def get_tables(self):
'''returns all tables required in the from clause for this query.
'''
tables = self.get_queried_tables()
# add the tables required to link the above tables together
db = DBConnect.getInstance()
exps = db.get_linking_expressions(tables)
for exp in exps:
tables += exp.get_tables()
return list(set(tables))
def __init__(self, parent, properties = None, show_controls = True, size=(600, 600), loadData = True, **kwargs):
wx.Frame.__init__(self, parent, -1, size=size, title='Dimensionality Reduction Plot', **kwargs)
self.SetName('Plot main')
if properties is not None:
global p
p = properties
if not p.is_initialized():
logging.critical('Classifier requires a properties file. Exiting.')
raise Exception('Classifier requires a properties file. Exiting.')
global db
db = DBConnect.getInstance()
global classifier
classifier = parent
if loadData:
# Define a progress dialog
dlg = wx.ProgressDialog('Fetching cell data...', '0% Complete', 100, classifier,
wx.PD_ELAPSED_TIME | wx.PD_ESTIMATED_TIME |
wx.PD_REMAINING_TIME | wx.PD_CAN_ABORT)
def cb(frac):
cont, skip = dlg.Update(int(frac * 100.), '%d%% Complete'%(frac * 100.))
if not cont: # cancel was pressed
dlg.Destroy()
raise StopCalculating()
# Load the data for each object
try:
self.data, self.data_dic = self.load_obj_measurements(cb)
except StopCalculating:
self.PostMessage('User canceled updating training set.')
return
dlg.Destroy()
else:
self.data, self.data_dic = None, None
self.features_dic = self.load_feature_names()
self.class_masks = None
self.class_names = None
self.object_opacity = None
figpanel = PlotNotebook(self)
self.figure_scores = figpanel.add('Scores')
self.figure_loadings = figpanel.add('Loadings')
self.update_figures()
sizer = wx.BoxSizer(wx.VERTICAL)
sizer.Add(figpanel, 1, wx.EXPAND)
configpanel = PlotControl(self, self.figure_scores, self.figure_loadings)
sizer.Add(configpanel, 0, wx.EXPAND | wx.ALL, 5)
self.SetSizer(sizer)
self.Centre()
def extractDataFromGroupsMysql(self, dependentDataValues, independentDataValues):
from properties import Properties
from dbconnect import (
DBConnect,
UniqueImageClause,
UniqueObjectClause,
GetWhereClauseForImages,
GetWhereClauseForObjects,
image_key_columns,
object_key_columns,
)
import sqltools as sql
p = Properties.getInstance()
p.LoadFile("C:\\Users\\Dalitso\\Desktop\\workspace2\\abhakar\\Properties_README.txt")
db = DBConnect.getInstance()
def buildquery(self, theGroup, var):
pairs = theGroup.pairsDict
if var == "dep":
for i in pairs.keys():
print i
q = "SELECT " + "`" + self.dependentVariable + "`" + "FROM " + self.table + " WHERE "
q2 = [i + " LIKE `" + pairs[i] + "` AND " for i in pairs.keys()]
result = q + "".join(q2)[:-4]
print result
if var == "ind":
for i in pairs.keys():
print i
q = "SELECT " + "`" + self.independentVariable + "`" + "FROM " + self.table + "WHERE"
q2 = [i + "`" + " LIKE `" + pairs[i] + "` AND " for i in pairs.keys()]
result = q + "".join(q2)[:-4]
print result
return result
import numpy as np
dataDict = {}
dependentDataValues = np.array(dependentDataValues)
independentDataValues = np.array(independentDataValues)
tmp = {}
for iGrp in self.groupDefinitions:
theGroup = iGrp
theGroup.checkMatchCount
tmp["dependentData"] = db.execute(buildquery(self, theGroup, "dep"))
tmp["independentData"] = db.execute(buildquery(self, theGroup, "ind"))
# tmp['pairs'] = theGroup.pairsDict[theGroup.description]
dataDict[theGroup.description] = tmp
# print iGrp,theGroup.description,tmp
return dataDict
def get_where_clause(self):
'''Build the where clause from conditions given by the user and
conditions that link all the tables together.
'''
db = DBConnect.getInstance()
conditions = []
conditions += ['(%s)'%(str(f)) for f in self.filters]
queried_tables = self.get_queried_tables()
if len(queried_tables) > 1:
link_exps = db.get_linking_expressions(queried_tables)
if link_exps:
conditions += [str(exp) for exp in link_exps]
if self.old_filters:
conditions += ['%s.%s = subquery_%d.%s'%(p.image_table, col, i, col)
for i in range(len(self.old_filters))
for col in image_key_columns()]
if self.wheres:
conditions += [str(where) for where in self.wheres]
return ' AND '.join(conditions)
from __future__ import with_statement
from dbconnect import DBConnect
from properties import Properties
from singleton import Singleton
from heapq import heappush, heappop
from weakref import WeakValueDictionary
import imagetools
import logging
import numpy
import threading
import wx
import os
db = DBConnect.getInstance()
p = Properties.getInstance()
def load_lock():
return TileCollection.getInstance().load_lock
class List(list):
pass
class TileCollection(Singleton):
'''
Main access point for loading tiles through the TileLoader.
'''
def __init__(self):
self.tileData = WeakValueDictionary()
import properties
import logging
import matplotlib.cm
import numpy as np
from itertools import groupby
import os
import sys
import re
import wx
import cpa.helpmenu
import csv
p = properties.Properties.getInstance()
# Hack the properties module so it doesn't require the object table.
properties.optional_vars += ['object_table']
db = DBConnect.getInstance()
required_fields = ['plate_shape', 'well_id']
fixed_width = (200,-1)
class PlateViewer(wx.Frame, CPATool):
def __init__(self, parent, size=(800,-1), **kwargs):
wx.Frame.__init__(self, parent, -1, size=size, title='Plate Viewer', **kwargs)
CPATool.__init__(self)
self.SetName(self.tool_name)
self.SetBackgroundColour("white") # Fixing the color
# Check for required properties fields.
fail = False
for field in required_fields:
def HTS_GroupDataExtractMySql(dataSelector,table):
from HTS_dataDict import HTS_dataDict
import xlrd as xl
import numpy as np
import matplotlib.pyplot as plt
from properties import Properties
from dbconnect import DBConnect, UniqueImageClause, UniqueObjectClause, GetWhereClauseForImages, GetWhereClauseForObjects, image_key_columns, object_key_columns
import sqltools as sql
p = Properties.getInstance()
db = DBConnect.getInstance()
dependentDataValues = False
independentDataValues = False
# def buildquery(self, table):
# q = 'SELECT ' + self.independentVar + ', '+ self.dependentVar +' FROM ' + table
# q2= [' WHERE '+ y[1] +' LIKE ' +y[0] for y in group.pairs]
# return q + ''.join(q2)
returnDict = HTS_dataDict(dataSelector)
#for iFile in range(nFiles):
dataSelector.clearAllIndici
print('HTS_GroupDataExtract: using sheet %s for %s\n',table)
query ='SELECT `' + dataSelector.independentVariable + '` FROM ' + '`' +table+'`'
print query
dataSelector.findValidIndiciFromDataColumn(dataSelector.independentVariable,db.execute(query))
query = 'SELECT `' + dataSelector.dependentVariable + '` FROM ' + '`' +table+'`'
print query
dataSelector.findValidIndiciFromDataColumn(dataSelector.dependentVariable,db.execute(query))
print dependentDataValues, independentDataValues, "variables"
if not dependentDataValues:
print 'HTS_GroupDataExtract: dependent variable not found in %s',
if not independentDataValues:
print 'HTS_GroupDataExtract: independent variable not found in %s'
# print dataSelector.extractDataFromGroups(dependentDataValues,independentDataValues)
dataSelector.table = table
returnDict.dict[table] = dataSelector.extractDataFromGroupsMysql(dependentDataValues,independentDataValues)
# if nFiles > 1:
# # Get data from the selector
# nGroups = dataSelector.nGroups
# groupKeys = dataSelector.getGroupDescriptions()
# # Create the combined group
# combinedData = {}
# tmpStruct = {}
# tmpStruct['dependentData'] = np.array([])
# tmpStruct['independentData'] = np.array([])
# for iGrp in range(nGroups):
# combinedData[groupKeys[iGrp]] = tmpStruct
# for iFile in range(nFiles):
# #print('the key = %s\n')
# fileData = returnDict.dict[dataFiles[iFile]]
# for iGrp in range(nGroups):
# grpKey = groupKeys[iGrp]
# #combDepData = combinedData[grpKey]['dependentData']
# fileDepData = fileData[grpKey]['dependentData']
# tmpStruct['dependentData'] = np.concatenate((tmpStruct['dependentData'],fileDepData[:]))
# #combIndData = [combinedData[grpKey]['independentData']]
# fileIndData = fileData[grpKey]['independentData']
# tmpStruct['independentData'] = np.concatenate((tmpStruct['independentData'],fileIndData[:]))
# combinedData[grpKey] = tmpStruct
#
# returnDict.dict['combinedData'] = combinedData
return returnDict
f.write('\n')
f.close()
def make_unique_plot_name(self, prefix):
'''This function must be called to generate a unique name for each plot.
eg: plot.SetName(wx.GetApp().make_unique_plot_name('Histogram'))
'''
plot_num = max([int(plot.Name[len(prefix):])
for plot in self.plots if plot.Name.startswith(prefix)])
return '%s %d'%(prefix, plot_num)
if __name__ == "__main__":
# Initialize the app early because the fancy exception handler
# depends on it in order to show a dialog.
app = CPAnalyst(redirect=False)
if sys.platform=='darwin':
import bioformats
# Install our own pretty exception handler unless one has already
# been installed (e.g., a debugger)
if sys.excepthook == sys.__excepthook__:
from errors import show_exception_as_dialog
sys.excepthook = show_exception_as_dialog
# Black magic: Bus errors occur on certain Macs if we wait until
# later to connect, so we'll do it here.
DBConnect.getInstance().connect()
app.MainLoop()
os._exit(0)
def __init__(self,
parent,
properties=None,
show_controls=True,
size=(600, 600),
loadData=True,
**kwargs):
wx.Frame.__init__(self,
parent,
-1,
size=size,
title='Dimensionality Reduction Plot',
**kwargs)
self.SetName('Plot main')
if properties is not None:
global p
p = properties
if not p.is_initialized():
logging.critical(
'Classifier requires a properties file. Exiting.')
raise Exception(
'Classifier requires a properties file. Exiting.')
global db
db = DBConnect.getInstance()
global classifier
classifier = parent
if loadData:
# Define a progress dialog
dlg = wx.ProgressDialog(
'Fetching cell data...', '0% Complete', 100, classifier,
wx.PD_ELAPSED_TIME | wx.PD_ESTIMATED_TIME
| wx.PD_REMAINING_TIME | wx.PD_CAN_ABORT)
def cb(frac):
cont, skip = dlg.Update(int(frac * 100.),
'%d%% Complete' % (frac * 100.))
if not cont: # cancel was pressed
dlg.Destroy()
raise StopCalculating()
# Load the data for each object
try:
self.data, self.data_dic = self.load_obj_measurements(cb)
except StopCalculating:
self.PostMessage('User canceled updating training set.')
return
dlg.Destroy()
else:
self.data, self.data_dic = None, None
self.features_dic = self.load_feature_names()
self.class_masks = None
self.class_names = None
self.object_opacity = None
figpanel = PlotNotebook(self)
self.figure_scores = figpanel.add('Scores')
self.figure_loadings = figpanel.add('Loadings')
self.update_figures()
sizer = wx.BoxSizer(wx.VERTICAL)
sizer.Add(figpanel, 1, wx.EXPAND)
configpanel = PlotControl(self, self.figure_scores,
self.figure_loadings)
sizer.Add(configpanel, 0, wx.EXPAND | wx.ALL, 5)
self.SetSizer(sizer)
self.Centre()
