#
# This file is part of Hooke.
#
-# Hooke is free software: you can redistribute it and/or
-# modify it under the terms of the GNU Lesser General Public
-# License as published by the Free Software Foundation, either
-# version 3 of the License, or (at your option) any later version.
+# Hooke is free software: you can redistribute it and/or modify it
+# under the terms of the GNU Lesser General Public License as
+# published by the Free Software Foundation, either version 3 of the
+# License, or (at your option) any later version.
#
-# Hooke is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-# GNU Lesser General Public License for more details.
+# Hooke is distributed in the hope that it will be useful, but WITHOUT
+# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
+# or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General
+# Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with Hooke. If not, see
storing force curves.
"""
+import logging
import os.path
+
import numpy
+from .command_stack import CommandStack
+
class NotRecognized (ValueError):
def __init__(self, curve):
- msg = 'Not a recognizable curve format: %s' % curve.path
- ValueError.__init__(self, msg)
- self.curve = curve
+ self.__setstate__(curve)
+
+ def __getstate__(self):
+ return self.curve
+
+ def __setstate__(self, data):
+ if isinstance(data, Curve):
+ msg = 'Not a recognizable curve format: %s' % data.path
+ super(NotRecognized, self).__init__(msg)
+ self.curve = data
class Data (numpy.ndarray):
"""Stores a single, continuous data set.
See :mod:`numpy.doc.subclassing` for the peculiarities of
subclassing :class:`numpy.ndarray`.
+
+ Examples
+ --------
+
+ >>> d = Data(shape=(3,2), info={'columns':['distance (m)', 'force (N)']})
+ >>> type(d)
+ <class 'hooke.curve.Data'>
+ >>> for i in range(3): # initialize d
+ ... for j in range(2):
+ ... d[i,j] = i*10 + j
+ >>> d
+ Data([[ 0., 1.],
+ [ 10., 11.],
+ [ 20., 21.]])
+ >>> d.info
+ {'columns': ['distance (m)', 'force (N)']}
+
+ The information gets passed on to slices.
+
+ >>> row_a = d[:,0]
+ >>> row_a
+ Data([ 0., 10., 20.])
+ >>> row_a.info
+ {'columns': ['distance (m)', 'force (N)']}
+
+ The data-type is also pickleable, to ensure we can move it between
+ processes with :class:`multiprocessing.Queue`\s.
+
+ >>> import pickle
+ >>> s = pickle.dumps(d)
+ >>> z = pickle.loads(s)
+ >>> z
+ Data([[ 0., 1.],
+ [ 10., 11.],
+ [ 20., 21.]])
+ >>> z.info
+ {'columns': ['distance (m)', 'force (N)']}
"""
- def __new__(self, subtype, shape, dtype=numpy.float, buffer=None, offset=0,
+ def __new__(subtype, shape, dtype=numpy.float, buffer=None, offset=0,
strides=None, order=None, info=None):
"""Create the ndarray instance of our type, given the usual
input arguments. This will call the standard ndarray
constructor, but return an object of our type.
"""
- obj = np.ndarray.__new__(subtype=subtype, shape=shape, dtype=dtype,
- buffer=buffer, offset=offset, strides=strides,
- order=order)
+ obj = numpy.ndarray.__new__(
+ subtype, shape, dtype, buffer, offset, strides, order)
# add the new attribute to the created instance
if info == None:
info = {}
self.info = getattr(obj, 'info', {})
# We do not need to return anything
+ def __reduce__(self):
+ """Collapse an instance for pickling.
+
+ Returns
+ -------
+ reconstruct : callable
+ Called to create the initial version of the object.
+ args : tuple
+ A tuple of arguments for `reconstruct`
+ state : (optional)
+ The state to be passed to __setstate__, if present.
+ iter : iterator (optional)
+ Yielded items will be appended to the reconstructed
+ object.
+ dict : iterator (optional)
+ Yielded (key,value) tuples pushed back onto the
+ reconstructed object.
+ """
+ base_reduce = list(numpy.ndarray.__reduce__(self))
+ # tack our stuff onto ndarray's setstate portion.
+ base_reduce[2] = (base_reduce[2], (self.info,))
+ return tuple(base_reduce)
+
+ def __setstate__(self, state):
+ base_class_state,own_state = state
+ numpy.ndarray.__setstate__(self, base_class_state)
+ self.info, = own_state
+
class Curve (object):
"""A grouped set of :class:`Data` runs from the same file with metadata.
`experiment`. These are two strings that can be used by Hooke
commands/plugins to understand what they are looking at.
- * `.info['filetype']` should contain the name of the exact
+ * :attr:`info['filetype']` should contain the name of the exact
filetype defined by the driver (so that filetype-speciofic
commands can know if they're dealing with the correct filetype).
- * `.info['experiment']` should contain an instance of a
+ * :attr:`info['experiment']` should contain an instance of a
:class:`hooke.experiment.Experiment` subclass to identify the
experiment type. For example, various
:class:`hooke.driver.Driver`\s can read in force-clamp data, but
Hooke commands could like to know if they're looking at force
clamp data, regardless of their origin.
+
+ Another important attribute is :attr:`command_stack`, which holds
+ a :class:`~hooke.command_stack.CommandStack` listing the commands
+ that have been applied to the `Curve` since loading.
"""
def __init__(self, path, info=None):
#the data dictionary contains: {name of data: list of data sets [{[x], [y]}]
self.path = path
self.driver = None
- self.data = []
+ self.data = None
if info == None:
info = {}
self.info = info
self.name = os.path.basename(path)
+ self.command_stack = CommandStack()
+ self._hooke = None # Hooke instance for Curve.load()
+
+ def __str__(self):
+ return str(self.__unicode__())
+
+ def __unicode__(self):
+ return u'<%s %s>' % (self.__class__.__name__, self.name)
+
+ def __repr__(self):
+ return self.__str__()
+
+ def set_hooke(self, hooke=None):
+ if hooke != None:
+ self._hooke = hooke
def identify(self, drivers):
"""Identify the appropriate :class:`hooke.driver.Driver` for
the curve file (`.path`).
"""
+ if 'filetype' in self.info:
+ driver = [d for d in drivers if d.name == self.info['filetype']]
+ if len(driver) == 1:
+ driver = driver[0]
+ if driver.is_me(self.path):
+ self.driver = driver
+ return
for driver in drivers:
if driver.is_me(self.path):
self.driver = driver # remember the working driver
return
raise NotRecognized(self)
- def load(self):
+ def load(self, hooke=None):
"""Use the driver to read the curve into memory.
+
+ Also runs any commands in :attr:`command_stack`. All
+ arguments are passed through to
+ :meth:`hooke.command_stack.CommandStack.execute`.
+ """
+ self.set_hooke(hooke)
+ log = logging.getLogger('hooke')
+ log.debug('loading curve %s with driver %s' % (self.name, self.driver))
+ data,info = self.driver.read(self.path, self.info)
+ self.data = data
+ for key,value in info.items():
+ self.info[key] = value
+ if self._hooke != None:
+ self.command_stack.execute(self._hooke)
+ elif len(self.command_stack) > 0:
+ log.warn(
+ 'could not execute command stack for %s without Hooke instance'
+ % self.name)
+
+ def unload(self):
+ """Release memory intensive :attr:`.data`.
"""
- pass
+ log = logging.getLogger('hooke')
+ log.debug('unloading curve %s' % self.name)
+ self.data = None
projects / hooke.git / blobdiff