name='export block',
arguments=[
CurveArgument,
- Argument(name='block', aliases=['set'], type='int', default=0,
+ Argument(name='block', type='int', default=0,
help="""
Data block to save. For an approach/retract force curve, `0` selects
the approaching curve and `1` selects the retracting curve.
f.close()
class DifferenceCommand (Command):
- """Calculate the difference between two blocks of data.
+ """Calculate the difference between two columns of data.
+
+ The difference is added to block A as a new column.
+
+ Note that the command will fail if the columns have different
+ lengths, so be careful when differencing columns from different
+ blocks.
"""
def __init__(self, plugin):
super(DifferenceCommand, self).__init__(
- name='block difference',
+ name='difference',
arguments=[
CurveArgument,
- Argument(name='block one', aliases=['set one'], type='int',
- default=1,
+ Argument(name='block A', type='int',
help="""
Block A in A-B. For an approach/retract force curve, `0` selects the
-approaching curve and `1` selects the retracting curve.
+approaching curve and `1` selects the retracting curve. Defaults to
+the first block.
+""".strip()),
+ Argument(name='block B', type='int',
+ help="""
+Block B in A-B. Defaults to matching `block A`.
+""".strip()),
+ Argument(name='column A', type='string',
+ help="""
+Column of data from block A to difference. Defaults to the first column.
""".strip()),
- Argument(name='block two', aliases=['set two'], type='int',
- default=0,
- help='Block B in A-B.'),
- Argument(name='x column', type='int', default=0,
+ Argument(name='column B', type='string', default=1,
help="""
-Column of data to return as x values.
+Column of data from block B to difference. Defaults to matching `column A`.
""".strip()),
- Argument(name='y column', type='int', default=1,
+ Argument(name='output column name', type='string',
help="""
-Column of data block to difference.
+Name of the new column for storing the difference (without units, defaults to
+`difference of <block A> <column A> and <block B> <column B>`).
""".strip()),
],
help=self.__doc__, plugin=plugin)
def _run(self, hooke, inqueue, outqueue, params):
- a = params['curve'].data[params['block one']]
- b = params['curve'].data[params['block two']]
- assert a[:,params['x column']] == b[:,params['x column']]
- out = Data((a.shape[0],2), dtype=a.dtype)
- out[:,0] = a[:,params['x column']]
- out[:,1] = a[:,params['y column']] - b[:,params['y column']]
- outqueue.put(out)
+ data_A = params['curve'].data[params['block A']]
+ data_B = params['curve'].data[params['block B']]
+ # HACK? rely on params['curve'] being bound to the local hooke
+ # playlist (i.e. not a copy, as you would get by passing a
+ # curve through the queue). Ugh. Stupid queues. As an
+ # alternative, we could pass lookup information through the
+ # queue...
+ new = Data((data_A.shape[0], data_A.shape[1]+1), dtype=data_A.dtype)
+ new.info = copy.deepcopy(data.info)
+ new[:,:-1] = data_A
+
+ a_col = data_A.info['columns'].index(params['column A'])
+ b_col = data_A.info['columns'].index(params['column A'])
+ out = data_A[:,a_col] - data_B[:,b_col]
+
+ a_name,a_units = split_data_label(params['column A'])
+ b_name,b_units = split_data_label(params['column B'])
+ assert a_units == b_units, (
+ 'Unit missmatch: %s != %s' % (a_units, b_units))
+ if params['output column name'] == None:
+ params['output column name'] = (
+ 'difference of %s %s and %s %s' % (
+ block_A.info['name'], params['column A'],
+ block_B.info['name'], params['column B']))
+ new.info['columns'].append(
+ join_data_label(params['output distance column'], a_units)
+ new[:,-1] = out
+ params['curve'].data[params['block A']] = new
+
class DerivativeCommand (Command):
"""Calculate the derivative (actually, the discrete differentiation)
"""
def __init__(self, plugin):
super(DerivativeCommand, self).__init__(
- name='block derivative',
+ name='derivative',
arguments=[
CurveArgument,
- Argument(name='block', aliases=['set'], type='int', default=0,
+ Argument(name='block', type='int', default=0,
help="""
Data block to differentiate. For an approach/retract force curve, `0`
selects the approaching curve and `1` selects the retracting curve.
""".strip()),
Argument(name='output column name', type='string',
help="""
-Name of the new column for storing the derivative (without units, defaults to `derivative of <f column name> with respect to <x column name>`).
+Name of the new column for storing the derivative (without units, defaults to
+`derivative of <f column name> with respect to <x column name>`).
""".strip()),
],
help=self.__doc__, plugin=plugin)
"""
def __init__(self, plugin):
super(PowerSpectrumCommand, self).__init__(
- name='block power spectrum',
+ name='power spectrum',
arguments=[
CurveArgument,
- Argument(name='block', aliases=['set'], type='int', default=0,
+ Argument(name='block', type='int', default=0,
help="""
Data block to act on. For an approach/retract force curve, `0`
selects the approaching curve and `1` selects the retracting curve.
""".strip()),
Argument(name='output block name', type='string',
help="""
-Name of the new data block (defaults to `power spectrum of <source block name> <source column name>`) for storing the power spectrum.
+Name of the new data block for storing the power spectrum (defaults to
+`power spectrum of <source block name> <source column name>`).
""".strip()),
],
help=self.__doc__, plugin=plugin)