本文整理汇总了Python中tables.openFile方法的典型用法代码示例。如果您正苦于以下问题:Python tables.openFile方法的具体用法?Python tables.openFile怎么用?Python tables.openFile使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类tables
的用法示例。
在下文中一共展示了tables.openFile方法的14个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: merge_all_files_into_pytables
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def merge_all_files_into_pytables(file_dir, file_out):
"""
process each file into pytables
"""
start = None
start = datetime.datetime.now()
out_h5 = tables.openFile(file_out,
mode="w",
title="bars",
filters=tables.Filters(complevel=9,
complib='zlib'))
table = None
for file_in in glob.glob(file_dir + "/*.gz"):
gzip_file = gzip.open(file_in)
expected_header = ["dt", "sid", "open", "high", "low", "close",
"volume"]
csv_reader = csv.DictReader(gzip_file)
header = csv_reader.fieldnames
if header != expected_header:
logging.warn("expected header %s\n" % (expected_header))
logging.warn("header_found %s" % (header))
return
for current_date, rows in parse_csv(csv_reader):
table = out_h5.createTable("/TD", "date_" + current_date,
OHLCTableDescription,
expectedrows=len(rows),
createparents=True)
table.append(rows)
table.flush()
if table is not None:
table.flush()
end = datetime.datetime.now()
diff = (end - start).seconds
logging.debug("finished it took %d." % (diff))
示例2: safe_hdf
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def safe_hdf(array, name):
if os.path.isfile(name + '.hdf') and not args.overwrite:
logger.warning("Not saving %s, already exists." % (name + '.hdf'))
else:
if os.path.isfile(name + '.hdf'):
logger.info("Overwriting %s." % (name + '.hdf'))
else:
logger.info("Saving to %s." % (name + '.hdf'))
with tables.openFile(name + '.hdf', 'w') as f:
atom = tables.Atom.from_dtype(array.dtype)
filters = tables.Filters(complib='blosc', complevel=5)
ds = f.createCArray(f.root, name.replace('.', ''), atom,
array.shape, filters=filters)
ds[:] = array
示例3: open_h5_file_read
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def open_h5_file_read(h5filename):
"""
Open an existing H5 in read mode.
Same function as in hdf5_utils, here so we avoid one import
"""
return tables.openFile(h5filename, mode='r')
示例4: _f_open
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def _f_open(self, args):
if not self._opened:
self._filename = args["filename"]
self._title = args["title"]
if self._title is None or not isinstance(self._title, basestring):
self._title = strftime("PicoTape-%Y%m%d-%H%M%S")
self._limit = args["limit"]
self._overwrite = args["overwrite"]
if self._filename is not None:
self._fhandle = None
error = "OK"
try:
if not os.path.exists(os.path.dirname(self._filename)):
error = "Path to %s not found" % self._filename
elif not self._overwrite and os.path.exists(self._filename):
error = "File %s exists" % self._filename
else:
self._fhandle = tb.openFile(self._filename, title=self._title, mode="w")
except Exception as ex:
self._fhandle = None
error = ex.message
if self._fhandle is not None:
self._opened = True
self._readq.put(error)
else:
self._memstore = True
self._opened = True
self._readq.put("OK")
self._stats = args["stats"] and not self._memstore
示例5: save_h5
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def save_h5(self, filename):
try:
shutil.copyfile(filename, '{}_bak'.format(filename))
except IOError:
print 'could not make backup of model param file (which is normal if we haven\'t saved one until now)'
with tables.openFile(filename, 'w') as h5file:
for p in self.params:
h5file.createArray(h5file.root, p.name, p.get_value())
h5file.flush()
示例6: load_h5
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def load_h5(self, filename):
h5file = tables.openFile(filename, 'r')
new_params = {}
for p in h5file.listNodes(h5file.root):
new_params[p.name] = p.read()
self.updateparams_fromdict(new_params)
h5file.close()
示例7: init_hdf5
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def init_hdf5(self, path, shapes,
title="Pytables Dataset",
y_dtype='float'):
"""
Initializes the hdf5 file into which the data will be stored. This must
be called before calling fill_hdf5.
Parameters
----------
path : string
The name of the hdf5 file.
shapes : tuple
The shapes of X and y.
title : string, optional
Name of the dataset. e.g. For SVHN, set this to "SVHN Dataset".
"Pytables Dataset" is used as title, by default.
y_dtype : string, optional
Either 'float' or 'int'. Decides the type of pytables atom
used to store the y data. By default 'float' type is used.
"""
assert y_dtype in ['float', 'int'], (
"y_dtype can be 'float' or 'int' only"
)
x_shape, y_shape = shapes
# make pytables
ensure_tables()
h5file = tables.openFile(path, mode="w", title=title)
gcolumns = h5file.createGroup(h5file.root, "Data", "Data")
atom = (tables.Float32Atom() if config.floatX == 'float32'
else tables.Float64Atom())
h5file.createCArray(gcolumns, 'X', atom=atom, shape=x_shape,
title="Data values", filters=self.filters)
if y_dtype != 'float':
# For 1D ndarray of int labels, override the atom to integer
atom = (tables.Int32Atom() if config.floatX == 'float32'
else tables.Int64Atom())
h5file.createCArray(gcolumns, 'y', atom=atom, shape=y_shape,
title="Data targets", filters=self.filters)
return h5file, gcolumns
示例8: read_mat_file_into_bag
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def read_mat_file_into_bag(mat_fname):
try:
import scipy.io as sio
x = sio.loadmat(mat_fname)
return Bag(**x)
except NotImplementedError:
import tables
from src.utils import tables_utils as tu
x = tables.openFile(mat_fname)
ret = Bag(**tu.read_tables_into_dict(x))
x.close()
return ret
return None
示例9: create_hdf5_file
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def create_hdf5_file(file_name):
try:
return tables.open_file(file_name, mode='w')
except:
return tables.openFile(file_name, mode='w')
示例10: open_hdf5_file
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def open_hdf5_file(file_name, mode='a'):
try:
return tables.open_file(file_name, mode=mode)
except:
return tables.openFile(file_name, mode=mode)
# dtype = np.dtype('int16') / np.dtype('float64')
示例11: get_length
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def get_length(path):
if tables.__version__[0] == '2':
target_table = tables.openFile(path, 'r')
target_index = target_table.getNode('/indices')
else:
target_table = tables.open_file(path, 'r')
target_index = target_table.get_node('/indices')
return target_index.shape[0]
示例12: synchronized_open_file
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def synchronized_open_file(*args, **kwargs):
if tables.__version__[0] == '2':
tbf = tables.openFile(*args, **kwargs)
else:
tbf = tables.open_file(*args, **kwargs)
return tbf
示例13: test_output
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def test_output():
import tables as T
h5 = T.openFile('/Users/ebruning/out/LYLOUT_040526_213000_0600.dat.gz.flash.h5')
flashes = h5.root.flashes.LMA_040526_213000_600
events = h5.root.events.LMA_040526_213000_600
# flashes.cols.n_points[0:100]
big = [fl['flash_id'] for fl in flashes if fl['n_points'] > 100]
a_flash = big[0]
points = [ev['lat'] for ev in events if ev['flash_id'] == a_flash]
print(flashes.cols.init_lon[0:10])
示例14: dump_test_set
# 需要导入模块: import tables [as 别名]
# 或者: from tables import openFile [as 别名]
def dump_test_set(self, h5filepath, nframes, framesize):
# set rng to a hardcoded state, so we always have the same test set!
self.numpy_rng.seed(1)
with tables.openFile(h5filepath, 'w') as h5file:
h5file.createArray(h5file.root, 'test_targets',
self.partitions['test']['targets'])
vids = h5file.createCArray(
h5file.root,
'test_images',
tables.Float32Atom(),
shape=(10000,
nframes, framesize, framesize),
filters=tables.Filters(complevel=5, complib='zlib'))
pos = h5file.createCArray(
h5file.root,
'test_pos',
tables.UInt16Atom(),
shape=(10000,
nframes, 2),
filters=tables.Filters(complevel=5, complib='zlib'))
for i in range(100):
print i
(vids[i*100:(i+1)*100],
pos[i*100:(i+1)*100], _) = self.get_batch(
'test', 100, nframes, framesize,
idx=np.arange(i*100,(i+1)*100))
h5file.flush()