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Some stuff on tasks.

This commit is contained in:
Einar Ryeng 2007-09-03 13:22:11 +00:00
parent 16ed2fd9c9
commit bfb039328c
2 changed files with 29 additions and 276 deletions

View File

@ -88,12 +88,6 @@ class Workflow:
for fun in stage.functions:
print ' %s' % fun.name
# def add_project(self,project):
# if project == None:
# logger.log('notice','Proejct is empty')
# logger.log('notice','Project added in : %s' %self.name)
# self.project = project
class EmptyWorkflow(Workflow):
name = 'Empty Workflow'
@ -122,24 +116,32 @@ class Stage:
self.functions_by_id[fun.id] = fun
class Function:
class Task:
"""A Function object encapsulates a function on a data set.
Each Function instance encapsulates some function that can be applied
to one or more types of data.
"""
def __init__(self, id, name):
self.id = id
self.name = name
title = ""
def __init__(self, input):
self.input = input
self.options = Options()
self.datasets = {}
self.arrays = {}
self.plots = {}
# just return a Validation object
def validate_input(input):
return Validation(True,"Validation Not Implemented")
def run(self):
pass
print self.input
def show_options_gui(self, editable=False):
pass
class Validation:
def __init__(self,result, reason):
@ -461,3 +463,9 @@ class WorkflowMenu (gtk.Menu):
menuitem.show()
return menuitem
class Options():
def __init__(self):
pass

View File

@ -10,113 +10,28 @@ class TestWorkflow (workflow.Workflow):
name = 'Test Workflow'
ident = 'test'
description = 'Test Gene Ontology Workflow. This workflow currently serves as a general testing workflow.'
description = 'This workflow currently serves as a general testing workflow.'
def __init__(self, app):
workflow.Workflow.__init__(self, app)
load = workflow.Stage('load', 'Load Data')
load.add_function(CelFileImportFunction())
load.add_function(DataLoadTestFunction(self))
load = workflow.Stage('load', 'Test Data')
load.add_function(TestDataFunction())
load.add_function(DatasetLoadFunction())
load.add_function(SelectFunction())
self.add_stage(load)
preproc = workflow.Stage('preprocess', 'Preprocessing')
preproc.add_function(DatasetLog())
preproc.add_function(workflow.Function('rma', 'RMA'))
self.add_stage(preproc)
go = workflow.Stage('go', 'Gene Ontology Data')
go.add_function(GODistanceFunction())
go.add_function(ImagePlotFunction())
self.add_stage(go)
regression = workflow.Stage('regression', 'Regression')
regression.add_function(workflow.Function('pls', 'PLS'))
self.add_stage(regression)
explore = workflow.Stage('explore', 'Explorative analysis')
explore.add_function(PCAFunction(self))
self.add_stage(explore)
save = workflow.Stage('save', 'Save Data')
save.add_function(DatasetSaveFunction())
self.add_stage(save)
class LoadAnnotationsFunction(workflow.Function):
class TestDataTask(workflow.Task):
title = "Test data"
def __init__(self):
workflow.Function.__init__(self, 'load-go-ann', 'Load Annotations')
self.annotations = None
def load_file(self, filename):
f = open(filename)
self.annotations = Annotations('genes', 'go-terms')
logger.log('notice', 'Loading annotation file: %s' % filename)
for line in f.readlines():
val = line.split(' \t')
if len(val) > 1:
val = [v.strip() for v in val]
retval.add_annotations('genes', val[0],
'go-terms', set(val[1:]))
def on_response(self, dialog, response):
if response == gtk.RESPONSE_OK:
logger.log('notice', 'Reading file: %s' % dialog.get_filename())
self.load_file(dialog.get_filename())
def run(self):
btns = ('Open', gtk.RESPONSE_OK, \
'Cancel', gtk.RESPONSE_CANCEL)
dialog = gtk.FileChooserDialog('Open GO Annotation File',
buttons=btns)
dialog.connect('response', self.on_response)
dialog.run()
dialog.destroy()
return [self.annotations]
class GODistanceFunction(workflow.Function):
def __init__(self):
workflow.Function.__init__(self, 'go_diatance', 'GO Distances')
self.output = None
def run(self, data):
logger.log('debug', 'datatype: %s' % type(data))
if not type(data) == Annotations:
return None
logger.log('debug', 'dimensions: %s' % data.dimensions)
genes = data.get_ids('genes')
gene_distances = array((len(genes), len(genes)))
return gene_distances
class ImagePlotFunction(workflow.Function):
def __init__(self):
workflow.Function.__init__(self, 'image', 'Show Image')
def run(self, data):
return [plots.ImagePlot(data, name='foo')]
class TestDataFunction(workflow.Function):
def __init__(self):
workflow.Function.__init__(self, 'test_data', 'Generate Test Data')
workflow.Task.__init__(self)
def run(self):
logger.log('notice', 'Injecting foo test data')
x = randn(500,15)
X = dataset.Dataset(x)
p = plots.ScatterPlot(X, X, 'rows', 'rows', '0_1', '0_2',name='scatter')
p2 = plots.ScatterMarkerPlot(X, X, 'rows', 'rows', '0_1', '0_2',name='marker')
# p2 = plots.ScatterMarkerPlot(X, X, 'rows', 'rows', '0_1', '0_2',name='marker')
graph = networkx.XGraph()
for x in 'ABCDEF':
for y in 'ADE':
@ -125,181 +40,11 @@ class TestDataFunction(workflow.Function):
ds_plot = plots.NetworkPlot(ds)
cds = dataset.CategoryDataset(ones([3, 3]))
ds_scatter = plots.ScatterMarkerPlot(ds, ds, 'rows_0', 'rows_0', '0_1', '0_2')
ds_scatter = plots.ScatterMarkerPlot(ds, ds,
'rows_0', 'rows_0',
'0_1', '0_2')
lp = plots.LineViewPlot(X,major_axis=0)
vp = plots.VennPlot()
self.datasets = [p]
return [X, ds, p, ds_plot, ds_scatter, p2, cds, lp, vp]
class SelectFunction(workflow.Function):
def __init__(self):
workflow.Function.__init__(self, 'select', 'Select')
def run(self, data):
s = dataset.Selection('Arbitrary selection')
s.select('rows', ['0_1', '0_2'])
return [s]
class DatasetLog(workflow.Function):
def __init__(self):
workflow.Function.__init__(self, 'log', 'Log')
def run(self, data):
logger.log('notice', 'Taking the log of dataset %s' % data.get_name())
d = data.asarray()
d = log(d)
new_data_name = 'log(%s)' % data.get_name()
ds = dataset.Dataset(d, name=new_data_name)
return [ds]
class DatasetLoadFunction(workflow.Function):
"""Loader for previously pickled Datasets."""
def __init__(self):
workflow.Function.__init__(self, 'load_data', 'Load Pickled Dataset')
def run(self):
chooser = gtk.FileChooserDialog(title="Select cel files...", parent=None,
action=gtk.FILE_CHOOSER_ACTION_OPEN,
buttons=(gtk.STOCK_CANCEL, gtk.RESPONSE_CANCEL,
gtk.STOCK_OPEN, gtk.RESPONSE_OK))
pkl_filter = gtk.FileFilter()
pkl_filter.set_name("Python pickled data files (*.pkl)")
pkl_filter.add_pattern("*.[pP][kK][lL]")
all_filter = gtk.FileFilter()
all_filter.set_name("All Files (*.*)")
all_filter.add_pattern("*")
chooser.add_filter(pkl_filter)
chooser.add_filter(all_filter)
try:
if chooser.run() == gtk.RESPONSE_OK:
return [cPickle.load(open(chooser.get_filename()))]
finally:
chooser.destroy()
class DatasetSaveFunction(workflow.Function):
"""QND way to save data to file for later import to this program."""
def __init__(self):
workflow.Function.__init__(self, 'save_data', 'Save Pickled Dataset')
def run(self):
if not data:
logger.log("notice", "No data to save.")
return
else:
data = data[0]
chooser = gtk.FileChooserDialog(title="Save pickled data...", parent=None,
action=gtk.FILE_CHOOSER_ACTION_SAVE,
buttons=(gtk.STOCK_CANCEL, gtk.RESPONSE_CANCEL,
gtk.STOCK_SAVE, gtk.RESPONSE_OK))
pkl_filter = gtk.FileFilter()
pkl_filter.set_name("Python pickled data files (*.pkl)")
pkl_filter.add_pattern("*.[pP][kK][lL]")
all_filter = gtk.FileFilter()
all_filter.set_name("All Files (*.*)")
all_filter.add_pattern("*")
chooser.add_filter(pkl_filter)
chooser.add_filter(all_filter)
chooser.set_current_name(data.get_name() + ".pkl")
try:
if chooser.run() == gtk.RESPONSE_OK:
cPickle.dump(data, open(chooser.get_filename(), "w"), protocol=2)
logger.log("notice", "Saved data to %r." % chooser.get_filename())
finally:
chooser.destroy()
class CelFileImportFunction(workflow.Function):
"""Loads AffyMetrix .CEL-files into matrix."""
def __init__(self):
workflow.Function.__init__(self, 'cel_import', 'Import Affy')
def run(self, data):
import rpy
chooser = gtk.FileChooserDialog(title="Select cel files...", parent=None,
action=gtk.FILE_CHOOSER_ACTION_OPEN,
buttons=(gtk.STOCK_CANCEL, gtk.RESPONSE_CANCEL,
gtk.STOCK_OPEN, gtk.RESPONSE_OK))
chooser.set_select_multiple(True)
cel_filter = gtk.FileFilter()
cel_filter.set_name("Cel Files (*.cel)")
cel_filter.add_pattern("*.[cC][eE][lL]")
all_filter = gtk.FileFilter()
all_filter.set_name("All Files (*.*)")
all_filter.add_pattern("*")
chooser.add_filter(cel_filter)
chooser.add_filter(all_filter)
try:
if chooser.run() == gtk.RESPONSE_OK:
rpy.r.library("affy")
silent_eval = rpy.with_mode(rpy.NO_CONVERSION, rpy.r)
silent_eval('E <- ReadAffy(filenames=c("%s"))' % '", "'.join(chooser.get_filenames()))
silent_eval('E <- rma(E)')
m = rpy.r('m <- E@exprs')
vector_eval = rpy.with_mode(rpy.VECTOR_CONVERSION, rpy.r)
rownames = vector_eval('rownames(m)')
colnames = vector_eval('colnames(m)')
# We should be nice and clean up after ourselves
rpy.r.rm(["E", "m"])
if m:
data = dataset.Dataset(m, (('ids', rownames), ('filename', colnames)), name="AffyMatrix Data")
plot = plots.LinePlot(data, "Gene profiles")
return [data, plot]
else:
logger.log("notice", "No data loaded from importer.")
finally:
chooser.destroy()
class DataLoadTestFunction(workflow.Function):
def __init__(self, wf):
workflow.Function.__init__(self, 'datadirload', 'Load from datadir')
self._wf = wf
def run(self):
print self._wf.get_data_file_name('smoker-x.ftsv')
fn = self._wf.get_data_file_name('smoker-x.ftsv')
if fn:
fd = open(fn)
ds = dataset.read_ftsv(fd)
return [ds]
else:
print "Cannot find file %s" % fn
return []
class PCAFunction(workflow.Function):
"""Generic PCA function."""
def __init__(self, wf):
workflow.Function.__init__(self, 'pca', 'PCA')
self._workflow = wf
def run(self, data):
import rpy
dim_2, dim_1 = data.get_dim_names()
silent_eval = rpy.with_mode(rpy.NO_CONVERSION, rpy.r)
rpy.with_mode(rpy.NO_CONVERSION, rpy.r.assign)("m", data.asarray())
silent_eval("t = prcomp(t(m))")
T_ids = map(str, range(1, rpy.r("dim(t$x)")[1]+1))
T = dataset.Dataset(rpy.r("t$x"), [(dim_1, data.get_identifiers(dim_1)),
("component", T_ids)], name="T")
P = dataset.Dataset(rpy.r("t$rotation"), [(dim_2, data.get_identifiers(dim_2)),
("component", T_ids)], name="P")
# cleanup
rpy.r.rm(["t", "m"])
loading_plot = plots.ScatterMarkerPlot(P, P, 'ids','component','1','2', "Loadings")
score_plot = plots.ScatterMarkerPlot(T, T,'filename','component','1','2', "Scores")
return [T, P, loading_plot, score_plot]