Multiple lib changes

This commit is contained in:
2007-01-25 11:58:10 +00:00
parent a65d79697f
commit 1c2c2c8895
7 changed files with 519 additions and 152 deletions

View File

@@ -1,7 +1,9 @@
"""This module contains bilinear models(Functions)
"""
import pygtk
import gtk
import gtk.glade
from fluents.workflow import Function, OptionsDialog, Options
from fluents.dataset import Dataset
from fluents import plots, dataset, workflow, logger
@@ -12,7 +14,7 @@ from cx_utils import mat_center
from validation import *
import blmplots
import engines
import copy
class Model(Function):
"""Base class of bilinear models.
@@ -39,23 +41,42 @@ class PCA(Model):
Model.__init__(self,id,name)
self._options = PcaOptions()
def pre_validation(self, amax, n_sets, val_engine):
"""Model calculations for maximum number of components.
def validation(self, amax, cv_val_sets, pert_val_sets, cv_val_method, pert_val_method):
"""Model validation and estimate of optimal numer of components.
"""
rmsep = val_engine(self.model['E0'], amax, n_sets)
self.model['rmsep'] = rmsep
self.model['aopt'] = rmsep.argmin()
if self._options['calc_cv']:
if cv_val_method == 'random':
sep, aopt = pca_cv_val(self.model['E0'], amax, cv_val_sets)
self.model['sep'] = sep
if self._options['calc_pert']:
if pert_val_method == 'random_diag':
sep, aopt = pca_alter_val(self.model['E0'], amax, pert_val_sets)
self.model['sep'] = sep
if self._options['calc_cv']==False and self._options['calc_pert']==False:
self.model['sep'] = None
aopt = self._options['amax']
if self._options['auto_aopt']:
logger.log("notice", "Auto aopt: " + str(aopt))
self._options['aopt'] = aopt
if aopt==1:
logger.log('notice', 'Aopt at first component!')
def confidence(self, aopt, n_sets, alpha, p_center,
crot, strict, cov_center ):
"""Returns a confidence measure for model parameters.
Based on aopt.
"""
aopt = self.model['aopt']
if aopt<2:
aopt = 2
logger.log('notice','Hotellings T2 needs more than 1 comp.\n switching to 2!!')
jk_segments = pca_jkP(self.model['E0'], aopt, n_sets)
Pcal = self.model['P'][:,:aopt]
tsq = hotelling(jk_segments, Pcal, p_center,
cov_center, alpha, crot, strict)
cov_center, alpha, crot, strict)
self.model['p_tsq'] = tsq
def make_model(self, amax, mode, scale):
@@ -96,8 +117,8 @@ class PCA(Model):
# vars
ids_1 = [dim_name_1, DX.get_identifiers(dim_name_1, sorted=True)]
# components (hidden)
pc_ids = ['_comp_a', map(str,range(self.model['aopt'])) ]
pc_ids_opt = ['_comp_o', map(str, range(self.model['aopt'])) ]
pc_ids = ['_amax', map(str,range(self._options['amax'])) ]
pc_ids_opt = ['_aopt', map(str, range(self._options['aopt'])) ]
zero_dim = ['_doe', ['0']] # null dim, vector (hidden)
match_ids = {'E':[ids_0, ids_1],
'E0':[ids_0, ids_1],
@@ -121,8 +142,7 @@ class PCA(Model):
#try:
out.append(plt(self))
#except:
# print plt
#logger.log('debug', 'Plot: %s failed') %plt
# logger.log('debug', 'Plot: %s failed') %str(plt)
return out
def run_o(self, data):
@@ -130,6 +150,8 @@ class PCA(Model):
"""
self.clear()
options = self._options
for item in options.items():
print item
self._dataset['X'] = data
self._data['X'] = data.asarray().astype('<f8')
if options['center']:
@@ -137,8 +159,9 @@ class PCA(Model):
self.model['E0'] = center(self._data['X'])
else:
self.model['E0'] = data.asarray()
self.pre_validation(**options.pre_validation_options())
self.validation(**options.validation_options())
self.model['aopt'] = self._options['aopt']
self.make_model(**options.make_model_options())
if options['calc_conf']:
self.confidence(**options.confidence_options())
@@ -159,7 +182,6 @@ class PCA(Model):
if response == gtk.RESPONSE_OK:
# set output data and plots
dialog.set_output()
#run with current data and options
return self.run_o(data)
@@ -172,10 +194,10 @@ class PLS(Model):
def pre_validation(self, amax, n_sets, val_engine):
"""Returns rmsec,rmsep for model.
"""
rmsep = val_engine(self.model['E0'], self.model['F0'],
rmsep, aopt = val_engine(self.model['E0'], self.model['F0'],
amax, n_sets)
self.model['rmsep'] = rmsep.mean(0)
self.model['aopt'] = rmsep.mean(0).argmin()
self.model['aopt'] = aopt
def confidence(self, aopt, n_sets, alpha, p_center,
crot, strict, cov_center ):
@@ -341,34 +363,39 @@ class PcaOptions(Options):
opt['algo'] = 'pca'
opt['engine'] = engines.pca
opt['mode'] = 'normal' # how much info to calculate
opt['lod'] = 'compact' # how much info to store
opt['amax'] = 5
opt['aopt'] = 5
opt['amax'] = 10
opt['aopt'] = 100
opt['auto_aopt'] = False
opt['center'] = True
opt['center_mth'] = mat_center
opt['scale'] = 'scores'
opt['calc_conf'] = True
opt['n_sets'] = 5
opt['calc_conf'] = False
opt['n_sets'] = 5
opt['strict'] = True
opt['p_center'] = 'med'
opt['alpha'] = .8
opt['cov_center'] = 'med'
opt['crot'] = True
opt['val_engine'] = pca_alter_val
opt['val_n_sets'] = 10
opt['calc_cv'] = False
opt['calc_pert'] = True
opt['pert_val_method'] = 'random_diag'
opt['cv_val_method'] = 'random'
opt['cv_val_sets'] = 10
opt['pert_val_sets'] = 10
opt['all_data'] = [('T', 'scores', True),
('P', 'loadings', True),
('E','residuals', False),
('p_tsq', 't2', False),
('rmsep', 'root mean square error of prediction', False)
('rmsep', 'RMSEP', False)
]
opt['all_plots'] = [(blmplots.PcaScorePlot, 'Scores', True),
(blmplots.PcaLoadingPlot, 'Loadings', True),
(blmplots.LineViewXc, 'Line view', True)
(blmplots.LineViewXc, 'Line view', True),
(blmplots.PredictionErrorPlot, 'Residual Error', True)
]
opt['out_data'] = ['T','P', 'p_tsq']
@@ -387,9 +414,10 @@ class PcaOptions(Options):
'strict', 'crot', 'cov_center']
return self._copy_from_list(opt_list)
def pre_validation_options(self):
def validation_options(self):
"""Options for pre_validation method."""
opt_list = ['amax', 'n_sets', 'val_engine']
opt_list = ['amax', 'cv_val_sets', 'pert_val_sets',
'cv_val_method', 'pert_val_method']
return self._copy_from_list(opt_list)
@@ -411,7 +439,7 @@ class PlsOptions(Options):
opt['center'] = True
opt['center_mth'] = mat_center
opt['scale'] = 'scores'
opt['calc_conf'] = True
opt['calc_conf'] = False
opt['n_sets'] = 10
opt['strict'] = True
@@ -419,14 +447,16 @@ class PlsOptions(Options):
opt['alpha'] = .2
opt['cov_center'] = 'med'
opt['crot'] = True
opt['calc_cv'] = True
opt['calc_pert'] = False
opt['val_engine'] = w_pls_cv_val
opt['all_data'] = [('T', 'scores', True),
('P', 'loadings', True),
('E','residuals', False),
('p_tsq', 't2', False),
('rmsep', 'root mean square error of prediction', False)
('rmsep', 'RMSEP', False)
]
opt['all_plots'] = [(blmplots.PlsScorePlot, 'Scores', True),
@@ -434,7 +464,7 @@ class PlsOptions(Options):
(blmplots.LineViewXc, 'Line view', True)]
opt['out_plots'] = [blmplots.PlsScorePlot,
blmplots.PlsLoadingPlot,
blmplots.PlsLoadingPlot,
blmplots.LineViewXc]
opt['out_data'] = None
@@ -453,7 +483,7 @@ class PlsOptions(Options):
def confidence_options(self):
"""Options for confidence method."""
opt_list = ['n_sets', 'aopt', 'alpha', 'p_center',
'strict', 'crot', 'cov_center']
'strict', 'crot', 'cov_center']
return self._copy_from_list(opt_list)
def pre_validation_options(self):
@@ -468,9 +498,175 @@ class PcaOptionsDialog(OptionsDialog):
def __init__(self, data, options, input_names=['X']):
OptionsDialog.__init__(self, data, options, input_names)
glade_file = "/home/flatberg/Projects/project4/project4.glade"
notebook_name = "vbox1"
page_name = "Options"
self.add_page_from_glade(glade_file, notebook_name, page_name)
# connect signals to handlers
dic = {"on_amax_value_changed" : self.on_amax_changed,
"on_aopt_value_changed" : self.on_aopt_changed,
"auto_aopt_toggled" : self.auto_aopt_toggled,
"center_toggled" : self.center_toggled,
"on_scale_changed" : self.on_scale_changed,
"on_val_none" : self.val_toggled,
"on_val_cv" : self.cv_toggled,
"on_val_pert" : self.pert_toggled,
"on_cv_method_changed" : self.on_cv_method_changed,
"on_cv_sets_changed" : self.on_cv_sets_changed,
"on_pert_sets_changed" : self.on_pert_sets_changed,
"on_conf_toggled" : self.on_conf_toggled
}
self.wTree.signal_autoconnect(dic)
# set/ensure valid default values/ranges
amax_sb = self.wTree.get_widget("amax_spinbutton")
max_comp = min(data[0].shape) # max num of components
if self._options['amax']>max_comp:
logger.log('debug', 'amax default too large ... adjusting')
self._options['amax'] = max_comp
amax_sb.get_adjustment().set_all(self._options['amax'], 1, max_comp, 1, 0, 0)
# aopt spin button
aopt_sb = self.wTree.get_widget("aopt_spinbutton")
if self._options['aopt']>self._options['amax']:
self._options['aopt'] = self._options['amax'] + 1 - 1
aopt_sb.get_adjustment().set_all(self._options['aopt'], 1, self._options['amax'], 1, 0, 0)
# scale
scale_cb = self.wTree.get_widget("scale_combobox")
scale_cb.set_active(0)
# validation frames
if self._options['calc_cv']==False:
cv_frame = self.wTree.get_widget("cv_frame")
cv_frame.set_sensitive(False)
if self._options['calc_pert']==False:
pert_frame = self.wTree.get_widget("pert_frame")
pert_frame.set_sensitive(False)
cv = self.wTree.get_widget("cv_method").set_active(0)
pm = self.wTree.get_widget("pert_method").set_active(0)
# confidence
if self._options['calc_conf']==True:
self.wTree.get_widget("subset_frame").set_sensitive(True)
else:
self.wTree.get_widget("subset_frame").set_sensitive(False)
def on_amax_changed(self, sb):
logger.log("debug", "amax changed: new value: %s" %sb.get_value_as_int())
amax = sb.get_value_as_int()
# update aopt if needed
if amax<self._options['aopt']:
self._options['aopt'] = amax
aopt_sb = self.wTree.get_widget("aopt_spinbutton")
aopt_sb.get_adjustment().set_all(self._options['aopt'], 1, amax, 1, 0, 0)
self._options['amax'] = sb.get_value_as_int()
def on_aopt_changed(self, sb):
aopt = sb.get_value_as_int()
self._options['aopt'] = aopt
def auto_aopt_toggled(self, tb):
aopt_sb = self.wTree.get_widget("aopt_spinbutton")
if tb.get_active():
self._options['auto_aopt'] = True
aopt_sb.set_sensitive(False)
else:
self._options['auto_aopt'] = False
aopt_sb.set_sensitive(True)
def center_toggled(self, tb):
if tb.get_active():
self._options['center'] = True
else:
logger.log("debug", "centering set to False")
self._options['center'] = False
def on_scale_changed(self, cb):
scale = cb.get_active_text()
if scale=='Scores':
self._options['scale'] = 'scores'
elif scale=='Loadings':
self._options['scale'] = 'loads'
else:
raise IOError
def val_toggled(self, tb):
"""Callback for validation: None. """
cv_frame = self.wTree.get_widget("cv_frame")
pert_frame = self.wTree.get_widget("pert_frame")
cv_tb = self.wTree.get_widget("cv_toggle")
p_tb = self.wTree.get_widget("pert_toggle")
if tb.get_active():
self._options['calc_cv'] = False
self._options['calc_pert'] = False
cv_frame.set_sensitive(False)
pert_frame.set_sensitive(False)
cv_tb.set_sensitive(False)
p_tb.set_sensitive(False)
else:
p_tb.set_sensitive(True)
cv_tb.set_sensitive(True)
if p_tb.get_active():
pert_frame.set_sensitive(True)
self._options['calc_pert'] = True
if cv_tb.get_active():
cv_frame.set_sensitive(True)
self._options['calc_cv'] = True
def cv_toggled(self, tb):
cv_frame = self.wTree.get_widget("cv_frame")
if tb.get_active():
cv_frame.set_sensitive(True)
self._options['calc_cv'] = True
else:
cv_frame.set_sensitive(False)
self._options['calc_cv'] = False
def pert_toggled(self, tb):
pert_frame = self.wTree.get_widget("pert_frame")
if tb.get_active():
pert_frame.set_sensitive(True)
self._options['calc_pert'] = True
else:
pert_frame.set_sensitive(False)
self._options['calc_pert'] = False
def on_cv_method_changed(self, cb):
method = cb.get_active_text()
if method == 'Random':
self._options['cv_val_method'] = 'random'
def on_pert_method_changed(self, cb):
method = cb.get_active_text()
if method == 'Random diags':
self._options['pert_val_method'] = 'random_diag'
def on_cv_sets_changed(self, sb):
val = sb.get_value_as_int()
self._options['cv_val_sets'] = val
def on_pert_sets_changed(self, sb):
val = sb.get_value_as_int()
self._options['pert_val_sets'] = val
def on_conf_toggled(self, tb):
if tb.get_active():
self._options['calc_conf'] = False
self.wTree.get_widget("subset_frame").set_sensitive(False)
else:
self._options['calc_conf'] = True
self.wTree.get_widget("subset_frame").set_sensitive(True)
class PlsOptionsDialog(OptionsDialog):
"""Options dialog for Partial Least Squares Regression.
"""
def __init__(self, data, options, input_names=['X', 'Y']):
OptionsDialog.__init__(self, data, options, input_names)