index):
' return the sub-interval numbered @p index '
raise NotImplementedError | return the sub-interval numbered @p index | metalibm_core/core/indexing.py | get_sub_interval | kalray/metalibm | 27 | python | def get_sub_interval(self, index):
' '
raise NotImplementedError | def get_sub_interval(self, index):
' '
raise NotImplementedError<|docstring|>return the sub-interval numbered @p index<|endoftext|> |
192859110cc8136d7e32b4f312e138a2c1be500cf0e40b62cb7073c641a79538 | def get_sub_list(self):
' return the list of sub-intervals ordered by index '
raise NotImplementedError | return the list of sub-intervals ordered by index | metalibm_core/core/indexing.py | get_sub_list | kalray/metalibm | 27 | python | def get_sub_list(self):
' '
raise NotImplementedError | def get_sub_list(self):
' '
raise NotImplementedError<|docstring|>return the list of sub-intervals ordered by index<|endoftext|> |
b606a478c8b0ab26e6ccb3717679f999a2101b2ce6a04441c01e16a73fb82d90 | def get_index_node(self, vx):
' generation an operation sub-graph to compute the\n indexing from input vx\n\n :param vx: input operand\n :type vx: ML_Operation\n\n '
assert (vx.precision is self.precision)
int_precision = vx.precision.get_integer_format()
index_size = (self.exp_bits + self.field_bits)
index_mask = Constant(((2 ** index_size) - 1), precision=int_precision)
shift_amount = Constant((vx.get_precision().get_field_size() - self.field_bits), precision=int_precision)
exp_offset = Constant(self.precision.get_integer_coding((S2 ** self.low_exp_value)), precision=int_precision)
return BitLogicAnd(BitLogicRightShift(Subtraction(TypeCast(vx, precision=int_precision), exp_offset, precision=int_precision), shift_amount, precision=int_precision), index_mask, precision=int_precision) | generation an operation sub-graph to compute the
indexing from input vx
:param vx: input operand
:type vx: ML_Operation | metalibm_core/core/indexing.py | get_index_node | kalray/metalibm | 27 | python | def get_index_node(self, vx):
' generation an operation sub-graph to compute the\n indexing from input vx\n\n :param vx: input operand\n :type vx: ML_Operation\n\n '
assert (vx.precision is self.precision)
int_precision = vx.precision.get_integer_format()
index_size = (self.exp_bits + self.field_bits)
index_mask = Constant(((2 ** index_size) - 1), precision=int_precision)
shift_amount = Constant((vx.get_precision().get_field_size() - self.field_bits), precision=int_precision)
exp_offset = Constant(self.precision.get_integer_coding((S2 ** self.low_exp_value)), precision=int_precision)
return BitLogicAnd(BitLogicRightShift(Subtraction(TypeCast(vx, precision=int_precision), exp_offset, precision=int_precision), shift_amount, precision=int_precision), index_mask, precision=int_precision) | def get_index_node(self, vx):
' generation an operation sub-graph to compute the\n indexing from input vx\n\n :param vx: input operand\n :type vx: ML_Operation\n\n '
assert (vx.precision is self.precision)
int_precision = vx.precision.get_integer_format()
index_size = (self.exp_bits + self.field_bits)
index_mask = Constant(((2 ** index_size) - 1), precision=int_precision)
shift_amount = Constant((vx.get_precision().get_field_size() - self.field_bits), precision=int_precision)
exp_offset = Constant(self.precision.get_integer_coding((S2 ** self.low_exp_value)), precision=int_precision)
return BitLogicAnd(BitLogicRightShift(Subtraction(TypeCast(vx, precision=int_precision), exp_offset, precision=int_precision), shift_amount, precision=int_precision), index_mask, precision=int_precision)<|docstring|>generation an operation sub-graph to compute the
indexing from input vx
:param vx: input operand
:type vx: ML_Operation<|endoftext|> |
2408a590ff87e4027eb5739eac756cda49bbf0c2cf6c29265b297c77cff18dac | def get_sub_lo_bound(self, index):
' return the lower bound of the sub-interval\n of index @p index '
assert ((index >= 0) and (index < self.split_num))
field_index = (index % (2 ** self.field_bits))
exp_index = int((index / (2 ** self.field_bits)))
exp_value = (exp_index + self.low_exp_value)
lo_bound = ((1.0 + (field_index * (2 ** (- self.field_bits)))) * (S2 ** exp_value))
return lo_bound | return the lower bound of the sub-interval
of index @p index | metalibm_core/core/indexing.py | get_sub_lo_bound | kalray/metalibm | 27 | python | def get_sub_lo_bound(self, index):
' return the lower bound of the sub-interval\n of index @p index '
assert ((index >= 0) and (index < self.split_num))
field_index = (index % (2 ** self.field_bits))
exp_index = int((index / (2 ** self.field_bits)))
exp_value = (exp_index + self.low_exp_value)
lo_bound = ((1.0 + (field_index * (2 ** (- self.field_bits)))) * (S2 ** exp_value))
return lo_bound | def get_sub_lo_bound(self, index):
' return the lower bound of the sub-interval\n of index @p index '
assert ((index >= 0) and (index < self.split_num))
field_index = (index % (2 ** self.field_bits))
exp_index = int((index / (2 ** self.field_bits)))
exp_value = (exp_index + self.low_exp_value)
lo_bound = ((1.0 + (field_index * (2 ** (- self.field_bits)))) * (S2 ** exp_value))
return lo_bound<|docstring|>return the lower bound of the sub-interval
of index @p index<|endoftext|> |
cd829d96d9223e59cbe978eb79cc9d29137a43b3f621991d3cb5a67911e296c1 | def get_sub_hi_bound(self, index):
' return the upper bound of the sub-interval\n of index @p index '
assert ((index >= 0) and (index < self.split_num))
field_index = (index % (2 ** self.field_bits))
exp_index = int((index / (2 ** self.field_bits)))
exp_value = (exp_index + self.low_exp_value)
hi_bound = ((1.0 + ((field_index + 1) * (2 ** (- self.field_bits)))) * (S2 ** exp_value))
return hi_bound | return the upper bound of the sub-interval
of index @p index | metalibm_core/core/indexing.py | get_sub_hi_bound | kalray/metalibm | 27 | python | def get_sub_hi_bound(self, index):
' return the upper bound of the sub-interval\n of index @p index '
assert ((index >= 0) and (index < self.split_num))
field_index = (index % (2 ** self.field_bits))
exp_index = int((index / (2 ** self.field_bits)))
exp_value = (exp_index + self.low_exp_value)
hi_bound = ((1.0 + ((field_index + 1) * (2 ** (- self.field_bits)))) * (S2 ** exp_value))
return hi_bound | def get_sub_hi_bound(self, index):
' return the upper bound of the sub-interval\n of index @p index '
assert ((index >= 0) and (index < self.split_num))
field_index = (index % (2 ** self.field_bits))
exp_index = int((index / (2 ** self.field_bits)))
exp_value = (exp_index + self.low_exp_value)
hi_bound = ((1.0 + ((field_index + 1) * (2 ** (- self.field_bits)))) * (S2 ** exp_value))
return hi_bound<|docstring|>return the upper bound of the sub-interval
of index @p index<|endoftext|> |
f4e0eedf8eeafed70bca94a8090207a71b382694fbd8cb97c8f308d7f9d7b049 | def get_offseted_sub_interval(self, index):
' return a pair (offset, [0; size]) '
assert ((index >= 0) and (index < self.split_num))
lo_bound = self.get_sub_lo_bound(index)
hi_bound = self.get_sub_hi_bound(index)
return (lo_bound, Interval(0, (hi_bound - lo_bound))) | return a pair (offset, [0; size]) | metalibm_core/core/indexing.py | get_offseted_sub_interval | kalray/metalibm | 27 | python | def get_offseted_sub_interval(self, index):
' '
assert ((index >= 0) and (index < self.split_num))
lo_bound = self.get_sub_lo_bound(index)
hi_bound = self.get_sub_hi_bound(index)
return (lo_bound, Interval(0, (hi_bound - lo_bound))) | def get_offseted_sub_interval(self, index):
' '
assert ((index >= 0) and (index < self.split_num))
lo_bound = self.get_sub_lo_bound(index)
hi_bound = self.get_sub_hi_bound(index)
return (lo_bound, Interval(0, (hi_bound - lo_bound)))<|docstring|>return a pair (offset, [0; size])<|endoftext|> |
bebb3e1b9193184c0116f79aa42dc5f276d266138118168e995c9e61643f7b2c | def get_index_node(self, vx):
' return the meta graph to implement index calculation\n from input @p vx '
precision = vx.get_precision()
bound_low = inf(self.interval)
bound_high = sup(self.interval)
num_intervals = self.split_num
int_prec = precision.get_integer_format()
diff = Subtraction(vx, Constant(bound_low, precision=precision), tag='diff', precision=precision)
delta_ratio = Constant((num_intervals / (bound_high - bound_low)), precision=precision)
index = Max(0, Min(NearestInteger(Multiplication(diff, delta_ratio, precision=precision), precision=int_prec), (num_intervals - 1)), tag='index', precision=int_prec)
return index | return the meta graph to implement index calculation
from input @p vx | metalibm_core/core/indexing.py | get_index_node | kalray/metalibm | 27 | python | def get_index_node(self, vx):
' return the meta graph to implement index calculation\n from input @p vx '
precision = vx.get_precision()
bound_low = inf(self.interval)
bound_high = sup(self.interval)
num_intervals = self.split_num
int_prec = precision.get_integer_format()
diff = Subtraction(vx, Constant(bound_low, precision=precision), tag='diff', precision=precision)
delta_ratio = Constant((num_intervals / (bound_high - bound_low)), precision=precision)
index = Max(0, Min(NearestInteger(Multiplication(diff, delta_ratio, precision=precision), precision=int_prec), (num_intervals - 1)), tag='index', precision=int_prec)
return index | def get_index_node(self, vx):
' return the meta graph to implement index calculation\n from input @p vx '
precision = vx.get_precision()
bound_low = inf(self.interval)
bound_high = sup(self.interval)
num_intervals = self.split_num
int_prec = precision.get_integer_format()
diff = Subtraction(vx, Constant(bound_low, precision=precision), tag='diff', precision=precision)
delta_ratio = Constant((num_intervals / (bound_high - bound_low)), precision=precision)
index = Max(0, Min(NearestInteger(Multiplication(diff, delta_ratio, precision=precision), precision=int_prec), (num_intervals - 1)), tag='index', precision=int_prec)
return index<|docstring|>return the meta graph to implement index calculation
from input @p vx<|endoftext|> |
f8f5e25b4550cffe7745fc52428f1a578efc86ed360dd1865498ef7367bcff1b | def get_sub_interval(self, index):
' return the sub-interval numbered @p index '
subint_low = (self.bound_low + (i * interval_size))
subint_high = (self.bound_low + ((i + 1) * interval_size))
return Interval(subint_low, subint_high) | return the sub-interval numbered @p index | metalibm_core/core/indexing.py | get_sub_interval | kalray/metalibm | 27 | python | def get_sub_interval(self, index):
' '
subint_low = (self.bound_low + (i * interval_size))
subint_high = (self.bound_low + ((i + 1) * interval_size))
return Interval(subint_low, subint_high) | def get_sub_interval(self, index):
' '
subint_low = (self.bound_low + (i * interval_size))
subint_high = (self.bound_low + ((i + 1) * interval_size))
return Interval(subint_low, subint_high)<|docstring|>return the sub-interval numbered @p index<|endoftext|> |
46e6c1224f04bdfef7fa5f446d3172a83295b4ae0c2213eec106a3651f43cc7e | def create_pending_command(command_id: str='command-id', command_type: str='command-type', params: Optional[BaseModel]=None) -> cmd.Command:
'Given command data, build a pending command model.'
return cast(cmd.Command, cmd.BaseCommand(id=command_id, commandType=command_type, createdAt=datetime(year=2021, month=1, day=1), status=cmd.CommandStatus.QUEUED, params=(params or BaseModel()))) | Given command data, build a pending command model. | api/tests/opentrons/protocol_engine/state/command_fixtures.py | create_pending_command | mrod0101/opentrons | 0 | python | def create_pending_command(command_id: str='command-id', command_type: str='command-type', params: Optional[BaseModel]=None) -> cmd.Command:
return cast(cmd.Command, cmd.BaseCommand(id=command_id, commandType=command_type, createdAt=datetime(year=2021, month=1, day=1), status=cmd.CommandStatus.QUEUED, params=(params or BaseModel()))) | def create_pending_command(command_id: str='command-id', command_type: str='command-type', params: Optional[BaseModel]=None) -> cmd.Command:
return cast(cmd.Command, cmd.BaseCommand(id=command_id, commandType=command_type, createdAt=datetime(year=2021, month=1, day=1), status=cmd.CommandStatus.QUEUED, params=(params or BaseModel())))<|docstring|>Given command data, build a pending command model.<|endoftext|> |
9948daa9a5bb8707603df89d23b7e7f6c11a152b767aae6b4726580b8e70f104 | def create_running_command(command_id: str='command-id', command_type: str='command-type', params: Optional[BaseModel]=None) -> cmd.Command:
'Given command data, build a running command model.'
return cast(cmd.Command, cmd.BaseCommand(id=command_id, createdAt=datetime(year=2021, month=1, day=1), commandType=command_type, status=cmd.CommandStatus.RUNNING, params=(params or BaseModel()))) | Given command data, build a running command model. | api/tests/opentrons/protocol_engine/state/command_fixtures.py | create_running_command | mrod0101/opentrons | 0 | python | def create_running_command(command_id: str='command-id', command_type: str='command-type', params: Optional[BaseModel]=None) -> cmd.Command:
return cast(cmd.Command, cmd.BaseCommand(id=command_id, createdAt=datetime(year=2021, month=1, day=1), commandType=command_type, status=cmd.CommandStatus.RUNNING, params=(params or BaseModel()))) | def create_running_command(command_id: str='command-id', command_type: str='command-type', params: Optional[BaseModel]=None) -> cmd.Command:
return cast(cmd.Command, cmd.BaseCommand(id=command_id, createdAt=datetime(year=2021, month=1, day=1), commandType=command_type, status=cmd.CommandStatus.RUNNING, params=(params or BaseModel())))<|docstring|>Given command data, build a running command model.<|endoftext|> |
7491209d24d73526a034f1ccb19ab518664cb77437d56d995624ace458c39c99 | def create_failed_command(command_id: str='command-id', command_type: str='command-type', error_id: str='error-id', completed_at: datetime=datetime(year=2022, month=2, day=2), params: Optional[BaseModel]=None) -> cmd.Command:
'Given command data, build a failed command model.'
return cast(cmd.Command, cmd.BaseCommand(id=command_id, createdAt=datetime(year=2021, month=1, day=1), commandType=command_type, status=cmd.CommandStatus.FAILED, params=(params or BaseModel()), errorId=error_id, completedAt=completed_at)) | Given command data, build a failed command model. | api/tests/opentrons/protocol_engine/state/command_fixtures.py | create_failed_command | mrod0101/opentrons | 0 | python | def create_failed_command(command_id: str='command-id', command_type: str='command-type', error_id: str='error-id', completed_at: datetime=datetime(year=2022, month=2, day=2), params: Optional[BaseModel]=None) -> cmd.Command:
return cast(cmd.Command, cmd.BaseCommand(id=command_id, createdAt=datetime(year=2021, month=1, day=1), commandType=command_type, status=cmd.CommandStatus.FAILED, params=(params or BaseModel()), errorId=error_id, completedAt=completed_at)) | def create_failed_command(command_id: str='command-id', command_type: str='command-type', error_id: str='error-id', completed_at: datetime=datetime(year=2022, month=2, day=2), params: Optional[BaseModel]=None) -> cmd.Command:
return cast(cmd.Command, cmd.BaseCommand(id=command_id, createdAt=datetime(year=2021, month=1, day=1), commandType=command_type, status=cmd.CommandStatus.FAILED, params=(params or BaseModel()), errorId=error_id, completedAt=completed_at))<|docstring|>Given command data, build a failed command model.<|endoftext|> |
f975a36930132f666dcdad2e5fd2c5de3da61b575a71c08115785b7cdd8a55fa | def create_completed_command(command_id: str='command-id', command_type: str='command-type', params: Optional[BaseModel]=None, result: Optional[BaseModel]=None) -> cmd.Command:
'Given command data and result, build a completed command model.'
return cast(cmd.Command, cmd.BaseCommand(id=command_id, createdAt=datetime(year=2021, month=1, day=1), commandType=command_type, status=cmd.CommandStatus.SUCCEEDED, params=(params or BaseModel()), result=(result or BaseModel()))) | Given command data and result, build a completed command model. | api/tests/opentrons/protocol_engine/state/command_fixtures.py | create_completed_command | mrod0101/opentrons | 0 | python | def create_completed_command(command_id: str='command-id', command_type: str='command-type', params: Optional[BaseModel]=None, result: Optional[BaseModel]=None) -> cmd.Command:
return cast(cmd.Command, cmd.BaseCommand(id=command_id, createdAt=datetime(year=2021, month=1, day=1), commandType=command_type, status=cmd.CommandStatus.SUCCEEDED, params=(params or BaseModel()), result=(result or BaseModel()))) | def create_completed_command(command_id: str='command-id', command_type: str='command-type', params: Optional[BaseModel]=None, result: Optional[BaseModel]=None) -> cmd.Command:
return cast(cmd.Command, cmd.BaseCommand(id=command_id, createdAt=datetime(year=2021, month=1, day=1), commandType=command_type, status=cmd.CommandStatus.SUCCEEDED, params=(params or BaseModel()), result=(result or BaseModel())))<|docstring|>Given command data and result, build a completed command model.<|endoftext|> |
1fda68e4d5160e8bdca2d81466a336eee10a0f45ba537890dbdf4f09c4a4fb39 | def create_load_labware_command(labware_id: str, location: LabwareLocation, definition: LabwareDefinition, offset_id: Optional[str]) -> cmd.LoadLabware:
'Create a completed LoadLabware command.'
params = cmd.LoadLabwareParams(loadName=definition.parameters.loadName, namespace=definition.namespace, version=definition.version, location=location, labwareId=None)
result = cmd.LoadLabwareResult(labwareId=labware_id, definition=definition, offsetId=offset_id)
return cmd.LoadLabware(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | Create a completed LoadLabware command. | api/tests/opentrons/protocol_engine/state/command_fixtures.py | create_load_labware_command | mrod0101/opentrons | 0 | python | def create_load_labware_command(labware_id: str, location: LabwareLocation, definition: LabwareDefinition, offset_id: Optional[str]) -> cmd.LoadLabware:
params = cmd.LoadLabwareParams(loadName=definition.parameters.loadName, namespace=definition.namespace, version=definition.version, location=location, labwareId=None)
result = cmd.LoadLabwareResult(labwareId=labware_id, definition=definition, offsetId=offset_id)
return cmd.LoadLabware(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | def create_load_labware_command(labware_id: str, location: LabwareLocation, definition: LabwareDefinition, offset_id: Optional[str]) -> cmd.LoadLabware:
params = cmd.LoadLabwareParams(loadName=definition.parameters.loadName, namespace=definition.namespace, version=definition.version, location=location, labwareId=None)
result = cmd.LoadLabwareResult(labwareId=labware_id, definition=definition, offsetId=offset_id)
return cmd.LoadLabware(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result)<|docstring|>Create a completed LoadLabware command.<|endoftext|> |
e5ce8d3f979f313c288ecd84e0419a26a1e35a3aac558d0d0ce0d83de719ff74 | def create_add_definition_command(definition: LabwareDefinition) -> cmd.AddLabwareDefinition:
'Create a completed AddLabwareDefinition command.'
params = cmd.AddLabwareDefinitionParams(definition=definition)
result = cmd.AddLabwareDefinitionResult(loadName=definition.parameters.loadName, namespace=definition.namespace, version=definition.version)
return cmd.AddLabwareDefinition(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | Create a completed AddLabwareDefinition command. | api/tests/opentrons/protocol_engine/state/command_fixtures.py | create_add_definition_command | mrod0101/opentrons | 0 | python | def create_add_definition_command(definition: LabwareDefinition) -> cmd.AddLabwareDefinition:
params = cmd.AddLabwareDefinitionParams(definition=definition)
result = cmd.AddLabwareDefinitionResult(loadName=definition.parameters.loadName, namespace=definition.namespace, version=definition.version)
return cmd.AddLabwareDefinition(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | def create_add_definition_command(definition: LabwareDefinition) -> cmd.AddLabwareDefinition:
params = cmd.AddLabwareDefinitionParams(definition=definition)
result = cmd.AddLabwareDefinitionResult(loadName=definition.parameters.loadName, namespace=definition.namespace, version=definition.version)
return cmd.AddLabwareDefinition(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result)<|docstring|>Create a completed AddLabwareDefinition command.<|endoftext|> |
73f4a4c60f8380ee5bcf252845d3983f22eef0daaeaffd41c14ba797dfae3dc0 | def create_load_pipette_command(pipette_id: str, pipette_name: PipetteName, mount: MountType) -> cmd.LoadPipette:
'Get a completed LoadPipette command.'
params = cmd.LoadPipetteParams(pipetteName=pipette_name, mount=mount)
result = cmd.LoadPipetteResult(pipetteId=pipette_id)
return cmd.LoadPipette(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | Get a completed LoadPipette command. | api/tests/opentrons/protocol_engine/state/command_fixtures.py | create_load_pipette_command | mrod0101/opentrons | 0 | python | def create_load_pipette_command(pipette_id: str, pipette_name: PipetteName, mount: MountType) -> cmd.LoadPipette:
params = cmd.LoadPipetteParams(pipetteName=pipette_name, mount=mount)
result = cmd.LoadPipetteResult(pipetteId=pipette_id)
return cmd.LoadPipette(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | def create_load_pipette_command(pipette_id: str, pipette_name: PipetteName, mount: MountType) -> cmd.LoadPipette:
params = cmd.LoadPipetteParams(pipetteName=pipette_name, mount=mount)
result = cmd.LoadPipetteResult(pipetteId=pipette_id)
return cmd.LoadPipette(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result)<|docstring|>Get a completed LoadPipette command.<|endoftext|> |
316cad4c7f09e459e14f2ff038977c77c5c11e805d10476c5915f54d75c2111e | def create_aspirate_command(pipette_id: str, volume: float, labware_id: str='labware-id', well_name: str='A1', well_location: Optional[WellLocation]=None) -> cmd.Aspirate:
'Get a completed Aspirate command.'
params = cmd.AspirateParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name, wellLocation=(well_location or WellLocation()), volume=volume)
result = cmd.AspirateResult(volume=volume)
return cmd.Aspirate(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | Get a completed Aspirate command. | api/tests/opentrons/protocol_engine/state/command_fixtures.py | create_aspirate_command | mrod0101/opentrons | 0 | python | def create_aspirate_command(pipette_id: str, volume: float, labware_id: str='labware-id', well_name: str='A1', well_location: Optional[WellLocation]=None) -> cmd.Aspirate:
params = cmd.AspirateParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name, wellLocation=(well_location or WellLocation()), volume=volume)
result = cmd.AspirateResult(volume=volume)
return cmd.Aspirate(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | def create_aspirate_command(pipette_id: str, volume: float, labware_id: str='labware-id', well_name: str='A1', well_location: Optional[WellLocation]=None) -> cmd.Aspirate:
params = cmd.AspirateParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name, wellLocation=(well_location or WellLocation()), volume=volume)
result = cmd.AspirateResult(volume=volume)
return cmd.Aspirate(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result)<|docstring|>Get a completed Aspirate command.<|endoftext|> |
6836d764672ee50a869725479570a5954a9dc3665843d6cdc5bb277eef98cca6 | def create_dispense_command(pipette_id: str, volume: float, labware_id: str='labware-id', well_name: str='A1', well_location: Optional[WellLocation]=None) -> cmd.Dispense:
'Get a completed Dispense command.'
params = cmd.DispenseParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name, wellLocation=(well_location or WellLocation()), volume=volume)
result = cmd.DispenseResult(volume=volume)
return cmd.Dispense(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | Get a completed Dispense command. | api/tests/opentrons/protocol_engine/state/command_fixtures.py | create_dispense_command | mrod0101/opentrons | 0 | python | def create_dispense_command(pipette_id: str, volume: float, labware_id: str='labware-id', well_name: str='A1', well_location: Optional[WellLocation]=None) -> cmd.Dispense:
params = cmd.DispenseParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name, wellLocation=(well_location or WellLocation()), volume=volume)
result = cmd.DispenseResult(volume=volume)
return cmd.Dispense(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | def create_dispense_command(pipette_id: str, volume: float, labware_id: str='labware-id', well_name: str='A1', well_location: Optional[WellLocation]=None) -> cmd.Dispense:
params = cmd.DispenseParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name, wellLocation=(well_location or WellLocation()), volume=volume)
result = cmd.DispenseResult(volume=volume)
return cmd.Dispense(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result)<|docstring|>Get a completed Dispense command.<|endoftext|> |
6262bdc75750bda27cc70949ae5e6937b4684caaddba83e095ae8bd823dc33e4 | def create_pick_up_tip_command(pipette_id: str, labware_id: str='labware-id', well_name: str='A1') -> cmd.PickUpTip:
'Get a completed PickUpTip command.'
data = cmd.PickUpTipParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name)
result = cmd.PickUpTipResult()
return cmd.PickUpTip(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=data, result=result) | Get a completed PickUpTip command. | api/tests/opentrons/protocol_engine/state/command_fixtures.py | create_pick_up_tip_command | mrod0101/opentrons | 0 | python | def create_pick_up_tip_command(pipette_id: str, labware_id: str='labware-id', well_name: str='A1') -> cmd.PickUpTip:
data = cmd.PickUpTipParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name)
result = cmd.PickUpTipResult()
return cmd.PickUpTip(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=data, result=result) | def create_pick_up_tip_command(pipette_id: str, labware_id: str='labware-id', well_name: str='A1') -> cmd.PickUpTip:
data = cmd.PickUpTipParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name)
result = cmd.PickUpTipResult()
return cmd.PickUpTip(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=data, result=result)<|docstring|>Get a completed PickUpTip command.<|endoftext|> |
c20cd9818f6c45039d4c4f4eb6c6cfaf91057e7264ed614286ab4a7a12820045 | def create_drop_tip_command(pipette_id: str, labware_id: str='labware-id', well_name: str='A1') -> cmd.DropTip:
'Get a completed DropTip command.'
params = cmd.DropTipParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name)
result = cmd.DropTipResult()
return cmd.DropTip(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | Get a completed DropTip command. | api/tests/opentrons/protocol_engine/state/command_fixtures.py | create_drop_tip_command | mrod0101/opentrons | 0 | python | def create_drop_tip_command(pipette_id: str, labware_id: str='labware-id', well_name: str='A1') -> cmd.DropTip:
params = cmd.DropTipParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name)
result = cmd.DropTipResult()
return cmd.DropTip(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | def create_drop_tip_command(pipette_id: str, labware_id: str='labware-id', well_name: str='A1') -> cmd.DropTip:
params = cmd.DropTipParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name)
result = cmd.DropTipResult()
return cmd.DropTip(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result)<|docstring|>Get a completed DropTip command.<|endoftext|> |
5812c0944134aedadd19909b651e162bbdf24a5dd358d1d3fec47c1dd229a1fa | def create_move_to_well_command(pipette_id: str, labware_id: str='labware-id', well_name: str='A1') -> cmd.MoveToWell:
'Get a completed MoveToWell command.'
params = cmd.MoveToWellParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name)
result = cmd.MoveToWellResult()
return cmd.MoveToWell(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | Get a completed MoveToWell command. | api/tests/opentrons/protocol_engine/state/command_fixtures.py | create_move_to_well_command | mrod0101/opentrons | 0 | python | def create_move_to_well_command(pipette_id: str, labware_id: str='labware-id', well_name: str='A1') -> cmd.MoveToWell:
params = cmd.MoveToWellParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name)
result = cmd.MoveToWellResult()
return cmd.MoveToWell(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result) | def create_move_to_well_command(pipette_id: str, labware_id: str='labware-id', well_name: str='A1') -> cmd.MoveToWell:
params = cmd.MoveToWellParams(pipetteId=pipette_id, labwareId=labware_id, wellName=well_name)
result = cmd.MoveToWellResult()
return cmd.MoveToWell(id='command-id', status=cmd.CommandStatus.SUCCEEDED, createdAt=datetime.now(), params=params, result=result)<|docstring|>Get a completed MoveToWell command.<|endoftext|> |
8d76cf9c82e0ab20a833eb6468143f0468f1bd39c5e30159c4b88da47a44be6a | def _get_results(self, hash_output=False):
'Digest info in the statepoint and return as a string.'
sp = openmc.StatePoint(self._sp_name)
self.mgxs_lib.load_from_statepoint(sp)
self.mgxs_lib.build_hdf5_store(directory='.')
with h5py.File('mgxs.h5', 'r') as f:
outstr = ''
for domain in self.mgxs_lib.domains:
for mgxs_type in self.mgxs_lib.mgxs_types:
outstr += 'domain={0} type={1}\n'.format(domain.id, mgxs_type)
avg_key = 'mesh/{}/{}/average'.format(domain.id, mgxs_type)
std_key = 'mesh/{}/{}/std. dev.'.format(domain.id, mgxs_type)
outstr += '{}\n{}\n'.format(f[avg_key][...], f[std_key][...])
if hash_output:
sha512 = hashlib.sha512()
sha512.update(outstr.encode('utf-8'))
outstr = sha512.hexdigest()
return outstr | Digest info in the statepoint and return as a string. | tests/regression_tests/mgxs_library_hdf5/test.py | _get_results | MC-kit/openmc | 262 | python | def _get_results(self, hash_output=False):
sp = openmc.StatePoint(self._sp_name)
self.mgxs_lib.load_from_statepoint(sp)
self.mgxs_lib.build_hdf5_store(directory='.')
with h5py.File('mgxs.h5', 'r') as f:
outstr =
for domain in self.mgxs_lib.domains:
for mgxs_type in self.mgxs_lib.mgxs_types:
outstr += 'domain={0} type={1}\n'.format(domain.id, mgxs_type)
avg_key = 'mesh/{}/{}/average'.format(domain.id, mgxs_type)
std_key = 'mesh/{}/{}/std. dev.'.format(domain.id, mgxs_type)
outstr += '{}\n{}\n'.format(f[avg_key][...], f[std_key][...])
if hash_output:
sha512 = hashlib.sha512()
sha512.update(outstr.encode('utf-8'))
outstr = sha512.hexdigest()
return outstr | def _get_results(self, hash_output=False):
sp = openmc.StatePoint(self._sp_name)
self.mgxs_lib.load_from_statepoint(sp)
self.mgxs_lib.build_hdf5_store(directory='.')
with h5py.File('mgxs.h5', 'r') as f:
outstr =
for domain in self.mgxs_lib.domains:
for mgxs_type in self.mgxs_lib.mgxs_types:
outstr += 'domain={0} type={1}\n'.format(domain.id, mgxs_type)
avg_key = 'mesh/{}/{}/average'.format(domain.id, mgxs_type)
std_key = 'mesh/{}/{}/std. dev.'.format(domain.id, mgxs_type)
outstr += '{}\n{}\n'.format(f[avg_key][...], f[std_key][...])
if hash_output:
sha512 = hashlib.sha512()
sha512.update(outstr.encode('utf-8'))
outstr = sha512.hexdigest()
return outstr<|docstring|>Digest info in the statepoint and return as a string.<|endoftext|> |
da462d22cc3444c0dde0fe31b9bf928cf30c7a09228f1de1b55c40b859e2ba1b | def configure(config):
'\n | name | example | purpose |\n | ---- | ------- | ------- |\n | oblique_instance | https://oblique.sopel.chat/ | The Oblique instance to use when evaluating Python expressions (see <https://github.com/sopel-irc/oblique>) |\n '
config.define_section('py', PySection)
config.py.configure_setting('oblique_instance', 'Enter the base URL of a custom Oblique instance (optional): ') | | name | example | purpose |
| ---- | ------- | ------- |
| oblique_instance | https://oblique.sopel.chat/ | The Oblique instance to use when evaluating Python expressions (see <https://github.com/sopel-irc/oblique>) | | sopel/modules/py.py | configure | adamus1red/sopel | 555 | python | def configure(config):
'\n | name | example | purpose |\n | ---- | ------- | ------- |\n | oblique_instance | https://oblique.sopel.chat/ | The Oblique instance to use when evaluating Python expressions (see <https://github.com/sopel-irc/oblique>) |\n '
config.define_section('py', PySection)
config.py.configure_setting('oblique_instance', 'Enter the base URL of a custom Oblique instance (optional): ') | def configure(config):
'\n | name | example | purpose |\n | ---- | ------- | ------- |\n | oblique_instance | https://oblique.sopel.chat/ | The Oblique instance to use when evaluating Python expressions (see <https://github.com/sopel-irc/oblique>) |\n '
config.define_section('py', PySection)
config.py.configure_setting('oblique_instance', 'Enter the base URL of a custom Oblique instance (optional): ')<|docstring|>| name | example | purpose |
| ---- | ------- | ------- |
| oblique_instance | https://oblique.sopel.chat/ | The Oblique instance to use when evaluating Python expressions (see <https://github.com/sopel-irc/oblique>) |<|endoftext|> |
7ca53de1244e781cd2c65d386a9662ef4b114c984256e4afba1b3784c8225a39 | @plugin.command('py')
@plugin.output_prefix('[py] ')
@plugin.example('.py len([1,2,3])', '3', online=True, vcr=True)
def py(bot, trigger):
'Evaluate a Python expression.'
query = trigger.group(2)
if (not query):
bot.reply('What expression do you want me to evaluate?')
return
uri = (bot.config.py.oblique_instance + 'py/')
answer = get((uri + quote(query))).content.decode('utf-8')
if answer:
bot.say(answer)
else:
bot.reply('Sorry, no result.') | Evaluate a Python expression. | sopel/modules/py.py | py | adamus1red/sopel | 555 | python | @plugin.command('py')
@plugin.output_prefix('[py] ')
@plugin.example('.py len([1,2,3])', '3', online=True, vcr=True)
def py(bot, trigger):
query = trigger.group(2)
if (not query):
bot.reply('What expression do you want me to evaluate?')
return
uri = (bot.config.py.oblique_instance + 'py/')
answer = get((uri + quote(query))).content.decode('utf-8')
if answer:
bot.say(answer)
else:
bot.reply('Sorry, no result.') | @plugin.command('py')
@plugin.output_prefix('[py] ')
@plugin.example('.py len([1,2,3])', '3', online=True, vcr=True)
def py(bot, trigger):
query = trigger.group(2)
if (not query):
bot.reply('What expression do you want me to evaluate?')
return
uri = (bot.config.py.oblique_instance + 'py/')
answer = get((uri + quote(query))).content.decode('utf-8')
if answer:
bot.say(answer)
else:
bot.reply('Sorry, no result.')<|docstring|>Evaluate a Python expression.<|endoftext|> |
e3eb378ae172c1c3d1ba9e23330b931a3b60a764e6d0cee5a5de558511fb4e28 | def system_run() -> None:
'os.system ่ฟ่ก'
print('os.system start!')
os.system(bash_cmd) | os.system ่ฟ่ก | python_advance/ๅจpython่ๆฌไธญ่ฟ่ก่ๆฌ็ๅ ็งๆนๆณ/run_bash.py | system_run | Dustyposa/goSpider | 66 | python | def system_run() -> None:
print('os.system start!')
os.system(bash_cmd) | def system_run() -> None:
print('os.system start!')
os.system(bash_cmd)<|docstring|>os.system ่ฟ่ก<|endoftext|> |
b9c1dfcacbf8a071334ee0eba9d0fd0f7d7aba00986109b0a366a6bd670d71ee | def os_popen_run() -> None:
'ไฝฟ็จos.popen ่ฟ่กๅญ่ฟ็จ'
print('Start')
with os.popen(' '.join(python_cmd_list)) as pipe:
for line in pipe.readlines():
print(line, end='')
'\n with os.popen(bash_cmd) as pipe, open("bash_out.txt", "w", encoding="u8") as fp:\n for line in pipe.readlines():\n print(line, end="", file=fp)\n ' | ไฝฟ็จos.popen ่ฟ่กๅญ่ฟ็จ | python_advance/ๅจpython่ๆฌไธญ่ฟ่ก่ๆฌ็ๅ ็งๆนๆณ/run_bash.py | os_popen_run | Dustyposa/goSpider | 66 | python | def os_popen_run() -> None:
print('Start')
with os.popen(' '.join(python_cmd_list)) as pipe:
for line in pipe.readlines():
print(line, end=)
'\n with os.popen(bash_cmd) as pipe, open("bash_out.txt", "w", encoding="u8") as fp:\n for line in pipe.readlines():\n print(line, end=, file=fp)\n ' | def os_popen_run() -> None:
print('Start')
with os.popen(' '.join(python_cmd_list)) as pipe:
for line in pipe.readlines():
print(line, end=)
'\n with os.popen(bash_cmd) as pipe, open("bash_out.txt", "w", encoding="u8") as fp:\n for line in pipe.readlines():\n print(line, end=, file=fp)\n '<|docstring|>ไฝฟ็จos.popen ่ฟ่กๅญ่ฟ็จ<|endoftext|> |
99065a2a80a967db9a50ec611aa78f428763af1d89b7ae82926599c40ff73af4 | def os_exec_run() -> None:
'ๆฟไปฃๅฝๅ่ฟ็จ็่ฟ่ก'
print('python ๆญฃๅจ่ฟ่ก')
time.sleep(5)
print('python ่ฟ่กๅฎๆฏ๏ผๆง่ก bash ่ๆฌ')
os.execv(zsh_file, bash_cmd_list) | ๆฟไปฃๅฝๅ่ฟ็จ็่ฟ่ก | python_advance/ๅจpython่ๆฌไธญ่ฟ่ก่ๆฌ็ๅ ็งๆนๆณ/run_bash.py | os_exec_run | Dustyposa/goSpider | 66 | python | def os_exec_run() -> None:
print('python ๆญฃๅจ่ฟ่ก')
time.sleep(5)
print('python ่ฟ่กๅฎๆฏ๏ผๆง่ก bash ่ๆฌ')
os.execv(zsh_file, bash_cmd_list) | def os_exec_run() -> None:
print('python ๆญฃๅจ่ฟ่ก')
time.sleep(5)
print('python ่ฟ่กๅฎๆฏ๏ผๆง่ก bash ่ๆฌ')
os.execv(zsh_file, bash_cmd_list)<|docstring|>ๆฟไปฃๅฝๅ่ฟ็จ็่ฟ่ก<|endoftext|> |
c0d56ea2f4a75477710d2db05c6a5822c11a16a2225afd4791f8a63bcd2c1251 | def receive_binary(self, algorithm: str) -> bytes:
'\n Returns a list of 8-bit integer values.\n Each value being one color channel.\n 3 values representing one pixel\n '
self.sock.send(f'''STATE {algorithm}
'''.encode('ASCII'))
response = b''
while ((len(response) == 0) or (response[(- 1)] != 10)):
response += self.sock.recv((1024 * 4))
response = response[:(- 1)]
response = response.split(b' ', 2)[2]
return base64.b64decode(response) | Returns a list of 8-bit integer values.
Each value being one color channel.
3 values representing one pixel | frontend-python/src/pixelflut_client.py | receive_binary | ftsell/pixelflu | 7 | python | def receive_binary(self, algorithm: str) -> bytes:
'\n Returns a list of 8-bit integer values.\n Each value being one color channel.\n 3 values representing one pixel\n '
self.sock.send(f'STATE {algorithm}
'.encode('ASCII'))
response = b
while ((len(response) == 0) or (response[(- 1)] != 10)):
response += self.sock.recv((1024 * 4))
response = response[:(- 1)]
response = response.split(b' ', 2)[2]
return base64.b64decode(response) | def receive_binary(self, algorithm: str) -> bytes:
'\n Returns a list of 8-bit integer values.\n Each value being one color channel.\n 3 values representing one pixel\n '
self.sock.send(f'STATE {algorithm}
'.encode('ASCII'))
response = b
while ((len(response) == 0) or (response[(- 1)] != 10)):
response += self.sock.recv((1024 * 4))
response = response[:(- 1)]
response = response.split(b' ', 2)[2]
return base64.b64decode(response)<|docstring|>Returns a list of 8-bit integer values.
Each value being one color channel.
3 values representing one pixel<|endoftext|> |
d285f7e3ea99a00609640404b322005e309abb0b290a5f62b8bb91ff58eb3905 | def __init__(__self__, *, namespace: str, default_action: Optional[str]=None, filter_action: Optional[str]=None, filter_source: Optional[str]=None):
'\n :param str namespace: An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.\n :param str default_action: Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn\'t match the filter. The available actions are one of `"Include"` or `"Exclude"`.\n :param str filter_action: Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.\n :param str filter_source: Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression.\n '
pulumi.set(__self__, 'namespace', namespace)
if (default_action is not None):
pulumi.set(__self__, 'default_action', default_action)
if (filter_action is not None):
pulumi.set(__self__, 'filter_action', filter_action)
if (filter_source is not None):
pulumi.set(__self__, 'filter_source', filter_source) | :param str namespace: An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.
:param str default_action: Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn't match the filter. The available actions are one of `"Include"` or `"Exclude"`.
:param str filter_action: Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.
:param str filter_source: Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression. | sdk/python/pulumi_signalfx/aws/outputs.py | __init__ | pulumi/pulumi-signalfx | 2 | python | def __init__(__self__, *, namespace: str, default_action: Optional[str]=None, filter_action: Optional[str]=None, filter_source: Optional[str]=None):
'\n :param str namespace: An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.\n :param str default_action: Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn\'t match the filter. The available actions are one of `"Include"` or `"Exclude"`.\n :param str filter_action: Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.\n :param str filter_source: Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression.\n '
pulumi.set(__self__, 'namespace', namespace)
if (default_action is not None):
pulumi.set(__self__, 'default_action', default_action)
if (filter_action is not None):
pulumi.set(__self__, 'filter_action', filter_action)
if (filter_source is not None):
pulumi.set(__self__, 'filter_source', filter_source) | def __init__(__self__, *, namespace: str, default_action: Optional[str]=None, filter_action: Optional[str]=None, filter_source: Optional[str]=None):
'\n :param str namespace: An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.\n :param str default_action: Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn\'t match the filter. The available actions are one of `"Include"` or `"Exclude"`.\n :param str filter_action: Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.\n :param str filter_source: Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression.\n '
pulumi.set(__self__, 'namespace', namespace)
if (default_action is not None):
pulumi.set(__self__, 'default_action', default_action)
if (filter_action is not None):
pulumi.set(__self__, 'filter_action', filter_action)
if (filter_source is not None):
pulumi.set(__self__, 'filter_source', filter_source)<|docstring|>:param str namespace: An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.
:param str default_action: Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn't match the filter. The available actions are one of `"Include"` or `"Exclude"`.
:param str filter_action: Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.
:param str filter_source: Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression.<|endoftext|> |
06be44dbef1c56e4d7999dca4889f5f622779441a0a7ab21f444f10a02036ab0 | @property
@pulumi.getter
def namespace(self) -> str:
'\n An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.\n '
return pulumi.get(self, 'namespace') | An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information. | sdk/python/pulumi_signalfx/aws/outputs.py | namespace | pulumi/pulumi-signalfx | 2 | python | @property
@pulumi.getter
def namespace(self) -> str:
'\n \n '
return pulumi.get(self, 'namespace') | @property
@pulumi.getter
def namespace(self) -> str:
'\n \n '
return pulumi.get(self, 'namespace')<|docstring|>An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.<|endoftext|> |
53d8c20776227ce43db617bc59eda02fd579879887c1ff8e67b99778854b64af | @property
@pulumi.getter(name='defaultAction')
def default_action(self) -> Optional[str]:
'\n Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn\'t match the filter. The available actions are one of `"Include"` or `"Exclude"`.\n '
return pulumi.get(self, 'default_action') | Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn't match the filter. The available actions are one of `"Include"` or `"Exclude"`. | sdk/python/pulumi_signalfx/aws/outputs.py | default_action | pulumi/pulumi-signalfx | 2 | python | @property
@pulumi.getter(name='defaultAction')
def default_action(self) -> Optional[str]:
'\n Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn\'t match the filter. The available actions are one of `"Include"` or `"Exclude"`.\n '
return pulumi.get(self, 'default_action') | @property
@pulumi.getter(name='defaultAction')
def default_action(self) -> Optional[str]:
'\n Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn\'t match the filter. The available actions are one of `"Include"` or `"Exclude"`.\n '
return pulumi.get(self, 'default_action')<|docstring|>Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn't match the filter. The available actions are one of `"Include"` or `"Exclude"`.<|endoftext|> |
74c1c268ff3a2abb288da840122c52b189f69fedbdbe838c3cc028763a76c92c | @property
@pulumi.getter(name='filterAction')
def filter_action(self) -> Optional[str]:
'\n Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.\n '
return pulumi.get(self, 'filter_action') | Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`. | sdk/python/pulumi_signalfx/aws/outputs.py | filter_action | pulumi/pulumi-signalfx | 2 | python | @property
@pulumi.getter(name='filterAction')
def filter_action(self) -> Optional[str]:
'\n \n '
return pulumi.get(self, 'filter_action') | @property
@pulumi.getter(name='filterAction')
def filter_action(self) -> Optional[str]:
'\n \n '
return pulumi.get(self, 'filter_action')<|docstring|>Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.<|endoftext|> |
06d30016a12ec6de0b3cbceffd14427bcc06c941cdda0330927d4295df4194c1 | @property
@pulumi.getter(name='filterSource')
def filter_source(self) -> Optional[str]:
'\n Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression.\n '
return pulumi.get(self, 'filter_source') | Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression. | sdk/python/pulumi_signalfx/aws/outputs.py | filter_source | pulumi/pulumi-signalfx | 2 | python | @property
@pulumi.getter(name='filterSource')
def filter_source(self) -> Optional[str]:
'\n \n '
return pulumi.get(self, 'filter_source') | @property
@pulumi.getter(name='filterSource')
def filter_source(self) -> Optional[str]:
'\n \n '
return pulumi.get(self, 'filter_source')<|docstring|>Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression.<|endoftext|> |
d285f7e3ea99a00609640404b322005e309abb0b290a5f62b8bb91ff58eb3905 | def __init__(__self__, *, namespace: str, default_action: Optional[str]=None, filter_action: Optional[str]=None, filter_source: Optional[str]=None):
'\n :param str namespace: An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.\n :param str default_action: Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn\'t match the filter. The available actions are one of `"Include"` or `"Exclude"`.\n :param str filter_action: Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.\n :param str filter_source: Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression.\n '
pulumi.set(__self__, 'namespace', namespace)
if (default_action is not None):
pulumi.set(__self__, 'default_action', default_action)
if (filter_action is not None):
pulumi.set(__self__, 'filter_action', filter_action)
if (filter_source is not None):
pulumi.set(__self__, 'filter_source', filter_source) | :param str namespace: An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.
:param str default_action: Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn't match the filter. The available actions are one of `"Include"` or `"Exclude"`.
:param str filter_action: Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.
:param str filter_source: Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression. | sdk/python/pulumi_signalfx/aws/outputs.py | __init__ | pulumi/pulumi-signalfx | 2 | python | def __init__(__self__, *, namespace: str, default_action: Optional[str]=None, filter_action: Optional[str]=None, filter_source: Optional[str]=None):
'\n :param str namespace: An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.\n :param str default_action: Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn\'t match the filter. The available actions are one of `"Include"` or `"Exclude"`.\n :param str filter_action: Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.\n :param str filter_source: Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression.\n '
pulumi.set(__self__, 'namespace', namespace)
if (default_action is not None):
pulumi.set(__self__, 'default_action', default_action)
if (filter_action is not None):
pulumi.set(__self__, 'filter_action', filter_action)
if (filter_source is not None):
pulumi.set(__self__, 'filter_source', filter_source) | def __init__(__self__, *, namespace: str, default_action: Optional[str]=None, filter_action: Optional[str]=None, filter_source: Optional[str]=None):
'\n :param str namespace: An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.\n :param str default_action: Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn\'t match the filter. The available actions are one of `"Include"` or `"Exclude"`.\n :param str filter_action: Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.\n :param str filter_source: Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression.\n '
pulumi.set(__self__, 'namespace', namespace)
if (default_action is not None):
pulumi.set(__self__, 'default_action', default_action)
if (filter_action is not None):
pulumi.set(__self__, 'filter_action', filter_action)
if (filter_source is not None):
pulumi.set(__self__, 'filter_source', filter_source)<|docstring|>:param str namespace: An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.
:param str default_action: Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn't match the filter. The available actions are one of `"Include"` or `"Exclude"`.
:param str filter_action: Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.
:param str filter_source: Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression.<|endoftext|> |
06be44dbef1c56e4d7999dca4889f5f622779441a0a7ab21f444f10a02036ab0 | @property
@pulumi.getter
def namespace(self) -> str:
'\n An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.\n '
return pulumi.get(self, 'namespace') | An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information. | sdk/python/pulumi_signalfx/aws/outputs.py | namespace | pulumi/pulumi-signalfx | 2 | python | @property
@pulumi.getter
def namespace(self) -> str:
'\n \n '
return pulumi.get(self, 'namespace') | @property
@pulumi.getter
def namespace(self) -> str:
'\n \n '
return pulumi.get(self, 'namespace')<|docstring|>An AWS custom namespace having custom AWS metrics that you want to sync with SignalFx. See the AWS documentation on publishing metrics for more information.<|endoftext|> |
53d8c20776227ce43db617bc59eda02fd579879887c1ff8e67b99778854b64af | @property
@pulumi.getter(name='defaultAction')
def default_action(self) -> Optional[str]:
'\n Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn\'t match the filter. The available actions are one of `"Include"` or `"Exclude"`.\n '
return pulumi.get(self, 'default_action') | Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn't match the filter. The available actions are one of `"Include"` or `"Exclude"`. | sdk/python/pulumi_signalfx/aws/outputs.py | default_action | pulumi/pulumi-signalfx | 2 | python | @property
@pulumi.getter(name='defaultAction')
def default_action(self) -> Optional[str]:
'\n Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn\'t match the filter. The available actions are one of `"Include"` or `"Exclude"`.\n '
return pulumi.get(self, 'default_action') | @property
@pulumi.getter(name='defaultAction')
def default_action(self) -> Optional[str]:
'\n Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn\'t match the filter. The available actions are one of `"Include"` or `"Exclude"`.\n '
return pulumi.get(self, 'default_action')<|docstring|>Controls the SignalFx default behavior for processing data from an AWS namespace. If you do specify a filter, use this property to control how SignalFx treats data that doesn't match the filter. The available actions are one of `"Include"` or `"Exclude"`.<|endoftext|> |
74c1c268ff3a2abb288da840122c52b189f69fedbdbe838c3cc028763a76c92c | @property
@pulumi.getter(name='filterAction')
def filter_action(self) -> Optional[str]:
'\n Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.\n '
return pulumi.get(self, 'filter_action') | Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`. | sdk/python/pulumi_signalfx/aws/outputs.py | filter_action | pulumi/pulumi-signalfx | 2 | python | @property
@pulumi.getter(name='filterAction')
def filter_action(self) -> Optional[str]:
'\n \n '
return pulumi.get(self, 'filter_action') | @property
@pulumi.getter(name='filterAction')
def filter_action(self) -> Optional[str]:
'\n \n '
return pulumi.get(self, 'filter_action')<|docstring|>Controls how SignalFx processes data from a custom AWS namespace. The available actions are one of `"Include"` or `"Exclude"`.<|endoftext|> |
06d30016a12ec6de0b3cbceffd14427bcc06c941cdda0330927d4295df4194c1 | @property
@pulumi.getter(name='filterSource')
def filter_source(self) -> Optional[str]:
'\n Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression.\n '
return pulumi.get(self, 'filter_source') | Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression. | sdk/python/pulumi_signalfx/aws/outputs.py | filter_source | pulumi/pulumi-signalfx | 2 | python | @property
@pulumi.getter(name='filterSource')
def filter_source(self) -> Optional[str]:
'\n \n '
return pulumi.get(self, 'filter_source') | @property
@pulumi.getter(name='filterSource')
def filter_source(self) -> Optional[str]:
'\n \n '
return pulumi.get(self, 'filter_source')<|docstring|>Expression that selects the data that SignalFx should sync for the custom namespace associated with this sync rule. The expression uses the syntax defined for the SignalFlow `filter()` function; it can be any valid SignalFlow filter expression.<|endoftext|> |
53a59f8bc17acfab8fa3379cda28dbbdd8a55a551483de58d0e8cd43da3cead0 | @abstractmethod
def construct_circuit(self, mode, qubits=None, circuit=None):
"Construct the qft circuit.\n\n Args:\n mode (str): 'vector' or 'circuit'\n qubits (QuantumRegister or qubits): register or qubits to build the qft circuit on.\n circuit (QuantumCircuit): circuit for construction.\n\n Returns:\n The qft circuit.\n "
raise NotImplementedError() | Construct the qft circuit.
Args:
mode (str): 'vector' or 'circuit'
qubits (QuantumRegister or qubits): register or qubits to build the qft circuit on.
circuit (QuantumCircuit): circuit for construction.
Returns:
The qft circuit. | qiskit/aqua/components/qfts/qft.py | construct_circuit | dpad/qiskit-aqua | 0 | python | @abstractmethod
def construct_circuit(self, mode, qubits=None, circuit=None):
"Construct the qft circuit.\n\n Args:\n mode (str): 'vector' or 'circuit'\n qubits (QuantumRegister or qubits): register or qubits to build the qft circuit on.\n circuit (QuantumCircuit): circuit for construction.\n\n Returns:\n The qft circuit.\n "
raise NotImplementedError() | @abstractmethod
def construct_circuit(self, mode, qubits=None, circuit=None):
"Construct the qft circuit.\n\n Args:\n mode (str): 'vector' or 'circuit'\n qubits (QuantumRegister or qubits): register or qubits to build the qft circuit on.\n circuit (QuantumCircuit): circuit for construction.\n\n Returns:\n The qft circuit.\n "
raise NotImplementedError()<|docstring|>Construct the qft circuit.
Args:
mode (str): 'vector' or 'circuit'
qubits (QuantumRegister or qubits): register or qubits to build the qft circuit on.
circuit (QuantumCircuit): circuit for construction.
Returns:
The qft circuit.<|endoftext|> |
0363bffdeac2734b8288787f3dcd435665475132e8fd92b0698bc13fd7162b9f | def reporthook(count, block_size, total_size):
'\n Function that displays the status and speed of the download\n\n '
global start_time
if (count == 0):
start_time = time.time()
return
duration = (time.time() - start_time)
progress_size = int((count * block_size))
speed = int((progress_size / (1024 * duration)))
percent = int((((count * block_size) * 100) / total_size))
sys.stdout.write(('\r...%d%%, %d MB, %d KB/s, %d seconds passed' % (percent, (progress_size / (1024 * 1024)), speed, duration)))
sys.stdout.flush() | Function that displays the status and speed of the download | codes/util/input_output.py | reporthook | jagar2/Revealing-Ferroelectric-Switching-Character-Using-Deep-Recurrent-Neural-Networks | 20 | python | def reporthook(count, block_size, total_size):
'\n \n\n '
global start_time
if (count == 0):
start_time = time.time()
return
duration = (time.time() - start_time)
progress_size = int((count * block_size))
speed = int((progress_size / (1024 * duration)))
percent = int((((count * block_size) * 100) / total_size))
sys.stdout.write(('\r...%d%%, %d MB, %d KB/s, %d seconds passed' % (percent, (progress_size / (1024 * 1024)), speed, duration)))
sys.stdout.flush() | def reporthook(count, block_size, total_size):
'\n \n\n '
global start_time
if (count == 0):
start_time = time.time()
return
duration = (time.time() - start_time)
progress_size = int((count * block_size))
speed = int((progress_size / (1024 * duration)))
percent = int((((count * block_size) * 100) / total_size))
sys.stdout.write(('\r...%d%%, %d MB, %d KB/s, %d seconds passed' % (percent, (progress_size / (1024 * 1024)), speed, duration)))
sys.stdout.flush()<|docstring|>Function that displays the status and speed of the download<|endoftext|> |
ff1b6cd2b315906cd6816f8a584fa21960a81b6673d0b3bb42c42b46bbdc9657 | def download_file(url, filename):
'\n Function that downloads the data file from a URL\n\n Parameters\n ----------\n\n url : string\n url where the file to download is located\n filename : string\n location where to save the file\n reporthook : function\n callback to display the download progress\n\n '
if (not os.path.isfile(filename)):
urllib.request.urlretrieve(url, filename, reporthook) | Function that downloads the data file from a URL
Parameters
----------
url : string
url where the file to download is located
filename : string
location where to save the file
reporthook : function
callback to display the download progress | codes/util/input_output.py | download_file | jagar2/Revealing-Ferroelectric-Switching-Character-Using-Deep-Recurrent-Neural-Networks | 20 | python | def download_file(url, filename):
'\n Function that downloads the data file from a URL\n\n Parameters\n ----------\n\n url : string\n url where the file to download is located\n filename : string\n location where to save the file\n reporthook : function\n callback to display the download progress\n\n '
if (not os.path.isfile(filename)):
urllib.request.urlretrieve(url, filename, reporthook) | def download_file(url, filename):
'\n Function that downloads the data file from a URL\n\n Parameters\n ----------\n\n url : string\n url where the file to download is located\n filename : string\n location where to save the file\n reporthook : function\n callback to display the download progress\n\n '
if (not os.path.isfile(filename)):
urllib.request.urlretrieve(url, filename, reporthook)<|docstring|>Function that downloads the data file from a URL
Parameters
----------
url : string
url where the file to download is located
filename : string
location where to save the file
reporthook : function
callback to display the download progress<|endoftext|> |
34bacfa98f2311f2bd0b840f1515eae85f30d6b6e5030871fe5f1b8df48c975f | def compress_folder(base_name, format, root_dir=None):
'\n Function that zips a folder can save zip and tar\n\n Parameters\n ----------\n\n base_name : string\n base name of the zip file\n format : string\n sets the format of the zip file. Can either be zip or tar\n root_dir : string (optional)\n sets the root directory to save the file\n\n '
shutil.make_archive(base_name, format, root_dir) | Function that zips a folder can save zip and tar
Parameters
----------
base_name : string
base name of the zip file
format : string
sets the format of the zip file. Can either be zip or tar
root_dir : string (optional)
sets the root directory to save the file | codes/util/input_output.py | compress_folder | jagar2/Revealing-Ferroelectric-Switching-Character-Using-Deep-Recurrent-Neural-Networks | 20 | python | def compress_folder(base_name, format, root_dir=None):
'\n Function that zips a folder can save zip and tar\n\n Parameters\n ----------\n\n base_name : string\n base name of the zip file\n format : string\n sets the format of the zip file. Can either be zip or tar\n root_dir : string (optional)\n sets the root directory to save the file\n\n '
shutil.make_archive(base_name, format, root_dir) | def compress_folder(base_name, format, root_dir=None):
'\n Function that zips a folder can save zip and tar\n\n Parameters\n ----------\n\n base_name : string\n base name of the zip file\n format : string\n sets the format of the zip file. Can either be zip or tar\n root_dir : string (optional)\n sets the root directory to save the file\n\n '
shutil.make_archive(base_name, format, root_dir)<|docstring|>Function that zips a folder can save zip and tar
Parameters
----------
base_name : string
base name of the zip file
format : string
sets the format of the zip file. Can either be zip or tar
root_dir : string (optional)
sets the root directory to save the file<|endoftext|> |
599f37ce817e6f40f03afefccd2517b53cca050b32d8084f16a9cc9c89a0f751 | def unzip(filename, path):
'\n Function that unzips the files\n\n Parameters\n ----------\n\n filename : string\n base name of the zip file\n path : string\n path where the zip file will be saved\n\n '
zip_ref = zipfile.ZipFile(('./' + filename), 'r')
zip_ref.extractall(path)
zip_ref.close() | Function that unzips the files
Parameters
----------
filename : string
base name of the zip file
path : string
path where the zip file will be saved | codes/util/input_output.py | unzip | jagar2/Revealing-Ferroelectric-Switching-Character-Using-Deep-Recurrent-Neural-Networks | 20 | python | def unzip(filename, path):
'\n Function that unzips the files\n\n Parameters\n ----------\n\n filename : string\n base name of the zip file\n path : string\n path where the zip file will be saved\n\n '
zip_ref = zipfile.ZipFile(('./' + filename), 'r')
zip_ref.extractall(path)
zip_ref.close() | def unzip(filename, path):
'\n Function that unzips the files\n\n Parameters\n ----------\n\n filename : string\n base name of the zip file\n path : string\n path where the zip file will be saved\n\n '
zip_ref = zipfile.ZipFile(('./' + filename), 'r')
zip_ref.extractall(path)
zip_ref.close()<|docstring|>Function that unzips the files
Parameters
----------
filename : string
base name of the zip file
path : string
path where the zip file will be saved<|endoftext|> |
8b8b8347f89a24e63ee8ac44ca3539f091a33f6dba881ba2164cb396ff170d3e | def get_size(start_path='.'):
'\n\n Function that computes the size of a folder\n\n Parameters\n ----------\n\n start_path : string\n Path to compute the size of\n\n Return\n ----------\n\n total_size : float\n Size of the folder\n '
total_size = 0
for (dirpath, dirnames, filenames) in os.walk(start_path):
for f in filenames:
fp = os.path.join(dirpath, f)
total_size += os.path.getsize(fp)
return total_size | Function that computes the size of a folder
Parameters
----------
start_path : string
Path to compute the size of
Return
----------
total_size : float
Size of the folder | codes/util/input_output.py | get_size | jagar2/Revealing-Ferroelectric-Switching-Character-Using-Deep-Recurrent-Neural-Networks | 20 | python | def get_size(start_path='.'):
'\n\n Function that computes the size of a folder\n\n Parameters\n ----------\n\n start_path : string\n Path to compute the size of\n\n Return\n ----------\n\n total_size : float\n Size of the folder\n '
total_size = 0
for (dirpath, dirnames, filenames) in os.walk(start_path):
for f in filenames:
fp = os.path.join(dirpath, f)
total_size += os.path.getsize(fp)
return total_size | def get_size(start_path='.'):
'\n\n Function that computes the size of a folder\n\n Parameters\n ----------\n\n start_path : string\n Path to compute the size of\n\n Return\n ----------\n\n total_size : float\n Size of the folder\n '
total_size = 0
for (dirpath, dirnames, filenames) in os.walk(start_path):
for f in filenames:
fp = os.path.join(dirpath, f)
total_size += os.path.getsize(fp)
return total_size<|docstring|>Function that computes the size of a folder
Parameters
----------
start_path : string
Path to compute the size of
Return
----------
total_size : float
Size of the folder<|endoftext|> |
6b3e06b0191fb9def6954ee3a31013c0c82f795dd2dcda4c47457e2c6e43bea4 | def download_and_unzip(filename, url, save_path, download_data):
'\n\n Function that computes the size of a folder\n\n Parameters\n ----------\n\n filename : string\n filename to save the zip file\n url : string\n url where the file is located\n save_path : string\n place where the data is saved\n download_data : bool\n sets if to download the data\n\n '
if (np.int((get_size(save_path) / 1000000000.0)) < 1):
if (np.int((get_size(save_path) / 1000000000.0)) > 1):
print('Using files already downloaded')
elif download_data:
print('downloading data')
download_file(url, filename)
elif os.path.isfile(filename):
print('Using zip file already available')
else:
pass
if os.path.isfile(filename):
print(f'extracting {filename} to {save_path}')
unzip(filename, save_path) | Function that computes the size of a folder
Parameters
----------
filename : string
filename to save the zip file
url : string
url where the file is located
save_path : string
place where the data is saved
download_data : bool
sets if to download the data | codes/util/input_output.py | download_and_unzip | jagar2/Revealing-Ferroelectric-Switching-Character-Using-Deep-Recurrent-Neural-Networks | 20 | python | def download_and_unzip(filename, url, save_path, download_data):
'\n\n Function that computes the size of a folder\n\n Parameters\n ----------\n\n filename : string\n filename to save the zip file\n url : string\n url where the file is located\n save_path : string\n place where the data is saved\n download_data : bool\n sets if to download the data\n\n '
if (np.int((get_size(save_path) / 1000000000.0)) < 1):
if (np.int((get_size(save_path) / 1000000000.0)) > 1):
print('Using files already downloaded')
elif download_data:
print('downloading data')
download_file(url, filename)
elif os.path.isfile(filename):
print('Using zip file already available')
else:
pass
if os.path.isfile(filename):
print(f'extracting {filename} to {save_path}')
unzip(filename, save_path) | def download_and_unzip(filename, url, save_path, download_data):
'\n\n Function that computes the size of a folder\n\n Parameters\n ----------\n\n filename : string\n filename to save the zip file\n url : string\n url where the file is located\n save_path : string\n place where the data is saved\n download_data : bool\n sets if to download the data\n\n '
if (np.int((get_size(save_path) / 1000000000.0)) < 1):
if (np.int((get_size(save_path) / 1000000000.0)) > 1):
print('Using files already downloaded')
elif download_data:
print('downloading data')
download_file(url, filename)
elif os.path.isfile(filename):
print('Using zip file already available')
else:
pass
if os.path.isfile(filename):
print(f'extracting {filename} to {save_path}')
unzip(filename, save_path)<|docstring|>Function that computes the size of a folder
Parameters
----------
filename : string
filename to save the zip file
url : string
url where the file is located
save_path : string
place where the data is saved
download_data : bool
sets if to download the data<|endoftext|> |
ab3394018c574df266e9ed3a584d8d3b360bb3a19a580ecef3fb1a06f81b36a7 | def __dump_operator(operator: Operator, index: int):
'\n Prints operator in human-readable format.\n :param operator: The operator to dump.\n :param index: The index of the operator.\n '
if (operator.type == OperatorType.INTRINSIC):
readable_operator_name = operator.operand.name
readable_operator = f'${readable_operator_name}'
else:
readable_operator_type = operator.type.name
readable_operator = f'@{readable_operator_type}, {operator.operand}'
print(f'index {index}, {readable_operator}') | Prints operator in human-readable format.
:param operator: The operator to dump.
:param index: The index of the operator. | src/gofra/systems/dump.py | __dump_operator | GofraLang/core | 5 | python | def __dump_operator(operator: Operator, index: int):
'\n Prints operator in human-readable format.\n :param operator: The operator to dump.\n :param index: The index of the operator.\n '
if (operator.type == OperatorType.INTRINSIC):
readable_operator_name = operator.operand.name
readable_operator = f'${readable_operator_name}'
else:
readable_operator_type = operator.type.name
readable_operator = f'@{readable_operator_type}, {operator.operand}'
print(f'index {index}, {readable_operator}') | def __dump_operator(operator: Operator, index: int):
'\n Prints operator in human-readable format.\n :param operator: The operator to dump.\n :param index: The index of the operator.\n '
if (operator.type == OperatorType.INTRINSIC):
readable_operator_name = operator.operand.name
readable_operator = f'${readable_operator_name}'
else:
readable_operator_type = operator.type.name
readable_operator = f'@{readable_operator_type}, {operator.operand}'
print(f'index {index}, {readable_operator}')<|docstring|>Prints operator in human-readable format.
:param operator: The operator to dump.
:param index: The index of the operator.<|endoftext|> |
be0122d4f92b135fc90c10851792f9836fefc50bf0cfc31c4052813f91a5f7f6 | def dump(operators: List[Operator]):
'\n Prints all operators from given list in human-readable format.\n :param operators: List of operators.\n '
assert (len(operators) > 0), 'List of operators should be not empty!'
for (index, operator) in enumerate(operators):
__dump_operator(operator, index) | Prints all operators from given list in human-readable format.
:param operators: List of operators. | src/gofra/systems/dump.py | dump | GofraLang/core | 5 | python | def dump(operators: List[Operator]):
'\n Prints all operators from given list in human-readable format.\n :param operators: List of operators.\n '
assert (len(operators) > 0), 'List of operators should be not empty!'
for (index, operator) in enumerate(operators):
__dump_operator(operator, index) | def dump(operators: List[Operator]):
'\n Prints all operators from given list in human-readable format.\n :param operators: List of operators.\n '
assert (len(operators) > 0), 'List of operators should be not empty!'
for (index, operator) in enumerate(operators):
__dump_operator(operator, index)<|docstring|>Prints all operators from given list in human-readable format.
:param operators: List of operators.<|endoftext|> |
30650166082cb41096727c6981cb7e84d0ed9c077321cfec7eca208825297b50 | def connect_to_database(self, module_name: str=None, database: str=None, username: str=None, password: str=None, host: str=None, port: int=None, charset: str=None, config_file: str='db.cfg', autocommit: bool=False):
'Connect to database using DB API 2.0 module.\n\n :param module_name: database module to use\n :param database: name of the database\n :param username: of the user accessing the database\n :param password: of the user accessing the database\n :param host: SQL server address\n :param port: SQL server port\n :param charset: for example, "utf-8", defaults to None\n :param config_file: location of configuration file, defaults to "db.cfg"\n :param autocommit: set autocommit value for connect (only with pymssql atm)\n\n Example:\n\n .. code-block:: robotframework\n\n Connect To Database pymysql database username password host port\n Connect To Database ${CURDIR}${/}resources${/}dbconfig.cfg\n\n '
self.config.parse_arguments(module_name, database, username, password, host, port, charset, config_file)
if (self.config.module_name in ('excel', 'excelrw')):
self.db_api_module_name = 'pyodbc'
dbmodule = importlib.import_module('pyodbc')
else:
self.db_api_module_name = self.config.module_name
dbmodule = importlib.import_module(self.config.module_name)
if (module_name in ['MySQLdb', 'pymysql']):
self.config.set_default_port(3306)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(db=self.config.get('database'), user=self.config.get('username'), passwd=self.config.get('password'), host=self.config.get('host'), port=self.config.get('port'), charset=self.config.get('charset'))
elif (module_name == 'psycopg2'):
self.config.set_default_port(5432)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(database=self.config.get('database'), user=self.config.get('username'), password=self.config.get('password'), host=self.config.get('host'), port=self.config.get('port'))
elif (module_name in ('pyodbc', 'pypyodbc')):
self.config.set_default_port(1433)
self.config.set_val('connect_string', ('DRIVER={SQL Server};SERVER=%s,%s;DATABASE=%s;UID=%s;PWD=%s' % (self.config.get('host'), self.config.get('port'), self.config.get('database'), self.config.get('username'), self.config.get('password'))))
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(self.config.get('connect_string'))
elif (module_name == 'excel'):
self.config.set_val('connect_string', ('DRIVER={Microsoft Excel Driver (*.xls, *.xlsx, *.xlsm, *.xlsb)};DBQ=%s;ReadOnly=1;Extended Properties="Excel 8.0;HDR=YES";)' % self.config.get('database')))
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(self.config.get('connect_string'), autocommit=True)
elif (module_name == 'excelrw'):
self.config.set_val('connect_string', ('DRIVER={Microsoft Excel Driver (*.xls, *.xlsx, *.xlsm, *.xlsb)};DBQ=%s;ReadOnly=0;Extended Properties="Excel 8.0;HDR=YES";)' % self.config.get('database')))
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(self.config.get('connect_string'), autocommit=True)
elif (module_name in ('ibm_db', 'ibm_db_dbi')):
self.config.set_default_port(50000)
self.config.set_val('connect_string', ('DATABASE=%s;HOSTNAME=%s;PORT=%s;PROTOCOL=TCPIP;UID=%s;PWD=%s;' % (self.config.get('database'), self.config.get('host'), self.config.get('port'), self.config.get('username'), self.config.get('password'))))
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(self.config.get('connect_string'), '', '')
elif (module_name == 'cx_Oracle'):
self.config.set_default_port(1521)
oracle_dsn = dbmodule.makedsn(host=self.config.get('host'), port=self.config.get('port'), service_name=self.config.get('database'))
self.config.set_val('oracle_dsn', oracle_dsn)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(user=self.config.get('username'), password=self.config.get('password'), dsn=self.config.get('oracle_dsn'))
elif (module_name == 'teradata'):
self.config.set_default_port(1025)
teradata_udaExec = dbmodule.UdaExec(appName='RobotFramework', version='1.0', logConsole=False)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = teradata_udaExec.connect(method='odbc', system=self.config.get('host'), database=self.config.get('database'), username=self.config.get('username'), password=self.config.get('password'), host=self.config.get('host'), port=self.config.get('port'))
elif (module_name == 'pymssql'):
self.config.set_default_port(1433)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(server=self.config.get('host'), user=self.config.get('username'), password=self.config.get('password'), database=self.config.get('database'), port=self.config.get('port'), host=self.config.get('host', '.'), autocommit=autocommit)
else:
conf = self.config.all_but_empty()
self.logger.info(self.config.get_connection_parameters_as_string(conf))
self._dbconnection = dbmodule.connect(**conf) | Connect to database using DB API 2.0 module.
:param module_name: database module to use
:param database: name of the database
:param username: of the user accessing the database
:param password: of the user accessing the database
:param host: SQL server address
:param port: SQL server port
:param charset: for example, "utf-8", defaults to None
:param config_file: location of configuration file, defaults to "db.cfg"
:param autocommit: set autocommit value for connect (only with pymssql atm)
Example:
.. code-block:: robotframework
Connect To Database pymysql database username password host port
Connect To Database ${CURDIR}${/}resources${/}dbconfig.cfg | packages/main/src/RPA/Database.py | connect_to_database | rooky-c3bo/rpaframework | 518 | python | def connect_to_database(self, module_name: str=None, database: str=None, username: str=None, password: str=None, host: str=None, port: int=None, charset: str=None, config_file: str='db.cfg', autocommit: bool=False):
'Connect to database using DB API 2.0 module.\n\n :param module_name: database module to use\n :param database: name of the database\n :param username: of the user accessing the database\n :param password: of the user accessing the database\n :param host: SQL server address\n :param port: SQL server port\n :param charset: for example, "utf-8", defaults to None\n :param config_file: location of configuration file, defaults to "db.cfg"\n :param autocommit: set autocommit value for connect (only with pymssql atm)\n\n Example:\n\n .. code-block:: robotframework\n\n Connect To Database pymysql database username password host port\n Connect To Database ${CURDIR}${/}resources${/}dbconfig.cfg\n\n '
self.config.parse_arguments(module_name, database, username, password, host, port, charset, config_file)
if (self.config.module_name in ('excel', 'excelrw')):
self.db_api_module_name = 'pyodbc'
dbmodule = importlib.import_module('pyodbc')
else:
self.db_api_module_name = self.config.module_name
dbmodule = importlib.import_module(self.config.module_name)
if (module_name in ['MySQLdb', 'pymysql']):
self.config.set_default_port(3306)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(db=self.config.get('database'), user=self.config.get('username'), passwd=self.config.get('password'), host=self.config.get('host'), port=self.config.get('port'), charset=self.config.get('charset'))
elif (module_name == 'psycopg2'):
self.config.set_default_port(5432)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(database=self.config.get('database'), user=self.config.get('username'), password=self.config.get('password'), host=self.config.get('host'), port=self.config.get('port'))
elif (module_name in ('pyodbc', 'pypyodbc')):
self.config.set_default_port(1433)
self.config.set_val('connect_string', ('DRIVER={SQL Server};SERVER=%s,%s;DATABASE=%s;UID=%s;PWD=%s' % (self.config.get('host'), self.config.get('port'), self.config.get('database'), self.config.get('username'), self.config.get('password'))))
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(self.config.get('connect_string'))
elif (module_name == 'excel'):
self.config.set_val('connect_string', ('DRIVER={Microsoft Excel Driver (*.xls, *.xlsx, *.xlsm, *.xlsb)};DBQ=%s;ReadOnly=1;Extended Properties="Excel 8.0;HDR=YES";)' % self.config.get('database')))
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(self.config.get('connect_string'), autocommit=True)
elif (module_name == 'excelrw'):
self.config.set_val('connect_string', ('DRIVER={Microsoft Excel Driver (*.xls, *.xlsx, *.xlsm, *.xlsb)};DBQ=%s;ReadOnly=0;Extended Properties="Excel 8.0;HDR=YES";)' % self.config.get('database')))
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(self.config.get('connect_string'), autocommit=True)
elif (module_name in ('ibm_db', 'ibm_db_dbi')):
self.config.set_default_port(50000)
self.config.set_val('connect_string', ('DATABASE=%s;HOSTNAME=%s;PORT=%s;PROTOCOL=TCPIP;UID=%s;PWD=%s;' % (self.config.get('database'), self.config.get('host'), self.config.get('port'), self.config.get('username'), self.config.get('password'))))
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(self.config.get('connect_string'), , )
elif (module_name == 'cx_Oracle'):
self.config.set_default_port(1521)
oracle_dsn = dbmodule.makedsn(host=self.config.get('host'), port=self.config.get('port'), service_name=self.config.get('database'))
self.config.set_val('oracle_dsn', oracle_dsn)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(user=self.config.get('username'), password=self.config.get('password'), dsn=self.config.get('oracle_dsn'))
elif (module_name == 'teradata'):
self.config.set_default_port(1025)
teradata_udaExec = dbmodule.UdaExec(appName='RobotFramework', version='1.0', logConsole=False)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = teradata_udaExec.connect(method='odbc', system=self.config.get('host'), database=self.config.get('database'), username=self.config.get('username'), password=self.config.get('password'), host=self.config.get('host'), port=self.config.get('port'))
elif (module_name == 'pymssql'):
self.config.set_default_port(1433)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(server=self.config.get('host'), user=self.config.get('username'), password=self.config.get('password'), database=self.config.get('database'), port=self.config.get('port'), host=self.config.get('host', '.'), autocommit=autocommit)
else:
conf = self.config.all_but_empty()
self.logger.info(self.config.get_connection_parameters_as_string(conf))
self._dbconnection = dbmodule.connect(**conf) | def connect_to_database(self, module_name: str=None, database: str=None, username: str=None, password: str=None, host: str=None, port: int=None, charset: str=None, config_file: str='db.cfg', autocommit: bool=False):
'Connect to database using DB API 2.0 module.\n\n :param module_name: database module to use\n :param database: name of the database\n :param username: of the user accessing the database\n :param password: of the user accessing the database\n :param host: SQL server address\n :param port: SQL server port\n :param charset: for example, "utf-8", defaults to None\n :param config_file: location of configuration file, defaults to "db.cfg"\n :param autocommit: set autocommit value for connect (only with pymssql atm)\n\n Example:\n\n .. code-block:: robotframework\n\n Connect To Database pymysql database username password host port\n Connect To Database ${CURDIR}${/}resources${/}dbconfig.cfg\n\n '
self.config.parse_arguments(module_name, database, username, password, host, port, charset, config_file)
if (self.config.module_name in ('excel', 'excelrw')):
self.db_api_module_name = 'pyodbc'
dbmodule = importlib.import_module('pyodbc')
else:
self.db_api_module_name = self.config.module_name
dbmodule = importlib.import_module(self.config.module_name)
if (module_name in ['MySQLdb', 'pymysql']):
self.config.set_default_port(3306)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(db=self.config.get('database'), user=self.config.get('username'), passwd=self.config.get('password'), host=self.config.get('host'), port=self.config.get('port'), charset=self.config.get('charset'))
elif (module_name == 'psycopg2'):
self.config.set_default_port(5432)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(database=self.config.get('database'), user=self.config.get('username'), password=self.config.get('password'), host=self.config.get('host'), port=self.config.get('port'))
elif (module_name in ('pyodbc', 'pypyodbc')):
self.config.set_default_port(1433)
self.config.set_val('connect_string', ('DRIVER={SQL Server};SERVER=%s,%s;DATABASE=%s;UID=%s;PWD=%s' % (self.config.get('host'), self.config.get('port'), self.config.get('database'), self.config.get('username'), self.config.get('password'))))
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(self.config.get('connect_string'))
elif (module_name == 'excel'):
self.config.set_val('connect_string', ('DRIVER={Microsoft Excel Driver (*.xls, *.xlsx, *.xlsm, *.xlsb)};DBQ=%s;ReadOnly=1;Extended Properties="Excel 8.0;HDR=YES";)' % self.config.get('database')))
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(self.config.get('connect_string'), autocommit=True)
elif (module_name == 'excelrw'):
self.config.set_val('connect_string', ('DRIVER={Microsoft Excel Driver (*.xls, *.xlsx, *.xlsm, *.xlsb)};DBQ=%s;ReadOnly=0;Extended Properties="Excel 8.0;HDR=YES";)' % self.config.get('database')))
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(self.config.get('connect_string'), autocommit=True)
elif (module_name in ('ibm_db', 'ibm_db_dbi')):
self.config.set_default_port(50000)
self.config.set_val('connect_string', ('DATABASE=%s;HOSTNAME=%s;PORT=%s;PROTOCOL=TCPIP;UID=%s;PWD=%s;' % (self.config.get('database'), self.config.get('host'), self.config.get('port'), self.config.get('username'), self.config.get('password'))))
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(self.config.get('connect_string'), , )
elif (module_name == 'cx_Oracle'):
self.config.set_default_port(1521)
oracle_dsn = dbmodule.makedsn(host=self.config.get('host'), port=self.config.get('port'), service_name=self.config.get('database'))
self.config.set_val('oracle_dsn', oracle_dsn)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(user=self.config.get('username'), password=self.config.get('password'), dsn=self.config.get('oracle_dsn'))
elif (module_name == 'teradata'):
self.config.set_default_port(1025)
teradata_udaExec = dbmodule.UdaExec(appName='RobotFramework', version='1.0', logConsole=False)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = teradata_udaExec.connect(method='odbc', system=self.config.get('host'), database=self.config.get('database'), username=self.config.get('username'), password=self.config.get('password'), host=self.config.get('host'), port=self.config.get('port'))
elif (module_name == 'pymssql'):
self.config.set_default_port(1433)
self.logger.info(self.config.get_connection_parameters_as_string())
self._dbconnection = dbmodule.connect(server=self.config.get('host'), user=self.config.get('username'), password=self.config.get('password'), database=self.config.get('database'), port=self.config.get('port'), host=self.config.get('host', '.'), autocommit=autocommit)
else:
conf = self.config.all_but_empty()
self.logger.info(self.config.get_connection_parameters_as_string(conf))
self._dbconnection = dbmodule.connect(**conf)<|docstring|>Connect to database using DB API 2.0 module.
:param module_name: database module to use
:param database: name of the database
:param username: of the user accessing the database
:param password: of the user accessing the database
:param host: SQL server address
:param port: SQL server port
:param charset: for example, "utf-8", defaults to None
:param config_file: location of configuration file, defaults to "db.cfg"
:param autocommit: set autocommit value for connect (only with pymssql atm)
Example:
.. code-block:: robotframework
Connect To Database pymysql database username password host port
Connect To Database ${CURDIR}${/}resources${/}dbconfig.cfg<|endoftext|> |
8e4dbecec712c9cf443fcbb2755fc8723e96fe79f4285e653947eb02ecfc919e | def call_stored_procedure(self, name, params=None, sanstran=False):
'Call stored procedure with name and params.\n\n :param name: procedure name\n :param params: parameters for the procedure as a list, defaults to None\n :param sanstran: run command without an explicit transaction commit or rollback,\n defaults to False\n\n Example:\n\n .. code-block:: robotframework\n\n @{params} Create List FirstParam SecondParam ThirdParam\n @{results} Call Stored Procedure mystpr ${params}\n\n '
params = (params or [])
cur = None
try:
if (self.db_api_module_name == 'cx_Oracle'):
cur = self._dbconnection.cursor()
else:
cur = self._dbconnection.cursor(as_dict=False)
PY3K = (sys.version_info >= (3, 0))
if (not PY3K):
name = name.encode('ascii', 'ignore')
cur.callproc(name, params)
cur.nextset()
value = []
for row in cur:
value.append(row)
if (not sanstran):
self._dbconnection.commit()
return value
finally:
if cur:
if (not sanstran):
self._dbconnection.rollback() | Call stored procedure with name and params.
:param name: procedure name
:param params: parameters for the procedure as a list, defaults to None
:param sanstran: run command without an explicit transaction commit or rollback,
defaults to False
Example:
.. code-block:: robotframework
@{params} Create List FirstParam SecondParam ThirdParam
@{results} Call Stored Procedure mystpr ${params} | packages/main/src/RPA/Database.py | call_stored_procedure | rooky-c3bo/rpaframework | 518 | python | def call_stored_procedure(self, name, params=None, sanstran=False):
'Call stored procedure with name and params.\n\n :param name: procedure name\n :param params: parameters for the procedure as a list, defaults to None\n :param sanstran: run command without an explicit transaction commit or rollback,\n defaults to False\n\n Example:\n\n .. code-block:: robotframework\n\n @{params} Create List FirstParam SecondParam ThirdParam\n @{results} Call Stored Procedure mystpr ${params}\n\n '
params = (params or [])
cur = None
try:
if (self.db_api_module_name == 'cx_Oracle'):
cur = self._dbconnection.cursor()
else:
cur = self._dbconnection.cursor(as_dict=False)
PY3K = (sys.version_info >= (3, 0))
if (not PY3K):
name = name.encode('ascii', 'ignore')
cur.callproc(name, params)
cur.nextset()
value = []
for row in cur:
value.append(row)
if (not sanstran):
self._dbconnection.commit()
return value
finally:
if cur:
if (not sanstran):
self._dbconnection.rollback() | def call_stored_procedure(self, name, params=None, sanstran=False):
'Call stored procedure with name and params.\n\n :param name: procedure name\n :param params: parameters for the procedure as a list, defaults to None\n :param sanstran: run command without an explicit transaction commit or rollback,\n defaults to False\n\n Example:\n\n .. code-block:: robotframework\n\n @{params} Create List FirstParam SecondParam ThirdParam\n @{results} Call Stored Procedure mystpr ${params}\n\n '
params = (params or [])
cur = None
try:
if (self.db_api_module_name == 'cx_Oracle'):
cur = self._dbconnection.cursor()
else:
cur = self._dbconnection.cursor(as_dict=False)
PY3K = (sys.version_info >= (3, 0))
if (not PY3K):
name = name.encode('ascii', 'ignore')
cur.callproc(name, params)
cur.nextset()
value = []
for row in cur:
value.append(row)
if (not sanstran):
self._dbconnection.commit()
return value
finally:
if cur:
if (not sanstran):
self._dbconnection.rollback()<|docstring|>Call stored procedure with name and params.
:param name: procedure name
:param params: parameters for the procedure as a list, defaults to None
:param sanstran: run command without an explicit transaction commit or rollback,
defaults to False
Example:
.. code-block:: robotframework
@{params} Create List FirstParam SecondParam ThirdParam
@{results} Call Stored Procedure mystpr ${params}<|endoftext|> |
53f5083045e7a346d78cbc4ad1ee22a3bf24a344fbcbcb45215ab2fb7c7c1305 | def description(self, table):
'Get description of the SQL table\n\n :param table: name of the SQL table\n\n Example:\n\n .. code-block:: robotframework\n\n Connect To Database pymysql mydb user pass 127.0.0.1\n ${db_description} Description mytable\n\n '
try:
result = self.query(('DESCRIBE %s' % table), as_table=True)
except Exception as e:
raise AssertionError(("Operation not supported for '%s' type database" % self.db_api_module_name)) from e
return result.to_list() | Get description of the SQL table
:param table: name of the SQL table
Example:
.. code-block:: robotframework
Connect To Database pymysql mydb user pass 127.0.0.1
${db_description} Description mytable | packages/main/src/RPA/Database.py | description | rooky-c3bo/rpaframework | 518 | python | def description(self, table):
'Get description of the SQL table\n\n :param table: name of the SQL table\n\n Example:\n\n .. code-block:: robotframework\n\n Connect To Database pymysql mydb user pass 127.0.0.1\n ${db_description} Description mytable\n\n '
try:
result = self.query(('DESCRIBE %s' % table), as_table=True)
except Exception as e:
raise AssertionError(("Operation not supported for '%s' type database" % self.db_api_module_name)) from e
return result.to_list() | def description(self, table):
'Get description of the SQL table\n\n :param table: name of the SQL table\n\n Example:\n\n .. code-block:: robotframework\n\n Connect To Database pymysql mydb user pass 127.0.0.1\n ${db_description} Description mytable\n\n '
try:
result = self.query(('DESCRIBE %s' % table), as_table=True)
except Exception as e:
raise AssertionError(("Operation not supported for '%s' type database" % self.db_api_module_name)) from e
return result.to_list()<|docstring|>Get description of the SQL table
:param table: name of the SQL table
Example:
.. code-block:: robotframework
Connect To Database pymysql mydb user pass 127.0.0.1
${db_description} Description mytable<|endoftext|> |
e24fdd5359b8656c1443fdb0c45b09c536f327178c29770246f8e79d78327e07 | def disconnect_from_database(self):
'Close connection to SQL database\n\n Example:\n\n .. code-block:: robotframework\n\n Connect To Database pymysql mydb user pass 127.0.0.1\n ${result} Query Select firstname, lastname FROM table\n Disconnect From Database\n\n '
if self._dbconnection:
self._dbconnection.close() | Close connection to SQL database
Example:
.. code-block:: robotframework
Connect To Database pymysql mydb user pass 127.0.0.1
${result} Query Select firstname, lastname FROM table
Disconnect From Database | packages/main/src/RPA/Database.py | disconnect_from_database | rooky-c3bo/rpaframework | 518 | python | def disconnect_from_database(self):
'Close connection to SQL database\n\n Example:\n\n .. code-block:: robotframework\n\n Connect To Database pymysql mydb user pass 127.0.0.1\n ${result} Query Select firstname, lastname FROM table\n Disconnect From Database\n\n '
if self._dbconnection:
self._dbconnection.close() | def disconnect_from_database(self):
'Close connection to SQL database\n\n Example:\n\n .. code-block:: robotframework\n\n Connect To Database pymysql mydb user pass 127.0.0.1\n ${result} Query Select firstname, lastname FROM table\n Disconnect From Database\n\n '
if self._dbconnection:
self._dbconnection.close()<|docstring|>Close connection to SQL database
Example:
.. code-block:: robotframework
Connect To Database pymysql mydb user pass 127.0.0.1
${result} Query Select firstname, lastname FROM table
Disconnect From Database<|endoftext|> |
f618333c73f2752da894d304bddd166ed5862bf2d9e0cd0fd7f0db84cc7dbd2b | def execute_sql_script(self, filename, sanstran=False, encoding='utf-8'):
'Execute content of SQL script as SQL commands.\n\n :param filename: filepath to SQL script to execute\n :param sanstran: run command without an explicit transaction commit or rollback,\n defaults to False\n :param encoding: character encoding of file\n\n Example:\n\n .. code-block:: robotframework\n\n Execute SQL Script script.sql\n\n '
with open(filename, encoding=encoding) as script_file:
sql_script = script_file.readlines()
cur = None
try:
cur = self._dbconnection.cursor()
sqlStatement = ''
for line in sql_script:
if (line.startswith('#') or line.startswith('--')):
continue
sql_fragments = line.split(';')
if (len(sql_fragments) == 1):
sqlStatement += (line + ' ')
else:
for sqlFragment in sql_fragments:
sqlFragment = sqlFragment.strip()
if (len(sqlFragment) == 0):
continue
sqlStatement += (sqlFragment + ' ')
self.__execute_sql(cur, sqlStatement)
sqlStatement = ''
sqlStatement = sqlStatement.strip()
if (len(sqlStatement) != 0):
self.__execute_sql(cur, sqlStatement)
if (not sanstran):
self._dbconnection.commit()
finally:
if cur:
if (not sanstran):
self._dbconnection.rollback() | Execute content of SQL script as SQL commands.
:param filename: filepath to SQL script to execute
:param sanstran: run command without an explicit transaction commit or rollback,
defaults to False
:param encoding: character encoding of file
Example:
.. code-block:: robotframework
Execute SQL Script script.sql | packages/main/src/RPA/Database.py | execute_sql_script | rooky-c3bo/rpaframework | 518 | python | def execute_sql_script(self, filename, sanstran=False, encoding='utf-8'):
'Execute content of SQL script as SQL commands.\n\n :param filename: filepath to SQL script to execute\n :param sanstran: run command without an explicit transaction commit or rollback,\n defaults to False\n :param encoding: character encoding of file\n\n Example:\n\n .. code-block:: robotframework\n\n Execute SQL Script script.sql\n\n '
with open(filename, encoding=encoding) as script_file:
sql_script = script_file.readlines()
cur = None
try:
cur = self._dbconnection.cursor()
sqlStatement =
for line in sql_script:
if (line.startswith('#') or line.startswith('--')):
continue
sql_fragments = line.split(';')
if (len(sql_fragments) == 1):
sqlStatement += (line + ' ')
else:
for sqlFragment in sql_fragments:
sqlFragment = sqlFragment.strip()
if (len(sqlFragment) == 0):
continue
sqlStatement += (sqlFragment + ' ')
self.__execute_sql(cur, sqlStatement)
sqlStatement =
sqlStatement = sqlStatement.strip()
if (len(sqlStatement) != 0):
self.__execute_sql(cur, sqlStatement)
if (not sanstran):
self._dbconnection.commit()
finally:
if cur:
if (not sanstran):
self._dbconnection.rollback() | def execute_sql_script(self, filename, sanstran=False, encoding='utf-8'):
'Execute content of SQL script as SQL commands.\n\n :param filename: filepath to SQL script to execute\n :param sanstran: run command without an explicit transaction commit or rollback,\n defaults to False\n :param encoding: character encoding of file\n\n Example:\n\n .. code-block:: robotframework\n\n Execute SQL Script script.sql\n\n '
with open(filename, encoding=encoding) as script_file:
sql_script = script_file.readlines()
cur = None
try:
cur = self._dbconnection.cursor()
sqlStatement =
for line in sql_script:
if (line.startswith('#') or line.startswith('--')):
continue
sql_fragments = line.split(';')
if (len(sql_fragments) == 1):
sqlStatement += (line + ' ')
else:
for sqlFragment in sql_fragments:
sqlFragment = sqlFragment.strip()
if (len(sqlFragment) == 0):
continue
sqlStatement += (sqlFragment + ' ')
self.__execute_sql(cur, sqlStatement)
sqlStatement =
sqlStatement = sqlStatement.strip()
if (len(sqlStatement) != 0):
self.__execute_sql(cur, sqlStatement)
if (not sanstran):
self._dbconnection.commit()
finally:
if cur:
if (not sanstran):
self._dbconnection.rollback()<|docstring|>Execute content of SQL script as SQL commands.
:param filename: filepath to SQL script to execute
:param sanstran: run command without an explicit transaction commit or rollback,
defaults to False
:param encoding: character encoding of file
Example:
.. code-block:: robotframework
Execute SQL Script script.sql<|endoftext|> |
edc1f371ea6d9d821e11062fa8b975917ad73ab2dceafccd219e6389052e66e7 | def query(self, statement: str, assertion: str=None, sanstran: bool=False, as_table: bool=True):
"Make a SQL query.\n\n :param statement: SQL statement to execute\n :param assertion: assert on query result, row_count or columns.\n Works only for SELECT statements Defaults to None.\n :param sanstran: run command without an explicit transaction commit or rollback,\n defaults to False\n :param as_table: if result should be instance of ``Table``, defaults to `True`\n `False` means that return type would be `list`\n\n Example:\n\n .. code-block:: robotframework\n\n @{res} Query Select firstname, lastname FROM table\n FOR ${row} IN @{RES}\n Log ${row}\n END\n @{res} Query Select * FROM table row_count > ${EXPECTED}\n @{res} Query Select * FROM table 'arvo' in columns\n @{res} Query Select * FROM table columns == ['id', 'arvo']\n\n "
rows = None
columns = None
result = None
cursor = None
try:
cursor = self._dbconnection.cursor()
self.logger.info('Executing : Query | %s ', statement)
result = self.__execute_sql(cursor, statement)
if self._is_returnable_statement(statement):
rows = cursor.fetchall()
columns = [c[0] for c in cursor.description]
self._result_assertion(rows, columns, assertion)
if as_table:
return Table(rows, columns)
return rows
else:
if (result is not None):
if (not sanstran):
self._dbconnection.commit()
if (not sanstran):
self._dbconnection.commit()
finally:
if cursor:
if (not sanstran):
self._dbconnection.rollback()
return result | Make a SQL query.
:param statement: SQL statement to execute
:param assertion: assert on query result, row_count or columns.
Works only for SELECT statements Defaults to None.
:param sanstran: run command without an explicit transaction commit or rollback,
defaults to False
:param as_table: if result should be instance of ``Table``, defaults to `True`
`False` means that return type would be `list`
Example:
.. code-block:: robotframework
@{res} Query Select firstname, lastname FROM table
FOR ${row} IN @{RES}
Log ${row}
END
@{res} Query Select * FROM table row_count > ${EXPECTED}
@{res} Query Select * FROM table 'arvo' in columns
@{res} Query Select * FROM table columns == ['id', 'arvo'] | packages/main/src/RPA/Database.py | query | rooky-c3bo/rpaframework | 518 | python | def query(self, statement: str, assertion: str=None, sanstran: bool=False, as_table: bool=True):
"Make a SQL query.\n\n :param statement: SQL statement to execute\n :param assertion: assert on query result, row_count or columns.\n Works only for SELECT statements Defaults to None.\n :param sanstran: run command without an explicit transaction commit or rollback,\n defaults to False\n :param as_table: if result should be instance of ``Table``, defaults to `True`\n `False` means that return type would be `list`\n\n Example:\n\n .. code-block:: robotframework\n\n @{res} Query Select firstname, lastname FROM table\n FOR ${row} IN @{RES}\n Log ${row}\n END\n @{res} Query Select * FROM table row_count > ${EXPECTED}\n @{res} Query Select * FROM table 'arvo' in columns\n @{res} Query Select * FROM table columns == ['id', 'arvo']\n\n "
rows = None
columns = None
result = None
cursor = None
try:
cursor = self._dbconnection.cursor()
self.logger.info('Executing : Query | %s ', statement)
result = self.__execute_sql(cursor, statement)
if self._is_returnable_statement(statement):
rows = cursor.fetchall()
columns = [c[0] for c in cursor.description]
self._result_assertion(rows, columns, assertion)
if as_table:
return Table(rows, columns)
return rows
else:
if (result is not None):
if (not sanstran):
self._dbconnection.commit()
if (not sanstran):
self._dbconnection.commit()
finally:
if cursor:
if (not sanstran):
self._dbconnection.rollback()
return result | def query(self, statement: str, assertion: str=None, sanstran: bool=False, as_table: bool=True):
"Make a SQL query.\n\n :param statement: SQL statement to execute\n :param assertion: assert on query result, row_count or columns.\n Works only for SELECT statements Defaults to None.\n :param sanstran: run command without an explicit transaction commit or rollback,\n defaults to False\n :param as_table: if result should be instance of ``Table``, defaults to `True`\n `False` means that return type would be `list`\n\n Example:\n\n .. code-block:: robotframework\n\n @{res} Query Select firstname, lastname FROM table\n FOR ${row} IN @{RES}\n Log ${row}\n END\n @{res} Query Select * FROM table row_count > ${EXPECTED}\n @{res} Query Select * FROM table 'arvo' in columns\n @{res} Query Select * FROM table columns == ['id', 'arvo']\n\n "
rows = None
columns = None
result = None
cursor = None
try:
cursor = self._dbconnection.cursor()
self.logger.info('Executing : Query | %s ', statement)
result = self.__execute_sql(cursor, statement)
if self._is_returnable_statement(statement):
rows = cursor.fetchall()
columns = [c[0] for c in cursor.description]
self._result_assertion(rows, columns, assertion)
if as_table:
return Table(rows, columns)
return rows
else:
if (result is not None):
if (not sanstran):
self._dbconnection.commit()
if (not sanstran):
self._dbconnection.commit()
finally:
if cursor:
if (not sanstran):
self._dbconnection.rollback()
return result<|docstring|>Make a SQL query.
:param statement: SQL statement to execute
:param assertion: assert on query result, row_count or columns.
Works only for SELECT statements Defaults to None.
:param sanstran: run command without an explicit transaction commit or rollback,
defaults to False
:param as_table: if result should be instance of ``Table``, defaults to `True`
`False` means that return type would be `list`
Example:
.. code-block:: robotframework
@{res} Query Select firstname, lastname FROM table
FOR ${row} IN @{RES}
Log ${row}
END
@{res} Query Select * FROM table row_count > ${EXPECTED}
@{res} Query Select * FROM table 'arvo' in columns
@{res} Query Select * FROM table columns == ['id', 'arvo']<|endoftext|> |
7163ccf3b81e4d56b0e37f828facf448fffc38287bf261517f93dada5bfa425a | def set_auto_commit(self, autocommit=True):
'Set database auto commit mode.\n\n :param autocommit: boolean value for auto commit, defaults to True\n\n Example:\n\n .. code-block:: robotframework\n\n Set Auto Commit # auto commit is set on\n Set Auto Commit False # auto commit is turned off\n\n '
self._dbconnection.autocommit = autocommit | Set database auto commit mode.
:param autocommit: boolean value for auto commit, defaults to True
Example:
.. code-block:: robotframework
Set Auto Commit # auto commit is set on
Set Auto Commit False # auto commit is turned off | packages/main/src/RPA/Database.py | set_auto_commit | rooky-c3bo/rpaframework | 518 | python | def set_auto_commit(self, autocommit=True):
'Set database auto commit mode.\n\n :param autocommit: boolean value for auto commit, defaults to True\n\n Example:\n\n .. code-block:: robotframework\n\n Set Auto Commit # auto commit is set on\n Set Auto Commit False # auto commit is turned off\n\n '
self._dbconnection.autocommit = autocommit | def set_auto_commit(self, autocommit=True):
'Set database auto commit mode.\n\n :param autocommit: boolean value for auto commit, defaults to True\n\n Example:\n\n .. code-block:: robotframework\n\n Set Auto Commit # auto commit is set on\n Set Auto Commit False # auto commit is turned off\n\n '
self._dbconnection.autocommit = autocommit<|docstring|>Set database auto commit mode.
:param autocommit: boolean value for auto commit, defaults to True
Example:
.. code-block:: robotframework
Set Auto Commit # auto commit is set on
Set Auto Commit False # auto commit is turned off<|endoftext|> |
fb4c1cfaa93e1e3d6a10be04edac539ea97ffa9469beb17bc4fad2f3dfd11f0f | def get_rows(self, table, columns=None, conditions=None, as_table=True):
"Get rows from table. Columns and conditions can be\n set to filter result.\n\n :param table: name of the SQL table\n :param columns: name of columns to return, defaults to `None`\n means that all columns are returned\n :param conditions: limiting result by WHERE clause, defaults to `None`\n :param as_table: if result should be instance of ``Table``, defaults to `True`\n `False` means that return type would be `list`\n\n Example:\n\n .. code-block:: robotframework\n\n @{res} Get Rows tablename arvo\n @{res} Get Rows tablename arvo columns=id,name\n @{res} Get Rows tablename columns=id conditions=column1='newvalue'\n @{res} Get Rows tablename conditions=column2='updatedvalue'\n\n "
columns = (columns or '*')
where_cond = (f' WHERE {conditions}' if conditions else '')
return self.query(('SELECT %s FROM %s%s' % (columns, table, where_cond)), as_table=as_table) | Get rows from table. Columns and conditions can be
set to filter result.
:param table: name of the SQL table
:param columns: name of columns to return, defaults to `None`
means that all columns are returned
:param conditions: limiting result by WHERE clause, defaults to `None`
:param as_table: if result should be instance of ``Table``, defaults to `True`
`False` means that return type would be `list`
Example:
.. code-block:: robotframework
@{res} Get Rows tablename arvo
@{res} Get Rows tablename arvo columns=id,name
@{res} Get Rows tablename columns=id conditions=column1='newvalue'
@{res} Get Rows tablename conditions=column2='updatedvalue' | packages/main/src/RPA/Database.py | get_rows | rooky-c3bo/rpaframework | 518 | python | def get_rows(self, table, columns=None, conditions=None, as_table=True):
"Get rows from table. Columns and conditions can be\n set to filter result.\n\n :param table: name of the SQL table\n :param columns: name of columns to return, defaults to `None`\n means that all columns are returned\n :param conditions: limiting result by WHERE clause, defaults to `None`\n :param as_table: if result should be instance of ``Table``, defaults to `True`\n `False` means that return type would be `list`\n\n Example:\n\n .. code-block:: robotframework\n\n @{res} Get Rows tablename arvo\n @{res} Get Rows tablename arvo columns=id,name\n @{res} Get Rows tablename columns=id conditions=column1='newvalue'\n @{res} Get Rows tablename conditions=column2='updatedvalue'\n\n "
columns = (columns or '*')
where_cond = (f' WHERE {conditions}' if conditions else )
return self.query(('SELECT %s FROM %s%s' % (columns, table, where_cond)), as_table=as_table) | def get_rows(self, table, columns=None, conditions=None, as_table=True):
"Get rows from table. Columns and conditions can be\n set to filter result.\n\n :param table: name of the SQL table\n :param columns: name of columns to return, defaults to `None`\n means that all columns are returned\n :param conditions: limiting result by WHERE clause, defaults to `None`\n :param as_table: if result should be instance of ``Table``, defaults to `True`\n `False` means that return type would be `list`\n\n Example:\n\n .. code-block:: robotframework\n\n @{res} Get Rows tablename arvo\n @{res} Get Rows tablename arvo columns=id,name\n @{res} Get Rows tablename columns=id conditions=column1='newvalue'\n @{res} Get Rows tablename conditions=column2='updatedvalue'\n\n "
columns = (columns or '*')
where_cond = (f' WHERE {conditions}' if conditions else )
return self.query(('SELECT %s FROM %s%s' % (columns, table, where_cond)), as_table=as_table)<|docstring|>Get rows from table. Columns and conditions can be
set to filter result.
:param table: name of the SQL table
:param columns: name of columns to return, defaults to `None`
means that all columns are returned
:param conditions: limiting result by WHERE clause, defaults to `None`
:param as_table: if result should be instance of ``Table``, defaults to `True`
`False` means that return type would be `list`
Example:
.. code-block:: robotframework
@{res} Get Rows tablename arvo
@{res} Get Rows tablename arvo columns=id,name
@{res} Get Rows tablename columns=id conditions=column1='newvalue'
@{res} Get Rows tablename conditions=column2='updatedvalue'<|endoftext|> |
2f40fc22651e6025daef967b53799ce2ef04672929f5ef2970c932eb11e73cb1 | def get_number_of_rows(self, table, conditions=None):
"Get number of rows in a table. Conditions can be given\n as arguments for WHERE clause.\n\n :param table: name of the SQL table\n :param conditions: restrictions for selections, defaults to None\n\n Example:\n\n .. code-block:: robotframework\n\n ${count} Get Number Of Rows tablename\n ${count} Get Number Of Rows tablename column1=5 and column2='x'\n\n "
where_cond = (f' WHERE {conditions}' if conditions else '')
result = self.query(('SELECT COUNT(*) FROM %s%s' % (table, where_cond)), as_table=False)
return result[0][0] | Get number of rows in a table. Conditions can be given
as arguments for WHERE clause.
:param table: name of the SQL table
:param conditions: restrictions for selections, defaults to None
Example:
.. code-block:: robotframework
${count} Get Number Of Rows tablename
${count} Get Number Of Rows tablename column1=5 and column2='x' | packages/main/src/RPA/Database.py | get_number_of_rows | rooky-c3bo/rpaframework | 518 | python | def get_number_of_rows(self, table, conditions=None):
"Get number of rows in a table. Conditions can be given\n as arguments for WHERE clause.\n\n :param table: name of the SQL table\n :param conditions: restrictions for selections, defaults to None\n\n Example:\n\n .. code-block:: robotframework\n\n ${count} Get Number Of Rows tablename\n ${count} Get Number Of Rows tablename column1=5 and column2='x'\n\n "
where_cond = (f' WHERE {conditions}' if conditions else )
result = self.query(('SELECT COUNT(*) FROM %s%s' % (table, where_cond)), as_table=False)
return result[0][0] | def get_number_of_rows(self, table, conditions=None):
"Get number of rows in a table. Conditions can be given\n as arguments for WHERE clause.\n\n :param table: name of the SQL table\n :param conditions: restrictions for selections, defaults to None\n\n Example:\n\n .. code-block:: robotframework\n\n ${count} Get Number Of Rows tablename\n ${count} Get Number Of Rows tablename column1=5 and column2='x'\n\n "
where_cond = (f' WHERE {conditions}' if conditions else )
result = self.query(('SELECT COUNT(*) FROM %s%s' % (table, where_cond)), as_table=False)
return result[0][0]<|docstring|>Get number of rows in a table. Conditions can be given
as arguments for WHERE clause.
:param table: name of the SQL table
:param conditions: restrictions for selections, defaults to None
Example:
.. code-block:: robotframework
${count} Get Number Of Rows tablename
${count} Get Number Of Rows tablename column1=5 and column2='x'<|endoftext|> |
5cf0738494cca1d0ded09f6b784e02e65980e7fd8ad81c6ee3541d05f06dd092 | @abstractmethod
def _create_splits(self) -> Dict[(str, Tuple[str])]:
'Create the key splits using keys as the split name (i.e. ``train``) and the\n values as a list of the keys for the corresponding split.\n\n '
pass | Create the key splits using keys as the split name (i.e. ``train``) and the
values as a list of the keys for the corresponding split. | src/python/zensols/dataset/split.py | _create_splits | plandes/deeplearn | 2 | python | @abstractmethod
def _create_splits(self) -> Dict[(str, Tuple[str])]:
'Create the key splits using keys as the split name (i.e. ``train``) and the\n values as a list of the keys for the corresponding split.\n\n '
pass | @abstractmethod
def _create_splits(self) -> Dict[(str, Tuple[str])]:
'Create the key splits using keys as the split name (i.e. ``train``) and the\n values as a list of the keys for the corresponding split.\n\n '
pass<|docstring|>Create the key splits using keys as the split name (i.e. ``train``) and the
values as a list of the keys for the corresponding split.<|endoftext|> |
b5b2a842b0171f85d65becf96cf5140f6e5be13282fa759f9f60c5b636b6a014 | def _create_splits_and_write(self):
'Write the keys in order to the file system.\n\n '
self.key_path.mkdir(parents=True, exist_ok=True)
for (name, keys) in self._create_splits().items():
fname = self.pattern.format(**{'name': name})
key_path = (self.key_path / fname)
with open(key_path, 'w') as f:
for k in keys:
f.write((k + '\n')) | Write the keys in order to the file system. | src/python/zensols/dataset/split.py | _create_splits_and_write | plandes/deeplearn | 2 | python | def _create_splits_and_write(self):
'\n\n '
self.key_path.mkdir(parents=True, exist_ok=True)
for (name, keys) in self._create_splits().items():
fname = self.pattern.format(**{'name': name})
key_path = (self.key_path / fname)
with open(key_path, 'w') as f:
for k in keys:
f.write((k + '\n')) | def _create_splits_and_write(self):
'\n\n '
self.key_path.mkdir(parents=True, exist_ok=True)
for (name, keys) in self._create_splits().items():
fname = self.pattern.format(**{'name': name})
key_path = (self.key_path / fname)
with open(key_path, 'w') as f:
for k in keys:
f.write((k + '\n'))<|docstring|>Write the keys in order to the file system.<|endoftext|> |
5528bb232c32e299f52991a08f865de5a05ccc9837eec409cea359d75b8a260f | def _read_splits(self):
'Read the keys in order from the file system.\n\n '
by_name = {}
for path in self.key_path.iterdir():
p = parse.parse(self.pattern, path.name)
if (p is not None):
p = p.named
if ('name' in p):
with open(path) as f:
by_name[p['name']] = tuple(map((lambda ln: ln.strip()), f.readlines()))
return by_name | Read the keys in order from the file system. | src/python/zensols/dataset/split.py | _read_splits | plandes/deeplearn | 2 | python | def _read_splits(self):
'\n\n '
by_name = {}
for path in self.key_path.iterdir():
p = parse.parse(self.pattern, path.name)
if (p is not None):
p = p.named
if ('name' in p):
with open(path) as f:
by_name[p['name']] = tuple(map((lambda ln: ln.strip()), f.readlines()))
return by_name | def _read_splits(self):
'\n\n '
by_name = {}
for path in self.key_path.iterdir():
p = parse.parse(self.pattern, path.name)
if (p is not None):
p = p.named
if ('name' in p):
with open(path) as f:
by_name[p['name']] = tuple(map((lambda ln: ln.strip()), f.readlines()))
return by_name<|docstring|>Read the keys in order from the file system.<|endoftext|> |
1cfa2340c1ac29fe49c6191dcbd7a71ffc9dd28d109c9e2407cb74275fc9d23a | def explained_variance(ypred, y):
'\n Computes the fraction of variance that ypred explains about y\n ' | Computes the fraction of variance that ypred explains about y | baselines/common/math_util.py | explained_variance | baihuaxie/drl-lib | 0 | python | def explained_variance(ypred, y):
'\n \n ' | def explained_variance(ypred, y):
'\n \n '<|docstring|>Computes the fraction of variance that ypred explains about y<|endoftext|> |
db4d965456ee4587800b1e2af84aa6413e8f949295b0476d4e05987adc6f84d2 | def project_p3d(p: Vector, camera: bpy.types.Object=bpy.context.scene.camera, render: bpy.types.RenderSettings=bpy.context.scene.render) -> Vector:
'Project a point p onto the image plane of a camera. The returned value is\n in normalized device coordiantes. That is, left upper corner is -1,1, right\n bottom lower corner is 1/-1.\n\n Args:\n p (Vector): 3D vector to project to image plane\n camera (bpy.types.Object): blender camera to use for projection\n render (bpy.types.RenderSettings): render settings used for computation\n\n Returns:\n 2D vector with projected p in normalized device coordiantes\n '
if (camera.type != 'CAMERA'):
raise Exception(f'Object {camera.name} is not a camera')
if (len(p) != 3):
raise Exception(f'Vector {p} needs to be 3 dimensional')
depsgraph = bpy.context.evaluated_depsgraph_get()
modelview = camera.matrix_world.inverted()
projection = camera.calc_matrix_camera(depsgraph, x=render.resolution_x, y=render.resolution_y, scale_x=render.pixel_aspect_x, scale_y=render.pixel_aspect_y)
p_hom = ((projection @ modelview) @ Vector((p.x, p.y, p.z, 1)))
if (p_hom.w == 0.0):
return None
else:
return Vector(((p_hom.x / p_hom.w), (p_hom.y / p_hom.w))) | Project a point p onto the image plane of a camera. The returned value is
in normalized device coordiantes. That is, left upper corner is -1,1, right
bottom lower corner is 1/-1.
Args:
p (Vector): 3D vector to project to image plane
camera (bpy.types.Object): blender camera to use for projection
render (bpy.types.RenderSettings): render settings used for computation
Returns:
2D vector with projected p in normalized device coordiantes | src/amira_blender_rendering/math/geometry.py | project_p3d | patrickkesper/amira_blender_rendering | 26 | python | def project_p3d(p: Vector, camera: bpy.types.Object=bpy.context.scene.camera, render: bpy.types.RenderSettings=bpy.context.scene.render) -> Vector:
'Project a point p onto the image plane of a camera. The returned value is\n in normalized device coordiantes. That is, left upper corner is -1,1, right\n bottom lower corner is 1/-1.\n\n Args:\n p (Vector): 3D vector to project to image plane\n camera (bpy.types.Object): blender camera to use for projection\n render (bpy.types.RenderSettings): render settings used for computation\n\n Returns:\n 2D vector with projected p in normalized device coordiantes\n '
if (camera.type != 'CAMERA'):
raise Exception(f'Object {camera.name} is not a camera')
if (len(p) != 3):
raise Exception(f'Vector {p} needs to be 3 dimensional')
depsgraph = bpy.context.evaluated_depsgraph_get()
modelview = camera.matrix_world.inverted()
projection = camera.calc_matrix_camera(depsgraph, x=render.resolution_x, y=render.resolution_y, scale_x=render.pixel_aspect_x, scale_y=render.pixel_aspect_y)
p_hom = ((projection @ modelview) @ Vector((p.x, p.y, p.z, 1)))
if (p_hom.w == 0.0):
return None
else:
return Vector(((p_hom.x / p_hom.w), (p_hom.y / p_hom.w))) | def project_p3d(p: Vector, camera: bpy.types.Object=bpy.context.scene.camera, render: bpy.types.RenderSettings=bpy.context.scene.render) -> Vector:
'Project a point p onto the image plane of a camera. The returned value is\n in normalized device coordiantes. That is, left upper corner is -1,1, right\n bottom lower corner is 1/-1.\n\n Args:\n p (Vector): 3D vector to project to image plane\n camera (bpy.types.Object): blender camera to use for projection\n render (bpy.types.RenderSettings): render settings used for computation\n\n Returns:\n 2D vector with projected p in normalized device coordiantes\n '
if (camera.type != 'CAMERA'):
raise Exception(f'Object {camera.name} is not a camera')
if (len(p) != 3):
raise Exception(f'Vector {p} needs to be 3 dimensional')
depsgraph = bpy.context.evaluated_depsgraph_get()
modelview = camera.matrix_world.inverted()
projection = camera.calc_matrix_camera(depsgraph, x=render.resolution_x, y=render.resolution_y, scale_x=render.pixel_aspect_x, scale_y=render.pixel_aspect_y)
p_hom = ((projection @ modelview) @ Vector((p.x, p.y, p.z, 1)))
if (p_hom.w == 0.0):
return None
else:
return Vector(((p_hom.x / p_hom.w), (p_hom.y / p_hom.w)))<|docstring|>Project a point p onto the image plane of a camera. The returned value is
in normalized device coordiantes. That is, left upper corner is -1,1, right
bottom lower corner is 1/-1.
Args:
p (Vector): 3D vector to project to image plane
camera (bpy.types.Object): blender camera to use for projection
render (bpy.types.RenderSettings): render settings used for computation
Returns:
2D vector with projected p in normalized device coordiantes<|endoftext|> |
b19ad39faba010fdb21bebc63ea77d8b02bd10dbdbcc024cf80e3389c56c2a08 | def p2d_to_pixel_coords(p: Vector, render: bpy.types.RenderSettings=bpy.context.scene.render) -> Vector:
'Take a 2D point in normalized device coordiantes to pixel coordinates\n using specified render settings.\n\n Args:\n p (Vector): 2D vector in normalized device coordinates\n render (bpy.types.RenderSettings): blender render settings to use for\n pixel calculation\n\n Returns:\n 2D vector containing screen space (pixel) coordinate of p\n '
if (len(p) != 2):
raise Exception(f'Vector {p} needs to be 2 dimensinoal')
return Vector(((((render.resolution_x - 1) * (p.x + 1.0)) / (+ 2.0)), (((render.resolution_y - 1) * (p.y - 1.0)) / (- 2.0)))) | Take a 2D point in normalized device coordiantes to pixel coordinates
using specified render settings.
Args:
p (Vector): 2D vector in normalized device coordinates
render (bpy.types.RenderSettings): blender render settings to use for
pixel calculation
Returns:
2D vector containing screen space (pixel) coordinate of p | src/amira_blender_rendering/math/geometry.py | p2d_to_pixel_coords | patrickkesper/amira_blender_rendering | 26 | python | def p2d_to_pixel_coords(p: Vector, render: bpy.types.RenderSettings=bpy.context.scene.render) -> Vector:
'Take a 2D point in normalized device coordiantes to pixel coordinates\n using specified render settings.\n\n Args:\n p (Vector): 2D vector in normalized device coordinates\n render (bpy.types.RenderSettings): blender render settings to use for\n pixel calculation\n\n Returns:\n 2D vector containing screen space (pixel) coordinate of p\n '
if (len(p) != 2):
raise Exception(f'Vector {p} needs to be 2 dimensinoal')
return Vector(((((render.resolution_x - 1) * (p.x + 1.0)) / (+ 2.0)), (((render.resolution_y - 1) * (p.y - 1.0)) / (- 2.0)))) | def p2d_to_pixel_coords(p: Vector, render: bpy.types.RenderSettings=bpy.context.scene.render) -> Vector:
'Take a 2D point in normalized device coordiantes to pixel coordinates\n using specified render settings.\n\n Args:\n p (Vector): 2D vector in normalized device coordinates\n render (bpy.types.RenderSettings): blender render settings to use for\n pixel calculation\n\n Returns:\n 2D vector containing screen space (pixel) coordinate of p\n '
if (len(p) != 2):
raise Exception(f'Vector {p} needs to be 2 dimensinoal')
return Vector(((((render.resolution_x - 1) * (p.x + 1.0)) / (+ 2.0)), (((render.resolution_y - 1) * (p.y - 1.0)) / (- 2.0))))<|docstring|>Take a 2D point in normalized device coordiantes to pixel coordinates
using specified render settings.
Args:
p (Vector): 2D vector in normalized device coordinates
render (bpy.types.RenderSettings): blender render settings to use for
pixel calculation
Returns:
2D vector containing screen space (pixel) coordinate of p<|endoftext|> |
ace303e3f89efdcf97e4917d4b4831f04f10063fb58e5830ea88ce68439b06eb | def get_relative_rotation(obj1: bpy.types.Object, obj2: bpy.types.Object=bpy.context.scene.camera) -> Euler:
"Get the relative rotation between two objects in terms of the second\n object's coordinate system. Note that the second object will be default\n initialized to the scene's camera.\n\n Returns:\n Euler angles given in radians\n "
obj1_m = obj1.matrix_world.to_3x3().normalized()
obj2_m = obj2.matrix_world.to_3x3().normalized()
rel_rotation = (obj2_m.inverted() @ obj1_m).to_euler()
return rel_rotation | Get the relative rotation between two objects in terms of the second
object's coordinate system. Note that the second object will be default
initialized to the scene's camera.
Returns:
Euler angles given in radians | src/amira_blender_rendering/math/geometry.py | get_relative_rotation | patrickkesper/amira_blender_rendering | 26 | python | def get_relative_rotation(obj1: bpy.types.Object, obj2: bpy.types.Object=bpy.context.scene.camera) -> Euler:
"Get the relative rotation between two objects in terms of the second\n object's coordinate system. Note that the second object will be default\n initialized to the scene's camera.\n\n Returns:\n Euler angles given in radians\n "
obj1_m = obj1.matrix_world.to_3x3().normalized()
obj2_m = obj2.matrix_world.to_3x3().normalized()
rel_rotation = (obj2_m.inverted() @ obj1_m).to_euler()
return rel_rotation | def get_relative_rotation(obj1: bpy.types.Object, obj2: bpy.types.Object=bpy.context.scene.camera) -> Euler:
"Get the relative rotation between two objects in terms of the second\n object's coordinate system. Note that the second object will be default\n initialized to the scene's camera.\n\n Returns:\n Euler angles given in radians\n "
obj1_m = obj1.matrix_world.to_3x3().normalized()
obj2_m = obj2.matrix_world.to_3x3().normalized()
rel_rotation = (obj2_m.inverted() @ obj1_m).to_euler()
return rel_rotation<|docstring|>Get the relative rotation between two objects in terms of the second
object's coordinate system. Note that the second object will be default
initialized to the scene's camera.
Returns:
Euler angles given in radians<|endoftext|> |
81ef0b072c1eb391762699be2029067d4f810068bee1da1f4b3b11d7d51f2fd2 | def get_relative_rotation_to_cam_deg(obj, cam, zeroing=Vector((90, 0, 0))):
"Get the relative rotation between an object and a camera in the camera's\n frame of reference.\n\n For more details, see get_relative_rotation_to_cam_rad.\n\n Args:\n obj: object to compute relative rotation for\n cam: camera to used\n zeroing: camera zeroing angles (in degrees)\n\n Returns:\n Relative rotation between object and camera in the coordinate frame of\n the camera.\n "
return get_relative_rotation_to_cam_rad(obj, cam, ((zeroing * pi) / 180)) | Get the relative rotation between an object and a camera in the camera's
frame of reference.
For more details, see get_relative_rotation_to_cam_rad.
Args:
obj: object to compute relative rotation for
cam: camera to used
zeroing: camera zeroing angles (in degrees)
Returns:
Relative rotation between object and camera in the coordinate frame of
the camera. | src/amira_blender_rendering/math/geometry.py | get_relative_rotation_to_cam_deg | patrickkesper/amira_blender_rendering | 26 | python | def get_relative_rotation_to_cam_deg(obj, cam, zeroing=Vector((90, 0, 0))):
"Get the relative rotation between an object and a camera in the camera's\n frame of reference.\n\n For more details, see get_relative_rotation_to_cam_rad.\n\n Args:\n obj: object to compute relative rotation for\n cam: camera to used\n zeroing: camera zeroing angles (in degrees)\n\n Returns:\n Relative rotation between object and camera in the coordinate frame of\n the camera.\n "
return get_relative_rotation_to_cam_rad(obj, cam, ((zeroing * pi) / 180)) | def get_relative_rotation_to_cam_deg(obj, cam, zeroing=Vector((90, 0, 0))):
"Get the relative rotation between an object and a camera in the camera's\n frame of reference.\n\n For more details, see get_relative_rotation_to_cam_rad.\n\n Args:\n obj: object to compute relative rotation for\n cam: camera to used\n zeroing: camera zeroing angles (in degrees)\n\n Returns:\n Relative rotation between object and camera in the coordinate frame of\n the camera.\n "
return get_relative_rotation_to_cam_rad(obj, cam, ((zeroing * pi) / 180))<|docstring|>Get the relative rotation between an object and a camera in the camera's
frame of reference.
For more details, see get_relative_rotation_to_cam_rad.
Args:
obj: object to compute relative rotation for
cam: camera to used
zeroing: camera zeroing angles (in degrees)
Returns:
Relative rotation between object and camera in the coordinate frame of
the camera.<|endoftext|> |
f293ef8c2a71d576f121d7dbdf0be746368ad8a1cf1da4e46cca8803e606f964 | def get_relative_rotation_to_cam_rad(obj, cam, zeroing=Vector(((pi / 2), 0, 0))):
"Get the relative rotation between an object and a camera in the camera's\n frame of reference.\n\n This function allows to specify a certain 'zeroing' rotation.\n\n A default camera in blender with 0 rotation applied to its transform looks\n along the -Z direction. Blender's modelling viewport, however, assumes that\n the surface plane is spanned by X and Y, where X indicates left/right. This\n can be observed by putting the modelling viewport into the front viewpoint\n (Numpad 1). Then, the viewport looks along the Y direction.\n\n As a consequence, the relative rotation between a camera image and an object\n is only 0 when the camera would look onto the top of the object. Note that\n this is rather unintuitive, as most people would expect that the relative\n rotation is 0 when the camera looks at the front of an object.\n\n Args:\n obj: object to compute relative rotation for\n cam: camera to used\n zeroing: camera zeroing angles (in radians)\n\n Returns:\n Relative rotation between object and camera in the coordinate frame of\n the camera.\n "
obj_m = obj.matrix_world.to_3x3().normalized()
cam_m = cam.matrix_world.to_3x3().normalized()
rel_rotation = (cam_m.inverted() @ obj_m)
cam_rot = Euler([zeroing[0], zeroing[1], zeroing[2]]).to_matrix()
return (cam_rot @ rel_rotation).to_euler() | Get the relative rotation between an object and a camera in the camera's
frame of reference.
This function allows to specify a certain 'zeroing' rotation.
A default camera in blender with 0 rotation applied to its transform looks
along the -Z direction. Blender's modelling viewport, however, assumes that
the surface plane is spanned by X and Y, where X indicates left/right. This
can be observed by putting the modelling viewport into the front viewpoint
(Numpad 1). Then, the viewport looks along the Y direction.
As a consequence, the relative rotation between a camera image and an object
is only 0 when the camera would look onto the top of the object. Note that
this is rather unintuitive, as most people would expect that the relative
rotation is 0 when the camera looks at the front of an object.
Args:
obj: object to compute relative rotation for
cam: camera to used
zeroing: camera zeroing angles (in radians)
Returns:
Relative rotation between object and camera in the coordinate frame of
the camera. | src/amira_blender_rendering/math/geometry.py | get_relative_rotation_to_cam_rad | patrickkesper/amira_blender_rendering | 26 | python | def get_relative_rotation_to_cam_rad(obj, cam, zeroing=Vector(((pi / 2), 0, 0))):
"Get the relative rotation between an object and a camera in the camera's\n frame of reference.\n\n This function allows to specify a certain 'zeroing' rotation.\n\n A default camera in blender with 0 rotation applied to its transform looks\n along the -Z direction. Blender's modelling viewport, however, assumes that\n the surface plane is spanned by X and Y, where X indicates left/right. This\n can be observed by putting the modelling viewport into the front viewpoint\n (Numpad 1). Then, the viewport looks along the Y direction.\n\n As a consequence, the relative rotation between a camera image and an object\n is only 0 when the camera would look onto the top of the object. Note that\n this is rather unintuitive, as most people would expect that the relative\n rotation is 0 when the camera looks at the front of an object.\n\n Args:\n obj: object to compute relative rotation for\n cam: camera to used\n zeroing: camera zeroing angles (in radians)\n\n Returns:\n Relative rotation between object and camera in the coordinate frame of\n the camera.\n "
obj_m = obj.matrix_world.to_3x3().normalized()
cam_m = cam.matrix_world.to_3x3().normalized()
rel_rotation = (cam_m.inverted() @ obj_m)
cam_rot = Euler([zeroing[0], zeroing[1], zeroing[2]]).to_matrix()
return (cam_rot @ rel_rotation).to_euler() | def get_relative_rotation_to_cam_rad(obj, cam, zeroing=Vector(((pi / 2), 0, 0))):
"Get the relative rotation between an object and a camera in the camera's\n frame of reference.\n\n This function allows to specify a certain 'zeroing' rotation.\n\n A default camera in blender with 0 rotation applied to its transform looks\n along the -Z direction. Blender's modelling viewport, however, assumes that\n the surface plane is spanned by X and Y, where X indicates left/right. This\n can be observed by putting the modelling viewport into the front viewpoint\n (Numpad 1). Then, the viewport looks along the Y direction.\n\n As a consequence, the relative rotation between a camera image and an object\n is only 0 when the camera would look onto the top of the object. Note that\n this is rather unintuitive, as most people would expect that the relative\n rotation is 0 when the camera looks at the front of an object.\n\n Args:\n obj: object to compute relative rotation for\n cam: camera to used\n zeroing: camera zeroing angles (in radians)\n\n Returns:\n Relative rotation between object and camera in the coordinate frame of\n the camera.\n "
obj_m = obj.matrix_world.to_3x3().normalized()
cam_m = cam.matrix_world.to_3x3().normalized()
rel_rotation = (cam_m.inverted() @ obj_m)
cam_rot = Euler([zeroing[0], zeroing[1], zeroing[2]]).to_matrix()
return (cam_rot @ rel_rotation).to_euler()<|docstring|>Get the relative rotation between an object and a camera in the camera's
frame of reference.
This function allows to specify a certain 'zeroing' rotation.
A default camera in blender with 0 rotation applied to its transform looks
along the -Z direction. Blender's modelling viewport, however, assumes that
the surface plane is spanned by X and Y, where X indicates left/right. This
can be observed by putting the modelling viewport into the front viewpoint
(Numpad 1). Then, the viewport looks along the Y direction.
As a consequence, the relative rotation between a camera image and an object
is only 0 when the camera would look onto the top of the object. Note that
this is rather unintuitive, as most people would expect that the relative
rotation is 0 when the camera looks at the front of an object.
Args:
obj: object to compute relative rotation for
cam: camera to used
zeroing: camera zeroing angles (in radians)
Returns:
Relative rotation between object and camera in the coordinate frame of
the camera.<|endoftext|> |
356eefac7204119fd2a094b939927a743ac4cc23af248cb3651e8bbfe5a67798 | def get_relative_translation(obj1: bpy.types.Object, obj2: bpy.types.Object=bpy.context.scene.camera) -> Vector:
"Get the relative translation between two objects in terms of the second\n object's coordinate system. Note that the second object will be default\n initialized to the scene's camera.\n\n Args:\n obj1 (bpy.types.Object): first object\n obj2 (bpy.types.Object): second object, relative to which the\n translation will be computed.\n\n Returns:\n 3D Vector with relative translation (in OpenGL coordinates)\n "
v = (obj1.matrix_world.to_translation() - obj2.matrix_world.to_translation())
rot = obj2.matrix_world.to_3x3().normalized()
return (rot.inverted() @ v) | Get the relative translation between two objects in terms of the second
object's coordinate system. Note that the second object will be default
initialized to the scene's camera.
Args:
obj1 (bpy.types.Object): first object
obj2 (bpy.types.Object): second object, relative to which the
translation will be computed.
Returns:
3D Vector with relative translation (in OpenGL coordinates) | src/amira_blender_rendering/math/geometry.py | get_relative_translation | patrickkesper/amira_blender_rendering | 26 | python | def get_relative_translation(obj1: bpy.types.Object, obj2: bpy.types.Object=bpy.context.scene.camera) -> Vector:
"Get the relative translation between two objects in terms of the second\n object's coordinate system. Note that the second object will be default\n initialized to the scene's camera.\n\n Args:\n obj1 (bpy.types.Object): first object\n obj2 (bpy.types.Object): second object, relative to which the\n translation will be computed.\n\n Returns:\n 3D Vector with relative translation (in OpenGL coordinates)\n "
v = (obj1.matrix_world.to_translation() - obj2.matrix_world.to_translation())
rot = obj2.matrix_world.to_3x3().normalized()
return (rot.inverted() @ v) | def get_relative_translation(obj1: bpy.types.Object, obj2: bpy.types.Object=bpy.context.scene.camera) -> Vector:
"Get the relative translation between two objects in terms of the second\n object's coordinate system. Note that the second object will be default\n initialized to the scene's camera.\n\n Args:\n obj1 (bpy.types.Object): first object\n obj2 (bpy.types.Object): second object, relative to which the\n translation will be computed.\n\n Returns:\n 3D Vector with relative translation (in OpenGL coordinates)\n "
v = (obj1.matrix_world.to_translation() - obj2.matrix_world.to_translation())
rot = obj2.matrix_world.to_3x3().normalized()
return (rot.inverted() @ v)<|docstring|>Get the relative translation between two objects in terms of the second
object's coordinate system. Note that the second object will be default
initialized to the scene's camera.
Args:
obj1 (bpy.types.Object): first object
obj2 (bpy.types.Object): second object, relative to which the
translation will be computed.
Returns:
3D Vector with relative translation (in OpenGL coordinates)<|endoftext|> |
34f00b2bf25d5ccea9b8a13e879a6dfe960edae5fa47a3c6fa6159f685065048 | def get_relative_transform(obj1: bpy.types.Object, obj2: bpy.types.Object=bpy.context.scene.camera):
"Get the relative transform between obj1 and obj2 in obj2's coordinate\n frame.\n\n Args:\n obj1 (bpy.types.Object): first object\n obj2 (bpy.types.Object): second object, relative to which the\n transform will be computed.\n\n Returns:\n tuple containing the translation and rotation between obj1 and obj2\n (relative to obj2)\n\n "
t = get_relative_translation(obj1, obj2)
r = get_relative_rotation(obj1, obj2)
return (t, r) | Get the relative transform between obj1 and obj2 in obj2's coordinate
frame.
Args:
obj1 (bpy.types.Object): first object
obj2 (bpy.types.Object): second object, relative to which the
transform will be computed.
Returns:
tuple containing the translation and rotation between obj1 and obj2
(relative to obj2) | src/amira_blender_rendering/math/geometry.py | get_relative_transform | patrickkesper/amira_blender_rendering | 26 | python | def get_relative_transform(obj1: bpy.types.Object, obj2: bpy.types.Object=bpy.context.scene.camera):
"Get the relative transform between obj1 and obj2 in obj2's coordinate\n frame.\n\n Args:\n obj1 (bpy.types.Object): first object\n obj2 (bpy.types.Object): second object, relative to which the\n transform will be computed.\n\n Returns:\n tuple containing the translation and rotation between obj1 and obj2\n (relative to obj2)\n\n "
t = get_relative_translation(obj1, obj2)
r = get_relative_rotation(obj1, obj2)
return (t, r) | def get_relative_transform(obj1: bpy.types.Object, obj2: bpy.types.Object=bpy.context.scene.camera):
"Get the relative transform between obj1 and obj2 in obj2's coordinate\n frame.\n\n Args:\n obj1 (bpy.types.Object): first object\n obj2 (bpy.types.Object): second object, relative to which the\n transform will be computed.\n\n Returns:\n tuple containing the translation and rotation between obj1 and obj2\n (relative to obj2)\n\n "
t = get_relative_translation(obj1, obj2)
r = get_relative_rotation(obj1, obj2)
return (t, r)<|docstring|>Get the relative transform between obj1 and obj2 in obj2's coordinate
frame.
Args:
obj1 (bpy.types.Object): first object
obj2 (bpy.types.Object): second object, relative to which the
transform will be computed.
Returns:
tuple containing the translation and rotation between obj1 and obj2
(relative to obj2)<|endoftext|> |
cf89d3fc00fe0519bfb8b1b14ec1048341ed878cd967ab192c69c6232897a3f0 | def test_visibility(obj, cam, width, height, require_all=True):
'Test if an object is visible from a camera by projecting the bounding box\n of the object and testing if the vertices are visible from the camera or not.\n\n Note that this does not test for occlusions!\n\n Args:\n obj : Object to test visibility for\n cam : Camera object\n width : Viewport width\n height : Viewport height\n require_all: test all (True) or at least one (False) bounding box vertex\n\n Returns:\n True, if object is visible, false if not.\n '
render = bpy.context.scene.render
vs = [(obj.matrix_world @ Vector(v)) for v in obj.bound_box]
ps = [project_p3d(v, cam, render=render) for v in vs]
if (None in ps):
return False
else:
pxs = [p2d_to_pixel_coords(p, render=render) for p in ps]
oks = [((px[0] >= 0) and (px[0] < width) and (px[1] >= 0) and (px[1] < height)) for px in pxs]
return (all(oks) if require_all else any(oks)) | Test if an object is visible from a camera by projecting the bounding box
of the object and testing if the vertices are visible from the camera or not.
Note that this does not test for occlusions!
Args:
obj : Object to test visibility for
cam : Camera object
width : Viewport width
height : Viewport height
require_all: test all (True) or at least one (False) bounding box vertex
Returns:
True, if object is visible, false if not. | src/amira_blender_rendering/math/geometry.py | test_visibility | patrickkesper/amira_blender_rendering | 26 | python | def test_visibility(obj, cam, width, height, require_all=True):
'Test if an object is visible from a camera by projecting the bounding box\n of the object and testing if the vertices are visible from the camera or not.\n\n Note that this does not test for occlusions!\n\n Args:\n obj : Object to test visibility for\n cam : Camera object\n width : Viewport width\n height : Viewport height\n require_all: test all (True) or at least one (False) bounding box vertex\n\n Returns:\n True, if object is visible, false if not.\n '
render = bpy.context.scene.render
vs = [(obj.matrix_world @ Vector(v)) for v in obj.bound_box]
ps = [project_p3d(v, cam, render=render) for v in vs]
if (None in ps):
return False
else:
pxs = [p2d_to_pixel_coords(p, render=render) for p in ps]
oks = [((px[0] >= 0) and (px[0] < width) and (px[1] >= 0) and (px[1] < height)) for px in pxs]
return (all(oks) if require_all else any(oks)) | def test_visibility(obj, cam, width, height, require_all=True):
'Test if an object is visible from a camera by projecting the bounding box\n of the object and testing if the vertices are visible from the camera or not.\n\n Note that this does not test for occlusions!\n\n Args:\n obj : Object to test visibility for\n cam : Camera object\n width : Viewport width\n height : Viewport height\n require_all: test all (True) or at least one (False) bounding box vertex\n\n Returns:\n True, if object is visible, false if not.\n '
render = bpy.context.scene.render
vs = [(obj.matrix_world @ Vector(v)) for v in obj.bound_box]
ps = [project_p3d(v, cam, render=render) for v in vs]
if (None in ps):
return False
else:
pxs = [p2d_to_pixel_coords(p, render=render) for p in ps]
oks = [((px[0] >= 0) and (px[0] < width) and (px[1] >= 0) and (px[1] < height)) for px in pxs]
return (all(oks) if require_all else any(oks))<|docstring|>Test if an object is visible from a camera by projecting the bounding box
of the object and testing if the vertices are visible from the camera or not.
Note that this does not test for occlusions!
Args:
obj : Object to test visibility for
cam : Camera object
width : Viewport width
height : Viewport height
require_all: test all (True) or at least one (False) bounding box vertex
Returns:
True, if object is visible, false if not.<|endoftext|> |
8bbc84aea569bd3f20064cd441ad6ca3672c5c285559a900bbf19a9a9da05d09 | def test_occlusion(scene, layer, cam, obj, width, height, require_all=True, origin_offset=0.01):
"Test if an object is visible or occluded by another object by checking its vertices.\n Note that this also tests if an object is visible.\n\n Args:\n scene: the scene for which to test\n layer: view layer to use for ray casting, e.g. scene.view_layers['View Layer']\n cam: camera to evaluate\n obj: object to evaluate\n width: scene render width, e.g. scene.render.resolution_x\n height: scene render height, e.g. scene.render.resolution_y\n require_all: test all vertices of the object for visibility and\n occlusion or not\n origin_offset: for ray-casting, add this offset along the ray to the\n origin. This helps to prevent numerical issues when a mesh is exactly at\n cam's location.\n\n Returns:\n True if an object is not visible or occluded, False if the object is\n visible and not occluded. Note that the returned value depends on\n argument require_all. Specifically, if require_all is set to False, then\n this function returns False if one of its vertices is visible and not\n occluded, and True if none of the vertex is visible or all are occluded.\n "
dg = bpy.context.evaluated_depsgraph_get()
dg.update()
render = bpy.context.scene.render
mesh = obj.evaluated_get(dg).to_mesh()
origin = cam.matrix_world.to_translation()
vs = [(obj.matrix_world @ v.co) for v in mesh.vertices]
obj.to_mesh_clear()
ps = [project_p3d(v, cam, render=render) for v in vs]
if (None in ps):
return True
pxs = [p2d_to_pixel_coords(p, render=render) for p in ps]
vs_visible = [((px[0] >= 0) and (px[0] < width) and (px[1] >= 0) and (px[1] < height)) for px in pxs]
vs_occluded = ([False] * len(vs))
for (i, v) in enumerate(vs):
direction = (v - origin)
direction.normalize()
local_origin = (origin + (origin_offset * direction))
try:
hit_record = scene.ray_cast(layer, local_origin, direction)
except TypeError:
hit_record = scene.ray_cast(layer.depsgraph, local_origin, direction)
hit = hit_record[0]
hit_obj = hit_record[4]
if (hit and (not (hit_obj.type == 'CAMERA')) and (not (hit_obj == obj))):
vs_occluded[i] = True
if require_all:
return (not (all(vs_visible) and all([(not oc) for oc in vs_occluded])))
else:
for i in range(len(vs_visible)):
if (vs_visible[i] and (not vs_occluded[i])):
return False
return True | Test if an object is visible or occluded by another object by checking its vertices.
Note that this also tests if an object is visible.
Args:
scene: the scene for which to test
layer: view layer to use for ray casting, e.g. scene.view_layers['View Layer']
cam: camera to evaluate
obj: object to evaluate
width: scene render width, e.g. scene.render.resolution_x
height: scene render height, e.g. scene.render.resolution_y
require_all: test all vertices of the object for visibility and
occlusion or not
origin_offset: for ray-casting, add this offset along the ray to the
origin. This helps to prevent numerical issues when a mesh is exactly at
cam's location.
Returns:
True if an object is not visible or occluded, False if the object is
visible and not occluded. Note that the returned value depends on
argument require_all. Specifically, if require_all is set to False, then
this function returns False if one of its vertices is visible and not
occluded, and True if none of the vertex is visible or all are occluded. | src/amira_blender_rendering/math/geometry.py | test_occlusion | patrickkesper/amira_blender_rendering | 26 | python | def test_occlusion(scene, layer, cam, obj, width, height, require_all=True, origin_offset=0.01):
"Test if an object is visible or occluded by another object by checking its vertices.\n Note that this also tests if an object is visible.\n\n Args:\n scene: the scene for which to test\n layer: view layer to use for ray casting, e.g. scene.view_layers['View Layer']\n cam: camera to evaluate\n obj: object to evaluate\n width: scene render width, e.g. scene.render.resolution_x\n height: scene render height, e.g. scene.render.resolution_y\n require_all: test all vertices of the object for visibility and\n occlusion or not\n origin_offset: for ray-casting, add this offset along the ray to the\n origin. This helps to prevent numerical issues when a mesh is exactly at\n cam's location.\n\n Returns:\n True if an object is not visible or occluded, False if the object is\n visible and not occluded. Note that the returned value depends on\n argument require_all. Specifically, if require_all is set to False, then\n this function returns False if one of its vertices is visible and not\n occluded, and True if none of the vertex is visible or all are occluded.\n "
dg = bpy.context.evaluated_depsgraph_get()
dg.update()
render = bpy.context.scene.render
mesh = obj.evaluated_get(dg).to_mesh()
origin = cam.matrix_world.to_translation()
vs = [(obj.matrix_world @ v.co) for v in mesh.vertices]
obj.to_mesh_clear()
ps = [project_p3d(v, cam, render=render) for v in vs]
if (None in ps):
return True
pxs = [p2d_to_pixel_coords(p, render=render) for p in ps]
vs_visible = [((px[0] >= 0) and (px[0] < width) and (px[1] >= 0) and (px[1] < height)) for px in pxs]
vs_occluded = ([False] * len(vs))
for (i, v) in enumerate(vs):
direction = (v - origin)
direction.normalize()
local_origin = (origin + (origin_offset * direction))
try:
hit_record = scene.ray_cast(layer, local_origin, direction)
except TypeError:
hit_record = scene.ray_cast(layer.depsgraph, local_origin, direction)
hit = hit_record[0]
hit_obj = hit_record[4]
if (hit and (not (hit_obj.type == 'CAMERA')) and (not (hit_obj == obj))):
vs_occluded[i] = True
if require_all:
return (not (all(vs_visible) and all([(not oc) for oc in vs_occluded])))
else:
for i in range(len(vs_visible)):
if (vs_visible[i] and (not vs_occluded[i])):
return False
return True | def test_occlusion(scene, layer, cam, obj, width, height, require_all=True, origin_offset=0.01):
"Test if an object is visible or occluded by another object by checking its vertices.\n Note that this also tests if an object is visible.\n\n Args:\n scene: the scene for which to test\n layer: view layer to use for ray casting, e.g. scene.view_layers['View Layer']\n cam: camera to evaluate\n obj: object to evaluate\n width: scene render width, e.g. scene.render.resolution_x\n height: scene render height, e.g. scene.render.resolution_y\n require_all: test all vertices of the object for visibility and\n occlusion or not\n origin_offset: for ray-casting, add this offset along the ray to the\n origin. This helps to prevent numerical issues when a mesh is exactly at\n cam's location.\n\n Returns:\n True if an object is not visible or occluded, False if the object is\n visible and not occluded. Note that the returned value depends on\n argument require_all. Specifically, if require_all is set to False, then\n this function returns False if one of its vertices is visible and not\n occluded, and True if none of the vertex is visible or all are occluded.\n "
dg = bpy.context.evaluated_depsgraph_get()
dg.update()
render = bpy.context.scene.render
mesh = obj.evaluated_get(dg).to_mesh()
origin = cam.matrix_world.to_translation()
vs = [(obj.matrix_world @ v.co) for v in mesh.vertices]
obj.to_mesh_clear()
ps = [project_p3d(v, cam, render=render) for v in vs]
if (None in ps):
return True
pxs = [p2d_to_pixel_coords(p, render=render) for p in ps]
vs_visible = [((px[0] >= 0) and (px[0] < width) and (px[1] >= 0) and (px[1] < height)) for px in pxs]
vs_occluded = ([False] * len(vs))
for (i, v) in enumerate(vs):
direction = (v - origin)
direction.normalize()
local_origin = (origin + (origin_offset * direction))
try:
hit_record = scene.ray_cast(layer, local_origin, direction)
except TypeError:
hit_record = scene.ray_cast(layer.depsgraph, local_origin, direction)
hit = hit_record[0]
hit_obj = hit_record[4]
if (hit and (not (hit_obj.type == 'CAMERA')) and (not (hit_obj == obj))):
vs_occluded[i] = True
if require_all:
return (not (all(vs_visible) and all([(not oc) for oc in vs_occluded])))
else:
for i in range(len(vs_visible)):
if (vs_visible[i] and (not vs_occluded[i])):
return False
return True<|docstring|>Test if an object is visible or occluded by another object by checking its vertices.
Note that this also tests if an object is visible.
Args:
scene: the scene for which to test
layer: view layer to use for ray casting, e.g. scene.view_layers['View Layer']
cam: camera to evaluate
obj: object to evaluate
width: scene render width, e.g. scene.render.resolution_x
height: scene render height, e.g. scene.render.resolution_y
require_all: test all vertices of the object for visibility and
occlusion or not
origin_offset: for ray-casting, add this offset along the ray to the
origin. This helps to prevent numerical issues when a mesh is exactly at
cam's location.
Returns:
True if an object is not visible or occluded, False if the object is
visible and not occluded. Note that the returned value depends on
argument require_all. Specifically, if require_all is set to False, then
this function returns False if one of its vertices is visible and not
occluded, and True if none of the vertex is visible or all are occluded.<|endoftext|> |
4a964143286e1ffde23b8043eaa3868930b52d9f920d5e1098c4e2c1eeb71805 | def _get_bvh(obj):
'Get the BVH for an object\n\n Args:\n obj (variant): object to get the BVH for\n\n Returns:\n BVH for obj\n '
mat = obj.matrix_world
vs = [(mat @ v.co) for v in obj.data.vertices]
ps = [p.vertices for p in obj.data.polygons]
return BVHTree.FromPolygons(vs, ps) | Get the BVH for an object
Args:
obj (variant): object to get the BVH for
Returns:
BVH for obj | src/amira_blender_rendering/math/geometry.py | _get_bvh | patrickkesper/amira_blender_rendering | 26 | python | def _get_bvh(obj):
'Get the BVH for an object\n\n Args:\n obj (variant): object to get the BVH for\n\n Returns:\n BVH for obj\n '
mat = obj.matrix_world
vs = [(mat @ v.co) for v in obj.data.vertices]
ps = [p.vertices for p in obj.data.polygons]
return BVHTree.FromPolygons(vs, ps) | def _get_bvh(obj):
'Get the BVH for an object\n\n Args:\n obj (variant): object to get the BVH for\n\n Returns:\n BVH for obj\n '
mat = obj.matrix_world
vs = [(mat @ v.co) for v in obj.data.vertices]
ps = [p.vertices for p in obj.data.polygons]
return BVHTree.FromPolygons(vs, ps)<|docstring|>Get the BVH for an object
Args:
obj (variant): object to get the BVH for
Returns:
BVH for obj<|endoftext|> |
11e771cf578f6dd99f0fcbd7aea13e88497153ebd0d4d2e1e98ec96e37f2f5f5 | def test_intersection(obj1, obj2):
'Test if two objects intersect each other\n\n Returns true if objects intersect, false if not.\n '
bvh1 = _get_bvh(obj1)
bvh2 = _get_bvh(obj2)
if bvh1.overlap(bvh2):
return True
else:
return False | Test if two objects intersect each other
Returns true if objects intersect, false if not. | src/amira_blender_rendering/math/geometry.py | test_intersection | patrickkesper/amira_blender_rendering | 26 | python | def test_intersection(obj1, obj2):
'Test if two objects intersect each other\n\n Returns true if objects intersect, false if not.\n '
bvh1 = _get_bvh(obj1)
bvh2 = _get_bvh(obj2)
if bvh1.overlap(bvh2):
return True
else:
return False | def test_intersection(obj1, obj2):
'Test if two objects intersect each other\n\n Returns true if objects intersect, false if not.\n '
bvh1 = _get_bvh(obj1)
bvh2 = _get_bvh(obj2)
if bvh1.overlap(bvh2):
return True
else:
return False<|docstring|>Test if two objects intersect each other
Returns true if objects intersect, false if not.<|endoftext|> |
d43fe7f349fcf893230c99fac816d45955a17e63ef22e4fc201f6fab0dcbf34f | def get_world_to_object_transform(cam2obj_pose: dict, camera: bpy.types.Object=bpy.context.scene.camera):
"\n Transform a pose {'R', 't'} expressed in camera coordinates to world coordinates\n\n Args:\n cam2obj_pose(dict): {\n 'R'(np.array(3)) : rotation matrix from camera to obj\n 't'(np.array(3,) : translation vector from camera to obh\n }\n camera(bpq.types.Object): scene camera\n\n Returns:\n {'R','t'} where\n R(np.array(3)): rotation matrix from world frame to object\n t(np.array(3,)): translation vector from world frame to object\n "
M_c2o = np.eye(4)
M_c2o[(:3, :3)] = cam2obj_pose['R']
M_c2o[(:3, 3)] = cam2obj_pose['t']
M_w2c = np.eye(4)
M_w2c[(:3, :3)] = camera.matrix_world.to_3x3().normalized()
M_w2c[(:3, 3)] = camera.matrix_world.to_translation()
M_w2o = M_w2c.dot(M_c2o)
R = M_w2o[(:3, :3)]
t = M_w2o[(:3, 3)]
return {'R': R, 't': t} | Transform a pose {'R', 't'} expressed in camera coordinates to world coordinates
Args:
cam2obj_pose(dict): {
'R'(np.array(3)) : rotation matrix from camera to obj
't'(np.array(3,) : translation vector from camera to obh
}
camera(bpq.types.Object): scene camera
Returns:
{'R','t'} where
R(np.array(3)): rotation matrix from world frame to object
t(np.array(3,)): translation vector from world frame to object | src/amira_blender_rendering/math/geometry.py | get_world_to_object_transform | patrickkesper/amira_blender_rendering | 26 | python | def get_world_to_object_transform(cam2obj_pose: dict, camera: bpy.types.Object=bpy.context.scene.camera):
"\n Transform a pose {'R', 't'} expressed in camera coordinates to world coordinates\n\n Args:\n cam2obj_pose(dict): {\n 'R'(np.array(3)) : rotation matrix from camera to obj\n 't'(np.array(3,) : translation vector from camera to obh\n }\n camera(bpq.types.Object): scene camera\n\n Returns:\n {'R','t'} where\n R(np.array(3)): rotation matrix from world frame to object\n t(np.array(3,)): translation vector from world frame to object\n "
M_c2o = np.eye(4)
M_c2o[(:3, :3)] = cam2obj_pose['R']
M_c2o[(:3, 3)] = cam2obj_pose['t']
M_w2c = np.eye(4)
M_w2c[(:3, :3)] = camera.matrix_world.to_3x3().normalized()
M_w2c[(:3, 3)] = camera.matrix_world.to_translation()
M_w2o = M_w2c.dot(M_c2o)
R = M_w2o[(:3, :3)]
t = M_w2o[(:3, 3)]
return {'R': R, 't': t} | def get_world_to_object_transform(cam2obj_pose: dict, camera: bpy.types.Object=bpy.context.scene.camera):
"\n Transform a pose {'R', 't'} expressed in camera coordinates to world coordinates\n\n Args:\n cam2obj_pose(dict): {\n 'R'(np.array(3)) : rotation matrix from camera to obj\n 't'(np.array(3,) : translation vector from camera to obh\n }\n camera(bpq.types.Object): scene camera\n\n Returns:\n {'R','t'} where\n R(np.array(3)): rotation matrix from world frame to object\n t(np.array(3,)): translation vector from world frame to object\n "
M_c2o = np.eye(4)
M_c2o[(:3, :3)] = cam2obj_pose['R']
M_c2o[(:3, 3)] = cam2obj_pose['t']
M_w2c = np.eye(4)
M_w2c[(:3, :3)] = camera.matrix_world.to_3x3().normalized()
M_w2c[(:3, 3)] = camera.matrix_world.to_translation()
M_w2o = M_w2c.dot(M_c2o)
R = M_w2o[(:3, :3)]
t = M_w2o[(:3, 3)]
return {'R': R, 't': t}<|docstring|>Transform a pose {'R', 't'} expressed in camera coordinates to world coordinates
Args:
cam2obj_pose(dict): {
'R'(np.array(3)) : rotation matrix from camera to obj
't'(np.array(3,) : translation vector from camera to obh
}
camera(bpq.types.Object): scene camera
Returns:
{'R','t'} where
R(np.array(3)): rotation matrix from world frame to object
t(np.array(3,)): translation vector from world frame to object<|endoftext|> |
5f9a8236d2aa27250fb9836244505d55ed15518eb728809c7d226d263cc99258 | def gl2cv(R, t):
'Convert transform from OpenGL to OpenCV\n\n Args:\n R(np.array(3,3): rotation matrix\n t(np.array(3,): translation vector\n Returns:\n R_cv\n t_cv\n '
M_gl = np.eye(4)
M_gl[(:3, :3)] = R
M_gl[(:3, 3)] = t
Ccv_Cgl = np.array([[1, 0, 0, 0], [0, (- 1), 0, 0], [0, 0, (- 1), 0], [0, 0, 0, 1]])
Cgl_W = (Ccv_Cgl @ M_gl)
return (Cgl_W[(:3, :3)], Cgl_W[(:3, 3)]) | Convert transform from OpenGL to OpenCV
Args:
R(np.array(3,3): rotation matrix
t(np.array(3,): translation vector
Returns:
R_cv
t_cv | src/amira_blender_rendering/math/geometry.py | gl2cv | patrickkesper/amira_blender_rendering | 26 | python | def gl2cv(R, t):
'Convert transform from OpenGL to OpenCV\n\n Args:\n R(np.array(3,3): rotation matrix\n t(np.array(3,): translation vector\n Returns:\n R_cv\n t_cv\n '
M_gl = np.eye(4)
M_gl[(:3, :3)] = R
M_gl[(:3, 3)] = t
Ccv_Cgl = np.array([[1, 0, 0, 0], [0, (- 1), 0, 0], [0, 0, (- 1), 0], [0, 0, 0, 1]])
Cgl_W = (Ccv_Cgl @ M_gl)
return (Cgl_W[(:3, :3)], Cgl_W[(:3, 3)]) | def gl2cv(R, t):
'Convert transform from OpenGL to OpenCV\n\n Args:\n R(np.array(3,3): rotation matrix\n t(np.array(3,): translation vector\n Returns:\n R_cv\n t_cv\n '
M_gl = np.eye(4)
M_gl[(:3, :3)] = R
M_gl[(:3, 3)] = t
Ccv_Cgl = np.array([[1, 0, 0, 0], [0, (- 1), 0, 0], [0, 0, (- 1), 0], [0, 0, 0, 1]])
Cgl_W = (Ccv_Cgl @ M_gl)
return (Cgl_W[(:3, :3)], Cgl_W[(:3, 3)])<|docstring|>Convert transform from OpenGL to OpenCV
Args:
R(np.array(3,3): rotation matrix
t(np.array(3,): translation vector
Returns:
R_cv
t_cv<|endoftext|> |
e7ac1f6bb22e772bd0ff10029f438dd3d2c5c855f6ecfc8c9ead6fa00c052cc1 | def euler_x_to_matrix(angle):
'Get rotation matrix from euler angle rotation around X.'
return np.array([[1, 0, 0], [0, np.cos(angle), (- np.sin(angle))], [0, np.sin(angle), np.cos(angle)]]) | Get rotation matrix from euler angle rotation around X. | src/amira_blender_rendering/math/geometry.py | euler_x_to_matrix | patrickkesper/amira_blender_rendering | 26 | python | def euler_x_to_matrix(angle):
return np.array([[1, 0, 0], [0, np.cos(angle), (- np.sin(angle))], [0, np.sin(angle), np.cos(angle)]]) | def euler_x_to_matrix(angle):
return np.array([[1, 0, 0], [0, np.cos(angle), (- np.sin(angle))], [0, np.sin(angle), np.cos(angle)]])<|docstring|>Get rotation matrix from euler angle rotation around X.<|endoftext|> |
370140bf30a73c4c1f035e4db5a09d7c6b2c2cbae28beef21d50aab2b9e34bed | def euler_y_to_matrix(angle):
'Get rotation matrix from euler angle rotation around Y.'
return np.array([[np.cos(angle), 0, np.sin(angle)], [0, 1, 0], [(- np.sin(angle)), 0, np.cos(angle)]]) | Get rotation matrix from euler angle rotation around Y. | src/amira_blender_rendering/math/geometry.py | euler_y_to_matrix | patrickkesper/amira_blender_rendering | 26 | python | def euler_y_to_matrix(angle):
return np.array([[np.cos(angle), 0, np.sin(angle)], [0, 1, 0], [(- np.sin(angle)), 0, np.cos(angle)]]) | def euler_y_to_matrix(angle):
return np.array([[np.cos(angle), 0, np.sin(angle)], [0, 1, 0], [(- np.sin(angle)), 0, np.cos(angle)]])<|docstring|>Get rotation matrix from euler angle rotation around Y.<|endoftext|> |
827d2d0f4a55c4ee05dacb1be556864652620060579fecb142ee7ef5a1d64a4c | def euler_z_to_matrix(angle):
'Get rotation matrix from euler angle rotation around Z.'
return np.array([[np.cos(angle), (- np.sin(angle)), 0], [np.sin(angle), np.cos(angle), 0], [0, 0, 1]]) | Get rotation matrix from euler angle rotation around Z. | src/amira_blender_rendering/math/geometry.py | euler_z_to_matrix | patrickkesper/amira_blender_rendering | 26 | python | def euler_z_to_matrix(angle):
return np.array([[np.cos(angle), (- np.sin(angle)), 0], [np.sin(angle), np.cos(angle), 0], [0, 0, 1]]) | def euler_z_to_matrix(angle):
return np.array([[np.cos(angle), (- np.sin(angle)), 0], [np.sin(angle), np.cos(angle), 0], [0, 0, 1]])<|docstring|>Get rotation matrix from euler angle rotation around Z.<|endoftext|> |
77d4f7f0503691f05efb5c412890ae685a24cc4b6f5dd06e870e97a5f5fa5929 | def rotation_matrix(alpha, axis, homogeneous=False):
'Euler rotation matrices\n\n Args:\n alpha (float): angle in radians\n axis (str): x/y/z\n homogeneous (bool): output homogeneous coordinates\n\n Returns:\n rotation matrix\n\n '
axis = axis.lower()
if (axis == 'x'):
rot = euler_x_to_matrix(alpha)
elif (axis == 'y'):
rot = euler_y_to_matrix(alpha)
elif (axis == 'z'):
rot = euler_z_to_matrix(alpha)
else:
get_logger().error('Axis needs to be x/y/z!')
raise ValueError
if (homogeneous is True):
h = np.eye(4)
h[(:3, :3)] = rot
return h
else:
return rot | Euler rotation matrices
Args:
alpha (float): angle in radians
axis (str): x/y/z
homogeneous (bool): output homogeneous coordinates
Returns:
rotation matrix | src/amira_blender_rendering/math/geometry.py | rotation_matrix | patrickkesper/amira_blender_rendering | 26 | python | def rotation_matrix(alpha, axis, homogeneous=False):
'Euler rotation matrices\n\n Args:\n alpha (float): angle in radians\n axis (str): x/y/z\n homogeneous (bool): output homogeneous coordinates\n\n Returns:\n rotation matrix\n\n '
axis = axis.lower()
if (axis == 'x'):
rot = euler_x_to_matrix(alpha)
elif (axis == 'y'):
rot = euler_y_to_matrix(alpha)
elif (axis == 'z'):
rot = euler_z_to_matrix(alpha)
else:
get_logger().error('Axis needs to be x/y/z!')
raise ValueError
if (homogeneous is True):
h = np.eye(4)
h[(:3, :3)] = rot
return h
else:
return rot | def rotation_matrix(alpha, axis, homogeneous=False):
'Euler rotation matrices\n\n Args:\n alpha (float): angle in radians\n axis (str): x/y/z\n homogeneous (bool): output homogeneous coordinates\n\n Returns:\n rotation matrix\n\n '
axis = axis.lower()
if (axis == 'x'):
rot = euler_x_to_matrix(alpha)
elif (axis == 'y'):
rot = euler_y_to_matrix(alpha)
elif (axis == 'z'):
rot = euler_z_to_matrix(alpha)
else:
get_logger().error('Axis needs to be x/y/z!')
raise ValueError
if (homogeneous is True):
h = np.eye(4)
h[(:3, :3)] = rot
return h
else:
return rot<|docstring|>Euler rotation matrices
Args:
alpha (float): angle in radians
axis (str): x/y/z
homogeneous (bool): output homogeneous coordinates
Returns:
rotation matrix<|endoftext|> |
e3c16004a969596eb2091db3f83c63374651373a394f0606b3a0d38013c97189 | def rotation_matrix_to_quaternion(rot_mat, isprecise=False):
'\n Computes the quaternion (with convention WXYZ) out of a given rotation matrix\n Inverse funtion of quaternion_to_rotation_matrix\n\n Parameters\n ----------\n :param rot_mat: np.array of shape (3, 3)\n\n Returns\n -------\n :return q: np.array of shape (4,), quaternion (WXYZ) corresponding to the rotation matrix rot_mat\n \n NOTE: the implementation comes from a mixture of codes. Inspiration is taken from Wikipedia and\n \n Homogeneous Transformation Matrices and Quaternions library\n :Author:\n `Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/>`_\n '
if isprecise:
trace = max(np.trace(rot_mat), (- 1.0))
qs = min((np.sqrt((trace + 1)) / 2.0), 1.0)
kx = (rot_mat[(2, 1)] - rot_mat[(1, 2)])
ky = (rot_mat[(0, 2)] - rot_mat[(2, 0)])
kz = (rot_mat[(1, 0)] - rot_mat[(0, 1)])
if ((rot_mat[(0, 0)] >= rot_mat[(1, 1)]) and (rot_mat[(0, 0)] >= rot_mat[(2, 2)])):
kx1 = (((rot_mat[(0, 0)] - rot_mat[(1, 1)]) - rot_mat[(2, 2)]) + 1)
ky1 = (rot_mat[(1, 0)] + rot_mat[(0, 1)])
kz1 = (rot_mat[(2, 0)] + rot_mat[(0, 2)])
add = (kx >= 0)
elif (rot_mat[(1, 1)] >= rot_mat[(2, 2)]):
kx1 = (rot_mat[(1, 0)] + rot_mat[(0, 1)])
ky1 = (((rot_mat[(1, 1)] - rot_mat[(0, 0)]) - rot_mat[(2, 2)]) + 1)
kz1 = (rot_mat[(2, 1)] + rot_mat[(1, 2)])
add = (ky >= 0)
else:
kx1 = (rot_mat[(2, 0)] + rot_mat[(0, 2)])
ky1 = (rot_mat[(2, 1)] + rot_mat[(1, 2)])
kz1 = (((rot_mat[(2, 2)] - rot_mat[(0, 0)]) - rot_mat[(1, 1)]) + 1)
add = (kz >= 0)
if add:
kx = (kx + kx1)
ky = (ky + ky1)
kz = (kz + kz1)
else:
kx = (kx - kx1)
ky = (ky - ky1)
kz = (kz - kz1)
nm = np.linalg.norm(np.array([kx, ky, kz]))
if (nm == 0):
q = np.array([1.0, 0.0, 0.0, 0.0])
else:
s = (np.sqrt((1 - (qs ** 2))) / nm)
qv = (s * np.array([kx, ky, kz]))
q = np.append(qs, qv)
else:
m00 = rot_mat[(0, 0)]
m01 = rot_mat[(0, 1)]
m02 = rot_mat[(0, 2)]
m10 = rot_mat[(1, 0)]
m11 = rot_mat[(1, 1)]
m12 = rot_mat[(1, 2)]
m20 = rot_mat[(2, 0)]
m21 = rot_mat[(2, 1)]
m22 = rot_mat[(2, 2)]
K = np.array([[((m00 - m11) - m22), 0.0, 0.0, 0.0], [(m01 + m10), ((m11 - m00) - m22), 0.0, 0.0], [(m02 + m20), (m12 + m21), ((m22 - m00) - m11), 0.0], [(m21 - m12), (m02 - m20), (m10 - m01), ((m00 + m11) + m22)]])
K /= 3.0
(w, V) = np.linalg.eigh(K)
q = V[([3, 0, 1, 2], np.argmax(w))]
if (q[0] < 0.0):
np.negative(q, q)
return q | Computes the quaternion (with convention WXYZ) out of a given rotation matrix
Inverse funtion of quaternion_to_rotation_matrix
Parameters
----------
:param rot_mat: np.array of shape (3, 3)
Returns
-------
:return q: np.array of shape (4,), quaternion (WXYZ) corresponding to the rotation matrix rot_mat
NOTE: the implementation comes from a mixture of codes. Inspiration is taken from Wikipedia and
Homogeneous Transformation Matrices and Quaternions library
:Author:
`Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/>`_ | src/amira_blender_rendering/math/geometry.py | rotation_matrix_to_quaternion | patrickkesper/amira_blender_rendering | 26 | python | def rotation_matrix_to_quaternion(rot_mat, isprecise=False):
'\n Computes the quaternion (with convention WXYZ) out of a given rotation matrix\n Inverse funtion of quaternion_to_rotation_matrix\n\n Parameters\n ----------\n :param rot_mat: np.array of shape (3, 3)\n\n Returns\n -------\n :return q: np.array of shape (4,), quaternion (WXYZ) corresponding to the rotation matrix rot_mat\n \n NOTE: the implementation comes from a mixture of codes. Inspiration is taken from Wikipedia and\n \n Homogeneous Transformation Matrices and Quaternions library\n :Author:\n `Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/>`_\n '
if isprecise:
trace = max(np.trace(rot_mat), (- 1.0))
qs = min((np.sqrt((trace + 1)) / 2.0), 1.0)
kx = (rot_mat[(2, 1)] - rot_mat[(1, 2)])
ky = (rot_mat[(0, 2)] - rot_mat[(2, 0)])
kz = (rot_mat[(1, 0)] - rot_mat[(0, 1)])
if ((rot_mat[(0, 0)] >= rot_mat[(1, 1)]) and (rot_mat[(0, 0)] >= rot_mat[(2, 2)])):
kx1 = (((rot_mat[(0, 0)] - rot_mat[(1, 1)]) - rot_mat[(2, 2)]) + 1)
ky1 = (rot_mat[(1, 0)] + rot_mat[(0, 1)])
kz1 = (rot_mat[(2, 0)] + rot_mat[(0, 2)])
add = (kx >= 0)
elif (rot_mat[(1, 1)] >= rot_mat[(2, 2)]):
kx1 = (rot_mat[(1, 0)] + rot_mat[(0, 1)])
ky1 = (((rot_mat[(1, 1)] - rot_mat[(0, 0)]) - rot_mat[(2, 2)]) + 1)
kz1 = (rot_mat[(2, 1)] + rot_mat[(1, 2)])
add = (ky >= 0)
else:
kx1 = (rot_mat[(2, 0)] + rot_mat[(0, 2)])
ky1 = (rot_mat[(2, 1)] + rot_mat[(1, 2)])
kz1 = (((rot_mat[(2, 2)] - rot_mat[(0, 0)]) - rot_mat[(1, 1)]) + 1)
add = (kz >= 0)
if add:
kx = (kx + kx1)
ky = (ky + ky1)
kz = (kz + kz1)
else:
kx = (kx - kx1)
ky = (ky - ky1)
kz = (kz - kz1)
nm = np.linalg.norm(np.array([kx, ky, kz]))
if (nm == 0):
q = np.array([1.0, 0.0, 0.0, 0.0])
else:
s = (np.sqrt((1 - (qs ** 2))) / nm)
qv = (s * np.array([kx, ky, kz]))
q = np.append(qs, qv)
else:
m00 = rot_mat[(0, 0)]
m01 = rot_mat[(0, 1)]
m02 = rot_mat[(0, 2)]
m10 = rot_mat[(1, 0)]
m11 = rot_mat[(1, 1)]
m12 = rot_mat[(1, 2)]
m20 = rot_mat[(2, 0)]
m21 = rot_mat[(2, 1)]
m22 = rot_mat[(2, 2)]
K = np.array([[((m00 - m11) - m22), 0.0, 0.0, 0.0], [(m01 + m10), ((m11 - m00) - m22), 0.0, 0.0], [(m02 + m20), (m12 + m21), ((m22 - m00) - m11), 0.0], [(m21 - m12), (m02 - m20), (m10 - m01), ((m00 + m11) + m22)]])
K /= 3.0
(w, V) = np.linalg.eigh(K)
q = V[([3, 0, 1, 2], np.argmax(w))]
if (q[0] < 0.0):
np.negative(q, q)
return q | def rotation_matrix_to_quaternion(rot_mat, isprecise=False):
'\n Computes the quaternion (with convention WXYZ) out of a given rotation matrix\n Inverse funtion of quaternion_to_rotation_matrix\n\n Parameters\n ----------\n :param rot_mat: np.array of shape (3, 3)\n\n Returns\n -------\n :return q: np.array of shape (4,), quaternion (WXYZ) corresponding to the rotation matrix rot_mat\n \n NOTE: the implementation comes from a mixture of codes. Inspiration is taken from Wikipedia and\n \n Homogeneous Transformation Matrices and Quaternions library\n :Author:\n `Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/>`_\n '
if isprecise:
trace = max(np.trace(rot_mat), (- 1.0))
qs = min((np.sqrt((trace + 1)) / 2.0), 1.0)
kx = (rot_mat[(2, 1)] - rot_mat[(1, 2)])
ky = (rot_mat[(0, 2)] - rot_mat[(2, 0)])
kz = (rot_mat[(1, 0)] - rot_mat[(0, 1)])
if ((rot_mat[(0, 0)] >= rot_mat[(1, 1)]) and (rot_mat[(0, 0)] >= rot_mat[(2, 2)])):
kx1 = (((rot_mat[(0, 0)] - rot_mat[(1, 1)]) - rot_mat[(2, 2)]) + 1)
ky1 = (rot_mat[(1, 0)] + rot_mat[(0, 1)])
kz1 = (rot_mat[(2, 0)] + rot_mat[(0, 2)])
add = (kx >= 0)
elif (rot_mat[(1, 1)] >= rot_mat[(2, 2)]):
kx1 = (rot_mat[(1, 0)] + rot_mat[(0, 1)])
ky1 = (((rot_mat[(1, 1)] - rot_mat[(0, 0)]) - rot_mat[(2, 2)]) + 1)
kz1 = (rot_mat[(2, 1)] + rot_mat[(1, 2)])
add = (ky >= 0)
else:
kx1 = (rot_mat[(2, 0)] + rot_mat[(0, 2)])
ky1 = (rot_mat[(2, 1)] + rot_mat[(1, 2)])
kz1 = (((rot_mat[(2, 2)] - rot_mat[(0, 0)]) - rot_mat[(1, 1)]) + 1)
add = (kz >= 0)
if add:
kx = (kx + kx1)
ky = (ky + ky1)
kz = (kz + kz1)
else:
kx = (kx - kx1)
ky = (ky - ky1)
kz = (kz - kz1)
nm = np.linalg.norm(np.array([kx, ky, kz]))
if (nm == 0):
q = np.array([1.0, 0.0, 0.0, 0.0])
else:
s = (np.sqrt((1 - (qs ** 2))) / nm)
qv = (s * np.array([kx, ky, kz]))
q = np.append(qs, qv)
else:
m00 = rot_mat[(0, 0)]
m01 = rot_mat[(0, 1)]
m02 = rot_mat[(0, 2)]
m10 = rot_mat[(1, 0)]
m11 = rot_mat[(1, 1)]
m12 = rot_mat[(1, 2)]
m20 = rot_mat[(2, 0)]
m21 = rot_mat[(2, 1)]
m22 = rot_mat[(2, 2)]
K = np.array([[((m00 - m11) - m22), 0.0, 0.0, 0.0], [(m01 + m10), ((m11 - m00) - m22), 0.0, 0.0], [(m02 + m20), (m12 + m21), ((m22 - m00) - m11), 0.0], [(m21 - m12), (m02 - m20), (m10 - m01), ((m00 + m11) + m22)]])
K /= 3.0
(w, V) = np.linalg.eigh(K)
q = V[([3, 0, 1, 2], np.argmax(w))]
if (q[0] < 0.0):
np.negative(q, q)
return q<|docstring|>Computes the quaternion (with convention WXYZ) out of a given rotation matrix
Inverse funtion of quaternion_to_rotation_matrix
Parameters
----------
:param rot_mat: np.array of shape (3, 3)
Returns
-------
:return q: np.array of shape (4,), quaternion (WXYZ) corresponding to the rotation matrix rot_mat
NOTE: the implementation comes from a mixture of codes. Inspiration is taken from Wikipedia and
Homogeneous Transformation Matrices and Quaternions library
:Author:
`Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/>`_<|endoftext|> |
3f43b2fbc95fa0bb467130c106484fc01f64b64f6b68c4e0e210f54054625577 | def file(path_or_f):
'\n Verifies that a file exists at a given path and that the file has a\n known extension type.\n\n :Parameters:\n path : `str`\n the path to a dump file\n\n '
if hasattr(path_or_f, 'readline'):
return path_or_f
else:
path = path_or_f
path = os.path.expanduser(path)
if (not os.path.isfile(path)):
raise FileTypeError(("Can't find file %s" % path))
match = EXT_RE.search(path)
if (match is None):
raise FileTypeError(('No extension found for %s.' % path))
elif (match.groups()[0] not in EXTENSIONS):
raise FileTypeError(('File type %r is not supported.' % path))
else:
return path | Verifies that a file exists at a given path and that the file has a
known extension type.
:Parameters:
path : `str`
the path to a dump file | mw/xml_dump/functions.py | file | makoshark/Mediawiki-Utilities | 23 | python | def file(path_or_f):
'\n Verifies that a file exists at a given path and that the file has a\n known extension type.\n\n :Parameters:\n path : `str`\n the path to a dump file\n\n '
if hasattr(path_or_f, 'readline'):
return path_or_f
else:
path = path_or_f
path = os.path.expanduser(path)
if (not os.path.isfile(path)):
raise FileTypeError(("Can't find file %s" % path))
match = EXT_RE.search(path)
if (match is None):
raise FileTypeError(('No extension found for %s.' % path))
elif (match.groups()[0] not in EXTENSIONS):
raise FileTypeError(('File type %r is not supported.' % path))
else:
return path | def file(path_or_f):
'\n Verifies that a file exists at a given path and that the file has a\n known extension type.\n\n :Parameters:\n path : `str`\n the path to a dump file\n\n '
if hasattr(path_or_f, 'readline'):
return path_or_f
else:
path = path_or_f
path = os.path.expanduser(path)
if (not os.path.isfile(path)):
raise FileTypeError(("Can't find file %s" % path))
match = EXT_RE.search(path)
if (match is None):
raise FileTypeError(('No extension found for %s.' % path))
elif (match.groups()[0] not in EXTENSIONS):
raise FileTypeError(('File type %r is not supported.' % path))
else:
return path<|docstring|>Verifies that a file exists at a given path and that the file has a
known extension type.
:Parameters:
path : `str`
the path to a dump file<|endoftext|> |
375c3bffc54dffe0a4e7e45ab8246ee19ede06f73d980df9a45a6d4b638fcf94 | def open_file(path_or_f):
'\n Turns a path to a dump file into a file-like object of (decompressed)\n XML data.\n\n :Parameters:\n path : `str`\n the path to the dump file to read\n '
if hasattr(path_or_f, 'read'):
return path_or_f
else:
path = path_or_f
match = EXT_RE.search(path)
ext = match.groups()[0]
p = subprocess.Popen((EXTENSIONS[ext] + [path]), stdout=subprocess.PIPE, stderr=open(os.devnull, 'w'))
return p.stdout | Turns a path to a dump file into a file-like object of (decompressed)
XML data.
:Parameters:
path : `str`
the path to the dump file to read | mw/xml_dump/functions.py | open_file | makoshark/Mediawiki-Utilities | 23 | python | def open_file(path_or_f):
'\n Turns a path to a dump file into a file-like object of (decompressed)\n XML data.\n\n :Parameters:\n path : `str`\n the path to the dump file to read\n '
if hasattr(path_or_f, 'read'):
return path_or_f
else:
path = path_or_f
match = EXT_RE.search(path)
ext = match.groups()[0]
p = subprocess.Popen((EXTENSIONS[ext] + [path]), stdout=subprocess.PIPE, stderr=open(os.devnull, 'w'))
return p.stdout | def open_file(path_or_f):
'\n Turns a path to a dump file into a file-like object of (decompressed)\n XML data.\n\n :Parameters:\n path : `str`\n the path to the dump file to read\n '
if hasattr(path_or_f, 'read'):
return path_or_f
else:
path = path_or_f
match = EXT_RE.search(path)
ext = match.groups()[0]
p = subprocess.Popen((EXTENSIONS[ext] + [path]), stdout=subprocess.PIPE, stderr=open(os.devnull, 'w'))
return p.stdout<|docstring|>Turns a path to a dump file into a file-like object of (decompressed)
XML data.
:Parameters:
path : `str`
the path to the dump file to read<|endoftext|> |
f628b0ad334baf93f540c988d22f34360604b58e1c1bbe3d0bd27877d940f5a6 | def append_new_entries(rsc_src: str, restore_new: dict, vocab_new: Dict[(str, int)]):
'\n ๊ธฐ๋ถ์ ์ฌ์ ๋น๋ ์ค์ ์๋ก ์ถ๊ฐ๊ฐ ํ์ํ ์ฌ์ ์ํธ๋ฆฌ๋ฅผ ํด๋น ์ฌ์ ์ ์ถ๊ฐํ๋ค.\n Args:\n rsc_src: ๋ฆฌ์ค์ ๋๋ ํ ๋ฆฌ\n restore_new: ์ํ๋ณต์ ์ฌ์ ์ ์ถ๊ฐํ ์ํธ๋ฆฌ\n vocab_new: ์ถ๋ ฅ ํ๊ทธ vocabulary์ ์ถ๊ฐํ ์ํธ๋ฆฌ\n '
if restore_new:
with open('{}/restore.dic'.format(rsc_src), 'a', encoding='UTF-8') as fout:
for ((char, tag_out), tag_num_mrp_chr_dic) in restore_new.items():
for (tag_num, mrp_chr) in tag_num_mrp_chr_dic.items():
new_entry_str = '{}/{}:{}\t{}'.format(char, tag_out, tag_num, mrp_chr)
logging.info('[RESTORE] %s', new_entry_str)
print(new_entry_str, file=fout)
if vocab_new:
with open('{}/vocab.out.more'.format(rsc_src), 'a', encoding='UTF-8') as fout:
new_tags = sorted([(num, tag) for (tag, num) in vocab_new.items()])
for (_, tag) in new_tags:
logging.info('[TAG] %s', tag)
print(tag, file=fout) | ๊ธฐ๋ถ์ ์ฌ์ ๋น๋ ์ค์ ์๋ก ์ถ๊ฐ๊ฐ ํ์ํ ์ฌ์ ์ํธ๋ฆฌ๋ฅผ ํด๋น ์ฌ์ ์ ์ถ๊ฐํ๋ค.
Args:
rsc_src: ๋ฆฌ์ค์ ๋๋ ํ ๋ฆฌ
restore_new: ์ํ๋ณต์ ์ฌ์ ์ ์ถ๊ฐํ ์ํธ๋ฆฌ
vocab_new: ์ถ๋ ฅ ํ๊ทธ vocabulary์ ์ถ๊ฐํ ์ํธ๋ฆฌ | rsc/bin/compile_restore.py | append_new_entries | juntf/khaiii | 1,235 | python | def append_new_entries(rsc_src: str, restore_new: dict, vocab_new: Dict[(str, int)]):
'\n ๊ธฐ๋ถ์ ์ฌ์ ๋น๋ ์ค์ ์๋ก ์ถ๊ฐ๊ฐ ํ์ํ ์ฌ์ ์ํธ๋ฆฌ๋ฅผ ํด๋น ์ฌ์ ์ ์ถ๊ฐํ๋ค.\n Args:\n rsc_src: ๋ฆฌ์ค์ ๋๋ ํ ๋ฆฌ\n restore_new: ์ํ๋ณต์ ์ฌ์ ์ ์ถ๊ฐํ ์ํธ๋ฆฌ\n vocab_new: ์ถ๋ ฅ ํ๊ทธ vocabulary์ ์ถ๊ฐํ ์ํธ๋ฆฌ\n '
if restore_new:
with open('{}/restore.dic'.format(rsc_src), 'a', encoding='UTF-8') as fout:
for ((char, tag_out), tag_num_mrp_chr_dic) in restore_new.items():
for (tag_num, mrp_chr) in tag_num_mrp_chr_dic.items():
new_entry_str = '{}/{}:{}\t{}'.format(char, tag_out, tag_num, mrp_chr)
logging.info('[RESTORE] %s', new_entry_str)
print(new_entry_str, file=fout)
if vocab_new:
with open('{}/vocab.out.more'.format(rsc_src), 'a', encoding='UTF-8') as fout:
new_tags = sorted([(num, tag) for (tag, num) in vocab_new.items()])
for (_, tag) in new_tags:
logging.info('[TAG] %s', tag)
print(tag, file=fout) | def append_new_entries(rsc_src: str, restore_new: dict, vocab_new: Dict[(str, int)]):
'\n ๊ธฐ๋ถ์ ์ฌ์ ๋น๋ ์ค์ ์๋ก ์ถ๊ฐ๊ฐ ํ์ํ ์ฌ์ ์ํธ๋ฆฌ๋ฅผ ํด๋น ์ฌ์ ์ ์ถ๊ฐํ๋ค.\n Args:\n rsc_src: ๋ฆฌ์ค์ ๋๋ ํ ๋ฆฌ\n restore_new: ์ํ๋ณต์ ์ฌ์ ์ ์ถ๊ฐํ ์ํธ๋ฆฌ\n vocab_new: ์ถ๋ ฅ ํ๊ทธ vocabulary์ ์ถ๊ฐํ ์ํธ๋ฆฌ\n '
if restore_new:
with open('{}/restore.dic'.format(rsc_src), 'a', encoding='UTF-8') as fout:
for ((char, tag_out), tag_num_mrp_chr_dic) in restore_new.items():
for (tag_num, mrp_chr) in tag_num_mrp_chr_dic.items():
new_entry_str = '{}/{}:{}\t{}'.format(char, tag_out, tag_num, mrp_chr)
logging.info('[RESTORE] %s', new_entry_str)
print(new_entry_str, file=fout)
if vocab_new:
with open('{}/vocab.out.more'.format(rsc_src), 'a', encoding='UTF-8') as fout:
new_tags = sorted([(num, tag) for (tag, num) in vocab_new.items()])
for (_, tag) in new_tags:
logging.info('[TAG] %s', tag)
print(tag, file=fout)<|docstring|>๊ธฐ๋ถ์ ์ฌ์ ๋น๋ ์ค์ ์๋ก ์ถ๊ฐ๊ฐ ํ์ํ ์ฌ์ ์ํธ๋ฆฌ๋ฅผ ํด๋น ์ฌ์ ์ ์ถ๊ฐํ๋ค.
Args:
rsc_src: ๋ฆฌ์ค์ ๋๋ ํ ๋ฆฌ
restore_new: ์ํ๋ณต์ ์ฌ์ ์ ์ถ๊ฐํ ์ํธ๋ฆฌ
vocab_new: ์ถ๋ ฅ ํ๊ทธ vocabulary์ ์ถ๊ฐํ ์ํธ๋ฆฌ<|endoftext|> |
e4400c32bb930182f1ac87b20616aa231ac3a21208810fba93e337c32a224ed6 | def _make_bin(restore_dic: dict, vocab_out: Dict[(str, int)], vocab_new: Dict[(str, int)]) -> dict:
'\n ๋ ํ
์คํธ ์ฌ์ ์ ์ฝ์ด๋ค์ฌ ๋ฐ์ด๋๋ฆฌ ํํ์ key-value ์ฌ์ ์ ๋ง๋ ๋ค.\n Args:\n restore_dic: ์ํ๋ณต์ ์ฌ์ \n vocab_out: ์ถ๋ ฅ ํ๊ทธ ์ฌ์ \n vocab_new: ์ถ๋ ฅ ํ๊ทธ ์ฌ์ ์ ์ถ๊ฐํ ์๋ก์ด ํ๊ทธ\n Retusns:\n ๋ฐ์ด๋๋ฆฌ ์ฌ์ \n '
bin_dic = {}
for ((char, tag), nums_out_dic) in restore_dic.items():
for (num, out) in nums_out_dic.items():
out_tag = '{}:{}'.format(tag, num)
logging.debug('%s/%s\t%s', char, out_tag, out)
if ((out_tag not in vocab_out) and (out_tag not in vocab_new)):
out_num = ((len(vocab_out) + len(vocab_new)) + 1)
logging.info('new output tag: [%d] %s', out_num, out_tag)
vocab_new[out_tag] = out_num
else:
out_num = vocab_out[out_tag]
key = ((ord(char) << 12) | out_num)
if (key in bin_dic):
raise KeyError(('duplicated key: 0x08x' % key))
vals = ([0] * MAX_VAL_LEN)
for (idx, char_tag) in enumerate(out.split()):
if (idx >= MAX_VAL_LEN):
raise ValueError('max value length exceeded: {} >= {}'.format(idx, MAX_VAL_LEN))
(char_val, tag_val) = char_tag.rsplit('/', 1)
val_mask = (0 if (tag_val[0] == 'B') else 128)
tag_val = tag_val[2:]
vals[idx] = ((ord(char_val) << 8) | (TAG_SET[tag_val] | val_mask))
bin_dic[key] = vals
logging.debug('\t0x%08x => %s', key, ' '.join([('0x%08x' % val) for val in vals]))
return bin_dic | ๋ ํ
์คํธ ์ฌ์ ์ ์ฝ์ด๋ค์ฌ ๋ฐ์ด๋๋ฆฌ ํํ์ key-value ์ฌ์ ์ ๋ง๋ ๋ค.
Args:
restore_dic: ์ํ๋ณต์ ์ฌ์
vocab_out: ์ถ๋ ฅ ํ๊ทธ ์ฌ์
vocab_new: ์ถ๋ ฅ ํ๊ทธ ์ฌ์ ์ ์ถ๊ฐํ ์๋ก์ด ํ๊ทธ
Retusns:
๋ฐ์ด๋๋ฆฌ ์ฌ์ | rsc/bin/compile_restore.py | _make_bin | juntf/khaiii | 1,235 | python | def _make_bin(restore_dic: dict, vocab_out: Dict[(str, int)], vocab_new: Dict[(str, int)]) -> dict:
'\n ๋ ํ
์คํธ ์ฌ์ ์ ์ฝ์ด๋ค์ฌ ๋ฐ์ด๋๋ฆฌ ํํ์ key-value ์ฌ์ ์ ๋ง๋ ๋ค.\n Args:\n restore_dic: ์ํ๋ณต์ ์ฌ์ \n vocab_out: ์ถ๋ ฅ ํ๊ทธ ์ฌ์ \n vocab_new: ์ถ๋ ฅ ํ๊ทธ ์ฌ์ ์ ์ถ๊ฐํ ์๋ก์ด ํ๊ทธ\n Retusns:\n ๋ฐ์ด๋๋ฆฌ ์ฌ์ \n '
bin_dic = {}
for ((char, tag), nums_out_dic) in restore_dic.items():
for (num, out) in nums_out_dic.items():
out_tag = '{}:{}'.format(tag, num)
logging.debug('%s/%s\t%s', char, out_tag, out)
if ((out_tag not in vocab_out) and (out_tag not in vocab_new)):
out_num = ((len(vocab_out) + len(vocab_new)) + 1)
logging.info('new output tag: [%d] %s', out_num, out_tag)
vocab_new[out_tag] = out_num
else:
out_num = vocab_out[out_tag]
key = ((ord(char) << 12) | out_num)
if (key in bin_dic):
raise KeyError(('duplicated key: 0x08x' % key))
vals = ([0] * MAX_VAL_LEN)
for (idx, char_tag) in enumerate(out.split()):
if (idx >= MAX_VAL_LEN):
raise ValueError('max value length exceeded: {} >= {}'.format(idx, MAX_VAL_LEN))
(char_val, tag_val) = char_tag.rsplit('/', 1)
val_mask = (0 if (tag_val[0] == 'B') else 128)
tag_val = tag_val[2:]
vals[idx] = ((ord(char_val) << 8) | (TAG_SET[tag_val] | val_mask))
bin_dic[key] = vals
logging.debug('\t0x%08x => %s', key, ' '.join([('0x%08x' % val) for val in vals]))
return bin_dic | def _make_bin(restore_dic: dict, vocab_out: Dict[(str, int)], vocab_new: Dict[(str, int)]) -> dict:
'\n ๋ ํ
์คํธ ์ฌ์ ์ ์ฝ์ด๋ค์ฌ ๋ฐ์ด๋๋ฆฌ ํํ์ key-value ์ฌ์ ์ ๋ง๋ ๋ค.\n Args:\n restore_dic: ์ํ๋ณต์ ์ฌ์ \n vocab_out: ์ถ๋ ฅ ํ๊ทธ ์ฌ์ \n vocab_new: ์ถ๋ ฅ ํ๊ทธ ์ฌ์ ์ ์ถ๊ฐํ ์๋ก์ด ํ๊ทธ\n Retusns:\n ๋ฐ์ด๋๋ฆฌ ์ฌ์ \n '
bin_dic = {}
for ((char, tag), nums_out_dic) in restore_dic.items():
for (num, out) in nums_out_dic.items():
out_tag = '{}:{}'.format(tag, num)
logging.debug('%s/%s\t%s', char, out_tag, out)
if ((out_tag not in vocab_out) and (out_tag not in vocab_new)):
out_num = ((len(vocab_out) + len(vocab_new)) + 1)
logging.info('new output tag: [%d] %s', out_num, out_tag)
vocab_new[out_tag] = out_num
else:
out_num = vocab_out[out_tag]
key = ((ord(char) << 12) | out_num)
if (key in bin_dic):
raise KeyError(('duplicated key: 0x08x' % key))
vals = ([0] * MAX_VAL_LEN)
for (idx, char_tag) in enumerate(out.split()):
if (idx >= MAX_VAL_LEN):
raise ValueError('max value length exceeded: {} >= {}'.format(idx, MAX_VAL_LEN))
(char_val, tag_val) = char_tag.rsplit('/', 1)
val_mask = (0 if (tag_val[0] == 'B') else 128)
tag_val = tag_val[2:]
vals[idx] = ((ord(char_val) << 8) | (TAG_SET[tag_val] | val_mask))
bin_dic[key] = vals
logging.debug('\t0x%08x => %s', key, ' '.join([('0x%08x' % val) for val in vals]))
return bin_dic<|docstring|>๋ ํ
์คํธ ์ฌ์ ์ ์ฝ์ด๋ค์ฌ ๋ฐ์ด๋๋ฆฌ ํํ์ key-value ์ฌ์ ์ ๋ง๋ ๋ค.
Args:
restore_dic: ์ํ๋ณต์ ์ฌ์
vocab_out: ์ถ๋ ฅ ํ๊ทธ ์ฌ์
vocab_new: ์ถ๋ ฅ ํ๊ทธ ์ฌ์ ์ ์ถ๊ฐํ ์๋ก์ด ํ๊ทธ
Retusns:
๋ฐ์ด๋๋ฆฌ ์ฌ์ <|endoftext|> |
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