1 # calibcant - tools for thermally calibrating AFM cantilevers
3 # Copyright (C) 2008-2011 W. Trevor King <wking@drexel.edu>
5 # This file is part of calibcant.
7 # calibcant is free software: you can redistribute it and/or
8 # modify it under the terms of the GNU Lesser General Public
9 # License as published by the Free Software Foundation, either
10 # version 3 of the License, or (at your option) any later version.
12 # calibcant is distributed in the hope that it will be useful,
13 # but WITHOUT ANY WARRANTY; without even the implied warranty of
14 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
15 # GNU Lesser General Public License for more details.
17 # You should have received a copy of the GNU Lesser General Public
18 # License along with calibcant. If not, see
19 # <http://www.gnu.org/licenses/>.
21 """Temperature analysis.
23 Separate the more general `T_analyze()` from the other `T_*()`
24 functions in calibcant.
26 The relevant physical quantities are:
28 * `T` Temperature at which thermal vibration measurements were acquired
33 >>> from .config import TemperatureConfig
34 >>> from h5config.storage.hdf5 import pprint_HDF5, HDF5_Storage
36 >>> fd,filename = tempfile.mkstemp(suffix='.h5', prefix='calibcant-')
39 >>> temperature_config = TemperatureConfig(storage=HDF5_Storage(
40 ... filename=filename, group='/T/config/'))
42 >>> raw_T = numpy.array([22, 23.5, 24])
43 >>> processed_T = T_analyze(raw_T, temperature_config)
44 >>> T_plot(raw_T=raw_T, processed_T=processed_T)
45 >>> T_save(filename=filename, group='/T/', raw_T=raw_T,
46 ... temperature_config=temperature_config, processed_T=processed_T)
48 >>> pprint_HDF5(filename) # doctest: +REPORT_UDIFF
52 <HDF5 dataset "default": shape (), type "|b1">
54 <HDF5 dataset "units": shape (), type "|S7">
56 <HDF5 dataset "processed": shape (3,), type "<f8">
57 [ 295.15 296.65 297.15]
58 <HDF5 dataset "raw": shape (3,), type "<f8">
61 >>> raw_T,temperature_config,processed_T = T_load(
62 ... filename=filename, group='/T/')
63 >>> print temperature_config.dump()
67 array([ 22. , 23.5, 24. ])
69 <type 'numpy.ndarray'>
71 array([ 295.15, 296.65, 297.15])
73 >>> os.remove(filename)
77 from scipy.constants import C2K as _C2K
80 import matplotlib as _matplotlib
81 import matplotlib.pyplot as _matplotlib_pyplot
82 import time as _time # for timestamping lines on plots
83 except (ImportError, RuntimeError), e:
85 _matplotlib_import_error = e
87 from h5config.storage.hdf5 import HDF5_Storage as _HDF5_Storage
88 from h5config.storage.hdf5 import h5_create_group as _h5_create_group
90 from . import LOG as _LOG
91 from . import package_config as _package_config
92 from .config import Celsius as _Celsius
93 from .config import Kelvin as _Kelvin
94 from .config import TemperatureConfig as _TemperatureConfig
97 def T_analyze(T, temperature_config):
98 """Convert measured temperature to Kelvin.
100 `T` should be a numpy ndarray or scalar. `temperature_config`
101 should be a `config._TemperatureConfig` instance.
103 if temperature_config['units'] == _Celsius:
108 def T_save(filename, group='/', raw_T=None, temperature_config=None,
110 with _h5py.File(filename, 'a') as f:
111 cwg = _h5_create_group(f, group)
112 if raw_T is not None:
118 if temperature_config:
119 config_cwg = _h5_create_group(cwg, 'config')
120 temperature_config.save(group=config_cwg)
121 if processed_T is not None:
126 cwg['processed'] = processed_T
128 def T_load(filename, group='/'):
129 assert group.endswith('/')
130 raw_T = processed_T = None
131 with _h5py.File(filename, 'a') as f:
133 raw_T = f[group+'raw'][...]
136 temperature_config = _TemperatureConfig(storage=_HDF5_Storage(
137 filename=filename, group=group+'config/'))
139 processed_T = f[group+'processed'][...]
142 temperature_config.load()
143 return (raw_T, temperature_config, processed_T)
145 def T_plot(raw_T=None, processed_T=None):
147 raise _matplotlib_import_error
148 figure = _matplotlib_pyplot.figure()
149 timestamp = _time.strftime('%H%M%S')
151 if processed_T is None:
152 return # nothing to plot
154 axes2 = figure.add_subplot(1, 1, 1)
155 elif processed_T is None:
156 axes1 = figure.add_subplot(1, 1, 1)
159 axes1 = figure.add_subplot(2, 1, 1)
160 axes2 = figure.add_subplot(2, 1, 2)
162 axes1.set_title('Raw Temperatures %s' % timestamp)
163 axes1.plot(raw_T, label='raw')
165 axes2.set_title('Processed Temperatures %s' % timestamp)
166 axes2.plot(processed_T, label='processed')