1 # calibcant - tools for thermally calibrating AFM cantilevers
3 # Copyright (C) 2008-2012 W. Trevor King <wking@drexel.edu>
5 # This file is part of calibcant.
7 # calibcant is free software: you can redistribute it and/or modify it under
8 # the terms of the GNU General Public License as published by the Free Software
9 # Foundation, either version 3 of the License, or (at your option) any later
12 # calibcant is distributed in the hope that it will be useful, but WITHOUT ANY
13 # WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
14 # A PARTICULAR PURPOSE. See the GNU General Public License for more details.
16 # You should have received a copy of the GNU General Public License along with
17 # calibcant. If not, see <http://www.gnu.org/licenses/>.
19 """Temperature analysis.
21 Separate the more general `T_analyze()` from the other `T_*()`
22 functions in calibcant.
24 The relevant physical quantities are:
26 * `T` Temperature at which thermal vibration measurements were acquired
31 >>> from .config import TemperatureConfig
32 >>> from h5config.storage.hdf5 import pprint_HDF5, HDF5_Storage
34 >>> fd,filename = tempfile.mkstemp(suffix='.h5', prefix='calibcant-')
37 >>> temperature_config = TemperatureConfig(storage=HDF5_Storage(
38 ... filename=filename, group='/T/config/'))
40 >>> raw_T = numpy.array([22, 23.5, 24])
41 >>> processed_T = T_analyze(raw_T, temperature_config)
42 >>> T_plot(raw_T=raw_T, processed_T=processed_T)
43 >>> T_save(filename=filename, group='/T/', raw_T=raw_T,
44 ... temperature_config=temperature_config, processed_T=processed_T)
46 >>> pprint_HDF5(filename) # doctest: +REPORT_UDIFF
50 <HDF5 dataset "default": shape (), type "|b1">
52 <HDF5 dataset "units": shape (), type "|S7">
54 <HDF5 dataset "processed": shape (3,), type "<f8">
55 [ 295.15 296.65 297.15]
56 <HDF5 dataset "raw": shape (3,), type "<f8">
59 >>> raw_T,temperature_config,processed_T = T_load(
60 ... filename=filename, group='/T/')
61 >>> print temperature_config.dump()
65 array([ 22. , 23.5, 24. ])
67 <type 'numpy.ndarray'>
69 array([ 295.15, 296.65, 297.15])
71 >>> os.remove(filename)
75 from scipy.constants import C2K as _C2K
78 import matplotlib as _matplotlib
79 import matplotlib.pyplot as _matplotlib_pyplot
80 import time as _time # for timestamping lines on plots
81 except (ImportError, RuntimeError), e:
83 _matplotlib_import_error = e
85 from h5config.storage.hdf5 import HDF5_Storage as _HDF5_Storage
86 from h5config.storage.hdf5 import h5_create_group as _h5_create_group
88 from . import LOG as _LOG
89 from . import package_config as _package_config
90 from .config import Celsius as _Celsius
91 from .config import Kelvin as _Kelvin
92 from .config import TemperatureConfig as _TemperatureConfig
95 def T_analyze(T, temperature_config):
96 """Convert measured temperature to Kelvin.
98 `T` should be a numpy ndarray or scalar. `temperature_config`
99 should be a `config._TemperatureConfig` instance.
101 if temperature_config['units'] == _Celsius:
106 def T_save(filename, group='/', raw_T=None, temperature_config=None,
108 with _h5py.File(filename, 'a') as f:
109 cwg = _h5_create_group(f, group)
110 if raw_T is not None:
116 if temperature_config is not None:
117 config_cwg = _h5_create_group(cwg, 'config')
118 storage = _HDF5_Storage()
119 storage.save(config=temperature_config, group=config_cwg)
120 if processed_T is not None:
125 cwg['processed'] = processed_T
127 def T_load(filename, group='/'):
128 assert group.endswith('/')
129 raw_T = processed_T = None
130 with _h5py.File(filename, 'a') as f:
132 raw_T = f[group+'raw'][...]
135 temperature_config = _TemperatureConfig(storage=_HDF5_Storage(
136 filename=filename, group=group+'config/'))
138 processed_T = f[group+'processed'][...]
141 temperature_config.load()
142 return (raw_T, temperature_config, processed_T)
144 def T_plot(raw_T=None, processed_T=None):
146 raise _matplotlib_import_error
147 figure = _matplotlib_pyplot.figure()
148 timestamp = _time.strftime('%H%M%S')
150 if processed_T is None:
151 return # nothing to plot
153 axes2 = figure.add_subplot(1, 1, 1)
154 elif processed_T is None:
155 axes1 = figure.add_subplot(1, 1, 1)
158 axes1 = figure.add_subplot(2, 1, 1)
159 axes2 = figure.add_subplot(2, 1, 2)
161 axes1.set_title('Raw Temperatures %s' % timestamp)
162 axes1.plot(raw_T, label='raw')
164 axes2.set_title('Processed Temperatures %s' % timestamp)
165 axes2.plot(processed_T, label='processed')
166 if hasattr(figure, 'show'):