How to use _load_from_file method in lisa

Best Python code snippet using lisa_python

context.py

Source: context.py Github

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...10 self.path = path11 self._data = {}12 self._defaults = {}13 self._mtime = 014 self._load_from_file()15 def _load_from_file(self):16 mtime = os.path.getmtime(self.path)17 if mtime - (self._mtime or 0) < 0.001:18 return19 data = yaml.safe_load(open(self.path))20 if not isinstance(data, dict):21 raise TypeError('the contextmap file is not dict-like')22 data.update(self._defaults)23 self._data = data24 self._mtime = mtime25 def get(self, key, default=None):26 return self._data.get(key, default)27 def pop(self, key, default=None):28 return self._data.pop(key, default)29 def get_keys(self):30 self._load_from_file()31 return list(self._data)32 def setdefault(self, key, default=None):33 try:34 return self._data[key]35 except LookupError:36 return self._defaults.setdefault(key, default)37class RealContextFile(ContextFile):38 def __init__(self, path, ttl=60):39 super(ContextFile, self).__init__(path)40 self._xtime = 041 self.ttl = ttl42 def get(self, key, default=None):43 current_time = time.time()44 # expired45 if current_time > self._xtime:46 self._load_from_file()47 self._xtime = current_time + self.ttl48 return self._data.get(key, default)49 def setdefault(self, key, default=None):50 return self._data.setdefault(key, default)51class ContextDirectory(object):52 def __init__(self, dir_path):53 if not os.path.isdir(dir_path):54 raise ValueError('requires a directory')55 self._cache = {}56 self._mtime = {}57 self.path = dir_path58 def _load_from_file(self, key):59 """60 Update _mtime and _cache if yaml.safe_load() is called.61 """62 path = join(self.path, key + '.yml')63 if not os.path.isfile(path):64 return65 mtime = os.path.getmtime(path)66 # avoid float equality test67 if mtime - self._mtime.get(key, 0) < 0.001:68 try:69 return self._cache[key]70 except LookupError:71 pass72 section = yaml.safe_load(open(path))73 self._mtime[key] = mtime74 self._cache[key] = section75 return section76 def setdefault(self, key, default=None):77 # only set default when key is not available in FS78 return self._cache.setdefault(key, self.get(key, default))79 def get(self, key, default=None):80 try:81 return self._cache[key]82 except LookupError:83 return self._load_from_file(key) or default84 def get_keys(self):85 _keys = []86 for filename in os.listdir(self.path):87 name, ext = os.path.splitext(filename)88 if ext == '.yml':89 _keys.append(name)90 return _keys91class RealContextDirectory(ContextDirectory):92 def __init__(self, dir_path, ttl=60):93 super(RealContextDirectory, self).__init__(dir_path)94 self._xtime = {}95 self.ttl = ttl96 def get(self, key, default=None):97 """98 Update _xtime if _load_from_file() is called and ttl available.99 Do NOT touch _cache and _mtime in this method;100 it is the job of _load_from_file.101 """102 current_time = time.time()103 expire_time = self._xtime.get(key, 0)104 # expired105 if current_time > expire_time:106 section = self._load_from_file(key)107 self._xtime[key] = current_time + self.ttl108 return section109 return super(RealContextDirectory, self).get(key, default)110 def setdefault(self, key, default=None):111 section = self._cache.setdefault(key, self.get(key, default))112 self._xtime.setdefault(key, float('inf'))113 return section114def context_load(path, ttl=None):115 if os.path.isdir(path):116 if ttl is None:117 return ContextDirectory(path)118 else:119 return RealContextDirectory(path, ttl)120 elif os.path.isfile(path):...

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coeffs.py

Source: coeffs.py Github

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...8 _HAVE_PYWT = True9except ImportError:10 _HAVE_PYWT = False11COEFF_CACHE = {}12def _load_from_file(basename, varnames):13 try:14 mat = COEFF_CACHE[basename]15 except KeyError:16 with resource_stream('pytorch_wavelets.dtcwt.data', basename + '.npz') as f:17 mat = dict(load(f))18 COEFF_CACHE[basename] = mat19 try:20 return tuple(mat[k] for k in varnames)21 except KeyError:22 raise ValueError(23 'Wavelet does not define ({0}) coefficients'.format(24 ', '.join(varnames)))25def biort(name):26 """ Deprecated. Use :py::func:`pytorch_wavelets.dtcwt.coeffs.level1`27 Instead28 """29 return level1(name, compact=True)30def level1(name, compact=False):31 """Load level 1 wavelet by name.32 :param name: a string specifying the wavelet family name33 :returns: a tuple of vectors giving filter coefficients34 ============= ============================================35 Name Wavelet36 ============= ============================================37 antonini Antonini 9,7 tap filters.38 farras Farras 8,8 tap filters39 legall LeGall 5,3 tap filters.40 near_sym_a Near-Symmetric 5,7 tap filters.41 near_sym_b Near-Symmetric 13,19 tap filters.42 near_sym_b_bp Near-Symmetric 13,19 tap filters + BP filter43 ============= ============================================44 Return a tuple whose elements are a vector specifying the h0o, g0o, h1o and45 g1o coefficients.46 See :ref:`rot-symm-wavelets` for an explanation of the ``near_sym_b_bp``47 wavelet filters.48 :raises IOError: if name does not correspond to a set of wavelets known to49 the library.50 :raises ValueError: if name doesn't specify51 :py:func:`pytorch_wavelets.dtcwt.coeffs.qshift` wavelet.52 """53 if compact:54 if name == 'near_sym_b_bp':55 return _load_from_file(name, ('h0o', 'g0o', 'h1o', 'g1o', 'h2o', 'g2o'))56 else:57 return _load_from_file(name, ('h0o', 'g0o', 'h1o', 'g1o'))58 else:59 return _load_from_file(name, ('h0a', 'h0b', 'g0a', 'g0b', 'h1a', 'h1b',60 'g1a', 'g1b'))61def qshift(name):62 """Load level >=2 wavelet by name,63 :param name: a string specifying the wavelet family name64 :returns: a tuple of vectors giving filter coefficients65 ============ ============================================66 Name Wavelet67 ============ ============================================68 qshift_06 Quarter Sample Shift Orthogonal (Q-Shift) 10,10 tap filters,69 (only 6,6 non-zero taps).70 qshift_a Q-shift 10,10 tap filters,71 (with 10,10 non-zero taps, unlike qshift_06).72 qshift_b Q-Shift 14,14 tap filters.73 qshift_c Q-Shift 16,16 tap filters.74 qshift_d Q-Shift 18,18 tap filters.75 qshift_b_bp Q-Shift 18,18 tap filters + BP76 ============ ============================================77 Return a tuple whose elements are a vector specifying the h0a, h0b, g0a,78 g0b, h1a, h1b, g1a and g1b coefficients.79 See :ref:`rot-symm-wavelets` for an explanation of the ``qshift_b_bp``80 wavelet filters.81 :raises IOError: if name does not correspond to a set of wavelets known to82 the library.83 :raises ValueError: if name doesn't specify a84 :py:func:`pytorch_wavelets.dtcwt.coeffs.biort` wavelet.85 """86 if name == 'qshift_b_bp':87 return _load_from_file(name, ('h0a', 'h0b', 'g0a', 'g0b', 'h1a', 'h1b',88 'g1a', 'g1b', 'h2a', 'h2b', 'g2a','g2b'))89 else:90 return _load_from_file(name, ('h0a', 'h0b', 'g0a', 'g0b', 'h1a', 'h1b',91 'g1a', 'g1b'))92def pywt_coeffs(name):93 """ Wraps pywt Wavelet function. """94 if not _HAVE_PYWT:95 raise ImportError("Could not find PyWavelets module")96 return pywt.Wavelet(name)...

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dice.py

Source: dice.py Github

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...5from math import sqrt67class Dice(Enum):8 @staticmethod9 def _load_from_file(path: str):10 dice = []11 path = os.path.join(os.path.dirname(os.path.realpath(__file__)), path)12 with open(path, 'r') as f:13 file_lines = f.readlines()14 for line in file_lines:15 faces = line.upper().strip().split(" ")16 # Validate faces17 # 1-3 letters are allowed18 face_lengths = [len(face) for face in faces]19 if min(face_lengths) == 0:20 raise ValueError("Cannot have empty faces")21 elif max(face_lengths) > 3:22 raise ValueError("Cannot have faces with more than 3 letters")23 ...

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