body_hash stringlengths 64 64 | body stringlengths 23 109k | docstring stringlengths 1 57k | path stringlengths 4 198 | name stringlengths 1 115 | repository_name stringlengths 7 111 | repository_stars float64 0 191k | lang stringclasses 1 value | body_without_docstring stringlengths 14 108k | unified stringlengths 45 133k |
|---|---|---|---|---|---|---|---|---|---|
e0fe1d0c73f014e021904eab73fa62cd9b2689a2ffaae993104ea6d8742b6b0b | def f(self, val, unit=None):
'\n Convert string or value/unit pair to float\n '
return self.__convert(val, unit) | Convert string or value/unit pair to float | spec2nii/fileiobase.py | f | NeutralKaon/spec2nii | 5 | python | def f(self, val, unit=None):
'\n \n '
return self.__convert(val, unit) | def f(self, val, unit=None):
'\n \n '
return self.__convert(val, unit)<|docstring|>Convert string or value/unit pair to float<|endoftext|> |
b138b6b2a5d3a26e2f4b8043277c6f6e2cffe9fd4a76e9a47e5296759fdf029a | def i(self, val, unit=None):
'\n Convert string or value/unit pair to integer\n '
return int(round(self.__convert(val, unit))) | Convert string or value/unit pair to integer | spec2nii/fileiobase.py | i | NeutralKaon/spec2nii | 5 | python | def i(self, val, unit=None):
'\n \n '
return int(round(self.__convert(val, unit))) | def i(self, val, unit=None):
'\n \n '
return int(round(self.__convert(val, unit)))<|docstring|>Convert string or value/unit pair to integer<|endoftext|> |
7dc49851170735b4b913f4c82e24e132850f65ac6bb1bb0c9745c76a1010b1e2 | def ppm(self, val):
'\n Convert to ppm\n '
return self.__pnt2unit(val, 'PPM') | Convert to ppm | spec2nii/fileiobase.py | ppm | NeutralKaon/spec2nii | 5 | python | def ppm(self, val):
'\n \n '
return self.__pnt2unit(val, 'PPM') | def ppm(self, val):
'\n \n '
return self.__pnt2unit(val, 'PPM')<|docstring|>Convert to ppm<|endoftext|> |
d14c15fe67e364c57d88fbe96d4493e85d64003559a11ed7d995c6e4b1d05d9f | def hz(self, val):
'\n Convert to Hz\n '
return self.__pnt2unit(val, 'HZ') | Convert to Hz | spec2nii/fileiobase.py | hz | NeutralKaon/spec2nii | 5 | python | def hz(self, val):
'\n \n '
return self.__pnt2unit(val, 'HZ') | def hz(self, val):
'\n \n '
return self.__pnt2unit(val, 'HZ')<|docstring|>Convert to Hz<|endoftext|> |
2dc7b34042b28998df204280d919d71f801245e081c91f0e2f6b02909b1cd7ba | def percent(self, val):
'\n Convert to percent\n '
return self.__pnt2unit(val, 'PERCENT') | Convert to percent | spec2nii/fileiobase.py | percent | NeutralKaon/spec2nii | 5 | python | def percent(self, val):
'\n \n '
return self.__pnt2unit(val, 'PERCENT') | def percent(self, val):
'\n \n '
return self.__pnt2unit(val, 'PERCENT')<|docstring|>Convert to percent<|endoftext|> |
9dca6dc09705699c698d9d3225e1ad9bbf7c191d2b34b9a0ad3ece20d4d88bd6 | def seconds(self, val):
'\n Convert to seconds\n '
return self.__pnt2unit(val, 'SEC') | Convert to seconds | spec2nii/fileiobase.py | seconds | NeutralKaon/spec2nii | 5 | python | def seconds(self, val):
'\n \n '
return self.__pnt2unit(val, 'SEC') | def seconds(self, val):
'\n \n '
return self.__pnt2unit(val, 'SEC')<|docstring|>Convert to seconds<|endoftext|> |
ce65f2f253ed7f59ba220c3f00168e7b641183ebcceabb8c569c2da6293db3da | def sec(self, val):
'\n Convert to seconds\n '
return self.__pnt2unit(val, 'SEC') | Convert to seconds | spec2nii/fileiobase.py | sec | NeutralKaon/spec2nii | 5 | python | def sec(self, val):
'\n \n '
return self.__pnt2unit(val, 'SEC') | def sec(self, val):
'\n \n '
return self.__pnt2unit(val, 'SEC')<|docstring|>Convert to seconds<|endoftext|> |
8926436b5a7f4f52f4a73a6c81f6d8d1654b48cd803243fe061c043252782053 | def ms(self, val):
'\n Convert to milliseconds (ms)\n '
return self.__pnt2unit(val, 'MS') | Convert to milliseconds (ms) | spec2nii/fileiobase.py | ms | NeutralKaon/spec2nii | 5 | python | def ms(self, val):
'\n \n '
return self.__pnt2unit(val, 'MS') | def ms(self, val):
'\n \n '
return self.__pnt2unit(val, 'MS')<|docstring|>Convert to milliseconds (ms)<|endoftext|> |
53fd610a40ddddc63154d1e97d024eab5fee14db9fb0e6b85399610601614912 | def us(self, val):
'\n Convert to microseconds (us)\n '
return self.__pnt2unit(val, 'US') | Convert to microseconds (us) | spec2nii/fileiobase.py | us | NeutralKaon/spec2nii | 5 | python | def us(self, val):
'\n \n '
return self.__pnt2unit(val, 'US') | def us(self, val):
'\n \n '
return self.__pnt2unit(val, 'US')<|docstring|>Convert to microseconds (us)<|endoftext|> |
62b0b48f25eec4ebae30f51a031b7c4e4e6356b934c565a56749e9ed14aa8068 | def unit(self, val, unit):
'\n Convert val points to unit\n '
return self.__pnt2unit(val, unit) | Convert val points to unit | spec2nii/fileiobase.py | unit | NeutralKaon/spec2nii | 5 | python | def unit(self, val, unit):
'\n \n '
return self.__pnt2unit(val, unit) | def unit(self, val, unit):
'\n \n '
return self.__pnt2unit(val, unit)<|docstring|>Convert val points to unit<|endoftext|> |
2db7d97ba196f2c4d91f2e168bc240017a71f53f4e68f5f31671dec06d0c3480 | def percent_limits(self):
'\n Return tuple of left and right edges in percent\n '
return (0.0, 100.0) | Return tuple of left and right edges in percent | spec2nii/fileiobase.py | percent_limits | NeutralKaon/spec2nii | 5 | python | def percent_limits(self):
'\n \n '
return (0.0, 100.0) | def percent_limits(self):
'\n \n '
return (0.0, 100.0)<|docstring|>Return tuple of left and right edges in percent<|endoftext|> |
7ed2e64c07280cd50baa1232d3ff18dc0174aefe83a7a40d16a11a705713cd26 | def percent_scale(self):
'\n Return array of percent values\n '
return np.linspace(0.0, 100.0, self._size) | Return array of percent values | spec2nii/fileiobase.py | percent_scale | NeutralKaon/spec2nii | 5 | python | def percent_scale(self):
'\n \n '
return np.linspace(0.0, 100.0, self._size) | def percent_scale(self):
'\n \n '
return np.linspace(0.0, 100.0, self._size)<|docstring|>Return array of percent values<|endoftext|> |
e381058f928fd15a4a81c6cac80010e492e338a42fa71be09d08be90371e929e | def ppm_limits(self):
'\n Return tuple of left and right edges in ppm\n '
return (self.ppm(0), self.ppm((self._size - 1))) | Return tuple of left and right edges in ppm | spec2nii/fileiobase.py | ppm_limits | NeutralKaon/spec2nii | 5 | python | def ppm_limits(self):
'\n \n '
return (self.ppm(0), self.ppm((self._size - 1))) | def ppm_limits(self):
'\n \n '
return (self.ppm(0), self.ppm((self._size - 1)))<|docstring|>Return tuple of left and right edges in ppm<|endoftext|> |
ffdc3fec4c3e3f7a1200d21e5922f56ffd1d6bf338d988d88fe3e92d77068bc3 | def ppm_scale(self):
'\n Return array of ppm values\n '
(x0, x1) = self.ppm_limits()
return np.linspace(x0, x1, self._size) | Return array of ppm values | spec2nii/fileiobase.py | ppm_scale | NeutralKaon/spec2nii | 5 | python | def ppm_scale(self):
'\n \n '
(x0, x1) = self.ppm_limits()
return np.linspace(x0, x1, self._size) | def ppm_scale(self):
'\n \n '
(x0, x1) = self.ppm_limits()
return np.linspace(x0, x1, self._size)<|docstring|>Return array of ppm values<|endoftext|> |
05cb707567ff638a76e2bc342f09a4e7b67669c308cfd7c5f656f9dac8fa8732 | def hz_limits(self):
'\n Return tuple of left and right edges in Hz\n '
return (self.hz(0), self.hz((self._size - 1))) | Return tuple of left and right edges in Hz | spec2nii/fileiobase.py | hz_limits | NeutralKaon/spec2nii | 5 | python | def hz_limits(self):
'\n \n '
return (self.hz(0), self.hz((self._size - 1))) | def hz_limits(self):
'\n \n '
return (self.hz(0), self.hz((self._size - 1)))<|docstring|>Return tuple of left and right edges in Hz<|endoftext|> |
9e6814dc8121831d52bb95927f9ff4cd909ec2d54bb90ea0b2ec52348f043f1a | def hz_scale(self):
'\n Return array of Hz values\n '
(x0, x1) = self.hz_limits()
return np.linspace(x0, x1, self._size) | Return array of Hz values | spec2nii/fileiobase.py | hz_scale | NeutralKaon/spec2nii | 5 | python | def hz_scale(self):
'\n \n '
(x0, x1) = self.hz_limits()
return np.linspace(x0, x1, self._size) | def hz_scale(self):
'\n \n '
(x0, x1) = self.hz_limits()
return np.linspace(x0, x1, self._size)<|docstring|>Return array of Hz values<|endoftext|> |
4f6e8a834316ae1d59b71717fce802706200e4808f3858d90664225f5e38c16a | def sec_limits(self):
'\n Return tuple of left and right edges in seconds\n '
return (self.sec(0), self.sec((self._size - 1))) | Return tuple of left and right edges in seconds | spec2nii/fileiobase.py | sec_limits | NeutralKaon/spec2nii | 5 | python | def sec_limits(self):
'\n \n '
return (self.sec(0), self.sec((self._size - 1))) | def sec_limits(self):
'\n \n '
return (self.sec(0), self.sec((self._size - 1)))<|docstring|>Return tuple of left and right edges in seconds<|endoftext|> |
c9ad3992152bfe67b5df8f2c77f55b6561394e53ac979e48fa60ea44cac4c69b | def sec_scale(self):
'\n Return array of seconds values\n '
(x0, x1) = self.sec_limits()
return np.linspace(x0, x1, self._size) | Return array of seconds values | spec2nii/fileiobase.py | sec_scale | NeutralKaon/spec2nii | 5 | python | def sec_scale(self):
'\n \n '
(x0, x1) = self.sec_limits()
return np.linspace(x0, x1, self._size) | def sec_scale(self):
'\n \n '
(x0, x1) = self.sec_limits()
return np.linspace(x0, x1, self._size)<|docstring|>Return array of seconds values<|endoftext|> |
b4a5acb976432dffc58cda372117c94b37152607337ee08c547209a29df5d4ad | def ms_limits(self):
'\n Return tuple of left and right edges in milliseconds\n '
return (self.ms(0), self.ms((self._size - 1))) | Return tuple of left and right edges in milliseconds | spec2nii/fileiobase.py | ms_limits | NeutralKaon/spec2nii | 5 | python | def ms_limits(self):
'\n \n '
return (self.ms(0), self.ms((self._size - 1))) | def ms_limits(self):
'\n \n '
return (self.ms(0), self.ms((self._size - 1)))<|docstring|>Return tuple of left and right edges in milliseconds<|endoftext|> |
a1063d009d18a255a37df887f29e415b193ba2bff97d2900932de9feeb038e3e | def ms_scale(self):
'\n Return array of seconds values\n '
(x0, x1) = self.ms_limits()
return np.linspace(x0, x1, self._size) | Return array of seconds values | spec2nii/fileiobase.py | ms_scale | NeutralKaon/spec2nii | 5 | python | def ms_scale(self):
'\n \n '
(x0, x1) = self.ms_limits()
return np.linspace(x0, x1, self._size) | def ms_scale(self):
'\n \n '
(x0, x1) = self.ms_limits()
return np.linspace(x0, x1, self._size)<|docstring|>Return array of seconds values<|endoftext|> |
713e90cc0d7d79eff532f8cfe5bdfe3cac72c97dfafda9b7f3fc99b574331447 | def us_limits(self):
'\n Return tuple of left and right edges in milliseconds\n '
return (self.us(0), self.us((self._size - 1))) | Return tuple of left and right edges in milliseconds | spec2nii/fileiobase.py | us_limits | NeutralKaon/spec2nii | 5 | python | def us_limits(self):
'\n \n '
return (self.us(0), self.us((self._size - 1))) | def us_limits(self):
'\n \n '
return (self.us(0), self.us((self._size - 1)))<|docstring|>Return tuple of left and right edges in milliseconds<|endoftext|> |
156e62df062e0faf951a06b0c579ab1fa38fcd7f7f357506313962cf3b46f0a6 | def us_scale(self):
'\n Return array of seconds values\n '
(x0, x1) = self.us_limits()
return np.linspace(x0, x1, self._size) | Return array of seconds values | spec2nii/fileiobase.py | us_scale | NeutralKaon/spec2nii | 5 | python | def us_scale(self):
'\n \n '
(x0, x1) = self.us_limits()
return np.linspace(x0, x1, self._size) | def us_scale(self):
'\n \n '
(x0, x1) = self.us_limits()
return np.linspace(x0, x1, self._size)<|docstring|>Return array of seconds values<|endoftext|> |
31e6e1dc5db78d994e940378a687b8dec48211c241b6ba28f0ee68c9e88772aa | def __setdimandshape__(self):
' Set the the ndim and shape attributes from fshape '
self.ndim = len(self.fshape)
self.shape = tuple([self.fshape[i] for i in self.order]) | Set the the ndim and shape attributes from fshape | spec2nii/fileiobase.py | __setdimandshape__ | NeutralKaon/spec2nii | 5 | python | def __setdimandshape__(self):
' '
self.ndim = len(self.fshape)
self.shape = tuple([self.fshape[i] for i in self.order]) | def __setdimandshape__(self):
' '
self.ndim = len(self.fshape)
self.shape = tuple([self.fshape[i] for i in self.order])<|docstring|>Set the the ndim and shape attributes from fshape<|endoftext|> |
029ea59ed308ce3848fd1938ba8bd7befbb6d3163bd7e5c0f9d89d7a13af1c2d | def __copy__(self):
'\n create a copy\n '
return self.__fcopy__(self, self.order) | create a copy | spec2nii/fileiobase.py | __copy__ | NeutralKaon/spec2nii | 5 | python | def __copy__(self):
'\n \n '
return self.__fcopy__(self, self.order) | def __copy__(self):
'\n \n '
return self.__fcopy__(self, self.order)<|docstring|>create a copy<|endoftext|> |
0193bef117998990d59fef98339cca205bf6123b1e9a287cc33845b6066dedc0 | def __getitem__(self, key):
'\n x.__getitem__(y) <==> x[y]\n '
if (not isinstance(key, tuple)):
rlist = [key]
else:
rlist = list(key)
while (Ellipsis in rlist):
i = rlist.index(Ellipsis)
rlist.pop(i)
for j in range((self.ndim - len(rlist))):
rlist.insert(i, slice(None))
if (len(rlist) > self.ndim):
raise IndexError('invalid index')
for (i, v) in enumerate(rlist):
if (not isinstance(v, slice)):
if (v >= self.shape[i]):
raise IndexError(('index(%s) out of range(0 <= index < %s) in dimension %s' % (v, (self.shape[i] - 1), i)))
if (v <= (((- 1) * self.shape[i]) - 1)):
raise IndexError(('index(%s) out of range(0 <= index < %s) in dimension %s' % (v, (self.shape[i] - 1), i)))
if (v < 0):
w = (self.shape[i] + v)
rlist[i] = slice(w, (w + 1), 1)
else:
rlist[i] = slice(v, (v + 1), 1)
for i in range(len(rlist), self.ndim):
rlist.append(slice(None))
frlist = [rlist[self.order.index(i)] for i in range(self.ndim)]
data = self.__fgetitem__(tuple(frlist))
if (data.shape != (0,)):
return np.squeeze(data.transpose(self.order))
else:
return data | x.__getitem__(y) <==> x[y] | spec2nii/fileiobase.py | __getitem__ | NeutralKaon/spec2nii | 5 | python | def __getitem__(self, key):
'\n \n '
if (not isinstance(key, tuple)):
rlist = [key]
else:
rlist = list(key)
while (Ellipsis in rlist):
i = rlist.index(Ellipsis)
rlist.pop(i)
for j in range((self.ndim - len(rlist))):
rlist.insert(i, slice(None))
if (len(rlist) > self.ndim):
raise IndexError('invalid index')
for (i, v) in enumerate(rlist):
if (not isinstance(v, slice)):
if (v >= self.shape[i]):
raise IndexError(('index(%s) out of range(0 <= index < %s) in dimension %s' % (v, (self.shape[i] - 1), i)))
if (v <= (((- 1) * self.shape[i]) - 1)):
raise IndexError(('index(%s) out of range(0 <= index < %s) in dimension %s' % (v, (self.shape[i] - 1), i)))
if (v < 0):
w = (self.shape[i] + v)
rlist[i] = slice(w, (w + 1), 1)
else:
rlist[i] = slice(v, (v + 1), 1)
for i in range(len(rlist), self.ndim):
rlist.append(slice(None))
frlist = [rlist[self.order.index(i)] for i in range(self.ndim)]
data = self.__fgetitem__(tuple(frlist))
if (data.shape != (0,)):
return np.squeeze(data.transpose(self.order))
else:
return data | def __getitem__(self, key):
'\n \n '
if (not isinstance(key, tuple)):
rlist = [key]
else:
rlist = list(key)
while (Ellipsis in rlist):
i = rlist.index(Ellipsis)
rlist.pop(i)
for j in range((self.ndim - len(rlist))):
rlist.insert(i, slice(None))
if (len(rlist) > self.ndim):
raise IndexError('invalid index')
for (i, v) in enumerate(rlist):
if (not isinstance(v, slice)):
if (v >= self.shape[i]):
raise IndexError(('index(%s) out of range(0 <= index < %s) in dimension %s' % (v, (self.shape[i] - 1), i)))
if (v <= (((- 1) * self.shape[i]) - 1)):
raise IndexError(('index(%s) out of range(0 <= index < %s) in dimension %s' % (v, (self.shape[i] - 1), i)))
if (v < 0):
w = (self.shape[i] + v)
rlist[i] = slice(w, (w + 1), 1)
else:
rlist[i] = slice(v, (v + 1), 1)
for i in range(len(rlist), self.ndim):
rlist.append(slice(None))
frlist = [rlist[self.order.index(i)] for i in range(self.ndim)]
data = self.__fgetitem__(tuple(frlist))
if (data.shape != (0,)):
return np.squeeze(data.transpose(self.order))
else:
return data<|docstring|>x.__getitem__(y) <==> x[y]<|endoftext|> |
afbbc775c37550a39501750aa139a57dd6f79ce97fc7225cb21657c4204e5c29 | def __len__(self):
'\n x._len__ <==> len(x)\n '
return self.shape[0] | x._len__ <==> len(x) | spec2nii/fileiobase.py | __len__ | NeutralKaon/spec2nii | 5 | python | def __len__(self):
'\n \n '
return self.shape[0] | def __len__(self):
'\n \n '
return self.shape[0]<|docstring|>x._len__ <==> len(x)<|endoftext|> |
0cf7b2a4c54cc34ca2348cb7207e3a28fa05f47cc4c4569dc17bf82e321f0e01 | def __iter__(self):
' x.__iter__() <==> iter(x) '
for index in range(0, self.shape[0]):
(yield self[index]) | x.__iter__() <==> iter(x) | spec2nii/fileiobase.py | __iter__ | NeutralKaon/spec2nii | 5 | python | def __iter__(self):
' '
for index in range(0, self.shape[0]):
(yield self[index]) | def __iter__(self):
' '
for index in range(0, self.shape[0]):
(yield self[index])<|docstring|>x.__iter__() <==> iter(x)<|endoftext|> |
df304deb9fd910a6c72df2882a0d8ea531e26ac965e8c964a84639b599131d4c | def swapaxes(self, axis1, axis2):
'\n Return object with `axis1` and `axis2` interchanged.\n '
(axis1, axis2) = (int(axis1), int(axis2))
if (axis1 < 0):
axis1 = (self.ndim - axis1)
if (axis2 < 0):
axis2 = (self.ndim - axis2)
if (axis1 >= self.ndim):
raise ValueError('bad axis1 argument to swapaxes')
if (axis2 >= self.ndim):
raise ValueError('bad axis2 argument to swapaxes')
order = list(self.order)
(order[axis1], order[axis2]) = (order[axis2], order[axis1])
n = self.__fcopy__(order=order)
return n | Return object with `axis1` and `axis2` interchanged. | spec2nii/fileiobase.py | swapaxes | NeutralKaon/spec2nii | 5 | python | def swapaxes(self, axis1, axis2):
'\n \n '
(axis1, axis2) = (int(axis1), int(axis2))
if (axis1 < 0):
axis1 = (self.ndim - axis1)
if (axis2 < 0):
axis2 = (self.ndim - axis2)
if (axis1 >= self.ndim):
raise ValueError('bad axis1 argument to swapaxes')
if (axis2 >= self.ndim):
raise ValueError('bad axis2 argument to swapaxes')
order = list(self.order)
(order[axis1], order[axis2]) = (order[axis2], order[axis1])
n = self.__fcopy__(order=order)
return n | def swapaxes(self, axis1, axis2):
'\n \n '
(axis1, axis2) = (int(axis1), int(axis2))
if (axis1 < 0):
axis1 = (self.ndim - axis1)
if (axis2 < 0):
axis2 = (self.ndim - axis2)
if (axis1 >= self.ndim):
raise ValueError('bad axis1 argument to swapaxes')
if (axis2 >= self.ndim):
raise ValueError('bad axis2 argument to swapaxes')
order = list(self.order)
(order[axis1], order[axis2]) = (order[axis2], order[axis1])
n = self.__fcopy__(order=order)
return n<|docstring|>Return object with `axis1` and `axis2` interchanged.<|endoftext|> |
8e0e6f386f36d4a423b4618f0ede4b90c1fc97e422c7218175088b4e0d59b47f | def transpose(self, *axes):
"\n Return object with axes transposed.\n\n Parameters\n ----------\n axes : None, tuple or ints, or `n` ints\n * None or no arguments: reverse order of the axes\n\n * tuple of ints: `i` in the `j`-th place in the tuples means the\n 'i'-th axis becomes the new objects `j`-th axis.\n\n * `n` ints: same as an n-tuple.\n\n Returns\n -------\n out : data_nd object\n Object whose axes are permuted.\n\n "
if (axes == ()):
axes = range(self.ndim)[::(- 1)]
if (len(axes) == 1):
axes = axes[0]
try:
axes = [int(i) for i in axes]
except Exception:
raise TypeError('an integer is required')
if (len(axes) != self.ndim):
raise ValueError("axes don't match array")
for (i, v) in enumerate(axes):
if (v < 0):
axes[i] = (self.ndim + v)
for v in axes:
if (v >= self.ndim):
raise ValueError('invalid axis for this array')
if (len(set(axes)) != self.ndim):
raise ValueError('repeated axis in tranpose')
return self.__fcopy__(order=tuple([self.order[i] for i in axes])) | Return object with axes transposed.
Parameters
----------
axes : None, tuple or ints, or `n` ints
* None or no arguments: reverse order of the axes
* tuple of ints: `i` in the `j`-th place in the tuples means the
'i'-th axis becomes the new objects `j`-th axis.
* `n` ints: same as an n-tuple.
Returns
-------
out : data_nd object
Object whose axes are permuted. | spec2nii/fileiobase.py | transpose | NeutralKaon/spec2nii | 5 | python | def transpose(self, *axes):
"\n Return object with axes transposed.\n\n Parameters\n ----------\n axes : None, tuple or ints, or `n` ints\n * None or no arguments: reverse order of the axes\n\n * tuple of ints: `i` in the `j`-th place in the tuples means the\n 'i'-th axis becomes the new objects `j`-th axis.\n\n * `n` ints: same as an n-tuple.\n\n Returns\n -------\n out : data_nd object\n Object whose axes are permuted.\n\n "
if (axes == ()):
axes = range(self.ndim)[::(- 1)]
if (len(axes) == 1):
axes = axes[0]
try:
axes = [int(i) for i in axes]
except Exception:
raise TypeError('an integer is required')
if (len(axes) != self.ndim):
raise ValueError("axes don't match array")
for (i, v) in enumerate(axes):
if (v < 0):
axes[i] = (self.ndim + v)
for v in axes:
if (v >= self.ndim):
raise ValueError('invalid axis for this array')
if (len(set(axes)) != self.ndim):
raise ValueError('repeated axis in tranpose')
return self.__fcopy__(order=tuple([self.order[i] for i in axes])) | def transpose(self, *axes):
"\n Return object with axes transposed.\n\n Parameters\n ----------\n axes : None, tuple or ints, or `n` ints\n * None or no arguments: reverse order of the axes\n\n * tuple of ints: `i` in the `j`-th place in the tuples means the\n 'i'-th axis becomes the new objects `j`-th axis.\n\n * `n` ints: same as an n-tuple.\n\n Returns\n -------\n out : data_nd object\n Object whose axes are permuted.\n\n "
if (axes == ()):
axes = range(self.ndim)[::(- 1)]
if (len(axes) == 1):
axes = axes[0]
try:
axes = [int(i) for i in axes]
except Exception:
raise TypeError('an integer is required')
if (len(axes) != self.ndim):
raise ValueError("axes don't match array")
for (i, v) in enumerate(axes):
if (v < 0):
axes[i] = (self.ndim + v)
for v in axes:
if (v >= self.ndim):
raise ValueError('invalid axis for this array')
if (len(set(axes)) != self.ndim):
raise ValueError('repeated axis in tranpose')
return self.__fcopy__(order=tuple([self.order[i] for i in axes]))<|docstring|>Return object with axes transposed.
Parameters
----------
axes : None, tuple or ints, or `n` ints
* None or no arguments: reverse order of the axes
* tuple of ints: `i` in the `j`-th place in the tuples means the
'i'-th axis becomes the new objects `j`-th axis.
* `n` ints: same as an n-tuple.
Returns
-------
out : data_nd object
Object whose axes are permuted.<|endoftext|> |
8829f34e32a5fbf4929a37cc5ccc70e74214c7d915a50ddbbdda58f0422d5331 | def tearDown(self):
' Be a good person and always clean up unit test data '
if exists(self.filename):
unlink(self.filename) | Be a good person and always clean up unit test data | py23/tests/base.py | tearDown | cooperlees/py23 | 1 | python | def tearDown(self):
' '
if exists(self.filename):
unlink(self.filename) | def tearDown(self):
' '
if exists(self.filename):
unlink(self.filename)<|docstring|>Be a good person and always clean up unit test data<|endoftext|> |
06a38400f17d768935325123d960adc2188d2cf3081b989f94a783276a5497e2 | def get_pecan_config():
'Returns the pecan config.'
filename = app_config.__file__.replace('.pyc', '.py')
return pecan.configuration.conf_from_file(filename) | Returns the pecan config. | starfish/frame_api/app.py | get_pecan_config | JayLiu7319/Starfish | 0 | python | def get_pecan_config():
filename = app_config.__file__.replace('.pyc', '.py')
return pecan.configuration.conf_from_file(filename) | def get_pecan_config():
filename = app_config.__file__.replace('.pyc', '.py')
return pecan.configuration.conf_from_file(filename)<|docstring|>Returns the pecan config.<|endoftext|> |
26aeef060412e89f8de41eb0a9209ea31226004b1d7b44da94dddc63a5743a8e | def setup_app(pecan_config=None, debug=True, argv=None):
'Creates and returns a pecan wsgi app.'
if (argv is None):
argv = sys.argv
octavia_service.prepare_service(argv)
cfg.CONF.log_opt_values(LOG, logging.DEBUG)
if (not pecan_config):
pecan_config = get_pecan_config()
pecan.configuration.set_config(dict(pecan_config), overwrite=True)
return pecan.make_app(pecan_config.app.root, debug=debug, hooks=pecan_config.app.hooks, wsme=pecan_config.wsme) | Creates and returns a pecan wsgi app. | starfish/frame_api/app.py | setup_app | JayLiu7319/Starfish | 0 | python | def setup_app(pecan_config=None, debug=True, argv=None):
if (argv is None):
argv = sys.argv
octavia_service.prepare_service(argv)
cfg.CONF.log_opt_values(LOG, logging.DEBUG)
if (not pecan_config):
pecan_config = get_pecan_config()
pecan.configuration.set_config(dict(pecan_config), overwrite=True)
return pecan.make_app(pecan_config.app.root, debug=debug, hooks=pecan_config.app.hooks, wsme=pecan_config.wsme) | def setup_app(pecan_config=None, debug=True, argv=None):
if (argv is None):
argv = sys.argv
octavia_service.prepare_service(argv)
cfg.CONF.log_opt_values(LOG, logging.DEBUG)
if (not pecan_config):
pecan_config = get_pecan_config()
pecan.configuration.set_config(dict(pecan_config), overwrite=True)
return pecan.make_app(pecan_config.app.root, debug=debug, hooks=pecan_config.app.hooks, wsme=pecan_config.wsme)<|docstring|>Creates and returns a pecan wsgi app.<|endoftext|> |
571f4c0ae6a05a8d2c3a732a559b7892ba60f492bf40be1b1441362a418033ae | def header(fn):
'\n Custom header for isomiR-SEA importer.\n\n Args:\n *fn (str)*: file name with isomiR-SEA GFF output\n\n Returns:\n *(str)*: isomiR-SEA header string.\n '
h = ''
return h | Custom header for isomiR-SEA importer.
Args:
*fn (str)*: file name with isomiR-SEA GFF output
Returns:
*(str)*: isomiR-SEA header string. | mirtop/importer/isomirsea.py | header | srinivas32/mirtop | 0 | python | def header(fn):
'\n Custom header for isomiR-SEA importer.\n\n Args:\n *fn (str)*: file name with isomiR-SEA GFF output\n\n Returns:\n *(str)*: isomiR-SEA header string.\n '
h =
return h | def header(fn):
'\n Custom header for isomiR-SEA importer.\n\n Args:\n *fn (str)*: file name with isomiR-SEA GFF output\n\n Returns:\n *(str)*: isomiR-SEA header string.\n '
h =
return h<|docstring|>Custom header for isomiR-SEA importer.
Args:
*fn (str)*: file name with isomiR-SEA GFF output
Returns:
*(str)*: isomiR-SEA header string.<|endoftext|> |
50e335e5b6ed1ffa722a220a7ae21d04a82582269f188be54ac1e25dd07efb5d | def read_file(fn, args):
'\n Read isomiR-SEA file and convert to mirtop GFF format.\n\n Args:\n *fn(str)*: file name with isomiR-SEA output information.\n\n *database(str)*: database name.\n\n *args(namedtuple)*: arguments from command line.\n See *mirtop.libs.parse.add_subparser_gff()*.\n\n Returns:\n *reads (nested dicts)*:gff_list has the format as\n defined in *mirtop.gff.body.read()*.\n\n '
database = args.database
gtf = args.gtf
sep = (' ' if (args.out_format == 'gtf') else '=')
map_mir = mapper.read_gtf_to_mirna(gtf)
reads = defaultdict(dict)
reads_in = 0
sample = os.path.splitext(os.path.basename(fn))[0]
hits = _get_hits(fn)
logger.debug(('ISOMIRSEA::SAMPLE::%s' % sample))
with open(fn) as handle:
for line in handle:
cols = line.strip().split('\t')
attr = read_attributes(line, '=')
query_name = attr['TS']
query_sequence = attr['TS'].replace('U', 'T')
start = int(cols[3])
end = int(cols[4])
isomirseq_iso = attr['ISO']
if ((query_name not in reads) and (query_sequence == None)):
continue
if (query_sequence and (query_sequence.find('N') > (- 1))):
continue
counts = attr['TC']
chrom = cols[0]
cigar = attr['CI'].replace('U', 'T')
idu = make_id(query_sequence)
isoformat = cigar2variants(cigar, query_sequence, attr['ISO'])
logger.debug('\nISOMIRSEA::NEW::query: {query_sequence}\n precursor {chrom}\n name: {query_name}\n idu: {idu}\n start: {start}\n cigar: {cigar}\n iso: {isoformat}\n variant: {isoformat}'.format(**locals()))
source = ('isomiR' if (isoformat != 'NA') else 'ref_miRNA')
strand = '+'
database = cols[1]
mirName = attr['MIN'].split()[0]
preName = attr['PIN'].split()[0]
score = '.'
Filter = attr['FILTER']
isotag = attr['ISO']
(tchrom, tstart) = _genomic2transcript(map_mir[mirName], chrom, start)
start = (start if (not tstart) else tstart)
chrom = (chrom if (not tstart) else tchrom)
end = (start + len(query_sequence))
hit = hits[idu]
fields = {'seq_name': query_sequence, 'idseq': idu, 'name': mirName, 'parent': preName, 'variant': isoformat, 'cigar': cigar, 'counts': counts, 'filter': Filter, 'hits': hit, 'chrom': chrom, 'start': start, 'end': end, 'database': database, 'source': source, 'score': score, 'strand': strand}
line = feature(fields).line
if args.add_extra:
extra = variant_with_nt(line, args.precursors, args.matures)
line = ('%s Changes %s;' % (line, extra))
line = paste_columns(feature(line), sep=sep)
if (start not in reads[chrom]):
reads[chrom][start] = []
if (Filter == 'Pass'):
reads_in += 1
reads[chrom][start].append([idu, chrom, counts, sample, line])
logger.info(('Hits: %s' % reads_in))
return reads | Read isomiR-SEA file and convert to mirtop GFF format.
Args:
*fn(str)*: file name with isomiR-SEA output information.
*database(str)*: database name.
*args(namedtuple)*: arguments from command line.
See *mirtop.libs.parse.add_subparser_gff()*.
Returns:
*reads (nested dicts)*:gff_list has the format as
defined in *mirtop.gff.body.read()*. | mirtop/importer/isomirsea.py | read_file | srinivas32/mirtop | 0 | python | def read_file(fn, args):
'\n Read isomiR-SEA file and convert to mirtop GFF format.\n\n Args:\n *fn(str)*: file name with isomiR-SEA output information.\n\n *database(str)*: database name.\n\n *args(namedtuple)*: arguments from command line.\n See *mirtop.libs.parse.add_subparser_gff()*.\n\n Returns:\n *reads (nested dicts)*:gff_list has the format as\n defined in *mirtop.gff.body.read()*.\n\n '
database = args.database
gtf = args.gtf
sep = (' ' if (args.out_format == 'gtf') else '=')
map_mir = mapper.read_gtf_to_mirna(gtf)
reads = defaultdict(dict)
reads_in = 0
sample = os.path.splitext(os.path.basename(fn))[0]
hits = _get_hits(fn)
logger.debug(('ISOMIRSEA::SAMPLE::%s' % sample))
with open(fn) as handle:
for line in handle:
cols = line.strip().split('\t')
attr = read_attributes(line, '=')
query_name = attr['TS']
query_sequence = attr['TS'].replace('U', 'T')
start = int(cols[3])
end = int(cols[4])
isomirseq_iso = attr['ISO']
if ((query_name not in reads) and (query_sequence == None)):
continue
if (query_sequence and (query_sequence.find('N') > (- 1))):
continue
counts = attr['TC']
chrom = cols[0]
cigar = attr['CI'].replace('U', 'T')
idu = make_id(query_sequence)
isoformat = cigar2variants(cigar, query_sequence, attr['ISO'])
logger.debug('\nISOMIRSEA::NEW::query: {query_sequence}\n precursor {chrom}\n name: {query_name}\n idu: {idu}\n start: {start}\n cigar: {cigar}\n iso: {isoformat}\n variant: {isoformat}'.format(**locals()))
source = ('isomiR' if (isoformat != 'NA') else 'ref_miRNA')
strand = '+'
database = cols[1]
mirName = attr['MIN'].split()[0]
preName = attr['PIN'].split()[0]
score = '.'
Filter = attr['FILTER']
isotag = attr['ISO']
(tchrom, tstart) = _genomic2transcript(map_mir[mirName], chrom, start)
start = (start if (not tstart) else tstart)
chrom = (chrom if (not tstart) else tchrom)
end = (start + len(query_sequence))
hit = hits[idu]
fields = {'seq_name': query_sequence, 'idseq': idu, 'name': mirName, 'parent': preName, 'variant': isoformat, 'cigar': cigar, 'counts': counts, 'filter': Filter, 'hits': hit, 'chrom': chrom, 'start': start, 'end': end, 'database': database, 'source': source, 'score': score, 'strand': strand}
line = feature(fields).line
if args.add_extra:
extra = variant_with_nt(line, args.precursors, args.matures)
line = ('%s Changes %s;' % (line, extra))
line = paste_columns(feature(line), sep=sep)
if (start not in reads[chrom]):
reads[chrom][start] = []
if (Filter == 'Pass'):
reads_in += 1
reads[chrom][start].append([idu, chrom, counts, sample, line])
logger.info(('Hits: %s' % reads_in))
return reads | def read_file(fn, args):
'\n Read isomiR-SEA file and convert to mirtop GFF format.\n\n Args:\n *fn(str)*: file name with isomiR-SEA output information.\n\n *database(str)*: database name.\n\n *args(namedtuple)*: arguments from command line.\n See *mirtop.libs.parse.add_subparser_gff()*.\n\n Returns:\n *reads (nested dicts)*:gff_list has the format as\n defined in *mirtop.gff.body.read()*.\n\n '
database = args.database
gtf = args.gtf
sep = (' ' if (args.out_format == 'gtf') else '=')
map_mir = mapper.read_gtf_to_mirna(gtf)
reads = defaultdict(dict)
reads_in = 0
sample = os.path.splitext(os.path.basename(fn))[0]
hits = _get_hits(fn)
logger.debug(('ISOMIRSEA::SAMPLE::%s' % sample))
with open(fn) as handle:
for line in handle:
cols = line.strip().split('\t')
attr = read_attributes(line, '=')
query_name = attr['TS']
query_sequence = attr['TS'].replace('U', 'T')
start = int(cols[3])
end = int(cols[4])
isomirseq_iso = attr['ISO']
if ((query_name not in reads) and (query_sequence == None)):
continue
if (query_sequence and (query_sequence.find('N') > (- 1))):
continue
counts = attr['TC']
chrom = cols[0]
cigar = attr['CI'].replace('U', 'T')
idu = make_id(query_sequence)
isoformat = cigar2variants(cigar, query_sequence, attr['ISO'])
logger.debug('\nISOMIRSEA::NEW::query: {query_sequence}\n precursor {chrom}\n name: {query_name}\n idu: {idu}\n start: {start}\n cigar: {cigar}\n iso: {isoformat}\n variant: {isoformat}'.format(**locals()))
source = ('isomiR' if (isoformat != 'NA') else 'ref_miRNA')
strand = '+'
database = cols[1]
mirName = attr['MIN'].split()[0]
preName = attr['PIN'].split()[0]
score = '.'
Filter = attr['FILTER']
isotag = attr['ISO']
(tchrom, tstart) = _genomic2transcript(map_mir[mirName], chrom, start)
start = (start if (not tstart) else tstart)
chrom = (chrom if (not tstart) else tchrom)
end = (start + len(query_sequence))
hit = hits[idu]
fields = {'seq_name': query_sequence, 'idseq': idu, 'name': mirName, 'parent': preName, 'variant': isoformat, 'cigar': cigar, 'counts': counts, 'filter': Filter, 'hits': hit, 'chrom': chrom, 'start': start, 'end': end, 'database': database, 'source': source, 'score': score, 'strand': strand}
line = feature(fields).line
if args.add_extra:
extra = variant_with_nt(line, args.precursors, args.matures)
line = ('%s Changes %s;' % (line, extra))
line = paste_columns(feature(line), sep=sep)
if (start not in reads[chrom]):
reads[chrom][start] = []
if (Filter == 'Pass'):
reads_in += 1
reads[chrom][start].append([idu, chrom, counts, sample, line])
logger.info(('Hits: %s' % reads_in))
return reads<|docstring|>Read isomiR-SEA file and convert to mirtop GFF format.
Args:
*fn(str)*: file name with isomiR-SEA output information.
*database(str)*: database name.
*args(namedtuple)*: arguments from command line.
See *mirtop.libs.parse.add_subparser_gff()*.
Returns:
*reads (nested dicts)*:gff_list has the format as
defined in *mirtop.gff.body.read()*.<|endoftext|> |
3090e5ab3702cf2e720dc560908716d31d6c358b51eca8a8a62c4aad16c90fd2 | def cigar2variants(cigar, sequence, tag):
'From cigar to Variants in GFF format'
pos = 0
iso5p = 0
logger.debug(('\nISOMIRSEA:: expanded: %s' % expand_cigar(cigar)))
for l in expand_cigar(cigar):
if (l == 'I'):
iso5p -= 1
elif (l == 'D'):
iso5p += 1
else:
break
iso3p = 0
for l in reversed(expand_cigar(cigar)):
if (l == 'I'):
iso3p += 1
elif (l == 'D'):
iso3p -= 1
else:
break
isosnp = []
for l in expand_cigar(cigar):
if (l in ['A', 'T', 'C', 'G']):
isosnp.append([pos, sequence[pos], l])
if (l in ['D']):
continue
pos += 1
iso5p = (('iso_5p:%s' % _fix(iso5p)) if iso5p else '')
if ((tag[(- 1)] == 'T') or (iso3p < 0)):
iso3p = (('iso_3p:%s' % _fix(iso3p)) if iso3p else '')
else:
iso3p = (('iso_add3p:%s' % iso3p) if iso3p else '')
variant = ''
for iso in [iso5p, iso3p, _define_snp(isosnp)]:
if iso:
variant += ('%s,' % iso)
variant = ('NA;' if (not variant) else variant)
return variant[:(- 1)] | From cigar to Variants in GFF format | mirtop/importer/isomirsea.py | cigar2variants | srinivas32/mirtop | 0 | python | def cigar2variants(cigar, sequence, tag):
pos = 0
iso5p = 0
logger.debug(('\nISOMIRSEA:: expanded: %s' % expand_cigar(cigar)))
for l in expand_cigar(cigar):
if (l == 'I'):
iso5p -= 1
elif (l == 'D'):
iso5p += 1
else:
break
iso3p = 0
for l in reversed(expand_cigar(cigar)):
if (l == 'I'):
iso3p += 1
elif (l == 'D'):
iso3p -= 1
else:
break
isosnp = []
for l in expand_cigar(cigar):
if (l in ['A', 'T', 'C', 'G']):
isosnp.append([pos, sequence[pos], l])
if (l in ['D']):
continue
pos += 1
iso5p = (('iso_5p:%s' % _fix(iso5p)) if iso5p else )
if ((tag[(- 1)] == 'T') or (iso3p < 0)):
iso3p = (('iso_3p:%s' % _fix(iso3p)) if iso3p else )
else:
iso3p = (('iso_add3p:%s' % iso3p) if iso3p else )
variant =
for iso in [iso5p, iso3p, _define_snp(isosnp)]:
if iso:
variant += ('%s,' % iso)
variant = ('NA;' if (not variant) else variant)
return variant[:(- 1)] | def cigar2variants(cigar, sequence, tag):
pos = 0
iso5p = 0
logger.debug(('\nISOMIRSEA:: expanded: %s' % expand_cigar(cigar)))
for l in expand_cigar(cigar):
if (l == 'I'):
iso5p -= 1
elif (l == 'D'):
iso5p += 1
else:
break
iso3p = 0
for l in reversed(expand_cigar(cigar)):
if (l == 'I'):
iso3p += 1
elif (l == 'D'):
iso3p -= 1
else:
break
isosnp = []
for l in expand_cigar(cigar):
if (l in ['A', 'T', 'C', 'G']):
isosnp.append([pos, sequence[pos], l])
if (l in ['D']):
continue
pos += 1
iso5p = (('iso_5p:%s' % _fix(iso5p)) if iso5p else )
if ((tag[(- 1)] == 'T') or (iso3p < 0)):
iso3p = (('iso_3p:%s' % _fix(iso3p)) if iso3p else )
else:
iso3p = (('iso_add3p:%s' % iso3p) if iso3p else )
variant =
for iso in [iso5p, iso3p, _define_snp(isosnp)]:
if iso:
variant += ('%s,' % iso)
variant = ('NA;' if (not variant) else variant)
return variant[:(- 1)]<|docstring|>From cigar to Variants in GFF format<|endoftext|> |
44f163bbd35312ea967687a16089a2832567b632d1a8256b6f2049e606a46afa | def __init__(self, kube_client: client.CoreV1Api=None, in_cluster: bool=True, cluster_context: Optional[str]=None, extract_xcom: bool=False):
'\n Deprecated class for launching pods. please use\n airflow.providers.cncf.kubernetes.utils.pod_launcher.PodLauncher instead\n Creates the launcher.\n\n :param kube_client: kubernetes client\n :param in_cluster: whether we are in cluster\n :param cluster_context: context of the cluster\n :param extract_xcom: whether we should extract xcom\n '
super().__init__()
self._client = (kube_client or get_kube_client(in_cluster=in_cluster, cluster_context=cluster_context))
self._watch = watch.Watch()
self.extract_xcom = extract_xcom | Deprecated class for launching pods. please use
airflow.providers.cncf.kubernetes.utils.pod_launcher.PodLauncher instead
Creates the launcher.
:param kube_client: kubernetes client
:param in_cluster: whether we are in cluster
:param cluster_context: context of the cluster
:param extract_xcom: whether we should extract xcom | airflow/kubernetes/pod_launcher_deprecated.py | __init__ | legau/airflow | 27 | python | def __init__(self, kube_client: client.CoreV1Api=None, in_cluster: bool=True, cluster_context: Optional[str]=None, extract_xcom: bool=False):
'\n Deprecated class for launching pods. please use\n airflow.providers.cncf.kubernetes.utils.pod_launcher.PodLauncher instead\n Creates the launcher.\n\n :param kube_client: kubernetes client\n :param in_cluster: whether we are in cluster\n :param cluster_context: context of the cluster\n :param extract_xcom: whether we should extract xcom\n '
super().__init__()
self._client = (kube_client or get_kube_client(in_cluster=in_cluster, cluster_context=cluster_context))
self._watch = watch.Watch()
self.extract_xcom = extract_xcom | def __init__(self, kube_client: client.CoreV1Api=None, in_cluster: bool=True, cluster_context: Optional[str]=None, extract_xcom: bool=False):
'\n Deprecated class for launching pods. please use\n airflow.providers.cncf.kubernetes.utils.pod_launcher.PodLauncher instead\n Creates the launcher.\n\n :param kube_client: kubernetes client\n :param in_cluster: whether we are in cluster\n :param cluster_context: context of the cluster\n :param extract_xcom: whether we should extract xcom\n '
super().__init__()
self._client = (kube_client or get_kube_client(in_cluster=in_cluster, cluster_context=cluster_context))
self._watch = watch.Watch()
self.extract_xcom = extract_xcom<|docstring|>Deprecated class for launching pods. please use
airflow.providers.cncf.kubernetes.utils.pod_launcher.PodLauncher instead
Creates the launcher.
:param kube_client: kubernetes client
:param in_cluster: whether we are in cluster
:param cluster_context: context of the cluster
:param extract_xcom: whether we should extract xcom<|endoftext|> |
dc7f2f60f4028251f55e16285294b7fd2f772e0432002e7665ac378692d95f50 | def run_pod_async(self, pod: V1Pod, **kwargs):
'Runs POD asynchronously'
pod_mutation_hook(pod)
sanitized_pod = self._client.api_client.sanitize_for_serialization(pod)
json_pod = json.dumps(sanitized_pod, indent=2)
self.log.debug('Pod Creation Request: \n%s', json_pod)
try:
resp = self._client.create_namespaced_pod(body=sanitized_pod, namespace=pod.metadata.namespace, **kwargs)
self.log.debug('Pod Creation Response: %s', resp)
except Exception as e:
self.log.exception('Exception when attempting to create Namespaced Pod: %s', json_pod)
raise e
return resp | Runs POD asynchronously | airflow/kubernetes/pod_launcher_deprecated.py | run_pod_async | legau/airflow | 27 | python | def run_pod_async(self, pod: V1Pod, **kwargs):
pod_mutation_hook(pod)
sanitized_pod = self._client.api_client.sanitize_for_serialization(pod)
json_pod = json.dumps(sanitized_pod, indent=2)
self.log.debug('Pod Creation Request: \n%s', json_pod)
try:
resp = self._client.create_namespaced_pod(body=sanitized_pod, namespace=pod.metadata.namespace, **kwargs)
self.log.debug('Pod Creation Response: %s', resp)
except Exception as e:
self.log.exception('Exception when attempting to create Namespaced Pod: %s', json_pod)
raise e
return resp | def run_pod_async(self, pod: V1Pod, **kwargs):
pod_mutation_hook(pod)
sanitized_pod = self._client.api_client.sanitize_for_serialization(pod)
json_pod = json.dumps(sanitized_pod, indent=2)
self.log.debug('Pod Creation Request: \n%s', json_pod)
try:
resp = self._client.create_namespaced_pod(body=sanitized_pod, namespace=pod.metadata.namespace, **kwargs)
self.log.debug('Pod Creation Response: %s', resp)
except Exception as e:
self.log.exception('Exception when attempting to create Namespaced Pod: %s', json_pod)
raise e
return resp<|docstring|>Runs POD asynchronously<|endoftext|> |
48f47bc37088cd587a64d6968639bf23a941d5f3be4d74bdd99d6ab5dbbf0a06 | def delete_pod(self, pod: V1Pod):
'Deletes POD'
try:
self._client.delete_namespaced_pod(pod.metadata.name, pod.metadata.namespace, body=client.V1DeleteOptions())
except ApiException as e:
if (e.status != 404):
raise | Deletes POD | airflow/kubernetes/pod_launcher_deprecated.py | delete_pod | legau/airflow | 27 | python | def delete_pod(self, pod: V1Pod):
try:
self._client.delete_namespaced_pod(pod.metadata.name, pod.metadata.namespace, body=client.V1DeleteOptions())
except ApiException as e:
if (e.status != 404):
raise | def delete_pod(self, pod: V1Pod):
try:
self._client.delete_namespaced_pod(pod.metadata.name, pod.metadata.namespace, body=client.V1DeleteOptions())
except ApiException as e:
if (e.status != 404):
raise<|docstring|>Deletes POD<|endoftext|> |
c45cd2a9882b3418fe094bfff32791d1bddbd7d75101ad4194a108502d7be575 | def start_pod(self, pod: V1Pod, startup_timeout: int=120):
'\n Launches the pod synchronously and waits for completion.\n\n :param pod:\n :param startup_timeout: Timeout for startup of the pod (if pod is pending for too long, fails task)\n :return:\n '
resp = self.run_pod_async(pod)
curr_time = dt.now()
if (resp.status.start_time is None):
while self.pod_not_started(pod):
self.log.warning('Pod not yet started: %s', pod.metadata.name)
delta = (dt.now() - curr_time)
if (delta.total_seconds() >= startup_timeout):
raise AirflowException('Pod took too long to start')
time.sleep(1) | Launches the pod synchronously and waits for completion.
:param pod:
:param startup_timeout: Timeout for startup of the pod (if pod is pending for too long, fails task)
:return: | airflow/kubernetes/pod_launcher_deprecated.py | start_pod | legau/airflow | 27 | python | def start_pod(self, pod: V1Pod, startup_timeout: int=120):
'\n Launches the pod synchronously and waits for completion.\n\n :param pod:\n :param startup_timeout: Timeout for startup of the pod (if pod is pending for too long, fails task)\n :return:\n '
resp = self.run_pod_async(pod)
curr_time = dt.now()
if (resp.status.start_time is None):
while self.pod_not_started(pod):
self.log.warning('Pod not yet started: %s', pod.metadata.name)
delta = (dt.now() - curr_time)
if (delta.total_seconds() >= startup_timeout):
raise AirflowException('Pod took too long to start')
time.sleep(1) | def start_pod(self, pod: V1Pod, startup_timeout: int=120):
'\n Launches the pod synchronously and waits for completion.\n\n :param pod:\n :param startup_timeout: Timeout for startup of the pod (if pod is pending for too long, fails task)\n :return:\n '
resp = self.run_pod_async(pod)
curr_time = dt.now()
if (resp.status.start_time is None):
while self.pod_not_started(pod):
self.log.warning('Pod not yet started: %s', pod.metadata.name)
delta = (dt.now() - curr_time)
if (delta.total_seconds() >= startup_timeout):
raise AirflowException('Pod took too long to start')
time.sleep(1)<|docstring|>Launches the pod synchronously and waits for completion.
:param pod:
:param startup_timeout: Timeout for startup of the pod (if pod is pending for too long, fails task)
:return:<|endoftext|> |
b8a2f21bb83941fcbd12850348b0cdf49a88419b636d8c240b6c2be463e1ad81 | def monitor_pod(self, pod: V1Pod, get_logs: bool) -> Tuple[(State, Optional[str])]:
'\n Monitors a pod and returns the final state\n\n :param pod: pod spec that will be monitored\n :type pod : V1Pod\n :param get_logs: whether to read the logs locally\n :return: Tuple[State, Optional[str]]\n '
if get_logs:
read_logs_since_sec = None
last_log_time = None
while True:
logs = self.read_pod_logs(pod, timestamps=True, since_seconds=read_logs_since_sec)
for line in logs:
(timestamp, message) = self.parse_log_line(line.decode('utf-8'))
last_log_time = pendulum.parse(timestamp)
self.log.info(message)
time.sleep(1)
if (not self.base_container_is_running(pod)):
break
self.log.warning('Pod %s log read interrupted', pod.metadata.name)
if last_log_time:
delta = (pendulum.now() - last_log_time)
read_logs_since_sec = math.ceil(delta.total_seconds())
result = None
if self.extract_xcom:
while self.base_container_is_running(pod):
self.log.info('Container %s has state %s', pod.metadata.name, State.RUNNING)
time.sleep(2)
result = self._extract_xcom(pod)
self.log.info(result)
result = json.loads(result)
while self.pod_is_running(pod):
self.log.info('Pod %s has state %s', pod.metadata.name, State.RUNNING)
time.sleep(2)
return (self._task_status(self.read_pod(pod)), result) | Monitors a pod and returns the final state
:param pod: pod spec that will be monitored
:type pod : V1Pod
:param get_logs: whether to read the logs locally
:return: Tuple[State, Optional[str]] | airflow/kubernetes/pod_launcher_deprecated.py | monitor_pod | legau/airflow | 27 | python | def monitor_pod(self, pod: V1Pod, get_logs: bool) -> Tuple[(State, Optional[str])]:
'\n Monitors a pod and returns the final state\n\n :param pod: pod spec that will be monitored\n :type pod : V1Pod\n :param get_logs: whether to read the logs locally\n :return: Tuple[State, Optional[str]]\n '
if get_logs:
read_logs_since_sec = None
last_log_time = None
while True:
logs = self.read_pod_logs(pod, timestamps=True, since_seconds=read_logs_since_sec)
for line in logs:
(timestamp, message) = self.parse_log_line(line.decode('utf-8'))
last_log_time = pendulum.parse(timestamp)
self.log.info(message)
time.sleep(1)
if (not self.base_container_is_running(pod)):
break
self.log.warning('Pod %s log read interrupted', pod.metadata.name)
if last_log_time:
delta = (pendulum.now() - last_log_time)
read_logs_since_sec = math.ceil(delta.total_seconds())
result = None
if self.extract_xcom:
while self.base_container_is_running(pod):
self.log.info('Container %s has state %s', pod.metadata.name, State.RUNNING)
time.sleep(2)
result = self._extract_xcom(pod)
self.log.info(result)
result = json.loads(result)
while self.pod_is_running(pod):
self.log.info('Pod %s has state %s', pod.metadata.name, State.RUNNING)
time.sleep(2)
return (self._task_status(self.read_pod(pod)), result) | def monitor_pod(self, pod: V1Pod, get_logs: bool) -> Tuple[(State, Optional[str])]:
'\n Monitors a pod and returns the final state\n\n :param pod: pod spec that will be monitored\n :type pod : V1Pod\n :param get_logs: whether to read the logs locally\n :return: Tuple[State, Optional[str]]\n '
if get_logs:
read_logs_since_sec = None
last_log_time = None
while True:
logs = self.read_pod_logs(pod, timestamps=True, since_seconds=read_logs_since_sec)
for line in logs:
(timestamp, message) = self.parse_log_line(line.decode('utf-8'))
last_log_time = pendulum.parse(timestamp)
self.log.info(message)
time.sleep(1)
if (not self.base_container_is_running(pod)):
break
self.log.warning('Pod %s log read interrupted', pod.metadata.name)
if last_log_time:
delta = (pendulum.now() - last_log_time)
read_logs_since_sec = math.ceil(delta.total_seconds())
result = None
if self.extract_xcom:
while self.base_container_is_running(pod):
self.log.info('Container %s has state %s', pod.metadata.name, State.RUNNING)
time.sleep(2)
result = self._extract_xcom(pod)
self.log.info(result)
result = json.loads(result)
while self.pod_is_running(pod):
self.log.info('Pod %s has state %s', pod.metadata.name, State.RUNNING)
time.sleep(2)
return (self._task_status(self.read_pod(pod)), result)<|docstring|>Monitors a pod and returns the final state
:param pod: pod spec that will be monitored
:type pod : V1Pod
:param get_logs: whether to read the logs locally
:return: Tuple[State, Optional[str]]<|endoftext|> |
9372944828f824f16d55538662ddc27be788581feda66a7795c7ab046f88ffc9 | def parse_log_line(self, line: str) -> Tuple[(str, str)]:
'\n Parse K8s log line and returns the final state\n\n :param line: k8s log line\n :type line: str\n :return: timestamp and log message\n :rtype: Tuple[str, str]\n '
split_at = line.find(' ')
if (split_at == (- 1)):
raise Exception(f'Log not in "{{timestamp}} {{log}}" format. Got: {line}')
timestamp = line[:split_at]
message = line[(split_at + 1):].rstrip()
return (timestamp, message) | Parse K8s log line and returns the final state
:param line: k8s log line
:type line: str
:return: timestamp and log message
:rtype: Tuple[str, str] | airflow/kubernetes/pod_launcher_deprecated.py | parse_log_line | legau/airflow | 27 | python | def parse_log_line(self, line: str) -> Tuple[(str, str)]:
'\n Parse K8s log line and returns the final state\n\n :param line: k8s log line\n :type line: str\n :return: timestamp and log message\n :rtype: Tuple[str, str]\n '
split_at = line.find(' ')
if (split_at == (- 1)):
raise Exception(f'Log not in "{{timestamp}} {{log}}" format. Got: {line}')
timestamp = line[:split_at]
message = line[(split_at + 1):].rstrip()
return (timestamp, message) | def parse_log_line(self, line: str) -> Tuple[(str, str)]:
'\n Parse K8s log line and returns the final state\n\n :param line: k8s log line\n :type line: str\n :return: timestamp and log message\n :rtype: Tuple[str, str]\n '
split_at = line.find(' ')
if (split_at == (- 1)):
raise Exception(f'Log not in "{{timestamp}} {{log}}" format. Got: {line}')
timestamp = line[:split_at]
message = line[(split_at + 1):].rstrip()
return (timestamp, message)<|docstring|>Parse K8s log line and returns the final state
:param line: k8s log line
:type line: str
:return: timestamp and log message
:rtype: Tuple[str, str]<|endoftext|> |
855e2dd8223495ab9286b9d9bcf004fcc527fa9411294a4c113878d395130d56 | def pod_not_started(self, pod: V1Pod):
'Tests if pod has not started'
state = self._task_status(self.read_pod(pod))
return (state == State.QUEUED) | Tests if pod has not started | airflow/kubernetes/pod_launcher_deprecated.py | pod_not_started | legau/airflow | 27 | python | def pod_not_started(self, pod: V1Pod):
state = self._task_status(self.read_pod(pod))
return (state == State.QUEUED) | def pod_not_started(self, pod: V1Pod):
state = self._task_status(self.read_pod(pod))
return (state == State.QUEUED)<|docstring|>Tests if pod has not started<|endoftext|> |
ef5af0cf1b0c5c6a1a8ac0753cb995dcddcc5125c8c783d29e873c2430480586 | def pod_is_running(self, pod: V1Pod):
'Tests if pod is running'
state = self._task_status(self.read_pod(pod))
return (state not in (State.SUCCESS, State.FAILED)) | Tests if pod is running | airflow/kubernetes/pod_launcher_deprecated.py | pod_is_running | legau/airflow | 27 | python | def pod_is_running(self, pod: V1Pod):
state = self._task_status(self.read_pod(pod))
return (state not in (State.SUCCESS, State.FAILED)) | def pod_is_running(self, pod: V1Pod):
state = self._task_status(self.read_pod(pod))
return (state not in (State.SUCCESS, State.FAILED))<|docstring|>Tests if pod is running<|endoftext|> |
7926278dfb6997e92eb61d6420141a7e1130ef4aa411f2d8b04e82448de60e4a | def base_container_is_running(self, pod: V1Pod):
'Tests if base container is running'
event = self.read_pod(pod)
status = next(iter(filter((lambda s: (s.name == 'base')), event.status.container_statuses)), None)
if (not status):
return False
return (status.state.running is not None) | Tests if base container is running | airflow/kubernetes/pod_launcher_deprecated.py | base_container_is_running | legau/airflow | 27 | python | def base_container_is_running(self, pod: V1Pod):
event = self.read_pod(pod)
status = next(iter(filter((lambda s: (s.name == 'base')), event.status.container_statuses)), None)
if (not status):
return False
return (status.state.running is not None) | def base_container_is_running(self, pod: V1Pod):
event = self.read_pod(pod)
status = next(iter(filter((lambda s: (s.name == 'base')), event.status.container_statuses)), None)
if (not status):
return False
return (status.state.running is not None)<|docstring|>Tests if base container is running<|endoftext|> |
3227837018ec7af43ac9c2d360755e3c1002e33d35ed1bd7c66286b22853f58b | @tenacity.retry(stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_exponential(), reraise=True)
def read_pod_logs(self, pod: V1Pod, tail_lines: Optional[int]=None, timestamps: bool=False, since_seconds: Optional[int]=None):
'Reads log from the POD'
additional_kwargs = {}
if since_seconds:
additional_kwargs['since_seconds'] = since_seconds
if tail_lines:
additional_kwargs['tail_lines'] = tail_lines
try:
return self._client.read_namespaced_pod_log(name=pod.metadata.name, namespace=pod.metadata.namespace, container='base', follow=True, timestamps=timestamps, _preload_content=False, **additional_kwargs)
except HTTPError as e:
raise AirflowException(f'There was an error reading the kubernetes API: {e}') | Reads log from the POD | airflow/kubernetes/pod_launcher_deprecated.py | read_pod_logs | legau/airflow | 27 | python | @tenacity.retry(stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_exponential(), reraise=True)
def read_pod_logs(self, pod: V1Pod, tail_lines: Optional[int]=None, timestamps: bool=False, since_seconds: Optional[int]=None):
additional_kwargs = {}
if since_seconds:
additional_kwargs['since_seconds'] = since_seconds
if tail_lines:
additional_kwargs['tail_lines'] = tail_lines
try:
return self._client.read_namespaced_pod_log(name=pod.metadata.name, namespace=pod.metadata.namespace, container='base', follow=True, timestamps=timestamps, _preload_content=False, **additional_kwargs)
except HTTPError as e:
raise AirflowException(f'There was an error reading the kubernetes API: {e}') | @tenacity.retry(stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_exponential(), reraise=True)
def read_pod_logs(self, pod: V1Pod, tail_lines: Optional[int]=None, timestamps: bool=False, since_seconds: Optional[int]=None):
additional_kwargs = {}
if since_seconds:
additional_kwargs['since_seconds'] = since_seconds
if tail_lines:
additional_kwargs['tail_lines'] = tail_lines
try:
return self._client.read_namespaced_pod_log(name=pod.metadata.name, namespace=pod.metadata.namespace, container='base', follow=True, timestamps=timestamps, _preload_content=False, **additional_kwargs)
except HTTPError as e:
raise AirflowException(f'There was an error reading the kubernetes API: {e}')<|docstring|>Reads log from the POD<|endoftext|> |
9cb9df5638f5be83093bd8b03bb9af084eeec4d280515dbed22c78e4efd4f7cd | @tenacity.retry(stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_exponential(), reraise=True)
def read_pod_events(self, pod):
'Reads events from the POD'
try:
return self._client.list_namespaced_event(namespace=pod.metadata.namespace, field_selector=f'involvedObject.name={pod.metadata.name}')
except HTTPError as e:
raise AirflowException(f'There was an error reading the kubernetes API: {e}') | Reads events from the POD | airflow/kubernetes/pod_launcher_deprecated.py | read_pod_events | legau/airflow | 27 | python | @tenacity.retry(stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_exponential(), reraise=True)
def read_pod_events(self, pod):
try:
return self._client.list_namespaced_event(namespace=pod.metadata.namespace, field_selector=f'involvedObject.name={pod.metadata.name}')
except HTTPError as e:
raise AirflowException(f'There was an error reading the kubernetes API: {e}') | @tenacity.retry(stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_exponential(), reraise=True)
def read_pod_events(self, pod):
try:
return self._client.list_namespaced_event(namespace=pod.metadata.namespace, field_selector=f'involvedObject.name={pod.metadata.name}')
except HTTPError as e:
raise AirflowException(f'There was an error reading the kubernetes API: {e}')<|docstring|>Reads events from the POD<|endoftext|> |
013575fa3e1863ad1f3b494e903b75e7bd33dceec389413c8a9c0071743b8cbd | @tenacity.retry(stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_exponential(), reraise=True)
def read_pod(self, pod: V1Pod):
'Read POD information'
try:
return self._client.read_namespaced_pod(pod.metadata.name, pod.metadata.namespace)
except HTTPError as e:
raise AirflowException(f'There was an error reading the kubernetes API: {e}') | Read POD information | airflow/kubernetes/pod_launcher_deprecated.py | read_pod | legau/airflow | 27 | python | @tenacity.retry(stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_exponential(), reraise=True)
def read_pod(self, pod: V1Pod):
try:
return self._client.read_namespaced_pod(pod.metadata.name, pod.metadata.namespace)
except HTTPError as e:
raise AirflowException(f'There was an error reading the kubernetes API: {e}') | @tenacity.retry(stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_exponential(), reraise=True)
def read_pod(self, pod: V1Pod):
try:
return self._client.read_namespaced_pod(pod.metadata.name, pod.metadata.namespace)
except HTTPError as e:
raise AirflowException(f'There was an error reading the kubernetes API: {e}')<|docstring|>Read POD information<|endoftext|> |
571aa2ebf1efd0a3816871c7f2c6eea81bf7d36e9a398b2a51bd857d037e88aa | def process_status(self, job_id, status):
'Process status information for the JOB'
status = status.lower()
if (status == PodStatus.PENDING):
return State.QUEUED
elif (status == PodStatus.FAILED):
self.log.error('Event with job id %s Failed', job_id)
return State.FAILED
elif (status == PodStatus.SUCCEEDED):
self.log.info('Event with job id %s Succeeded', job_id)
return State.SUCCESS
elif (status == PodStatus.RUNNING):
return State.RUNNING
else:
self.log.error('Event: Invalid state %s on job %s', status, job_id)
return State.FAILED | Process status information for the JOB | airflow/kubernetes/pod_launcher_deprecated.py | process_status | legau/airflow | 27 | python | def process_status(self, job_id, status):
status = status.lower()
if (status == PodStatus.PENDING):
return State.QUEUED
elif (status == PodStatus.FAILED):
self.log.error('Event with job id %s Failed', job_id)
return State.FAILED
elif (status == PodStatus.SUCCEEDED):
self.log.info('Event with job id %s Succeeded', job_id)
return State.SUCCESS
elif (status == PodStatus.RUNNING):
return State.RUNNING
else:
self.log.error('Event: Invalid state %s on job %s', status, job_id)
return State.FAILED | def process_status(self, job_id, status):
status = status.lower()
if (status == PodStatus.PENDING):
return State.QUEUED
elif (status == PodStatus.FAILED):
self.log.error('Event with job id %s Failed', job_id)
return State.FAILED
elif (status == PodStatus.SUCCEEDED):
self.log.info('Event with job id %s Succeeded', job_id)
return State.SUCCESS
elif (status == PodStatus.RUNNING):
return State.RUNNING
else:
self.log.error('Event: Invalid state %s on job %s', status, job_id)
return State.FAILED<|docstring|>Process status information for the JOB<|endoftext|> |
e08cefe02a3e3ade0787dad64c7ffcbfda2f6183454997606fa3a945aa038326 | @staticmethod
def status(s):
'Prints things in bold.'
print('\x1b[1m{0}\x1b[0m'.format(s)) | Prints things in bold. | setup.py | status | zed/leap-second-client | 4 | python | @staticmethod
def status(s):
print('\x1b[1m{0}\x1b[0m'.format(s)) | @staticmethod
def status(s):
print('\x1b[1m{0}\x1b[0m'.format(s))<|docstring|>Prints things in bold.<|endoftext|> |
0c8ae1acc7cf5292540756f023922e9701446a0641aa9e78475e8b9c83ad2890 | def show(name, resource_group):
'\n Get the details of a domain.\n\n Required Parameters:\n - name -- Name of the domain.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n '
return _call_az('az eventgrid domain show', locals()) | Get the details of a domain.
Required Parameters:
- name -- Name of the domain.
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` | pyaz/eventgrid/domain/__init__.py | show | py-az-cli/py-az-cli | 0 | python | def show(name, resource_group):
'\n Get the details of a domain.\n\n Required Parameters:\n - name -- Name of the domain.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n '
return _call_az('az eventgrid domain show', locals()) | def show(name, resource_group):
'\n Get the details of a domain.\n\n Required Parameters:\n - name -- Name of the domain.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n '
return _call_az('az eventgrid domain show', locals())<|docstring|>Get the details of a domain.
Required Parameters:
- name -- Name of the domain.
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`<|endoftext|> |
eff4ef6d9029ef5a265392612ed3300d522debcdb8084c02d88407cb439b664e | def list(odata_query=None, resource_group=None):
'\n List available domains.\n\n Optional Parameters:\n - odata_query -- The OData query used for filtering the list results. Filtering is currently allowed on the Name property only. The supported operations include: CONTAINS, eq (for equal), ne (for not equal), AND, OR and NOT.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n '
return _call_az('az eventgrid domain list', locals()) | List available domains.
Optional Parameters:
- odata_query -- The OData query used for filtering the list results. Filtering is currently allowed on the Name property only. The supported operations include: CONTAINS, eq (for equal), ne (for not equal), AND, OR and NOT.
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` | pyaz/eventgrid/domain/__init__.py | list | py-az-cli/py-az-cli | 0 | python | def list(odata_query=None, resource_group=None):
'\n List available domains.\n\n Optional Parameters:\n - odata_query -- The OData query used for filtering the list results. Filtering is currently allowed on the Name property only. The supported operations include: CONTAINS, eq (for equal), ne (for not equal), AND, OR and NOT.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n '
return _call_az('az eventgrid domain list', locals()) | def list(odata_query=None, resource_group=None):
'\n List available domains.\n\n Optional Parameters:\n - odata_query -- The OData query used for filtering the list results. Filtering is currently allowed on the Name property only. The supported operations include: CONTAINS, eq (for equal), ne (for not equal), AND, OR and NOT.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n '
return _call_az('az eventgrid domain list', locals())<|docstring|>List available domains.
Optional Parameters:
- odata_query -- The OData query used for filtering the list results. Filtering is currently allowed on the Name property only. The supported operations include: CONTAINS, eq (for equal), ne (for not equal), AND, OR and NOT.
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`<|endoftext|> |
8ce16ff17b9c28f7d9bf5c10d17539b442278c7a6ff836424622bff163de0c0a | def create(name, resource_group, identity=None, inbound_ip_rules=None, input_mapping_default_values=None, input_mapping_fields=None, input_schema=None, location=None, public_network_access=None, sku=None, tags=None):
"\n Create a domain.\n\n Required Parameters:\n - name -- Name of the domain.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n\n Optional Parameters:\n - identity -- The managed identity type for the resource.\n - inbound_ip_rules -- None\n - input_mapping_default_values -- When input-schema is specified as customeventschema, this parameter can be used to specify input mappings based on default values. You can use this parameter when your custom schema does not include a field that corresponds to one of the three fields supported by this parameter. Specify space separated mappings in 'key=value' format. Allowed key names are 'subject', 'eventtype', 'dataversion'. The corresponding value names should specify the default values to be used for the mapping and they will be used only when the published event doesn't have a valid mapping for a particular field.\n - input_mapping_fields -- When input-schema is specified as customeventschema, this parameter is used to specify input mappings based on field names. Specify space separated mappings in 'key=value' format. Allowed key names are 'id', 'topic', 'eventtime', 'subject', 'eventtype', 'dataversion'. The corresponding value names should specify the names of the fields in the custom input schema. If a mapping for either 'id' or 'eventtime' is not provided, Event Grid will auto-generate a default value for these two fields.\n - input_schema -- Schema in which incoming events will be published to this topic/domain. If you specify customeventschema as the value for this parameter, you must also provide values for at least one of --input_mapping_default_values / --input_mapping_fields.\n - location -- Location. Values from: `az account list-locations`. You can configure the default location using `az configure --defaults location=<location>`.\n - public_network_access -- This determines if traffic is allowed over public network. By default it is enabled. You can further restrict to specific IPs by configuring.\n - sku -- The Sku name of the resource.\n - tags -- space-separated tags: key[=value] [key[=value] ...]. Use '' to clear existing tags.\n "
return _call_az('az eventgrid domain create', locals()) | Create a domain.
Required Parameters:
- name -- Name of the domain.
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`
Optional Parameters:
- identity -- The managed identity type for the resource.
- inbound_ip_rules -- None
- input_mapping_default_values -- When input-schema is specified as customeventschema, this parameter can be used to specify input mappings based on default values. You can use this parameter when your custom schema does not include a field that corresponds to one of the three fields supported by this parameter. Specify space separated mappings in 'key=value' format. Allowed key names are 'subject', 'eventtype', 'dataversion'. The corresponding value names should specify the default values to be used for the mapping and they will be used only when the published event doesn't have a valid mapping for a particular field.
- input_mapping_fields -- When input-schema is specified as customeventschema, this parameter is used to specify input mappings based on field names. Specify space separated mappings in 'key=value' format. Allowed key names are 'id', 'topic', 'eventtime', 'subject', 'eventtype', 'dataversion'. The corresponding value names should specify the names of the fields in the custom input schema. If a mapping for either 'id' or 'eventtime' is not provided, Event Grid will auto-generate a default value for these two fields.
- input_schema -- Schema in which incoming events will be published to this topic/domain. If you specify customeventschema as the value for this parameter, you must also provide values for at least one of --input_mapping_default_values / --input_mapping_fields.
- location -- Location. Values from: `az account list-locations`. You can configure the default location using `az configure --defaults location=<location>`.
- public_network_access -- This determines if traffic is allowed over public network. By default it is enabled. You can further restrict to specific IPs by configuring.
- sku -- The Sku name of the resource.
- tags -- space-separated tags: key[=value] [key[=value] ...]. Use '' to clear existing tags. | pyaz/eventgrid/domain/__init__.py | create | py-az-cli/py-az-cli | 0 | python | def create(name, resource_group, identity=None, inbound_ip_rules=None, input_mapping_default_values=None, input_mapping_fields=None, input_schema=None, location=None, public_network_access=None, sku=None, tags=None):
"\n Create a domain.\n\n Required Parameters:\n - name -- Name of the domain.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n\n Optional Parameters:\n - identity -- The managed identity type for the resource.\n - inbound_ip_rules -- None\n - input_mapping_default_values -- When input-schema is specified as customeventschema, this parameter can be used to specify input mappings based on default values. You can use this parameter when your custom schema does not include a field that corresponds to one of the three fields supported by this parameter. Specify space separated mappings in 'key=value' format. Allowed key names are 'subject', 'eventtype', 'dataversion'. The corresponding value names should specify the default values to be used for the mapping and they will be used only when the published event doesn't have a valid mapping for a particular field.\n - input_mapping_fields -- When input-schema is specified as customeventschema, this parameter is used to specify input mappings based on field names. Specify space separated mappings in 'key=value' format. Allowed key names are 'id', 'topic', 'eventtime', 'subject', 'eventtype', 'dataversion'. The corresponding value names should specify the names of the fields in the custom input schema. If a mapping for either 'id' or 'eventtime' is not provided, Event Grid will auto-generate a default value for these two fields.\n - input_schema -- Schema in which incoming events will be published to this topic/domain. If you specify customeventschema as the value for this parameter, you must also provide values for at least one of --input_mapping_default_values / --input_mapping_fields.\n - location -- Location. Values from: `az account list-locations`. You can configure the default location using `az configure --defaults location=<location>`.\n - public_network_access -- This determines if traffic is allowed over public network. By default it is enabled. You can further restrict to specific IPs by configuring.\n - sku -- The Sku name of the resource.\n - tags -- space-separated tags: key[=value] [key[=value] ...]. Use to clear existing tags.\n "
return _call_az('az eventgrid domain create', locals()) | def create(name, resource_group, identity=None, inbound_ip_rules=None, input_mapping_default_values=None, input_mapping_fields=None, input_schema=None, location=None, public_network_access=None, sku=None, tags=None):
"\n Create a domain.\n\n Required Parameters:\n - name -- Name of the domain.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n\n Optional Parameters:\n - identity -- The managed identity type for the resource.\n - inbound_ip_rules -- None\n - input_mapping_default_values -- When input-schema is specified as customeventschema, this parameter can be used to specify input mappings based on default values. You can use this parameter when your custom schema does not include a field that corresponds to one of the three fields supported by this parameter. Specify space separated mappings in 'key=value' format. Allowed key names are 'subject', 'eventtype', 'dataversion'. The corresponding value names should specify the default values to be used for the mapping and they will be used only when the published event doesn't have a valid mapping for a particular field.\n - input_mapping_fields -- When input-schema is specified as customeventschema, this parameter is used to specify input mappings based on field names. Specify space separated mappings in 'key=value' format. Allowed key names are 'id', 'topic', 'eventtime', 'subject', 'eventtype', 'dataversion'. The corresponding value names should specify the names of the fields in the custom input schema. If a mapping for either 'id' or 'eventtime' is not provided, Event Grid will auto-generate a default value for these two fields.\n - input_schema -- Schema in which incoming events will be published to this topic/domain. If you specify customeventschema as the value for this parameter, you must also provide values for at least one of --input_mapping_default_values / --input_mapping_fields.\n - location -- Location. Values from: `az account list-locations`. You can configure the default location using `az configure --defaults location=<location>`.\n - public_network_access -- This determines if traffic is allowed over public network. By default it is enabled. You can further restrict to specific IPs by configuring.\n - sku -- The Sku name of the resource.\n - tags -- space-separated tags: key[=value] [key[=value] ...]. Use to clear existing tags.\n "
return _call_az('az eventgrid domain create', locals())<|docstring|>Create a domain.
Required Parameters:
- name -- Name of the domain.
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`
Optional Parameters:
- identity -- The managed identity type for the resource.
- inbound_ip_rules -- None
- input_mapping_default_values -- When input-schema is specified as customeventschema, this parameter can be used to specify input mappings based on default values. You can use this parameter when your custom schema does not include a field that corresponds to one of the three fields supported by this parameter. Specify space separated mappings in 'key=value' format. Allowed key names are 'subject', 'eventtype', 'dataversion'. The corresponding value names should specify the default values to be used for the mapping and they will be used only when the published event doesn't have a valid mapping for a particular field.
- input_mapping_fields -- When input-schema is specified as customeventschema, this parameter is used to specify input mappings based on field names. Specify space separated mappings in 'key=value' format. Allowed key names are 'id', 'topic', 'eventtime', 'subject', 'eventtype', 'dataversion'. The corresponding value names should specify the names of the fields in the custom input schema. If a mapping for either 'id' or 'eventtime' is not provided, Event Grid will auto-generate a default value for these two fields.
- input_schema -- Schema in which incoming events will be published to this topic/domain. If you specify customeventschema as the value for this parameter, you must also provide values for at least one of --input_mapping_default_values / --input_mapping_fields.
- location -- Location. Values from: `az account list-locations`. You can configure the default location using `az configure --defaults location=<location>`.
- public_network_access -- This determines if traffic is allowed over public network. By default it is enabled. You can further restrict to specific IPs by configuring.
- sku -- The Sku name of the resource.
- tags -- space-separated tags: key[=value] [key[=value] ...]. Use '' to clear existing tags.<|endoftext|> |
71b26323a2d3bf3426aa0e559a6f5242ba6b09829715a4c8cb945647a49538a2 | def delete(name, resource_group):
'\n Delete a domain.\n\n Required Parameters:\n - name -- Name of the domain.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n '
return _call_az('az eventgrid domain delete', locals()) | Delete a domain.
Required Parameters:
- name -- Name of the domain.
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` | pyaz/eventgrid/domain/__init__.py | delete | py-az-cli/py-az-cli | 0 | python | def delete(name, resource_group):
'\n Delete a domain.\n\n Required Parameters:\n - name -- Name of the domain.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n '
return _call_az('az eventgrid domain delete', locals()) | def delete(name, resource_group):
'\n Delete a domain.\n\n Required Parameters:\n - name -- Name of the domain.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n '
return _call_az('az eventgrid domain delete', locals())<|docstring|>Delete a domain.
Required Parameters:
- name -- Name of the domain.
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`<|endoftext|> |
eb7a945e984b26cc8dbc57e1d8d48fe9a90cc134088464f74176d1fed9567574 | def update(name, resource_group, identity=None, inbound_ip_rules=None, public_network_access=None, sku=None, tags=None):
"\n Update a domain.\n\n Required Parameters:\n - name -- Name of the domain.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n\n Optional Parameters:\n - identity -- The managed identity type for the resource.\n - inbound_ip_rules -- None\n - public_network_access -- This determines if traffic is allowed over public network. By default it is enabled. You can further restrict to specific IPs by configuring.\n - sku -- The Sku name of the resource.\n - tags -- space-separated tags: key[=value] [key[=value] ...]. Use '' to clear existing tags.\n "
return _call_az('az eventgrid domain update', locals()) | Update a domain.
Required Parameters:
- name -- Name of the domain.
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`
Optional Parameters:
- identity -- The managed identity type for the resource.
- inbound_ip_rules -- None
- public_network_access -- This determines if traffic is allowed over public network. By default it is enabled. You can further restrict to specific IPs by configuring.
- sku -- The Sku name of the resource.
- tags -- space-separated tags: key[=value] [key[=value] ...]. Use '' to clear existing tags. | pyaz/eventgrid/domain/__init__.py | update | py-az-cli/py-az-cli | 0 | python | def update(name, resource_group, identity=None, inbound_ip_rules=None, public_network_access=None, sku=None, tags=None):
"\n Update a domain.\n\n Required Parameters:\n - name -- Name of the domain.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n\n Optional Parameters:\n - identity -- The managed identity type for the resource.\n - inbound_ip_rules -- None\n - public_network_access -- This determines if traffic is allowed over public network. By default it is enabled. You can further restrict to specific IPs by configuring.\n - sku -- The Sku name of the resource.\n - tags -- space-separated tags: key[=value] [key[=value] ...]. Use to clear existing tags.\n "
return _call_az('az eventgrid domain update', locals()) | def update(name, resource_group, identity=None, inbound_ip_rules=None, public_network_access=None, sku=None, tags=None):
"\n Update a domain.\n\n Required Parameters:\n - name -- Name of the domain.\n - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`\n\n Optional Parameters:\n - identity -- The managed identity type for the resource.\n - inbound_ip_rules -- None\n - public_network_access -- This determines if traffic is allowed over public network. By default it is enabled. You can further restrict to specific IPs by configuring.\n - sku -- The Sku name of the resource.\n - tags -- space-separated tags: key[=value] [key[=value] ...]. Use to clear existing tags.\n "
return _call_az('az eventgrid domain update', locals())<|docstring|>Update a domain.
Required Parameters:
- name -- Name of the domain.
- resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>`
Optional Parameters:
- identity -- The managed identity type for the resource.
- inbound_ip_rules -- None
- public_network_access -- This determines if traffic is allowed over public network. By default it is enabled. You can further restrict to specific IPs by configuring.
- sku -- The Sku name of the resource.
- tags -- space-separated tags: key[=value] [key[=value] ...]. Use '' to clear existing tags.<|endoftext|> |
644f49043831488e9c999677c83d89668559e0db71a6a231056326c0bdfee89f | def std_mad(x):
'Robust estimation of the standard deviation, based on the Corrected Median\n Absolute Deviation (MAD) of x.\n This computes the MAD of x, and applies the Gaussian distribution\n correction, making it a consistent estimator of the standard-deviation\n (when the sample looks Gaussian with outliers).\n\n Parameters\n ----------\n x : `np.ndarray`\n Input vector\n\n Returns\n -------\n output : `float`\n A robust estimation of the standard deviation\n '
from scipy.stats import norm
correction = (1 / norm.ppf((3 / 4)))
return (correction * np.median(np.abs((x - np.median(x))))) | Robust estimation of the standard deviation, based on the Corrected Median
Absolute Deviation (MAD) of x.
This computes the MAD of x, and applies the Gaussian distribution
correction, making it a consistent estimator of the standard-deviation
(when the sample looks Gaussian with outliers).
Parameters
----------
x : `np.ndarray`
Input vector
Returns
-------
output : `float`
A robust estimation of the standard deviation | tick/robust/robust.py | std_mad | andro2157/tick | 411 | python | def std_mad(x):
'Robust estimation of the standard deviation, based on the Corrected Median\n Absolute Deviation (MAD) of x.\n This computes the MAD of x, and applies the Gaussian distribution\n correction, making it a consistent estimator of the standard-deviation\n (when the sample looks Gaussian with outliers).\n\n Parameters\n ----------\n x : `np.ndarray`\n Input vector\n\n Returns\n -------\n output : `float`\n A robust estimation of the standard deviation\n '
from scipy.stats import norm
correction = (1 / norm.ppf((3 / 4)))
return (correction * np.median(np.abs((x - np.median(x))))) | def std_mad(x):
'Robust estimation of the standard deviation, based on the Corrected Median\n Absolute Deviation (MAD) of x.\n This computes the MAD of x, and applies the Gaussian distribution\n correction, making it a consistent estimator of the standard-deviation\n (when the sample looks Gaussian with outliers).\n\n Parameters\n ----------\n x : `np.ndarray`\n Input vector\n\n Returns\n -------\n output : `float`\n A robust estimation of the standard deviation\n '
from scipy.stats import norm
correction = (1 / norm.ppf((3 / 4)))
return (correction * np.median(np.abs((x - np.median(x)))))<|docstring|>Robust estimation of the standard deviation, based on the Corrected Median
Absolute Deviation (MAD) of x.
This computes the MAD of x, and applies the Gaussian distribution
correction, making it a consistent estimator of the standard-deviation
(when the sample looks Gaussian with outliers).
Parameters
----------
x : `np.ndarray`
Input vector
Returns
-------
output : `float`
A robust estimation of the standard deviation<|endoftext|> |
ec6611a6ac76322f974c41464022af1ff2a3cc42bdf4ce7e9e6eada6a5cba3df | def std_iqr(x):
'Robust estimation of the standard deviation, based on the inter-quartile\n (IQR) distance of x.\n This computes the IQR of x, and applies the Gaussian distribution\n correction, making it a consistent estimator of the standard-deviation\n (when the sample looks Gaussian with outliers).\n\n Parameters\n ----------\n x : `np.ndarray`\n Input vector\n\n Returns\n -------\n output : `float`\n A robust estimation of the standard deviation\n '
from scipy.stats import iqr
from scipy.special import erfinv
correction = ((2 ** 0.5) * erfinv(0.5))
return (correction * iqr(x)) | Robust estimation of the standard deviation, based on the inter-quartile
(IQR) distance of x.
This computes the IQR of x, and applies the Gaussian distribution
correction, making it a consistent estimator of the standard-deviation
(when the sample looks Gaussian with outliers).
Parameters
----------
x : `np.ndarray`
Input vector
Returns
-------
output : `float`
A robust estimation of the standard deviation | tick/robust/robust.py | std_iqr | andro2157/tick | 411 | python | def std_iqr(x):
'Robust estimation of the standard deviation, based on the inter-quartile\n (IQR) distance of x.\n This computes the IQR of x, and applies the Gaussian distribution\n correction, making it a consistent estimator of the standard-deviation\n (when the sample looks Gaussian with outliers).\n\n Parameters\n ----------\n x : `np.ndarray`\n Input vector\n\n Returns\n -------\n output : `float`\n A robust estimation of the standard deviation\n '
from scipy.stats import iqr
from scipy.special import erfinv
correction = ((2 ** 0.5) * erfinv(0.5))
return (correction * iqr(x)) | def std_iqr(x):
'Robust estimation of the standard deviation, based on the inter-quartile\n (IQR) distance of x.\n This computes the IQR of x, and applies the Gaussian distribution\n correction, making it a consistent estimator of the standard-deviation\n (when the sample looks Gaussian with outliers).\n\n Parameters\n ----------\n x : `np.ndarray`\n Input vector\n\n Returns\n -------\n output : `float`\n A robust estimation of the standard deviation\n '
from scipy.stats import iqr
from scipy.special import erfinv
correction = ((2 ** 0.5) * erfinv(0.5))
return (correction * iqr(x))<|docstring|>Robust estimation of the standard deviation, based on the inter-quartile
(IQR) distance of x.
This computes the IQR of x, and applies the Gaussian distribution
correction, making it a consistent estimator of the standard-deviation
(when the sample looks Gaussian with outliers).
Parameters
----------
x : `np.ndarray`
Input vector
Returns
-------
output : `float`
A robust estimation of the standard deviation<|endoftext|> |
36cd95d5616dbb686603ad26e4c1c002257fd1f0de16cd7ada01dce0d140a9a8 | def __init__(self, arr=None, already_heap=False):
'\n\t\tCreates an empty heap when passed with no parameters.\n\t\tInitializes self.arr when passed with a list that is already a heap.\n\t\tCalls build_heap when given list is not a heap.\n\t\t'
if (not arr):
self.arr = []
elif already_heap:
self.arr = arr
else:
self.build_heap(arr) | Creates an empty heap when passed with no parameters.
Initializes self.arr when passed with a list that is already a heap.
Calls build_heap when given list is not a heap. | BinaryHeap.py | __init__ | arunkumaraqm/Prims-Algorithm-Using-Fibonacci-Heap | 1 | python | def __init__(self, arr=None, already_heap=False):
'\n\t\tCreates an empty heap when passed with no parameters.\n\t\tInitializes self.arr when passed with a list that is already a heap.\n\t\tCalls build_heap when given list is not a heap.\n\t\t'
if (not arr):
self.arr = []
elif already_heap:
self.arr = arr
else:
self.build_heap(arr) | def __init__(self, arr=None, already_heap=False):
'\n\t\tCreates an empty heap when passed with no parameters.\n\t\tInitializes self.arr when passed with a list that is already a heap.\n\t\tCalls build_heap when given list is not a heap.\n\t\t'
if (not arr):
self.arr = []
elif already_heap:
self.arr = arr
else:
self.build_heap(arr)<|docstring|>Creates an empty heap when passed with no parameters.
Initializes self.arr when passed with a list that is already a heap.
Calls build_heap when given list is not a heap.<|endoftext|> |
f189c3fc3dd56faa8e07139f813640ed81d3d7fcbc8e7480e415b7edf7c79aea | def find_min_child(self, ind):
'\n\t\tReturns the index of the smaller child of a node.\n\t\tReturns -1 if node is a leaf.\n\t\t'
left = ((ind * 2) + 1)
right = (left + 1)
if (left >= len(self)):
return (- 1)
if (right >= len(self)):
return left
if (self.arr[left] < self.arr[right]):
return left
else:
return right | Returns the index of the smaller child of a node.
Returns -1 if node is a leaf. | BinaryHeap.py | find_min_child | arunkumaraqm/Prims-Algorithm-Using-Fibonacci-Heap | 1 | python | def find_min_child(self, ind):
'\n\t\tReturns the index of the smaller child of a node.\n\t\tReturns -1 if node is a leaf.\n\t\t'
left = ((ind * 2) + 1)
right = (left + 1)
if (left >= len(self)):
return (- 1)
if (right >= len(self)):
return left
if (self.arr[left] < self.arr[right]):
return left
else:
return right | def find_min_child(self, ind):
'\n\t\tReturns the index of the smaller child of a node.\n\t\tReturns -1 if node is a leaf.\n\t\t'
left = ((ind * 2) + 1)
right = (left + 1)
if (left >= len(self)):
return (- 1)
if (right >= len(self)):
return left
if (self.arr[left] < self.arr[right]):
return left
else:
return right<|docstring|>Returns the index of the smaller child of a node.
Returns -1 if node is a leaf.<|endoftext|> |
be646da3ab9de835530f2acb63442bb423afc1f230cfee72bc269d4bfe29478f | def sift_down(self, ind):
'\n\t\tSwaps node with the smaller child repeatedly \n\t\tuntil the node is smaller than both its children.\n\t\t'
while True:
desired_child = self.find_min_child(ind)
if (desired_child == (- 1)):
break
if (self.arr[ind] > self.arr[desired_child]):
self.swap(ind, desired_child)
ind = desired_child
else:
break | Swaps node with the smaller child repeatedly
until the node is smaller than both its children. | BinaryHeap.py | sift_down | arunkumaraqm/Prims-Algorithm-Using-Fibonacci-Heap | 1 | python | def sift_down(self, ind):
'\n\t\tSwaps node with the smaller child repeatedly \n\t\tuntil the node is smaller than both its children.\n\t\t'
while True:
desired_child = self.find_min_child(ind)
if (desired_child == (- 1)):
break
if (self.arr[ind] > self.arr[desired_child]):
self.swap(ind, desired_child)
ind = desired_child
else:
break | def sift_down(self, ind):
'\n\t\tSwaps node with the smaller child repeatedly \n\t\tuntil the node is smaller than both its children.\n\t\t'
while True:
desired_child = self.find_min_child(ind)
if (desired_child == (- 1)):
break
if (self.arr[ind] > self.arr[desired_child]):
self.swap(ind, desired_child)
ind = desired_child
else:
break<|docstring|>Swaps node with the smaller child repeatedly
until the node is smaller than both its children.<|endoftext|> |
76c6d27f3618a4f4839c545455aec33ae81b67d9d6304c07bddaf41b6011abe4 | def sift_up(self, ind):
'\n\t\tSwaps node with its parent repeatedly\n\t\tuntil the node is larger than its parent.\n\t\t'
while True:
if (ind == 0):
break
parent = ((ind - 1) // 2)
if (self.arr[ind] < self.arr[parent]):
self.swap(ind, parent)
ind = parent
else:
break | Swaps node with its parent repeatedly
until the node is larger than its parent. | BinaryHeap.py | sift_up | arunkumaraqm/Prims-Algorithm-Using-Fibonacci-Heap | 1 | python | def sift_up(self, ind):
'\n\t\tSwaps node with its parent repeatedly\n\t\tuntil the node is larger than its parent.\n\t\t'
while True:
if (ind == 0):
break
parent = ((ind - 1) // 2)
if (self.arr[ind] < self.arr[parent]):
self.swap(ind, parent)
ind = parent
else:
break | def sift_up(self, ind):
'\n\t\tSwaps node with its parent repeatedly\n\t\tuntil the node is larger than its parent.\n\t\t'
while True:
if (ind == 0):
break
parent = ((ind - 1) // 2)
if (self.arr[ind] < self.arr[parent]):
self.swap(ind, parent)
ind = parent
else:
break<|docstring|>Swaps node with its parent repeatedly
until the node is larger than its parent.<|endoftext|> |
060aa5765a0343d7388c70981622d9c5305ef031d579c9741dc495bde75c2649 | def extract_min(self):
'Removes and returns the minimum key from heap.'
if (len(self) == 0):
return None
minn = self.arr[0]
self.arr[0] = self.arr[(- 1)]
del self.arr[(- 1)]
self.sift_down(0)
return minn | Removes and returns the minimum key from heap. | BinaryHeap.py | extract_min | arunkumaraqm/Prims-Algorithm-Using-Fibonacci-Heap | 1 | python | def extract_min(self):
if (len(self) == 0):
return None
minn = self.arr[0]
self.arr[0] = self.arr[(- 1)]
del self.arr[(- 1)]
self.sift_down(0)
return minn | def extract_min(self):
if (len(self) == 0):
return None
minn = self.arr[0]
self.arr[0] = self.arr[(- 1)]
del self.arr[(- 1)]
self.sift_down(0)
return minn<|docstring|>Removes and returns the minimum key from heap.<|endoftext|> |
fca8935c9900a58de4c967836e30ee1af77821058e9ac36412f6bb4fa1340949 | def merge(self, other):
'Builds a new MinHeap after combining the two existing ones.'
return MinHeap((self.arr + other.arr)) | Builds a new MinHeap after combining the two existing ones. | BinaryHeap.py | merge | arunkumaraqm/Prims-Algorithm-Using-Fibonacci-Heap | 1 | python | def merge(self, other):
return MinHeap((self.arr + other.arr)) | def merge(self, other):
return MinHeap((self.arr + other.arr))<|docstring|>Builds a new MinHeap after combining the two existing ones.<|endoftext|> |
5997cc5ef2e4ac79b8a1c836894bf71c5c36365171882456fb4bcb2b2885885f | @staticmethod
def vstack(matrices, require_equal_columnlabels=True):
'Returns a new matrix equal to the row-wise\n concatenation of the given matrices'
assert (len(matrices) > 0)
if (len(matrices) == 1):
return matrices[0].copy()
for matrix in matrices:
assert isinstance(matrix, Matrix)
assert (matrix.columnlabels.shape == matrices[0].columnlabels.shape)
assert (matrix.data.shape[1] == matrices[0].data.shape[1])
if require_equal_columnlabels:
assert np.array_equal(matrix.columnlabels, matrices[0].columnlabels)
data = np.vstack([mtx.data for mtx in matrices])
rowlabels = np.hstack([mtx.rowlabels for mtx in matrices])
return Matrix(data, rowlabels, matrices[0].columnlabels.copy()) | Returns a new matrix equal to the row-wise
concatenation of the given matrices | server/analysis/matrix.py | vstack | newopscn/ottertune | 0 | python | @staticmethod
def vstack(matrices, require_equal_columnlabels=True):
'Returns a new matrix equal to the row-wise\n concatenation of the given matrices'
assert (len(matrices) > 0)
if (len(matrices) == 1):
return matrices[0].copy()
for matrix in matrices:
assert isinstance(matrix, Matrix)
assert (matrix.columnlabels.shape == matrices[0].columnlabels.shape)
assert (matrix.data.shape[1] == matrices[0].data.shape[1])
if require_equal_columnlabels:
assert np.array_equal(matrix.columnlabels, matrices[0].columnlabels)
data = np.vstack([mtx.data for mtx in matrices])
rowlabels = np.hstack([mtx.rowlabels for mtx in matrices])
return Matrix(data, rowlabels, matrices[0].columnlabels.copy()) | @staticmethod
def vstack(matrices, require_equal_columnlabels=True):
'Returns a new matrix equal to the row-wise\n concatenation of the given matrices'
assert (len(matrices) > 0)
if (len(matrices) == 1):
return matrices[0].copy()
for matrix in matrices:
assert isinstance(matrix, Matrix)
assert (matrix.columnlabels.shape == matrices[0].columnlabels.shape)
assert (matrix.data.shape[1] == matrices[0].data.shape[1])
if require_equal_columnlabels:
assert np.array_equal(matrix.columnlabels, matrices[0].columnlabels)
data = np.vstack([mtx.data for mtx in matrices])
rowlabels = np.hstack([mtx.rowlabels for mtx in matrices])
return Matrix(data, rowlabels, matrices[0].columnlabels.copy())<|docstring|>Returns a new matrix equal to the row-wise
concatenation of the given matrices<|endoftext|> |
06a5f49a0580ad3507e8daf74c92e9ee66c563dba7a39b1f371008574f5aeb89 | @staticmethod
def hstack(matrices, require_equal_rowlabels=True):
'Returns a new matrix equal to the column-wise\n concatenation of the given matrices'
assert (len(matrices) > 0)
if (len(matrices) == 1):
return matrices[0].copy()
for matrix in matrices:
assert isinstance(matrix, Matrix)
assert (matrix.data.shape[0] == matrices[0].data.shape[0])
assert (matrix.rowlabels.shape == matrices[0].rowlabels.shape)
if require_equal_rowlabels:
assert np.array_equal(matrix.rowlabels, matrices[0].rowlabels)
data = np.hstack([mtx.data for mtx in matrices])
columnlabels = np.hstack([mtx.columnlabels for mtx in matrices])
return Matrix(data, matrices[0].rowlabels.copy(), columnlabels) | Returns a new matrix equal to the column-wise
concatenation of the given matrices | server/analysis/matrix.py | hstack | newopscn/ottertune | 0 | python | @staticmethod
def hstack(matrices, require_equal_rowlabels=True):
'Returns a new matrix equal to the column-wise\n concatenation of the given matrices'
assert (len(matrices) > 0)
if (len(matrices) == 1):
return matrices[0].copy()
for matrix in matrices:
assert isinstance(matrix, Matrix)
assert (matrix.data.shape[0] == matrices[0].data.shape[0])
assert (matrix.rowlabels.shape == matrices[0].rowlabels.shape)
if require_equal_rowlabels:
assert np.array_equal(matrix.rowlabels, matrices[0].rowlabels)
data = np.hstack([mtx.data for mtx in matrices])
columnlabels = np.hstack([mtx.columnlabels for mtx in matrices])
return Matrix(data, matrices[0].rowlabels.copy(), columnlabels) | @staticmethod
def hstack(matrices, require_equal_rowlabels=True):
'Returns a new matrix equal to the column-wise\n concatenation of the given matrices'
assert (len(matrices) > 0)
if (len(matrices) == 1):
return matrices[0].copy()
for matrix in matrices:
assert isinstance(matrix, Matrix)
assert (matrix.data.shape[0] == matrices[0].data.shape[0])
assert (matrix.rowlabels.shape == matrices[0].rowlabels.shape)
if require_equal_rowlabels:
assert np.array_equal(matrix.rowlabels, matrices[0].rowlabels)
data = np.hstack([mtx.data for mtx in matrices])
columnlabels = np.hstack([mtx.columnlabels for mtx in matrices])
return Matrix(data, matrices[0].rowlabels.copy(), columnlabels)<|docstring|>Returns a new matrix equal to the column-wise
concatenation of the given matrices<|endoftext|> |
3a360b79a7de6bf1dcd495f9722774c3c6102305bd93bf0b71637be6c8953c5f | def unique_rows(self, return_index=False):
'Returns a new matrix containing the unique rows\n in this matrix'
unique_indices = Matrix._unique_helper(self.__data)
if (unique_indices.size == self.__data.shape[0]):
newmatrix = self.copy()
else:
newmatrix = Matrix(self.__data[unique_indices], self.__rowlabels[unique_indices], self.__columnlabels.copy())
if return_index:
return (newmatrix, unique_indices)
else:
return newmatrix | Returns a new matrix containing the unique rows
in this matrix | server/analysis/matrix.py | unique_rows | newopscn/ottertune | 0 | python | def unique_rows(self, return_index=False):
'Returns a new matrix containing the unique rows\n in this matrix'
unique_indices = Matrix._unique_helper(self.__data)
if (unique_indices.size == self.__data.shape[0]):
newmatrix = self.copy()
else:
newmatrix = Matrix(self.__data[unique_indices], self.__rowlabels[unique_indices], self.__columnlabels.copy())
if return_index:
return (newmatrix, unique_indices)
else:
return newmatrix | def unique_rows(self, return_index=False):
'Returns a new matrix containing the unique rows\n in this matrix'
unique_indices = Matrix._unique_helper(self.__data)
if (unique_indices.size == self.__data.shape[0]):
newmatrix = self.copy()
else:
newmatrix = Matrix(self.__data[unique_indices], self.__rowlabels[unique_indices], self.__columnlabels.copy())
if return_index:
return (newmatrix, unique_indices)
else:
return newmatrix<|docstring|>Returns a new matrix containing the unique rows
in this matrix<|endoftext|> |
71e2ff58b4f1415c50628234131e00e6c2c1e3a87336834ca7dc7002a3ee3971 | def unique_columns(self, return_index=False):
'Returns a new matrix containing the unique columns\n in this matrix'
unique_indices = Matrix._unique_helper(self.__data.T)
if (unique_indices.size == self.__data.shape[1]):
newmatrix = self.copy()
else:
newmatrix = Matrix(self.__data[(:, unique_indices)], self.__rowlabels.copy(), self.__columnlabels[unique_indices])
if return_index:
return (newmatrix, unique_indices)
else:
return newmatrix | Returns a new matrix containing the unique columns
in this matrix | server/analysis/matrix.py | unique_columns | newopscn/ottertune | 0 | python | def unique_columns(self, return_index=False):
'Returns a new matrix containing the unique columns\n in this matrix'
unique_indices = Matrix._unique_helper(self.__data.T)
if (unique_indices.size == self.__data.shape[1]):
newmatrix = self.copy()
else:
newmatrix = Matrix(self.__data[(:, unique_indices)], self.__rowlabels.copy(), self.__columnlabels[unique_indices])
if return_index:
return (newmatrix, unique_indices)
else:
return newmatrix | def unique_columns(self, return_index=False):
'Returns a new matrix containing the unique columns\n in this matrix'
unique_indices = Matrix._unique_helper(self.__data.T)
if (unique_indices.size == self.__data.shape[1]):
newmatrix = self.copy()
else:
newmatrix = Matrix(self.__data[(:, unique_indices)], self.__rowlabels.copy(), self.__columnlabels[unique_indices])
if return_index:
return (newmatrix, unique_indices)
else:
return newmatrix<|docstring|>Returns a new matrix containing the unique columns
in this matrix<|endoftext|> |
403d0aafc439353bd1c51b60c30d95662024b1925213a6445f9ab0cb2cda824c | def copy(self):
'Returns a copy of this matrix'
return Matrix(self.__data.copy(), self.__rowlabels.copy(), self.__columnlabels.copy()) | Returns a copy of this matrix | server/analysis/matrix.py | copy | newopscn/ottertune | 0 | python | def copy(self):
return Matrix(self.__data.copy(), self.__rowlabels.copy(), self.__columnlabels.copy()) | def copy(self):
return Matrix(self.__data.copy(), self.__rowlabels.copy(), self.__columnlabels.copy())<|docstring|>Returns a copy of this matrix<|endoftext|> |
07f7972b5115dbd0863d39fa79c2f6784d4fbfe037d320b66ea2dd38f303057e | def filter(self, labels, rows_or_columns):
"Returns a new matrix filtered by either the rows or\n columns given in 'labels'"
assert (rows_or_columns in ['rows', 'columns'])
logical_filter = self.get_membership_mask(labels, rows_or_columns)
if (rows_or_columns == 'rows'):
return Matrix(self.__data[logical_filter], self.__rowlabels[logical_filter], self.__columnlabels)
else:
return Matrix(self.__data[(:, logical_filter)], self.__rowlabels, self.__columnlabels[logical_filter]) | Returns a new matrix filtered by either the rows or
columns given in 'labels' | server/analysis/matrix.py | filter | newopscn/ottertune | 0 | python | def filter(self, labels, rows_or_columns):
"Returns a new matrix filtered by either the rows or\n columns given in 'labels'"
assert (rows_or_columns in ['rows', 'columns'])
logical_filter = self.get_membership_mask(labels, rows_or_columns)
if (rows_or_columns == 'rows'):
return Matrix(self.__data[logical_filter], self.__rowlabels[logical_filter], self.__columnlabels)
else:
return Matrix(self.__data[(:, logical_filter)], self.__rowlabels, self.__columnlabels[logical_filter]) | def filter(self, labels, rows_or_columns):
"Returns a new matrix filtered by either the rows or\n columns given in 'labels'"
assert (rows_or_columns in ['rows', 'columns'])
logical_filter = self.get_membership_mask(labels, rows_or_columns)
if (rows_or_columns == 'rows'):
return Matrix(self.__data[logical_filter], self.__rowlabels[logical_filter], self.__columnlabels)
else:
return Matrix(self.__data[(:, logical_filter)], self.__rowlabels, self.__columnlabels[logical_filter])<|docstring|>Returns a new matrix filtered by either the rows or
columns given in 'labels'<|endoftext|> |
c18b8bdb8388401d987a98861e4d3b017cc535675fdefdafff71a558997dc33e | def load_model_checkpoint(self):
'\n This function loads a model checkpoint if there is a checkpoint with the models configuration name\n :return:\n '
checkpoint_abs_path = os.path.join(self.checkpoint_folder_path, self.checkpoint_filename)
if os.path.exists(checkpoint_abs_path):
checkpoint = torch.load(checkpoint_abs_path)
self.model.load_state_dict(checkpoint['model_state_dict'])
self.optimizer.load_state_dict(checkpoint['optimizer_state_dict'])
self.start_epoch = checkpoint['epoch']
self.log.info('Loaded {} model. Starting from the epoch number {}. Checkpoint path: {}'.format(self.model_configuration_name, self.start_epoch, checkpoint_abs_path))
self.model.train()
else:
self.log.info('No checkpoint found at {}. Training will start from scratch.'.format(checkpoint_abs_path)) | This function loads a model checkpoint if there is a checkpoint with the models configuration name
:return: | trainer/trainer.py | load_model_checkpoint | sarodriguez/audio-source-separation | 0 | python | def load_model_checkpoint(self):
'\n This function loads a model checkpoint if there is a checkpoint with the models configuration name\n :return:\n '
checkpoint_abs_path = os.path.join(self.checkpoint_folder_path, self.checkpoint_filename)
if os.path.exists(checkpoint_abs_path):
checkpoint = torch.load(checkpoint_abs_path)
self.model.load_state_dict(checkpoint['model_state_dict'])
self.optimizer.load_state_dict(checkpoint['optimizer_state_dict'])
self.start_epoch = checkpoint['epoch']
self.log.info('Loaded {} model. Starting from the epoch number {}. Checkpoint path: {}'.format(self.model_configuration_name, self.start_epoch, checkpoint_abs_path))
self.model.train()
else:
self.log.info('No checkpoint found at {}. Training will start from scratch.'.format(checkpoint_abs_path)) | def load_model_checkpoint(self):
'\n This function loads a model checkpoint if there is a checkpoint with the models configuration name\n :return:\n '
checkpoint_abs_path = os.path.join(self.checkpoint_folder_path, self.checkpoint_filename)
if os.path.exists(checkpoint_abs_path):
checkpoint = torch.load(checkpoint_abs_path)
self.model.load_state_dict(checkpoint['model_state_dict'])
self.optimizer.load_state_dict(checkpoint['optimizer_state_dict'])
self.start_epoch = checkpoint['epoch']
self.log.info('Loaded {} model. Starting from the epoch number {}. Checkpoint path: {}'.format(self.model_configuration_name, self.start_epoch, checkpoint_abs_path))
self.model.train()
else:
self.log.info('No checkpoint found at {}. Training will start from scratch.'.format(checkpoint_abs_path))<|docstring|>This function loads a model checkpoint if there is a checkpoint with the models configuration name
:return:<|endoftext|> |
4e0c3adb8481e15e418174717958631ae6bb5bab890e488f7ecc3a581f281588 | def pull_nytimes() -> int:
'Adds new nytimes stuff to database and returns status code'
print('Getting newslets..')
search = f'https://api.nytimes.com/svc/search/v2/articlesearch.json?q=coronavirus&begindate=20200301&api-key={config.NYTIMES_KEY}'
resp = requests.get(search)
if (resp.status_code != 200):
return resp.status_code
for newslet in resp.json()['response']['docs']:
if (Newslet.query.filter_by(id=newslet['web_url']).first() is None):
new_newslet = Newslet(newslet['web_url'], newslet['snippet'], newslet['lead_paragraph'])
db.session.add(new_newslet)
db.session.commit()
return resp.status_code | Adds new nytimes stuff to database and returns status code | covidmap.py | pull_nytimes | sneakykiwi/CovidMap | 2 | python | def pull_nytimes() -> int:
print('Getting newslets..')
search = f'https://api.nytimes.com/svc/search/v2/articlesearch.json?q=coronavirus&begindate=20200301&api-key={config.NYTIMES_KEY}'
resp = requests.get(search)
if (resp.status_code != 200):
return resp.status_code
for newslet in resp.json()['response']['docs']:
if (Newslet.query.filter_by(id=newslet['web_url']).first() is None):
new_newslet = Newslet(newslet['web_url'], newslet['snippet'], newslet['lead_paragraph'])
db.session.add(new_newslet)
db.session.commit()
return resp.status_code | def pull_nytimes() -> int:
print('Getting newslets..')
search = f'https://api.nytimes.com/svc/search/v2/articlesearch.json?q=coronavirus&begindate=20200301&api-key={config.NYTIMES_KEY}'
resp = requests.get(search)
if (resp.status_code != 200):
return resp.status_code
for newslet in resp.json()['response']['docs']:
if (Newslet.query.filter_by(id=newslet['web_url']).first() is None):
new_newslet = Newslet(newslet['web_url'], newslet['snippet'], newslet['lead_paragraph'])
db.session.add(new_newslet)
db.session.commit()
return resp.status_code<|docstring|>Adds new nytimes stuff to database and returns status code<|endoftext|> |
ac056637b548e6f7c316621fd7691ef82e97218d6e750b2a49b4354fa30cce81 | def populate_db():
'Top-level function for getting all csv data from github'
dbpath = 'covidmap.db'
if os.path.exists(dbpath):
os.remove(dbpath)
print('Adding stats..')
db.create_all()
print('Adding newslets..')
nytimes_respcode = pull_nytimes()
if (nytimes_respcode != 200):
print(f"Failed to add newslets, error code: '{nytimes_respcode}'!")
print('Adding provinces..')
province_to_db()
csv_data = json.loads(csvtojson())
for country_name in csv_data:
new_country = Country(country_name, csv_data[country_name])
db.session.add(new_country)
db.session.commit() | Top-level function for getting all csv data from github | covidmap.py | populate_db | sneakykiwi/CovidMap | 2 | python | def populate_db():
dbpath = 'covidmap.db'
if os.path.exists(dbpath):
os.remove(dbpath)
print('Adding stats..')
db.create_all()
print('Adding newslets..')
nytimes_respcode = pull_nytimes()
if (nytimes_respcode != 200):
print(f"Failed to add newslets, error code: '{nytimes_respcode}'!")
print('Adding provinces..')
province_to_db()
csv_data = json.loads(csvtojson())
for country_name in csv_data:
new_country = Country(country_name, csv_data[country_name])
db.session.add(new_country)
db.session.commit() | def populate_db():
dbpath = 'covidmap.db'
if os.path.exists(dbpath):
os.remove(dbpath)
print('Adding stats..')
db.create_all()
print('Adding newslets..')
nytimes_respcode = pull_nytimes()
if (nytimes_respcode != 200):
print(f"Failed to add newslets, error code: '{nytimes_respcode}'!")
print('Adding provinces..')
province_to_db()
csv_data = json.loads(csvtojson())
for country_name in csv_data:
new_country = Country(country_name, csv_data[country_name])
db.session.add(new_country)
db.session.commit()<|docstring|>Top-level function for getting all csv data from github<|endoftext|> |
af089a6e5a7983c08a39d6f6b5b40b3f6b95c425bb93c9c879f5bad4b7c52541 | def _get_env(self, env: str, fallback: str=None) -> str:
'Gets env var (boilerplate interchangable)'
if fallback:
try:
return os.environ[env]
except:
return fallback
return os.environ[env] | Gets env var (boilerplate interchangable) | covidmap.py | _get_env | sneakykiwi/CovidMap | 2 | python | def _get_env(self, env: str, fallback: str=None) -> str:
if fallback:
try:
return os.environ[env]
except:
return fallback
return os.environ[env] | def _get_env(self, env: str, fallback: str=None) -> str:
if fallback:
try:
return os.environ[env]
except:
return fallback
return os.environ[env]<|docstring|>Gets env var (boilerplate interchangable)<|endoftext|> |
3b37056e14a526989e1ccfb435d228fa29f71bb1376d02aecc5bb09da9cf3d5e | @commands('weather', 'wea')
@example('.weather')
@example('.weather London')
@example('.weather Seattle, US')
@example('.weather 90210')
def weather_command(bot, trigger):
'.weather location - Show the weather at the given location.'
if ((bot.config.weather.weather_api_key is None) or (bot.config.weather.weather_api_key == '')):
return bot.reply('Weather API key missing. Please configure this module.')
if ((bot.config.weather.geocoords_api_key is None) or (bot.config.weather.geocoords_api_key == '')):
return bot.reply('GeoCoords API key missing. Please configure this module.')
location = trigger.group(2)
if (not location):
latitude = bot.db.get_nick_value(trigger.nick, 'latitude')
longitude = bot.db.get_nick_value(trigger.nick, 'longitude')
if ((not latitude) or (not longitude)):
return bot.say("I don't know where you live. Give me a location, like {pfx}{command} London, or tell me where you live by saying {pfx}setlocation London, for example.".format(command=trigger.group(1), pfx=bot.config.core.help_prefix))
try:
data = get_weather(bot, trigger)
except Exception as err:
bot.reply(('Could not get weather: ' + str(err)))
return
weather = u'{location}: {temp}, {condition}, {humidity}'.format(location=data['location'], temp=get_temp(data['temp']), condition=data['condition'], humidity=get_humidity(data['humidity']))
if ('uvindex' in data.keys()):
weather += ', UV Index: {uvindex}'.format(uvindex=data['uvindex'])
if bot.config.weather.sunrise_sunset:
tz = data['timezone']
sr = convert_timestamp(data['sunrise'], tz)
ss = convert_timestamp(data['sunset'], tz)
weather += ', Sunrise: {sunrise} Sunset: {sunset}'.format(sunrise=sr, sunset=ss)
weather += ', {wind}'.format(wind=get_wind(data['wind']['speed'], data['wind']['bearing']))
return bot.say(weather) | .weather location - Show the weather at the given location. | sopel_modules/weather/weather.py | weather_command | RustyBower/sopel-weather | 3 | python | @commands('weather', 'wea')
@example('.weather')
@example('.weather London')
@example('.weather Seattle, US')
@example('.weather 90210')
def weather_command(bot, trigger):
if ((bot.config.weather.weather_api_key is None) or (bot.config.weather.weather_api_key == )):
return bot.reply('Weather API key missing. Please configure this module.')
if ((bot.config.weather.geocoords_api_key is None) or (bot.config.weather.geocoords_api_key == )):
return bot.reply('GeoCoords API key missing. Please configure this module.')
location = trigger.group(2)
if (not location):
latitude = bot.db.get_nick_value(trigger.nick, 'latitude')
longitude = bot.db.get_nick_value(trigger.nick, 'longitude')
if ((not latitude) or (not longitude)):
return bot.say("I don't know where you live. Give me a location, like {pfx}{command} London, or tell me where you live by saying {pfx}setlocation London, for example.".format(command=trigger.group(1), pfx=bot.config.core.help_prefix))
try:
data = get_weather(bot, trigger)
except Exception as err:
bot.reply(('Could not get weather: ' + str(err)))
return
weather = u'{location}: {temp}, {condition}, {humidity}'.format(location=data['location'], temp=get_temp(data['temp']), condition=data['condition'], humidity=get_humidity(data['humidity']))
if ('uvindex' in data.keys()):
weather += ', UV Index: {uvindex}'.format(uvindex=data['uvindex'])
if bot.config.weather.sunrise_sunset:
tz = data['timezone']
sr = convert_timestamp(data['sunrise'], tz)
ss = convert_timestamp(data['sunset'], tz)
weather += ', Sunrise: {sunrise} Sunset: {sunset}'.format(sunrise=sr, sunset=ss)
weather += ', {wind}'.format(wind=get_wind(data['wind']['speed'], data['wind']['bearing']))
return bot.say(weather) | @commands('weather', 'wea')
@example('.weather')
@example('.weather London')
@example('.weather Seattle, US')
@example('.weather 90210')
def weather_command(bot, trigger):
if ((bot.config.weather.weather_api_key is None) or (bot.config.weather.weather_api_key == )):
return bot.reply('Weather API key missing. Please configure this module.')
if ((bot.config.weather.geocoords_api_key is None) or (bot.config.weather.geocoords_api_key == )):
return bot.reply('GeoCoords API key missing. Please configure this module.')
location = trigger.group(2)
if (not location):
latitude = bot.db.get_nick_value(trigger.nick, 'latitude')
longitude = bot.db.get_nick_value(trigger.nick, 'longitude')
if ((not latitude) or (not longitude)):
return bot.say("I don't know where you live. Give me a location, like {pfx}{command} London, or tell me where you live by saying {pfx}setlocation London, for example.".format(command=trigger.group(1), pfx=bot.config.core.help_prefix))
try:
data = get_weather(bot, trigger)
except Exception as err:
bot.reply(('Could not get weather: ' + str(err)))
return
weather = u'{location}: {temp}, {condition}, {humidity}'.format(location=data['location'], temp=get_temp(data['temp']), condition=data['condition'], humidity=get_humidity(data['humidity']))
if ('uvindex' in data.keys()):
weather += ', UV Index: {uvindex}'.format(uvindex=data['uvindex'])
if bot.config.weather.sunrise_sunset:
tz = data['timezone']
sr = convert_timestamp(data['sunrise'], tz)
ss = convert_timestamp(data['sunset'], tz)
weather += ', Sunrise: {sunrise} Sunset: {sunset}'.format(sunrise=sr, sunset=ss)
weather += ', {wind}'.format(wind=get_wind(data['wind']['speed'], data['wind']['bearing']))
return bot.say(weather)<|docstring|>.weather location - Show the weather at the given location.<|endoftext|> |
d3a3baff2020c9adf51e902d2542d594dd272dde0780296b770c22f1db83ae4f | @commands('forecast', 'fc')
@example('.forecast')
@example('.forecast London')
@example('.forecast Seattle, US')
@example('.forecast 90210')
def forecast_command(bot, trigger):
'.forecast location - Show the weather forecast for tomorrow at the given location.'
if ((bot.config.weather.weather_api_key is None) or (bot.config.weather.weather_api_key == '')):
return bot.reply('Weather API key missing. Please configure this module.')
if ((bot.config.weather.geocoords_api_key is None) or (bot.config.weather.geocoords_api_key == '')):
return bot.reply('GeoCoords API key missing. Please configure this module.')
location = trigger.group(2)
if (not location):
latitude = bot.db.get_nick_value(trigger.nick, 'latitude')
longitude = bot.db.get_nick_value(trigger.nick, 'longitude')
if ((not latitude) or (not longitude)):
return bot.say("I don't know where you live. Give me a location, like {pfx}{command} London, or tell me where you live by saying {pfx}setlocation London, for example.".format(command=trigger.group(1), pfx=bot.config.core.help_prefix))
try:
data = get_forecast(bot, trigger)
except Exception as err:
bot.reply(('Could not get forecast: ' + str(err)))
return
forecast = '{location}'.format(location=data['location'])
for day in data['data']:
forecast += ' :: {dow} - {summary} - {high_temp} / {low_temp}'.format(dow=day.get('dow'), summary=day.get('summary'), high_temp=get_temp(day.get('high_temp')), low_temp=get_temp(day.get('low_temp')))
return bot.say(forecast) | .forecast location - Show the weather forecast for tomorrow at the given location. | sopel_modules/weather/weather.py | forecast_command | RustyBower/sopel-weather | 3 | python | @commands('forecast', 'fc')
@example('.forecast')
@example('.forecast London')
@example('.forecast Seattle, US')
@example('.forecast 90210')
def forecast_command(bot, trigger):
if ((bot.config.weather.weather_api_key is None) or (bot.config.weather.weather_api_key == )):
return bot.reply('Weather API key missing. Please configure this module.')
if ((bot.config.weather.geocoords_api_key is None) or (bot.config.weather.geocoords_api_key == )):
return bot.reply('GeoCoords API key missing. Please configure this module.')
location = trigger.group(2)
if (not location):
latitude = bot.db.get_nick_value(trigger.nick, 'latitude')
longitude = bot.db.get_nick_value(trigger.nick, 'longitude')
if ((not latitude) or (not longitude)):
return bot.say("I don't know where you live. Give me a location, like {pfx}{command} London, or tell me where you live by saying {pfx}setlocation London, for example.".format(command=trigger.group(1), pfx=bot.config.core.help_prefix))
try:
data = get_forecast(bot, trigger)
except Exception as err:
bot.reply(('Could not get forecast: ' + str(err)))
return
forecast = '{location}'.format(location=data['location'])
for day in data['data']:
forecast += ' :: {dow} - {summary} - {high_temp} / {low_temp}'.format(dow=day.get('dow'), summary=day.get('summary'), high_temp=get_temp(day.get('high_temp')), low_temp=get_temp(day.get('low_temp')))
return bot.say(forecast) | @commands('forecast', 'fc')
@example('.forecast')
@example('.forecast London')
@example('.forecast Seattle, US')
@example('.forecast 90210')
def forecast_command(bot, trigger):
if ((bot.config.weather.weather_api_key is None) or (bot.config.weather.weather_api_key == )):
return bot.reply('Weather API key missing. Please configure this module.')
if ((bot.config.weather.geocoords_api_key is None) or (bot.config.weather.geocoords_api_key == )):
return bot.reply('GeoCoords API key missing. Please configure this module.')
location = trigger.group(2)
if (not location):
latitude = bot.db.get_nick_value(trigger.nick, 'latitude')
longitude = bot.db.get_nick_value(trigger.nick, 'longitude')
if ((not latitude) or (not longitude)):
return bot.say("I don't know where you live. Give me a location, like {pfx}{command} London, or tell me where you live by saying {pfx}setlocation London, for example.".format(command=trigger.group(1), pfx=bot.config.core.help_prefix))
try:
data = get_forecast(bot, trigger)
except Exception as err:
bot.reply(('Could not get forecast: ' + str(err)))
return
forecast = '{location}'.format(location=data['location'])
for day in data['data']:
forecast += ' :: {dow} - {summary} - {high_temp} / {low_temp}'.format(dow=day.get('dow'), summary=day.get('summary'), high_temp=get_temp(day.get('high_temp')), low_temp=get_temp(day.get('low_temp')))
return bot.say(forecast)<|docstring|>.forecast location - Show the weather forecast for tomorrow at the given location.<|endoftext|> |
293a1d999a4676ff35f62add98a8d6158607732e6aad66265677a23ecd752b9e | @commands('setlocation')
@example('.setlocation London')
@example('.setlocation Seattle, US')
@example('.setlocation 90210')
@example('.setlocation w7174408')
def update_location(bot, trigger):
'Set your location for fetching weather.'
if ((bot.config.weather.geocoords_api_key is None) or (bot.config.weather.geocoords_api_key == '')):
return bot.reply('GeoCoords API key missing. Please configure this module.')
if (not trigger.group(2)):
bot.reply('Give me a location, like "London" or "90210".')
return NOLIMIT
try:
(latitude, longitude, location) = get_geocoords(bot, trigger)
except Exception as err:
bot.reply(('Could not find location details: ' + str(err)))
return
bot.db.set_nick_value(trigger.nick, 'latitude', latitude)
bot.db.set_nick_value(trigger.nick, 'longitude', longitude)
bot.db.set_nick_value(trigger.nick, 'location', location)
return bot.reply('I now have you at {}'.format(location)) | Set your location for fetching weather. | sopel_modules/weather/weather.py | update_location | RustyBower/sopel-weather | 3 | python | @commands('setlocation')
@example('.setlocation London')
@example('.setlocation Seattle, US')
@example('.setlocation 90210')
@example('.setlocation w7174408')
def update_location(bot, trigger):
if ((bot.config.weather.geocoords_api_key is None) or (bot.config.weather.geocoords_api_key == )):
return bot.reply('GeoCoords API key missing. Please configure this module.')
if (not trigger.group(2)):
bot.reply('Give me a location, like "London" or "90210".')
return NOLIMIT
try:
(latitude, longitude, location) = get_geocoords(bot, trigger)
except Exception as err:
bot.reply(('Could not find location details: ' + str(err)))
return
bot.db.set_nick_value(trigger.nick, 'latitude', latitude)
bot.db.set_nick_value(trigger.nick, 'longitude', longitude)
bot.db.set_nick_value(trigger.nick, 'location', location)
return bot.reply('I now have you at {}'.format(location)) | @commands('setlocation')
@example('.setlocation London')
@example('.setlocation Seattle, US')
@example('.setlocation 90210')
@example('.setlocation w7174408')
def update_location(bot, trigger):
if ((bot.config.weather.geocoords_api_key is None) or (bot.config.weather.geocoords_api_key == )):
return bot.reply('GeoCoords API key missing. Please configure this module.')
if (not trigger.group(2)):
bot.reply('Give me a location, like "London" or "90210".')
return NOLIMIT
try:
(latitude, longitude, location) = get_geocoords(bot, trigger)
except Exception as err:
bot.reply(('Could not find location details: ' + str(err)))
return
bot.db.set_nick_value(trigger.nick, 'latitude', latitude)
bot.db.set_nick_value(trigger.nick, 'longitude', longitude)
bot.db.set_nick_value(trigger.nick, 'location', location)
return bot.reply('I now have you at {}'.format(location))<|docstring|>Set your location for fetching weather.<|endoftext|> |
5af94be2db4f8bb23993360789e9923994ddae4e85a18bae91ea426e3e85c56c | def tearDown(self):
'Clean up the rache:* redis keys'
keys = r.keys('{0}*'.format(REDIS_PREFIX))
for key in keys:
r.delete(key) | Clean up the rache:* redis keys | tests.py | tearDown | brutasse/rache | 3 | python | def tearDown(self):
keys = r.keys('{0}*'.format(REDIS_PREFIX))
for key in keys:
r.delete(key) | def tearDown(self):
keys = r.keys('{0}*'.format(REDIS_PREFIX))
for key in keys:
r.delete(key)<|docstring|>Clean up the rache:* redis keys<|endoftext|> |
4710d72c6edeca6bf77403f9d17a6f1b2c8aa507fa0fad7b5b3abc1f9c89ff96 | def fix_ang(ang: float) -> float:
'\n Transforms the given angle into the range -pi...pi\n '
return (((ang + math.pi) % math.tau) - math.pi) | Transforms the given angle into the range -pi...pi | RLBotPack/Sniper/rlmath.py | fix_ang | lucas-emery/RLBotPack | 13 | python | def fix_ang(ang: float) -> float:
'\n \n '
return (((ang + math.pi) % math.tau) - math.pi) | def fix_ang(ang: float) -> float:
'\n \n '
return (((ang + math.pi) % math.tau) - math.pi)<|docstring|>Transforms the given angle into the range -pi...pi<|endoftext|> |
5edfc5c53e8572a98b96d4ea6b7bbbd06b91fce8fd505b1608e98c643226b112 | def proj_onto(src: Vec3, dir: Vec3) -> Vec3:
'\n Returns the vector component of src that is parallel with dir, i.e. the projection of src onto dir.\n '
try:
return ((dot(src, dir) / dot(dir, dir)) * dir)
except ZeroDivisionError:
return Vec3() | Returns the vector component of src that is parallel with dir, i.e. the projection of src onto dir. | RLBotPack/Sniper/rlmath.py | proj_onto | lucas-emery/RLBotPack | 13 | python | def proj_onto(src: Vec3, dir: Vec3) -> Vec3:
'\n \n '
try:
return ((dot(src, dir) / dot(dir, dir)) * dir)
except ZeroDivisionError:
return Vec3() | def proj_onto(src: Vec3, dir: Vec3) -> Vec3:
'\n \n '
try:
return ((dot(src, dir) / dot(dir, dir)) * dir)
except ZeroDivisionError:
return Vec3()<|docstring|>Returns the vector component of src that is parallel with dir, i.e. the projection of src onto dir.<|endoftext|> |
c22170e9b335eb4bfa4b0e0a231eaaf92435d426a3afcfabb03a7c5817b37c63 | def proj_onto_size(src: Vec3, dir: Vec3) -> float:
'\n Returns the size of the vector that is the project of src onto dir\n '
try:
dir_n = normalize(dir)
return (dot(src, dir_n) / dot(dir_n, dir_n))
except ZeroDivisionError:
return norm(src) | Returns the size of the vector that is the project of src onto dir | RLBotPack/Sniper/rlmath.py | proj_onto_size | lucas-emery/RLBotPack | 13 | python | def proj_onto_size(src: Vec3, dir: Vec3) -> float:
'\n \n '
try:
dir_n = normalize(dir)
return (dot(src, dir_n) / dot(dir_n, dir_n))
except ZeroDivisionError:
return norm(src) | def proj_onto_size(src: Vec3, dir: Vec3) -> float:
'\n \n '
try:
dir_n = normalize(dir)
return (dot(src, dir_n) / dot(dir_n, dir_n))
except ZeroDivisionError:
return norm(src)<|docstring|>Returns the size of the vector that is the project of src onto dir<|endoftext|> |
af2562f88c8562bda6e04c4927e436291886ca456baa2e67e9e17076dd169450 | def curve_from_arrival_dir(src, target, arrival_direction, w=1):
'\n Returns a point that is equally far from src and target on the line going through target with the given direction\n '
dir = normalize(arrival_direction)
tx = target.x
ty = target.y
sx = src.x
sy = src.y
dx = dir.x
dy = dir.y
t = ((- ((((((tx * tx) - ((2 * tx) * sx)) + (ty * ty)) - ((2 * ty) * sy)) + (sx * sx)) + (sy * sy))) / (2 * ((((tx * dx) + (ty * dy)) - (sx * dx)) - (sy * dy))))
t = clip(t, (- 1700), 1700)
return (target + ((w * t) * dir)) | Returns a point that is equally far from src and target on the line going through target with the given direction | RLBotPack/Sniper/rlmath.py | curve_from_arrival_dir | lucas-emery/RLBotPack | 13 | python | def curve_from_arrival_dir(src, target, arrival_direction, w=1):
'\n \n '
dir = normalize(arrival_direction)
tx = target.x
ty = target.y
sx = src.x
sy = src.y
dx = dir.x
dy = dir.y
t = ((- ((((((tx * tx) - ((2 * tx) * sx)) + (ty * ty)) - ((2 * ty) * sy)) + (sx * sx)) + (sy * sy))) / (2 * ((((tx * dx) + (ty * dy)) - (sx * dx)) - (sy * dy))))
t = clip(t, (- 1700), 1700)
return (target + ((w * t) * dir)) | def curve_from_arrival_dir(src, target, arrival_direction, w=1):
'\n \n '
dir = normalize(arrival_direction)
tx = target.x
ty = target.y
sx = src.x
sy = src.y
dx = dir.x
dy = dir.y
t = ((- ((((((tx * tx) - ((2 * tx) * sx)) + (ty * ty)) - ((2 * ty) * sy)) + (sx * sx)) + (sy * sy))) / (2 * ((((tx * dx) + (ty * dy)) - (sx * dx)) - (sy * dy))))
t = clip(t, (- 1700), 1700)
return (target + ((w * t) * dir))<|docstring|>Returns a point that is equally far from src and target on the line going through target with the given direction<|endoftext|> |
5e6e806c7d1540e87d81e998eff900b4709e5e3e4230a0320e1bd6992d167d1f | def bezier(t: float, points: list) -> Vec3:
'\n Returns a point on a bezier curve made from the given controls points\n '
n = len(points)
if (n == 1):
return points[0]
else:
return (((1 - t) * bezier(t, points[0:(- 1)])) + (t * bezier(t, points[1:n]))) | Returns a point on a bezier curve made from the given controls points | RLBotPack/Sniper/rlmath.py | bezier | lucas-emery/RLBotPack | 13 | python | def bezier(t: float, points: list) -> Vec3:
'\n \n '
n = len(points)
if (n == 1):
return points[0]
else:
return (((1 - t) * bezier(t, points[0:(- 1)])) + (t * bezier(t, points[1:n]))) | def bezier(t: float, points: list) -> Vec3:
'\n \n '
n = len(points)
if (n == 1):
return points[0]
else:
return (((1 - t) * bezier(t, points[0:(- 1)])) + (t * bezier(t, points[1:n])))<|docstring|>Returns a point on a bezier curve made from the given controls points<|endoftext|> |
de04819004183c3347de77c77379be986d7f682285b39ffc7343b7644211011c | def is_closer_to_goal_than(a: Vec3, b: Vec3, team_index):
' Returns true if a is closer than b to goal owned by the given team '
return ((a.y < b.y), (a.y > b.y))[team_index] | Returns true if a is closer than b to goal owned by the given team | RLBotPack/Sniper/rlmath.py | is_closer_to_goal_than | lucas-emery/RLBotPack | 13 | python | def is_closer_to_goal_than(a: Vec3, b: Vec3, team_index):
' '
return ((a.y < b.y), (a.y > b.y))[team_index] | def is_closer_to_goal_than(a: Vec3, b: Vec3, team_index):
' '
return ((a.y < b.y), (a.y > b.y))[team_index]<|docstring|>Returns true if a is closer than b to goal owned by the given team<|endoftext|> |
b737f0ffadc519f841417334c6429b0d6ad79e8b75c8a21a5dba66d74f27720c | def __init__(self, replay_downloader, download_validator):
'\n Parameters\n ----------\n replay_downloader : clare.application.download_bot.interfaces.IReplayDownloader\n download_validator : clare.application.download_bot.interfaces.DownloadValidator\n '
self._replay_downloader = replay_downloader
self._download_validator = download_validator | Parameters
----------
replay_downloader : clare.application.download_bot.interfaces.IReplayDownloader
download_validator : clare.application.download_bot.interfaces.DownloadValidator | clare/clare/application/download_bot/download_bots.py | __init__ | dnguyen0304/room-list-watcher | 0 | python | def __init__(self, replay_downloader, download_validator):
'\n Parameters\n ----------\n replay_downloader : clare.application.download_bot.interfaces.IReplayDownloader\n download_validator : clare.application.download_bot.interfaces.DownloadValidator\n '
self._replay_downloader = replay_downloader
self._download_validator = download_validator | def __init__(self, replay_downloader, download_validator):
'\n Parameters\n ----------\n replay_downloader : clare.application.download_bot.interfaces.IReplayDownloader\n download_validator : clare.application.download_bot.interfaces.DownloadValidator\n '
self._replay_downloader = replay_downloader
self._download_validator = download_validator<|docstring|>Parameters
----------
replay_downloader : clare.application.download_bot.interfaces.IReplayDownloader
download_validator : clare.application.download_bot.interfaces.DownloadValidator<|endoftext|> |
8a87690c0621ef8ebd87af68764dac1cd2750b24c31b741918bfa337b4533197 | def run(self, url):
'\n Parameters\n ----------\n url : str\n\n Returns\n -------\n str\n Path to the downloaded file.\n '
self._replay_downloader.run(url=url)
file_path = self._download_validator.run()
return file_path | Parameters
----------
url : str
Returns
-------
str
Path to the downloaded file. | clare/clare/application/download_bot/download_bots.py | run | dnguyen0304/room-list-watcher | 0 | python | def run(self, url):
'\n Parameters\n ----------\n url : str\n\n Returns\n -------\n str\n Path to the downloaded file.\n '
self._replay_downloader.run(url=url)
file_path = self._download_validator.run()
return file_path | def run(self, url):
'\n Parameters\n ----------\n url : str\n\n Returns\n -------\n str\n Path to the downloaded file.\n '
self._replay_downloader.run(url=url)
file_path = self._download_validator.run()
return file_path<|docstring|>Parameters
----------
url : str
Returns
-------
str
Path to the downloaded file.<|endoftext|> |
9fd5d7be5d7643218a8839afdd9db2aaae8314dec376463136c93fced7abeb90 | def __init__(self, download_bot, logger):
'\n Parameters\n ----------\n download_bot : clare.application.download_bot.download_bots.DownloadBot\n logger : logging.Logger\n '
self._download_bot = download_bot
self._logger = logger | Parameters
----------
download_bot : clare.application.download_bot.download_bots.DownloadBot
logger : logging.Logger | clare/clare/application/download_bot/download_bots.py | __init__ | dnguyen0304/room-list-watcher | 0 | python | def __init__(self, download_bot, logger):
'\n Parameters\n ----------\n download_bot : clare.application.download_bot.download_bots.DownloadBot\n logger : logging.Logger\n '
self._download_bot = download_bot
self._logger = logger | def __init__(self, download_bot, logger):
'\n Parameters\n ----------\n download_bot : clare.application.download_bot.download_bots.DownloadBot\n logger : logging.Logger\n '
self._download_bot = download_bot
self._logger = logger<|docstring|>Parameters
----------
download_bot : clare.application.download_bot.download_bots.DownloadBot
logger : logging.Logger<|endoftext|> |
1b8c76ccbb09f29af68078c08cdbfedcb58a7f78d053f388698c4d6d471340f5 | def __init__(self, download_bot):
'\n Parameters\n ----------\n download_bot : clare.application.download_bot.download_bots.DownloadBot\n '
self._download_bot = download_bot | Parameters
----------
download_bot : clare.application.download_bot.download_bots.DownloadBot | clare/clare/application/download_bot/download_bots.py | __init__ | dnguyen0304/room-list-watcher | 0 | python | def __init__(self, download_bot):
'\n Parameters\n ----------\n download_bot : clare.application.download_bot.download_bots.DownloadBot\n '
self._download_bot = download_bot | def __init__(self, download_bot):
'\n Parameters\n ----------\n download_bot : clare.application.download_bot.download_bots.DownloadBot\n '
self._download_bot = download_bot<|docstring|>Parameters
----------
download_bot : clare.application.download_bot.download_bots.DownloadBot<|endoftext|> |
afc091db1c15a0480c90389b0e37f27bdcbc237bef6a909e67a494cb84afa3f4 | def __init__(self, download_bot, root_url):
'\n Parameters\n ----------\n download_bot : clare.application.download_bot.download_bots.DownloadBot\n root_url : str\n '
self._download_bot = download_bot
self._root_url = root_url | Parameters
----------
download_bot : clare.application.download_bot.download_bots.DownloadBot
root_url : str | clare/clare/application/download_bot/download_bots.py | __init__ | dnguyen0304/room-list-watcher | 0 | python | def __init__(self, download_bot, root_url):
'\n Parameters\n ----------\n download_bot : clare.application.download_bot.download_bots.DownloadBot\n root_url : str\n '
self._download_bot = download_bot
self._root_url = root_url | def __init__(self, download_bot, root_url):
'\n Parameters\n ----------\n download_bot : clare.application.download_bot.download_bots.DownloadBot\n root_url : str\n '
self._download_bot = download_bot
self._root_url = root_url<|docstring|>Parameters
----------
download_bot : clare.application.download_bot.download_bots.DownloadBot
root_url : str<|endoftext|> |
c967a88ee85132beee0a4fe26f427f1bdecffda76493900636d5a494d60a8388 | def setup_platform(hass, config, add_devices, discovery_info=None):
'Find and return Vera covers.'
add_devices((VeraCover(device, VERA_CONTROLLER) for device in VERA_DEVICES['cover'])) | Find and return Vera covers. | homeassistant/components/cover/vera.py | setup_platform | rubund/debian-home-assistant | 13 | python | def setup_platform(hass, config, add_devices, discovery_info=None):
add_devices((VeraCover(device, VERA_CONTROLLER) for device in VERA_DEVICES['cover'])) | def setup_platform(hass, config, add_devices, discovery_info=None):
add_devices((VeraCover(device, VERA_CONTROLLER) for device in VERA_DEVICES['cover']))<|docstring|>Find and return Vera covers.<|endoftext|> |
0abcb844f0e7d29c6ec1e2d58b79bb0bce5d50072516162de88f26e0dc1cfb4f | def __init__(self, vera_device, controller):
'Initialize the Vera device.'
VeraDevice.__init__(self, vera_device, controller) | Initialize the Vera device. | homeassistant/components/cover/vera.py | __init__ | rubund/debian-home-assistant | 13 | python | def __init__(self, vera_device, controller):
VeraDevice.__init__(self, vera_device, controller) | def __init__(self, vera_device, controller):
VeraDevice.__init__(self, vera_device, controller)<|docstring|>Initialize the Vera device.<|endoftext|> |
ba43772e990a6be4208e3d36886447fb0cdc241a99ace433c3c756f5df0b3259 | @property
def current_cover_position(self):
'\n Return current position of cover.\n\n 0 is closed, 100 is fully open.\n '
position = self.vera_device.get_level()
if (position <= 5):
return 0
if (position >= 95):
return 100
return position | Return current position of cover.
0 is closed, 100 is fully open. | homeassistant/components/cover/vera.py | current_cover_position | rubund/debian-home-assistant | 13 | python | @property
def current_cover_position(self):
'\n Return current position of cover.\n\n 0 is closed, 100 is fully open.\n '
position = self.vera_device.get_level()
if (position <= 5):
return 0
if (position >= 95):
return 100
return position | @property
def current_cover_position(self):
'\n Return current position of cover.\n\n 0 is closed, 100 is fully open.\n '
position = self.vera_device.get_level()
if (position <= 5):
return 0
if (position >= 95):
return 100
return position<|docstring|>Return current position of cover.
0 is closed, 100 is fully open.<|endoftext|> |
0ec56e07920a720f5c9e383a71e5ff0d6c2092349169f06f2152ac9db9cd2292 | def set_cover_position(self, position, **kwargs):
'Move the cover to a specific position.'
self.vera_device.set_level(position) | Move the cover to a specific position. | homeassistant/components/cover/vera.py | set_cover_position | rubund/debian-home-assistant | 13 | python | def set_cover_position(self, position, **kwargs):
self.vera_device.set_level(position) | def set_cover_position(self, position, **kwargs):
self.vera_device.set_level(position)<|docstring|>Move the cover to a specific position.<|endoftext|> |
278b7bcecd10e4ca04aa7bdf593a982efe1c35ae579e37b8e0481baefc6014c3 | @property
def is_closed(self):
'Return if the cover is closed.'
if (self.current_cover_position is not None):
if (self.current_cover_position > 0):
return False
else:
return True | Return if the cover is closed. | homeassistant/components/cover/vera.py | is_closed | rubund/debian-home-assistant | 13 | python | @property
def is_closed(self):
if (self.current_cover_position is not None):
if (self.current_cover_position > 0):
return False
else:
return True | @property
def is_closed(self):
if (self.current_cover_position is not None):
if (self.current_cover_position > 0):
return False
else:
return True<|docstring|>Return if the cover is closed.<|endoftext|> |
49b9f2f46f1c812d27458a0c64cd907fef61680d7fbfa61f59e85089a749d4bc | def open_cover(self, **kwargs):
'Open the cover.'
self.vera_device.open() | Open the cover. | homeassistant/components/cover/vera.py | open_cover | rubund/debian-home-assistant | 13 | python | def open_cover(self, **kwargs):
self.vera_device.open() | def open_cover(self, **kwargs):
self.vera_device.open()<|docstring|>Open the cover.<|endoftext|> |
64ba672013de1b9eed9de5130b4e832a5fd6ee69e7e54fda701212ad689632ca | def close_cover(self, **kwargs):
'Close the cover.'
self.vera_device.close() | Close the cover. | homeassistant/components/cover/vera.py | close_cover | rubund/debian-home-assistant | 13 | python | def close_cover(self, **kwargs):
self.vera_device.close() | def close_cover(self, **kwargs):
self.vera_device.close()<|docstring|>Close the cover.<|endoftext|> |
f392ff03dcf05524de0ba808bb576d16ac0e1309af25e34533c6b23bfa051f47 | def stop_cover(self, **kwargs):
'Stop the cover.'
self.vera_device.stop() | Stop the cover. | homeassistant/components/cover/vera.py | stop_cover | rubund/debian-home-assistant | 13 | python | def stop_cover(self, **kwargs):
self.vera_device.stop() | def stop_cover(self, **kwargs):
self.vera_device.stop()<|docstring|>Stop the cover.<|endoftext|> |
87c04b08babb26177fcf38bbeee64a15a23e63a78909653ac3365c9651100c7a | def validate_instantiation(**kwargs):
'Checks if a driver is instantiated other than by the unified driver.\n\n Helps check direct instantiation of netapp drivers.\n Call this function in every netapp block driver constructor.\n '
if (kwargs and (kwargs.get('netapp_mode') == 'proxy')):
return
LOG.warning(_LW('It is not the recommended way to use drivers by NetApp. Please use NetAppDriver to achieve the functionality.')) | Checks if a driver is instantiated other than by the unified driver.
Helps check direct instantiation of netapp drivers.
Call this function in every netapp block driver constructor. | cinder/volume/drivers/netapp/utils.py | validate_instantiation | bswartz/cinder | 11 | python | def validate_instantiation(**kwargs):
'Checks if a driver is instantiated other than by the unified driver.\n\n Helps check direct instantiation of netapp drivers.\n Call this function in every netapp block driver constructor.\n '
if (kwargs and (kwargs.get('netapp_mode') == 'proxy')):
return
LOG.warning(_LW('It is not the recommended way to use drivers by NetApp. Please use NetAppDriver to achieve the functionality.')) | def validate_instantiation(**kwargs):
'Checks if a driver is instantiated other than by the unified driver.\n\n Helps check direct instantiation of netapp drivers.\n Call this function in every netapp block driver constructor.\n '
if (kwargs and (kwargs.get('netapp_mode') == 'proxy')):
return
LOG.warning(_LW('It is not the recommended way to use drivers by NetApp. Please use NetAppDriver to achieve the functionality.'))<|docstring|>Checks if a driver is instantiated other than by the unified driver.
Helps check direct instantiation of netapp drivers.
Call this function in every netapp block driver constructor.<|endoftext|> |
6adb1bac209555f84b70b7a69e2271b67ac1e36655ebc56f4e906cfc29b7a44e | def check_flags(required_flags, configuration):
'Ensure that the flags we care about are set.'
for flag in required_flags:
if (not getattr(configuration, flag, None)):
msg = (_('Configuration value %s is not set.') % flag)
raise exception.InvalidInput(reason=msg) | Ensure that the flags we care about are set. | cinder/volume/drivers/netapp/utils.py | check_flags | bswartz/cinder | 11 | python | def check_flags(required_flags, configuration):
for flag in required_flags:
if (not getattr(configuration, flag, None)):
msg = (_('Configuration value %s is not set.') % flag)
raise exception.InvalidInput(reason=msg) | def check_flags(required_flags, configuration):
for flag in required_flags:
if (not getattr(configuration, flag, None)):
msg = (_('Configuration value %s is not set.') % flag)
raise exception.InvalidInput(reason=msg)<|docstring|>Ensure that the flags we care about are set.<|endoftext|> |
62e730c52d3af48cfcd00f86cb001dd3739a0c29f9bb0b116101127c150df550 | def to_bool(val):
'Converts true, yes, y, 1 to True, False otherwise.'
if val:
strg = six.text_type(val).lower()
if ((strg == 'true') or (strg == 'y') or (strg == 'yes') or (strg == 'enabled') or (strg == '1')):
return True
else:
return False
else:
return False | Converts true, yes, y, 1 to True, False otherwise. | cinder/volume/drivers/netapp/utils.py | to_bool | bswartz/cinder | 11 | python | def to_bool(val):
if val:
strg = six.text_type(val).lower()
if ((strg == 'true') or (strg == 'y') or (strg == 'yes') or (strg == 'enabled') or (strg == '1')):
return True
else:
return False
else:
return False | def to_bool(val):
if val:
strg = six.text_type(val).lower()
if ((strg == 'true') or (strg == 'y') or (strg == 'yes') or (strg == 'enabled') or (strg == '1')):
return True
else:
return False
else:
return False<|docstring|>Converts true, yes, y, 1 to True, False otherwise.<|endoftext|> |
455e945d15d7dd8896c9d8a3e5fb26d9a7a7e30a89c97ab93f5bd5227799bb85 | @utils.synchronized('safe_set_attr')
def set_safe_attr(instance, attr, val):
'Sets the attribute in a thread safe manner.\n\n Returns if new val was set on attribute.\n If attr already had the value then False.\n '
if ((not instance) or (not attr)):
return False
old_val = getattr(instance, attr, None)
if ((val is None) and (old_val is None)):
return False
elif (val == old_val):
return False
else:
setattr(instance, attr, val)
return True | Sets the attribute in a thread safe manner.
Returns if new val was set on attribute.
If attr already had the value then False. | cinder/volume/drivers/netapp/utils.py | set_safe_attr | bswartz/cinder | 11 | python | @utils.synchronized('safe_set_attr')
def set_safe_attr(instance, attr, val):
'Sets the attribute in a thread safe manner.\n\n Returns if new val was set on attribute.\n If attr already had the value then False.\n '
if ((not instance) or (not attr)):
return False
old_val = getattr(instance, attr, None)
if ((val is None) and (old_val is None)):
return False
elif (val == old_val):
return False
else:
setattr(instance, attr, val)
return True | @utils.synchronized('safe_set_attr')
def set_safe_attr(instance, attr, val):
'Sets the attribute in a thread safe manner.\n\n Returns if new val was set on attribute.\n If attr already had the value then False.\n '
if ((not instance) or (not attr)):
return False
old_val = getattr(instance, attr, None)
if ((val is None) and (old_val is None)):
return False
elif (val == old_val):
return False
else:
setattr(instance, attr, val)
return True<|docstring|>Sets the attribute in a thread safe manner.
Returns if new val was set on attribute.
If attr already had the value then False.<|endoftext|> |
3fd7939c242667c3981c510e48f647c59b9d1d430c6e416b7ae0105e1401b86d | def get_volume_extra_specs(volume):
'Provides extra specs associated with volume.'
ctxt = context.get_admin_context()
type_id = volume.get('volume_type_id')
if (type_id is None):
return {}
volume_type = volume_types.get_volume_type(ctxt, type_id)
if (volume_type is None):
return {}
extra_specs = volume_type.get('extra_specs', {})
log_extra_spec_warnings(extra_specs)
return extra_specs | Provides extra specs associated with volume. | cinder/volume/drivers/netapp/utils.py | get_volume_extra_specs | bswartz/cinder | 11 | python | def get_volume_extra_specs(volume):
ctxt = context.get_admin_context()
type_id = volume.get('volume_type_id')
if (type_id is None):
return {}
volume_type = volume_types.get_volume_type(ctxt, type_id)
if (volume_type is None):
return {}
extra_specs = volume_type.get('extra_specs', {})
log_extra_spec_warnings(extra_specs)
return extra_specs | def get_volume_extra_specs(volume):
ctxt = context.get_admin_context()
type_id = volume.get('volume_type_id')
if (type_id is None):
return {}
volume_type = volume_types.get_volume_type(ctxt, type_id)
if (volume_type is None):
return {}
extra_specs = volume_type.get('extra_specs', {})
log_extra_spec_warnings(extra_specs)
return extra_specs<|docstring|>Provides extra specs associated with volume.<|endoftext|> |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.