def getDialog(self):
options = self.Parent._options
return MDD.MultiDirDialog(self,
message=options.get('message', _('choose_folders')),
title=_('choose_folders_title'),
defaultPath=options.get('default_path', os.getcwd()),
agwStyle=MDD.DD_MULTIPLE | MDD.DD_DIR_MUST_EXIST)
def test_lib_agw_multidirdialogCtor(self):
dlg = MDD.MultiDirDialog(self.frame,
title="Custom MultiDirDialog",
agwStyle=MDD.DD_MULTIPLE
| MDD.DD_DIR_MUST_EXIST)
wx.CallLater(250, dlg.EndModal, wx.ID_OK)
dlg.ShowModal()
dlg.Destroy()
def test_lib_agw_multidirdialogMethods(self):
dlg = MDD.MultiDirDialog(self.frame, title="Custom MultiDirDialog",
agwStyle=MDD.DD_MULTIPLE|MDD.DD_DIR_MUST_EXIST)
self.assertTrue(isinstance(dlg.GetPaths(), list))
# it looks like the generic dir ctrl may start out with an item
# selected, so allow for that here
self.assertTrue(len(dlg.GetPaths()) in [0,1])
def open_multiple_dir_dialog(message, default):
dlg = MDD.MultiDirDialog(None,
message=message,
defaultPath=default,
agwStyle=MDD.DD_MULTIPLE | MDD.DD_DIR_MUST_EXIST)
dirs = None
if dlg.ShowModal() == wx.ID_OK:
dirs = ud.smartdecode(dlg.GetPaths())
dlg.Destroy()
return dirs
def onSelectDirs(self, event):
dlg = MDD.MultiDirDialog(self,
title="Choose source folder",
defaultPath=self.currentDirectory,
agwStyle=0)
if dlg.ShowModal() == wx.ID_OK:
paths = dlg.GetPaths()
print "Source folder selected:"
for path in paths:
print path
dlg.Destroy()
def onMultiDir(self, event):
"""
Create and show the MultiDirDialog
"""
dlg = MDD.MultiDirDialog(self,
title="Choose a directory:",
defaultPath=self.currentDirectory,
agwStyle=0)
if dlg.ShowModal() == wx.ID_OK:
paths = dlg.GetPaths()
print("You chose the following file(s):")
for path in paths:
print(path)
dlg.Destroy()
def selectFolders(self):
""" Select folders
Args: None
Returns: None
"""
if DEBUG: print("ImgProcsFrame.selectFolders()")
dlg = MDD.MultiDirDialog(
None,
title="Select folders with images to process.",
defaultPath=CWD,
agwStyle=MDD.DD_MULTIPLE|MDD.DD_DIR_MUST_EXIST,
) # select multiple folders
if dlg.ShowModal() == wx.ID_OK:
self.selectedFolders = dlg.GetPaths()
if sys.platform == 'darwin': # OS X
### remove root string
for i, fp in enumerate(self.selectedFolders):
si = fp.find("/")
if si != -1:
fp = fp[fp.index("/"):] # cut off the fisrt directory name,
# MultiDirDialog returns with disk name as root
# Instead of '/tmp',
# it returns 'Macintosh HD/tmp'.
self.selectedFolders[i] = fp
### include sub folder,
### if "including sub folder" option was checked.
sfChk = wx.FindWindowByName("subFolders_chk", self.panel["ui"])
if sfChk.GetValue() == True:
### update folder lists
folderL = copy(self.selectedFolders)
self.selectedFolders = []
for dp in folderL:
# go through selected folders
self.selectedFolders.append(dp) # append the selected folder
self.addFolders(dp) # add sub-folders in this folder
### show folder list in UI
selDir_txt = wx.FindWindowByName("selDir_txt",
self.panel["ui"])
_txt = str(self.selectedFolders)
_txt = _txt.strip("[]").replace("'","").replace(", ","\n\n")
selDir_txt.SetValue(_txt) # show list of selected folders
self.updateFileList() # update files to be renamed
dlg.Destroy()
def select_save_dir(self, e):
"""
Opens quick dialog to select the save directory for the output files (.txt, .png) from the automatic
measurements. Writes the directory name on the TextCtrl object on the GUI (self.save_tctrl).
:param e: Event handler.
:return: Nothing.
"""
# TODO: Currently, there is a problem with wx.DirDialog, so I have resorted to using multidirdialog
# TODO: When the bugs are fixed on their end, revert back to the nicer looking wx.DirDialog
with mdd.MultiDirDialog(None,
"Select save directory for output files.",
style=mdd.DD_DIR_MUST_EXIST
| mdd.DD_NEW_DIR_BUTTON) as dlg:
if dlg.ShowModal() == wx.ID_CANCEL:
return
# Correcting name format to fit future save functions
path = dlg.GetPaths()[0]
path = path.split(':')[0][-1] + ':' + path.split(':)')[1]
self.save_tctrl.SetValue(path)
def select_multi_directory_dialog():
""" Opens a directory selection dialog
Style - specifies style of dialog (read wx documentation for information)
"""
import wx.lib.agw.multidirdialog as MDD
app = wx.App(0)
dlg = MDD.MultiDirDialog(None,
title="Select directories",
defaultPath=os.getcwd(),
agwStyle=MDD.DD_MULTIPLE | MDD.DD_DIR_MUST_EXIST)
if dlg.ShowModal() != wx.ID_OK:
dlg.Destroy()
return
paths = dlg.GetPaths()
dlg.Destroy()
app.MainLoop()
return paths
def addDirectories(self):
app = wx.App(0)
dlg = MDD.MultiDirDialog(None, title="Custom MultiDirDialog", defaultPath="/home/lucas/Documents/Manip/", # defaultPath="C:/Users/users/Desktop/",
agwStyle=MDD.DD_MULTIPLE|MDD.DD_DIR_MUST_EXIST)
if dlg.ShowModal() != wx.ID_OK:
print("You Cancelled The Dialog!")
dlg.Destroy()
paths = dlg.GetPaths()
dlg.Destroy()
app.MainLoop()
for path in enumerate(paths):
directory= path[1].replace('Home directory','/home/lucas')
filesToAdd = os.listdir(directory)
for l in filesToAdd:
l = directory + '/' + l
self.textZone.insert(END, l+'\n')
self.heightTextZone +=1
if self.heightTextZone >= 40:
self.heightTextZone = 40
self.textZone.config(height=self.heightTextZone)
if directory:
self.buttonProcess.config(state=NORMAL)
def open_multiple_dir_dialog(message, default):
if default is None:
global default_dir
default = default_dir
dlg = MDD.MultiDirDialog(None, message=message, defaultPath=default,
agwStyle=MDD.DD_MULTIPLE | MDD.DD_DIR_MUST_EXIST)
#dlg = wx.DirDialog(None, message, default, wx.DD_MULTIPLE)
dirs = None
if dlg.ShowModal() == wx.ID_OK:
dirs = ud.smartdecode(dlg.GetPaths())
dirs2 = []
for d in dirs:
p = Path(d)
drive = p.parts[0]
if ")" in drive:
spot = drive.find(":")
drive_letter = drive[spot-1]
d=drive_letter+":\\"
d2 = os.path.join(*p.parts[1:])
d = os.path.join(d, d2)
dirs2.append(d)
dirs = dirs2
dlg.Destroy()
return dirs
def onButtonPressDown(self, event, flag=''):
""" wx.Butotn was pressed.
Args:
event (wx.Event)
flag (str, optional): Specifying intended operation of
the function call.
Returns: None
"""
if DEBUG: print("FileRenamerFrame.onButtonPressDown()")
objName = ''
if flag == '':
obj = event.GetEventObject()
objName = obj.GetName()
if flag == "selectFolders" or objName == "selFolders_btn":
# select folders to rename
dlg = MDD.MultiDirDialog(
None,
title="Select folders to apply renaming operations.",
defaultPath=CWD,
agwStyle=MDD.DD_MULTIPLE|MDD.DD_DIR_MUST_EXIST,
) # select multiple folders
if dlg.ShowModal() == wx.ID_OK:
self.selectedFolders = dlg.GetPaths()
if sys.platform == 'darwin': # OS X
### remove root string
for i, fp in enumerate(self.selectedFolders):
si = fp.find("/")
if si != -1:
fp = fp[fp.index("/"):] # cut off the fisrt directory name,
# MultiDirDialog returns with disk name as root
# Instead of '/tmp',
# it returns 'Macintosh HD/tmp'.
self.selectedFolders[i] = fp
### include sub folder, if "including sub folder" option was checked.
sfChk = wx.FindWindowByName("subFolders_chk", self.panel["tUI"])
if sfChk.GetValue() == True:
### update folder lists
folderL = copy(self.selectedFolders)
self.selectedFolders = []
for dp in folderL:
# go through selected folders
self.selectedFolders.append(dp) # append the selected folder
self.addFolders(dp) # add sub-folders in this folder
### show folder list in UI
selDir_txt = wx.FindWindowByName("selDir_txt",
self.panel["mp"])
_txt = str(self.selectedFolders)
_txt = _txt.strip("[]").replace("'","").replace(", ","\n\n")
selDir_txt.SetValue(_txt) # show list of selected folders
self.updateFileList() # update files to be renamed
dlg.Destroy()
elif objName == "selFolder2move_btn":
# select folder to move renamed files
dlg = wx.DirDialog(self,
"Select a folder to move renamed files.",
CWD) # select folder
if dlg.ShowModal() == wx.ID_OK:
self.folder2moveRenFile = dlg.GetPath() # get folder path
tc = wx.FindWindowByName("selFolder2move_txt", self.panel["tUI"])
tc.SetValue(self.folder2moveRenFile) # show it on UI
self.updateFileList() # update files to be renamed
dlg.Destroy()
elif objName == "run_btn":
msg = "Renamed files -----\n\n" # result message
msg4log = "" # log message
for i, fp in enumerate(self.fileList):
newFP = self.nFileList[i]
rename(fp, newFP) # rename file
msg4log += "%s, %s, %s\n\n"%(get_time_stamp(), fp, newFP)
msg += "%s\n\n"%(newFP)
writeFile(self.logFile, msg4log) # logging results
self.initList() # clear all file lists
wx.MessageBox(msg, 'Results', wx.OK)
def onAddDirectory(self, event):
from obspy.core.util.base import ENTRY_POINTS
from pkg_resources import load_entry_point
import wx.lib.agw.multidirdialog as mdd
# dlg = wx.DirDialog(self, "Choose a directory:",
# style=wx.DD_DEFAULT_STYLE
# | wx.DD_DIR_MUST_EXIST
# )
waveclient = self.psyProject.waveclient['db client']
if waveclient.waveformDirList:
start_path = waveclient.waveformDirList[0][2]
else:
start_path = os.getcwd()
dlg = mdd.MultiDirDialog(self,
title = 'Choose one or more directories',
defaultPath = start_path,
agwStyle = mdd.DD_DIR_MUST_EXIST)
# BUGFIX FS#81
# When the DD_MULTIPLE style is used, the root folder is kept in the
# selected paths list after setting the default path. When the user
# doesn't select any folder, the root folder will be returned together
# with the default path by the GetPaths() method.
# Setting the MULTIPLE flag after the initialization as a single
# selection dialog fixes this problem.
dlg.dirCtrl.GetTreeCtrl().SetWindowStyle(dlg.dirCtrl.GetTreeCtrl().GetWindowStyle() | wx.TR_MULTIPLE)
# If the user selects OK, then we process the dialog's data.
# This is done by getting the path data from the dialog - BEFORE
# we destroy it.
if dlg.ShowModal() == wx.ID_OK:
#bar = wx.ProgressDialog("Progress dialog example",
# "An informative message",
# parent=self,
# style = wx.PD_CAN_ABORT
# | wx.PD_APP_MODAL
# | wx.PD_ELAPSED_TIME
# | wx.PD_ESTIMATED_TIME
# | wx.PD_REMAINING_TIME
# )
selected_paths = dlg.GetPaths()
for cur_path in selected_paths:
# Fix the wrongly added 'Home Directory' in the path returned
# by the multidir dialog.
if cur_path.startswith('Home directory'):
cur_path = cur_path.replace('Home directory', os.getenv('HOME'))
matches = []
#count = 0
k = 0
filter_pattern = self.collectionNode.pref_manager.get_value('filter_pattern')
for root, dirnames, filenames in os.walk(cur_path, topdown = True):
dirnames.sort()
self.logger.info('Scanning directory: %s.', root)
for cur_pattern in filter_pattern:
for filename in fnmatch.filter(filenames, cur_pattern):
self.logger.info('Adding file %s', os.path.join(root, filename))
fsize = os.path.getsize(os.path.join(root, filename));
fsize = fsize/(1024.0 * 1024.0)
if self.check_file_format is True:
# Check the file formats.
EPS = ENTRY_POINTS['waveform']
for format_ep in [x for (key, x) in EPS.items() if key == 'MSEED']:
# search isFormat for given entry point
isFormat = load_entry_point(format_ep.dist.key,
'obspy.plugin.%s.%s' % ('waveform', format_ep.name),
'isFormat')
# check format
self.logger.debug('Checking format with %s.', isFormat)
if isFormat(os.path.join(root,filename)):
file_format = format_ep.name
break;
else:
file_format = 'unknown'
else:
file_format = 'not checked'
self.logger.debug('adding to matches')
matches.append((file_format, os.path.join(root, filename), '%.2f' % fsize))
k += 1
matches = [x for x in matches if x not in self.file_grid.GetTable().data]
self.file_grid.GetTable().data.extend(matches)
self.file_grid.GetTable().ResetView()
#bar.Destroy()
self.file_grid.doResize()
# Only destroy a dialog after you're done with it.
dlg.Destroy()
self.logger.debug('Exiting the onAddDirectory.')
import os
import wx
import wx.lib.agw.multidirdialog as MDD
# Our normal wxApp-derived class, as usual
app = wx.App(0)
dlg = MDD.MultiDirDialog(None, title="Custom MultiDirDialog", defaultPath=os.getcwd(),
agwStyle=MDD.DD_MULTIPLE|MDD.DD_DIR_MUST_EXIST)
if dlg.ShowModal() != wx.ID_OK:
print("You Cancelled The Dialog!")
dlg.Destroy()
paths = dlg.GetPaths()
for indx, path in enumerate(paths):
print("Path %d: %s"%(indx+1, path))
dlg.Destroy()
app.MainLoop()
en nu een regel
en nog een regel
#
def main():
# root = Tk()
# root.withdraw()
# file_names = askopenfilenames(initialdir = '/media/NAS/Public/Lucas/')
# file_names = root.tk.splitlist(file_names)
## file_name = '/home/roche/MANIP/results/trial 1-4-2015 - SAJ + BL/RESULTS_scenario_14_trial_2_a_1-4-15-21.txt'
# root.destroy()*
file_names = []
app = wx.App(0)
dlg = MDD.MultiDirDialog(
None,
title="Custom MultiDirDialog",
defaultPath=
"/media/NAS/Public/Lucas/", # defaultPath="C:/Users/users/Desktop/",
agwStyle=MDD.DD_MULTIPLE | MDD.DD_DIR_MUST_EXIST)
if dlg.ShowModal() != wx.ID_OK:
print("You Cancelled The Dialog!")
dlg.Destroy()
paths = dlg.GetPaths()
dlg.Destroy()
app.MainLoop()
for path in enumerate(paths):
directory = path[1] #.replace('Home directory','/home/lucas')
filesToAdd = os.listdir(directory)
for file in filesToAdd:
file_names.append(directory + '/' + file)
# file_names_HFO = [x for x in file_names if x.find('_s_')!=-1]
# file_names_HFOP = [x for x in file_names if x.find('_a_')!=-1]
# file_names_ULTRON = [x for x in file_names if x.find('_u_')!=-1]
# file_names_ROBOT = [x for x in file_names if x.find('_r_')!=-1]
# file_names_ALONE = [x for x in file_names if x.find('_w_')!=-1]
#
# file_names = file_names_HFO + file_names_HFOP + file_names_ULTRON + file_names_ROBOT + file_names_ALONE
Delta = []
for file in file_names:
DataClass = FileData(file)
DataClass.getDataFromFile()
for n in range(0, len(DataClass.Time) - DataClass.time2line(60)):
Delta.append(DataClass.Time[n + 1] - DataClass.Time[n])
print len(Delta), min(Delta), numpy.mean(Delta), max(Delta)
print float(len([x for x in Delta if (x < 0.000202 and x > 0.000198)
])) / len(Delta)
print float(len([x for x in Delta if (x < 0.00021 and x > 0.00019)
])) / len(Delta)
print float(len([x for x in Delta if (x < 0.00022 and x > 0.00018)
])) / len(Delta)
# N=100
# compte = [0]*N
# compte_pc = [0]*N
# T = 1/5000.
# for x in Delta:
# for n in range(0,N):
# low = T*(0.95 + 0.1/N*n)
# high = T*(0.95 + 0.1/N*(n+1))
# if x >= low and x < high:
# compte[n] += 1
# break
#
# for n in range(0, len(compte)):
# compte_pc[n] = float(compte[n])/len(Delta)
#
# for n in range(0, len(compte)):
# print T*(0.95 + 0.1/N*n), T*(0.95 + 0.1/N*(n+1)), compte[n]
#
# plt.figure(1)
# for n in range(0,N):
# plt.plot([T*(0.95 + 0.1/N*n), T*(0.95 + 0.1/N*n)], [0, compte[n]], color='k', linestyle='-', linewidth=2)
#
# plt.figure(2)
# for n in range(0,N):
# plt.plot([T*(0.95 + 0.1/N*n), T*(0.95 + 0.1/N*n)], [0, compte_pc[n]], color='k', linestyle='-', linewidth=2)
plt.figure()
ax = plt.subplot(111)
ax.hist(Delta, 100)
ax.xaxis.set_ticks_position('none')
plt.xlabel("Loop execution time (s)")
plt.ylabel("Count")
plt.show()
def on_open_multiple_ML_files(self, open_type, pathlist=[]):
# http://stackoverflow.com/questions/1252481/sort-dictionary-by-another-dictionary
# http://stackoverflow.com/questions/22520739/python-sort-a-dict-by-values-producing-a-list-how-to-sort-this-from-largest-to
self.config.ciuMode = 'MANUAL'
tempList = self.view.panelMML.filelist
tstart = time.clock()
if len(pathlist) > 0:
dlg = None
else:
if self.config.lastDir == None or not os.path.isdir(
self.config.lastDir):
self.config.lastDir = os.getcwd()
dlg = MDD.MultiDirDialog(self.view,
title="Choose MassLynx files to open:",
defaultPath=self.config.lastDir,
agwStyle=MDD.DD_MULTIPLE
| MDD.DD_DIR_MUST_EXIST)
if dlg.ShowModal() == wx.ID_OK:
pathlist = dlg.GetPaths()
if open_type == "multiple_files_add":
# Check if current document is a comparison document
# If so, it will be used
docList = self.checkIfAnyDocumentsAreOfType(type='Type: MANUAL')
if len(docList) == 0:
self.onThreading(None, (
"Did not find appropriate document. Creating a new one...",
4),
action='updateStatusbar')
dlg = wx.FileDialog(self.view,
"Please select a name for the document",
"", "", "",
wx.FD_SAVE | wx.FD_OVERWRITE_PROMPT)
if dlg.ShowModal() == wx.ID_OK:
path, idName = os.path.split(dlg.GetPath())
else:
return
# Create document
self.docs = documents()
self.docs.title = idName
self.docs.path = path
self.docs.userParameters = self.config.userParameters
self.docs.userParameters['date'] = getTime()
else:
self.selectDocDlg = panelSelectDocument(
self.view, self, docList)
if self.selectDocDlg.ShowModal() == wx.ID_OK:
pass
# Check that document exists
if self.currentDoc == None:
self.onThreading(None, ('Please select a document', 4),
action='updateStatusbar')
return
self.docs = self.documentsDict[self.currentDoc]
self.onThreading(
None, ('Using document: ' +
self.docs.title.encode('ascii', 'replace'), 4),
action='updateStatusbar')
elif open_type == "multiple_files_new_document":
dlg = wx.FileDialog(self.view,
"Please select a name for the document", "",
"", "", wx.FD_SAVE | wx.FD_OVERWRITE_PROMPT)
if dlg.ShowModal() == wx.ID_OK:
path, idName = os.path.split(dlg.GetPath())
else:
return
# Create document
self.docs = documents()
self.docs.title = idName
self.docs.path = path
self.docs.userParameters = self.config.userParameters
self.docs.userParameters['date'] = getTime()
for i, file_path in enumerate(pathlist):
path = self.checkIfRawFile(file_path)
if path is None:
continue
else:
try:
pathSplit = path.encode('ascii', 'replace').split(':)')
start = pathSplit[0].split('(')
start = start[-1]
path = ''.join([start, ':', pathSplit[1]])
except IndexError:
path = path
temp, rawfile = os.path.split(path)
# Update lastDir with current path
self.config.lastDir = path
parameters = self.config.importMassLynxInfFile(path=path,
manual=True)
xlimits = [parameters['startMS'], parameters['endMS']]
extract_kwargs = {'return_data': True}
msDataX, msDataY = io_waters.rawMassLynx_MS_extract(
path=path,
driftscope_path=self.config.driftscopePath,
**extract_kwargs)
extract_kwargs = {'return_data': True}
xvalsDT, imsData1D = io_waters.rawMassLynx_DT_extract(
path=path,
driftscope_path=self.config.driftscopePath,
**extract_kwargs)
if i <= 15: color = self.config.customColors[i]
else: color = randomColorGenerator(True)
color = self.view.panelMML.on_check_duplicate_colors(
color, document_name=self.docs.title)
tempList.Append([
rawfile,
str(parameters['trapCE']), self.docs.title,
os.path.splitext(rawfile)[0]
]) # name as initial label
tempList.SetItemBackgroundColour(tempList.GetItemCount() - 1,
convertRGB1to255(color))
self.docs.gotMultipleMS = True
self.docs.multipleMassSpectrum[rawfile] = {
'trap': parameters['trapCE'],
'xvals': msDataX,
'yvals': msDataY,
'ims1D': imsData1D,
'ims1DX': xvalsDT,
'xlabel': 'Drift time (bins)',
'xlabels': 'm/z (Da)',
'path': path,
'color': color,
'parameters': parameters,
'xlimits': xlimits
}
# Sum all mass spectra into one
if self.config.ms_enable_in_MML_start:
msFilenames = ["m/z"]
counter = 0
kwargs = {
'auto_range': self.config.ms_auto_range,
'mz_min': self.config.ms_mzStart,
'mz_max': self.config.ms_mzEnd,
'mz_bin': self.config.ms_mzBinSize,
'linearization_mode': self.config.ms_linearization_mode
}
msg = "Linearization method: {} | min: {} | max: {} | window: {} | auto-range: {}".format(
self.config.ms_linearization_mode, self.config.ms_mzStart,
self.config.ms_mzEnd, self.config.ms_mzBinSize,
self.config.ms_auto_range)
self.onThreading(None, (msg, 4), action='updateStatusbar')
for key in self.docs.multipleMassSpectrum:
msFilenames.append(key)
if counter == 0:
msDataX, tempArray = pr_spectra.linearize_data(
self.docs.multipleMassSpectrum[key]['xvals'],
self.docs.multipleMassSpectrum[key]['yvals'], **kwargs)
msList = tempArray
else:
msDataX, msList = pr_spectra.linearize_data(
self.docs.multipleMassSpectrum[key]['xvals'],
self.docs.multipleMassSpectrum[key]['yvals'], **kwargs)
tempArray = np.concatenate((tempArray, msList), axis=0)
counter += 1
# Reshape the list
combMS = tempArray.reshape((len(msList), int(counter)), order='F')
# Sum y-axis data
msDataY = np.sum(combMS, axis=1)
msDataY = pr_spectra.normalize_1D(inputData=msDataY)
xlimits = [parameters['startMS'], parameters['endMS']]
# Form pandas dataframe
combMSOut = np.concatenate((msDataX, tempArray), axis=0)
combMSOut = combMSOut.reshape((len(msList), int(counter + 1)),
order='F')
msSaveData = pd.DataFrame(data=combMSOut, columns=msFilenames)
# Add data
self.docs.gotMSSaveData = True
self.docs.massSpectraSave = msSaveData # pandas dataframe that can be exported as csv
self.docs.gotMS = True
self.docs.massSpectrum = {
'xvals': msDataX,
'yvals': msDataY,
'xlabels': 'm/z (Da)',
'xlimits': xlimits
}
# Plot
name_kwargs = {
"document": self.docs.title,
"dataset": "Mass Spectrum"
}
self.view.panelPlots.on_plot_MS(msDataX,
msDataY,
xlimits=xlimits,
**name_kwargs)
# Update status bar with MS range
self.view.SetStatusText(
"{}-{}".format(parameters['startMS'], parameters['endMS']), 1)
self.view.SetStatusText("MSMS: {}".format(parameters['setMS']), 2)
# Add info to document
self.docs.parameters = parameters
self.docs.dataType = 'Type: MANUAL'
self.docs.fileFormat = 'Format: MassLynx (.raw)'
self.OnUpdateDocument(self.docs, 'document')
# Show panel
self.view.onPaneOnOff(evt=ID_window_multipleMLList, check=True)
# Removing duplicates
self.view.panelMML.onRemoveDuplicates(evt=None)
tend = time.clock()
self.onThreading(None, ('Total time to extract %d files was: %.3gs' %
(len(pathlist), tend - tstart), 4),
action='updateStatusbar')
def main():
# root = Tk()
# root.withdraw()
# file_names = askopenfilenames(initialdir = '/media/NAS/Public/Lucas/OLD_MANIPS/')
# file_names_total = root.tk.splitlist(file_names)
# root.destroy()
app = wx.App(0)
dlg = MDD.MultiDirDialog(None, title="Custom MultiDirDialog", defaultPath="/media/NAS/Public/Lucas/", # defaultPath="C:/Users/users/Desktop/",
agwStyle=MDD.DD_MULTIPLE|MDD.DD_DIR_MUST_EXIST)
if dlg.ShowModal() != wx.ID_OK:
print("You Cancelled The Dialog!")
dlg.Destroy()
paths = dlg.GetPaths()
dlg.Destroy()
app.MainLoop()
file_names_total =[]
for path in enumerate(paths):
directory= path[1].replace('Home directory','/home/lucas')
print(directory)
file_names = os.listdir(directory)
#
for file in file_names:
file = directory + '/' + file
file_names_total.append(file)
expectedChoicesTotal = []
finalChoicesTotal = []
thresh_times = []
print "Threshold\tStartingTime\tStopTime\tSize\taveragetime\tAccuracy\tunknown\ttrueAcc"
for k in range (6,7):
for j in range(1,2):
for l in range(40,45):
expectedChoicesTotal = []
finalChoicesTotal = []
thresh_times = []
end_times = []
# fileType = []
for file in file_names_total:
DataClass = FileData(file)
DataClass.getDataFromFile()
if DataClass.fileType != 'HFOP' or file.find('~')!=-1:
continue
DataClass.threshold = 5*(k+1)*0.8
DataClass.analysisStartTime = 0.2 + j*0.1
# print DataClass.threshold, DataClass.analysisStartTime
DataClass.threshold_ext = 0.1*80
(tempE, tempF, tempT, tempET) = DataClass.intentionDetectionST()
expectedChoicesTotal.extend(tempE)
finalChoicesTotal.extend(tempF)
thresh_times.extend(tempT)
end_times.extend(tempET)
mean_thresh_time = np.mean(thresh_times)
thresh_min_time = min(thresh_times)
thresh_max_time = max(thresh_times)
N = len(finalChoicesTotal)
print len(finalChoicesTotal), len(thresh_times), len(end_times)
diff = []
for i in range (0, N):
try:
diff.append(end_times[i] - thresh_times[i])
except:
print i
#
results = [0]*N
unknown=0
for i in range (0, N):
# print expectedChoicesTotal[i], "\t",finalChoicesTotal[i], "\t",thresh_times[i]
if thresh_times[i] > 0.5 + l*0.05:
unknown +=1
else:
results[i] = expectedChoicesTotal[i] * finalChoicesTotal[i]
somme = float(sum(results))
size = float(len(results))
good = (somme+size)/2
# thresh_times_true = []
# thresh_times_false = []
# for i in range (0, N):
# if results[i] == 1:
# thresh_times_true.append(thresh_times[i])
# elif results[i] == -1:
# thresh_times_false.append(thresh_times[i])
#
# YT,XT = np.histogram(thresh_times_true, bins=40, range = (0,2))
# YF,XF = np.histogram(thresh_times_false, bins=40, range = (0,2))
#
#
## thresh_times = numpy.sort(thresh_times)
# plt.figure(DataClass.threshold)
## for i in range(0, N):
## if results[i] == 1:
## plt.plot(thresh_times[i], 0.2+j*0.1, 'g+')
## elif results[i] == -1:
## plt.plot(thresh_times[i], 0.2+j*0.1, 'r+')
## plt.plot(thresh_times, [0.2 + j*0.1]*len(thresh_times), 'b+')
# for i in range (0, len(YT)):
# if YT.all() == 0 and YF.all() == 0:
# continue
# plt.plot([XT[i], XT[i]], [0.2+0.1*j, 0.2+0.1*j + float(YT[i])*0.05/max(YT)], 'g-', linewidth = 2, solid_capstyle="round")
# plt.plot([XT[i], XT[i+1]],[0.2+0.1*j + float(YT[i])*0.05/max(YT), 0.2+0.1*j + float(YT[i])*0.05/max(YT)], 'g-', linewidth = 2, solid_capstyle="round")
# plt.plot([XT[i+1], XT[i+1]], [0.2+0.1*j, 0.2+0.1*j + float(YT[i])*0.05/max(YT)], 'g-', linewidth = 2, solid_capstyle="round")
# plt.plot([XF[i], XF[i]], [0.2+0.1*j, 0.2+0.1*j - float(YF[i])*0.05/max(YT)], 'r-', linewidth = 2, solid_capstyle="round")
# plt.plot([XF[i], XF[i+1]],[0.2+0.1*j -float(YF[i])*0.05/max(YT), 0.2+0.1*j -float(YF[i])*0.05/max(YT)], 'r-', linewidth = 2, solid_capstyle="round")
# plt.plot([XF[i+1], XF[i+1]], [0.2+0.1*j, 0.2+0.1*j - float(YF[i])*0.05/max(YT)], 'r-', linewidth = 2, solid_capstyle="round")
# plt.plot([0, 2], [0.2+0.1*j, 0.2+0.1*j], 'k-', linewidth = 1)
# plt.plot(mean_thresh_time, 0.2 + j*0.1, 'k+', markersize = 12)
# plt.axis([0,2.1,0.1,0.7])
#
# count_095 = 0.0
# count_100 = 0.0
# for i in range(0, N):
# if thresh_times[i] >= 0.95:
# count_095 += 1
# if thresh_times[i] >= 1.0:
# count_100 += 1
# count_095 = float(count_095)/N*100
# count_100 = float(count_100)/N*100
accuracy = good/size*100
if unknown != size:
true_accuracy = ((2*size*good/size - size)+ (size-unknown))/(2*(size-unknown))*100
else:
true_accuracy = 'NAN'
print 5*(k+1), "\t", 0.2 + j*0.1, "\t", 0.5 + l*0.05, "\t" ,size, "\t",mean_thresh_time, "\t", accuracy, "\t", unknown/size*100, "\t", true_accuracy, "\t", good , "\t", unknown, np.mean(diff), np.std(diff), min(diff), max(diff) #, "\t",thresh_min_time, "\t",thresh_max_time, "\t",count_095, "\t",count_100
plt.show()
def main():
# root = Tk()
# root.withdraw()
# file_names = askopenfilenames(initialdir = '~/Documents/Manip')
# file_names = root.tk.splitlist(file_names)
# root.destroy()
plot = 0
app = wx.App(0)
dlg = MDD.MultiDirDialog(None, title="Custom MultiDirDialog", defaultPath="/home/lucas/Documents/Manip/", # defaultPath="C:/Users/users/Desktop/",
agwStyle=MDD.DD_MULTIPLE|MDD.DD_DIR_MUST_EXIST)
if dlg.ShowModal() != wx.ID_OK:
print("You Cancelled The Dialog!")
dlg.Destroy()
paths = dlg.GetPaths()
dlg.Destroy()
app.MainLoop()
DATA = pandas.DataFrame(data={'SUBJ_NB': [], 'SUBJ_NAME1' : [], 'SUBJ_NAME2' : [], 'IS_TRAINING':[] , 'EXP_COND' : [], 'TRIAL_NB' : [], 'ST_TIME' : [], 'END_TIME' : [], 'SUBJ_TARGET1' : [], 'SUBJ_TARGET2' : [], 'FINAL_CHOICE' : [], 'FINAL_POS1': [], 'FINAL_POS2': [], 'FINAL_POSC' : [], 'TARGET_WIDTH1' : [], 'TARGET_WIDTH2' : []})
DATA_HIST = pandas.DataFrame(data={'SUBJ_NB':[], 'SUBJ_NAME1' : [], 'SUBJ_NAME2' : [], 'EXP_COND':[], 'HIST':[], 'TRIAL_NB' : [], 'IS_TRAINING':[]})
###### EXPE #####################################################################################################
for path in enumerate(paths):
directory= path[1].replace('Home directory','/home/lucas')
filesToAdd = os.listdir(directory)
fileName =[]
fileType = []
date = []
isTraining = []
for file in filesToAdd:
DataClass = FileData(directory + '/' + file)
if DataClass.fileName.find('_UI_')!=-1 or DataClass.fileName.find('~')!=-1:
continue
fileName.append(str(DataClass.fileName))
fileType.append(DataClass.fileType)
date.append(DataClass.fileDate)
df = pandas.DataFrame(data={'fileName': fileName, 'fileType': fileType, 'date':date})
df = df.sort_values(by=['fileType', 'date'])
tempType = ''
tempCount = 0
expCond=[]
for f in df['fileType']:
if f != tempType:
expCond.append(f)
tempCount = 0
if tempCount < 2:
isTraining.append(1)
else:
isTraining.append(0)
tempType = f
tempCount +=1
df['isTraining'] = isTraining
subj_names = [[],[]]
file_counter = 0
###### COND #####################################################################################################
for cond in expCond:
figNb = 0
nb_trial = 0
n_subplots = len(df[df['fileType'] == cond])
l=int(np.sqrt(n_subplots))
if n_subplots-l*l == 0:
i_subplots = l
j_subplots = l
elif n_subplots-l*l <= l:
i_subplots = l
j_subplots = l+1
elif n_subplots-l*l > l:
i_subplots = l+1
j_subplots = l+1
if plot:
if cond == 'ALONE':
axarr_pos = [[],[]]
axarr_vit = [[],[]]
f = [0]*4
f[0], axarr_pos[0] = plt.subplots(i_subplots, j_subplots)
f[1], axarr_pos[1] = plt.subplots(i_subplots, j_subplots)
f[2], axarr_vit[0] = plt.subplots(i_subplots, j_subplots)
f[3], axarr_vit[1] = plt.subplots(i_subplots, j_subplots)
axarr_pos[0] = np.matrix(axarr_pos[0])
axarr_pos[1] = np.matrix(axarr_pos[1])
axarr_vit[0] = np.matrix(axarr_vit[0])
axarr_vit[1] = np.matrix(axarr_vit[1])
else:
f[0], axarr_pos[0] = plt.subplots(i_subplots, j_subplots)
f[2], axarr_vit[0] = plt.subplots(i_subplots, j_subplots)
axarr_pos[0] = np.matrix(axarr_pos[0])
axarr_vit[0] = np.matrix(axarr_vit[0])
nb_subjects = 2
file_counter = 0
hist_vit = [[],[],[]]
hist_vit[0] = np.array([0]*101)
hist_vit[1] = np.array([0]*101)
hist_vit[2] = np.array([0]*101)
###### FILES #####################################################################################################
for file in df[df['fileType'] == cond]['fileName']:
print file
DataClass = FileData(file)
DataClass.getDataFromFile()
N = len(DataClass.Time)
DataClass.getDataFromUIFile()
subj_names[0] = DataClass.SUBJECT_NAMES[0]
subj_names[1] = DataClass.SUBJECT_NAMES[1]
nb_subjects = DataClass.UINbSubjects
if plot:
if cond == 'ALONE':
f[0].suptitle(subj_names[0])
f[1].suptitle(subj_names[1])
f[2].suptitle(subj_names[0])
f[3].suptitle(subj_names[1])
else:
f[0].suptitle(subj_names[0]+'+'+subj_names[1])
f[2].suptitle(subj_names[0]+'+'+subj_names[1])
nyq = 0.5*5000
low = 10/nyq
b, a = sig.butter(6, low, btype = 'low')
b2, a2 = sig.butter(2, 50/nyq, btype = 'low')
t0 = 0#int(2/DataClass.Time[N-1]*N)
tf = N#int(25/DataClass.Time[N-1]*N)
#Applying Butterworth filer to force signals
for1 = sig.lfilter(b, a, DataClass.Subj_for1)
for2 = sig.lfilter(b, a, DataClass.Subj_for2)
pos = [[],[]]
pos[0] = sig.lfilter(b2, a2, DataClass.Subj_pos1)
pos[1] = sig.lfilter(b2, a2, DataClass.Subj_pos2)
posC = sig.lfilter(b2, a2, DataClass.Curs_pos)
vit = [[],[]]
vit[0] = [0]*N
vit[1] = [0]*N
vitC = [0]*N
for i in range(4,N-4):
vit[0][i] = 1./280*pos[0][i-4] - 4./105*pos[0][i-3] + 1./5*pos[0][i-2] - 4./5*pos[0][i-1] + 4./5*pos[0][i+1] - 1./5*pos[0][i+2] + 4./105*pos[0][i+3] - 1./280*pos[0][i+4]
vit[1][i] = 1./280*pos[1][i-4] - 4./105*pos[1][i-3] + 1./5*pos[1][i-2] - 4./5*pos[1][i-1] + 4./5*pos[1][i+1] - 1./5*pos[1][i+2] + 4./105*pos[1][i+3] - 1./280*pos[1][i+4]
if cond == 'HFOP' or cond == 'HFO':
vitC[i] = 1./280*posC[i-4] - 4./105*posC[i-3] + 1./5*posC[i-2] - 4./5*posC[i-1] + 4./5*posC[i+1] - 1./5*posC[i+2] + 4./105*posC[i+3] - 1./280*posC[i+4]
indices_trial = [0]
indices_phase = [[],[]]
indices_phase[0] = [0]
indices_phase[1] = [0]
for i in range(0, N-1):
if DataClass.TimeTrial[i] > 0.05 and DataClass.TimeTrial[i+1] < 0.05:
indices_trial.append(i+1)
if DataClass.TimePhase1[i] > 0.05 and DataClass.TimePhase1[i+1] < 0.05:
indices_phase[0].append(i+1)
if DataClass.TimePhase2[i] > 0.05 and DataClass.TimePhase2[i+1] < 0.05:
indices_phase[1].append(i+1)
# indices_trial.append(N-1)
indices_phase[0].append(N-1)
indices_phase[1].append(N-1)
################## EXTRACT START AND END TIMES + VELOCITIES HISTOGRAMS
#######################"
if cond=='ALONE':
for k in range(0,nb_subjects):
st_timesC = []
end_timesC = []
st_timesF = []
end_timesF = []
for i in range(0, len(DataClass.UITrialNumber)):
t0 = indices_trial[2*i+1]
tf = indices_phase[k][4*i+3]- DataClass.time2line(1)
tempST = 0
tempEND = 0
if DataClass.UIFinalChoice[k][i] == DataClass.UITargetPosC[i]:
final_target = DataClass.UITargetPosC[i]
target_width = DataClass.UITargetWidth[0]
for j in range(t0, tf):
if abs(pos[k][j-1] - DataClass.UIStartPos[i]) < DataClass.UIStartWidth and abs(pos[k][j] - DataClass.UIStartPos[i]) > DataClass.UIStartWidth:
tempST = DataClass.Time[j-t0]
tempEND = DataClass.Time[tf-t0]
st_timesC.append(tempST)
end_timesC.append(tempEND)
elif DataClass.UIFinalChoice[k][i] == DataClass.UITargetPosF[i]:
final_target = DataClass.UITargetPosF[i]
target_width = DataClass.UITargetWidth[1]
for j in range(t0, tf):
if abs(pos[k][j-1] - DataClass.UIStartPos[i]) < DataClass.UIStartWidth and abs(pos[k][j] - DataClass.UIStartPos[i]) > DataClass.UIStartWidth:
tempST = DataClass.Time[j-t0]
tempEND = DataClass.Time[tf-t0]
st_timesF.append(tempST)
end_timesF.append(tempEND)
else:
final_target = 0
target_width = 0
tempdf = pandas.DataFrame(data={'SUBJ_NB': [k], 'SUBJ_NAME1':[subj_names[0]], 'SUBJ_NAME2': [subj_names[1]], 'IS_TRAINING':[int(df[df['fileName']==file]['isTraining'])] , 'EXP_COND' : [DataClass.fileType], 'TRIAL_NB' : [file_counter], 'ST_TIME' : [tempST], 'END_TIME' : [tempEND], 'SUBJ_TARGET1' : [DataClass.UITargetSubj[0][i]], 'SUBJ_TARGET2' : [DataClass.UITargetSubj[1][i]], 'FINAL_CHOICE' : [DataClass.UIFinalChoice[k][i]], 'FINAL_POS1': [pos[0][tf+DataClass.time2line(1)]], 'FINAL_POS2': [pos[1][tf+DataClass.time2line(1)]], 'FINAL_POSC' : ['-'], 'TARGET_WIDTH1' : [DataClass.UITargetWidth[0][i]], 'TARGET_WIDTH2' : [DataClass.UITargetWidth[1][i]] })
DATA = DATA.append(tempdf, ignore_index=True)
# if(not(int(df[df['fileName']==file]['isTraining']))):
# temp_hist, temp_bins = np.histogram([x for x in vit[k][t0:tf] if abs(x)>0.01], bins=101, range=(-0.75,1.5))
# hist_vit[k] = np.add(hist_vit[k], temp_hist)
temp_hist, temp_bins = np.histogram([x for x in vit[k][t0:tf] if abs(x)>0.01], bins=101, range=(-0.75,1.5))
if np.sum(temp_hist)!=0:
temp_hist = [float(x)/float(np.sum(temp_hist)) for x in temp_hist]
else:
temp_hist = [float(x) for x in temp_hist]
tempdf = pandas.DataFrame(data={'SUBJ_NB':[k], 'SUBJ_NAME1':[subj_names[0]], 'SUBJ_NAME2': [subj_names[1]], 'EXP_COND':[cond], 'HIST':[temp_hist], 'TRIAL_NB' : [file_counter], 'IS_TRAINING':[int(df[df['fileName']==file]['isTraining'])]})
DATA_HIST = DATA_HIST.append(tempdf,ignore_index=True)
elif cond=='HFOP':
st_timesC = []
end_timesC = []
st_timesF = []
end_timesF = []
for i in range(0, len(DataClass.UITrialNumber)):
t0 = indices_trial[2*i+1]
tf = indices_phase[0][4*i+3]- DataClass.time2line(1)
tempST = 0
tempEND = 0
if DataClass.UIFinalChoice[0][i] == DataClass.UITargetPosC[i]:
final_target = DataClass.UITargetPosC[i]
target_width = DataClass.UITargetWidth[0]
for j in range(t0, tf):
if abs(posC[j-1] - DataClass.UIStartPos[i]) < DataClass.UIStartWidth and abs(posC[j] - DataClass.UIStartPos[i]) > DataClass.UIStartWidth:
tempST = DataClass.Time[j-t0]
tempEND = DataClass.Time[tf-t0]
st_timesC.append(tempST)
end_timesC.append(tempEND)
elif DataClass.UIFinalChoice[0][i] == DataClass.UITargetPosF[i]:
final_target = DataClass.UITargetPosF[i]
target_width = DataClass.UITargetWidth[1]
for j in range(t0, tf):
if abs(posC[j-1] - DataClass.UIStartPos[i]) < DataClass.UIStartWidth and abs(posC[j] - DataClass.UIStartPos[i]) > DataClass.UIStartWidth:
tempST = DataClass.Time[j-t0]
tempEND = DataClass.Time[tf-t0]
st_timesF.append(tempST)
end_timesF.append(tempEND)
else:
final_target = 0
target_width = 0
tempdf = pandas.DataFrame(data={'SUBJ_NB': [2], 'SUBJ_NAME1':[subj_names[0]], 'SUBJ_NAME2': [subj_names[1]], 'IS_TRAINING':[int(df[df['fileName']==file]['isTraining'])] , 'EXP_COND' : [DataClass.fileType], 'TRIAL_NB' : [file_counter], 'ST_TIME' : [tempST], 'END_TIME' : [tempEND], 'SUBJ_TARGET1' : [DataClass.UITargetSubj[0][i]], 'SUBJ_TARGET2' : [DataClass.UITargetSubj[1][i]], 'FINAL_CHOICE' : [DataClass.UIFinalChoice[0][i]], 'FINAL_POS1': [pos[0][tf+DataClass.time2line(1)]], 'FINAL_POS2': [pos[1][tf+DataClass.time2line(1)]], 'FINAL_POSC' : [posC[tf+DataClass.time2line(1)]], 'TARGET_WIDTH1' : [DataClass.UITargetWidth[0][i]], 'TARGET_WIDTH2' : [DataClass.UITargetWidth[1][i]]})
DATA = DATA.append(tempdf, ignore_index=True)
# if(not(int(df[df['fileName']==file]['isTraining']))):
# temp_hist, temp_bins = np.histogram([x for x in vitC[t0:tf] if abs(x)>0.01], bins=101, range=(-0.75,1.5))
# hist_vit[2] = np.add(hist_vit[2], temp_hist)
temp_hist, temp_bins = np.histogram([x for x in vitC[t0:tf] if abs(x)>0.01], bins=101, range=(-0.75,1.5))
if np.sum(temp_hist)!=0:
temp_hist = [float(x)/float(np.sum(temp_hist)) for x in temp_hist]
else:
temp_hist = [float(x) for x in temp_hist]
tempdf = pandas.DataFrame(data={'SUBJ_NB':[2], 'SUBJ_NAME1':[subj_names[0]], 'SUBJ_NAME2': [subj_names[1]], 'EXP_COND':[cond], 'HIST':[temp_hist], 'TRIAL_NB' : [file_counter], 'IS_TRAINING':[int(df[df['fileName']==file]['isTraining'])]})
DATA_HIST = DATA_HIST.append(tempdf,ignore_index=True)
elif cond=='HFO':
st_timesC = []
end_timesC = []
st_timesF = []
end_timesF = []
for i in range(0, len(DataClass.UITrialNumber)):
t0 = indices_trial[2*i+1]
tf = indices_phase[0][4*i+3]- DataClass.time2line(1)
tempST = 0
tempEND = 0
if DataClass.UIFinalChoice[0][i] == DataClass.UITargetPosC[i]:
final_target = DataClass.UITargetPosC[i]
target_width = DataClass.UITargetWidth[0]
for j in range(t0, tf):
if abs(posC[j-1] - DataClass.UIStartPos[i]) < DataClass.UIStartWidth and abs(posC[j] - DataClass.UIStartPos[i]) > DataClass.UIStartWidth:
tempST = DataClass.Time[j-t0]
tempEND = DataClass.Time[tf-t0]
st_timesC.append(tempST)
end_timesC.append(tempEND)
elif DataClass.UIFinalChoice[0][i] == DataClass.UITargetPosF[i]:
final_target = DataClass.UITargetPosF[i]
target_width = DataClass.UITargetWidth[1]
for j in range(t0, tf):
if abs(posC[j-1] - DataClass.UIStartPos[i]) < DataClass.UIStartWidth and abs(posC[j] - DataClass.UIStartPos[i]) > DataClass.UIStartWidth:
tempST = DataClass.Time[j-t0]
tempEND = DataClass.Time[tf-t0]
st_timesF.append(tempST)
end_timesF.append(tempEND)
else:
final_target = 0
target_width = 0
tempdf = pandas.DataFrame(data={'SUBJ_NB': [2], 'SUBJ_NAME1':[subj_names[0]], 'SUBJ_NAME2': [subj_names[1]], 'IS_TRAINING':[int(df[df['fileName']==file]['isTraining'])] , 'EXP_COND' : [DataClass.fileType], 'TRIAL_NB' : [file_counter], 'ST_TIME' : [tempST], 'END_TIME' : [tempEND], 'SUBJ_TARGET1' : [DataClass.UITargetSubj[0][i]], 'SUBJ_TARGET2' : [DataClass.UITargetSubj[1][i]], 'FINAL_CHOICE' : [DataClass.UIFinalChoice[0][i]], 'FINAL_POS1': [pos[0][tf+DataClass.time2line(1)]], 'FINAL_POS2': [pos[1][tf+DataClass.time2line(1)]], 'FINAL_POSC' : [posC[tf+DataClass.time2line(1)]], 'TARGET_WIDTH1' : [DataClass.UITargetWidth[0][i]], 'TARGET_WIDTH2' : [DataClass.UITargetWidth[1][i]]})
DATA = DATA.append(tempdf, ignore_index=True)
# if(not(int(df[df['fileName']==file]['isTraining']))):
# temp_hist, temp_bins = np.histogram([x for x in vit[0][t0:tf] if abs(x)>0.01], bins=101, range=(-0.75,1.5))
# hist_vit[0] = np.add(hist_vit[0], temp_hist)
# temp_hist, temp_bins = np.histogram([x for x in vit[1][t0:tf] if abs(x)>0.01], bins=101, range=(-0.75,1.5))
# hist_vit[1] = np.add(hist_vit[1], temp_hist)
# temp_hist, temp_bins = np.histogram([x for x in vitC[t0:tf] if abs(x)>0.01], bins=101, range=(-0.75,1.5))
# hist_vit[2] = np.add(hist_vit[2], temp_hist)
for k in range(0, nb_subjects):
temp_hist, temp_bins = np.histogram([x for x in vit[k][t0:tf] if abs(x)>0.01], bins=101, range=(-0.75,1.5))
if np.sum(temp_hist)!=0:
temp_hist = [float(x)/float(np.sum(temp_hist)) for x in temp_hist]
else:
temp_hist = [float(x) for x in temp_hist]
tempdf = pandas.DataFrame(data={'SUBJ_NB':[k], 'SUBJ_NAME1':[subj_names[0]], 'SUBJ_NAME2': [subj_names[1]], 'EXP_COND':[cond], 'HIST':[temp_hist], 'TRIAL_NB' : [file_counter], 'IS_TRAINING':[int(df[df['fileName']==file]['isTraining'])]})
DATA_HIST = DATA_HIST.append(tempdf,ignore_index=True)
temp_hist, temp_bins = np.histogram([x for x in vitC[t0:tf] if abs(x)>0.01], bins=101, range=(-0.75,1.5))
temp_hist = [float(x)/float(np.sum(temp_hist)) for x in temp_hist]
tempdf = pandas.DataFrame(data={'SUBJ_NB':[2], 'SUBJ_NAME1':[subj_names[0]], 'SUBJ_NAME2': [subj_names[1]], 'EXP_COND':[cond], 'HIST':[temp_hist], 'TRIAL_NB' : [file_counter], 'IS_TRAINING':[int(df[df['fileName']==file]['isTraining'])]})
DATA_HIST = DATA_HIST.append(tempdf,ignore_index=True)
# print "Subject : ", k
# print "Mean Start Time Target C : ", np.mean(st_timesC)
# print "Mean End Time Target C : ", np.mean(end_timesC)
# print "Mean Start Time Target F : ", np.mean(st_timesF)
# print "Mean End Time Target F : ", np.mean(end_timesF)
# print "Mean Traj Time Target C : ", np.mean([end_timesC[i] - st_timesC[i] for i in range(0, len(st_timesC))])
# print "Mean Traj Time Target F : ", np.mean([end_timesF[i] - st_timesF[i] for i in range(0, len(st_timesF))])
# print ("\n")
########################PLOTS
#########################
if plot:
if cond == 'ALONE':
## PLOT POSITIONS
pos_targetC = [DataClass.UITargetPosC[0]]*(tf-t0)
pos_targetF = [DataClass.UITargetPosF[0]]*(tf-t0)
pos_start = [DataClass.UIStartPos[0]]*(tf-t0)
width_tC = DataClass.UITargetWidthC
width_tF = DataClass.UITargetWidthF
for k in range(0,nb_subjects):
plt.figure(f[k].number)
figNb+=1
# axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots] = plt.subplot(111)
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].axis([0, DataClass.WINDOW_WIDTH, 0, 2])
temp1 = []
temp2 = []
for i in range(0, len(DataClass.UITrialNumber)):
t0 = indices_trial[2*i+1]
tf = indices_phase[k][4*i+3]- DataClass.time2line(1)
time_local = [ x - DataClass.Time[t0] for x in DataClass.Time[t0:tf]]
pos_targetC = [DataClass.UITargetPosC[0]]*(tf-t0)
pos_targetF = [DataClass.UITargetPosF[0]]*(tf-t0)
pos_start = [DataClass.UIStartPos[0]]*(tf-t0)
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(pos_targetC, time_local,'k')
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([x-width_tC for x in pos_targetC], time_local,'k--')
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([x+width_tC for x in pos_targetC], time_local,'k--')
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(pos_targetF, time_local,'k')
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([x-width_tF for x in pos_targetF], time_local,'k--')
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([x+width_tF for x in pos_targetF], time_local,'k--')
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(pos_start, time_local,'k')
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([x-10 for x in pos_start], time_local,'k--')
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([x+10 for x in pos_start], time_local,'k--')
if DataClass.UIFinalChoice[k][i] == DataClass.UITargetPosC[i]:
# axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([0, DataClass.WINDOW_WIDTH],[DataClass.Time[indices_phase[0][2*i+1]]-DataClass.Time[t0], DataClass.Time[indices_phase[0][2*i+1]]-DataClass.Time[t0]], 'r--')
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([0, DataClass.WINDOW_WIDTH],[DataClass.Time[tf]-DataClass.Time[t0], DataClass.Time[tf]-DataClass.Time[t0]], 'g--')
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(pos[k][t0:tf], time_local,'g')
temp1.append(tf-t0)
elif DataClass.UIFinalChoice[k][i] == DataClass.UITargetPosF[i]:
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([0, DataClass.WINDOW_WIDTH],[DataClass.Time[tf]-DataClass.Time[t0], DataClass.Time[tf]-DataClass.Time[t0]], 'b--')
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(pos[k][t0:tf], time_local,'b')
temp2.append(tf-t0)
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([0, DataClass.WINDOW_WIDTH],[DataClass.Time[int(np.mean(temp1))], DataClass.Time[int(np.mean(temp1))]], 'g-', linewidth=3)
axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([0, DataClass.WINDOW_WIDTH],[DataClass.Time[int(np.mean(temp2))], DataClass.Time[int(np.mean(temp2))]], 'b-', linewidth=3)
## PLOT VITESSES
for k in range(0,nb_subjects):
plt.figure(f[k+2].number)
figNb+=1
for i in range(0, len(DataClass.UITrialNumber)):
t0 = indices_trial[2*i+1]
tf = indices_phase[k][4*i+3]- DataClass.time2line(1)
time_local = [ x - DataClass.Time[t0] for x in DataClass.Time[t0:tf]]
if DataClass.UIFinalChoice[k][i] == DataClass.UITargetPosC[i]:
axarr_vit[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(vit[k][t0:tf], time_local,'g')
temp1.append(tf-t0)
elif DataClass.UIFinalChoice[k][i] == DataClass.UITargetPosF[i]:
axarr_vit[k][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(vit[k][t0:tf], time_local,'b')
temp2.append(tf-t0)
elif cond == 'HFOP':
## PLOT POSITIONS
pos_targetC = [DataClass.UITargetPosC[0]]*(tf-t0)
pos_targetF = [DataClass.UITargetPosF[0]]*(tf-t0)
pos_start = [DataClass.UIStartPos[0]]*(tf-t0)
width_tC = DataClass.UITargetWidthC
width_tF = DataClass.UITargetWidthF
plt.figure(f[0].number)
figNb+=1
# axarr_pos[k][int(nb_trial/j_subplots), nb_trial%j_subplots] = plt.subplot(111)
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].axis([0, DataClass.WINDOW_WIDTH, 0, 2])
temp1 = []
temp2 = []
for i in range(0, len(DataClass.UITrialNumber)):
t0 = indices_trial[2*i+1]
tf = indices_phase[0][4*i+3]- DataClass.time2line(1)
time_local = [ x - DataClass.Time[t0] for x in DataClass.Time[t0:tf]]
pos_targetC = [DataClass.UITargetPosC[0]]*(tf-t0)
pos_targetF = [DataClass.UITargetPosF[0]]*(tf-t0)
pos_start = [DataClass.UIStartPos[0]]*(tf-t0)
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(pos_targetC, time_local,'k')
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([x-width_tC for x in pos_targetC], time_local,'k--')
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([x+width_tC for x in pos_targetC], time_local,'k--')
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(pos_targetF, time_local,'k')
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([x-width_tF for x in pos_targetF], time_local,'k--')
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([x+width_tF for x in pos_targetF], time_local,'k--')
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(pos_start, time_local,'k')
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([x-10 for x in pos_start], time_local,'k--')
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([x+10 for x in pos_start], time_local,'k--')
if DataClass.UIFinalChoice[0][i] == DataClass.UITargetPosC[i]:
# axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([0, DataClass.WINDOW_WIDTH],[DataClass.Time[indices_phase[0][2*i+1]]-DataClass.Time[t0], DataClass.Time[indices_phase[0][2*i+1]]-DataClass.Time[t0]], 'r--')
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([0, DataClass.WINDOW_WIDTH],[DataClass.Time[tf]-DataClass.Time[t0], DataClass.Time[tf]-DataClass.Time[t0]], 'g--')
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(posC[t0:tf], time_local,'g')
temp1.append(tf-t0)
elif DataClass.UIFinalChoice[0][i] == DataClass.UITargetPosF[i]:
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([0, DataClass.WINDOW_WIDTH],[DataClass.Time[tf]-DataClass.Time[t0], DataClass.Time[tf]-DataClass.Time[t0]], 'b--')
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(posC[t0:tf], time_local,'b')
temp2.append(tf-t0)
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([0, DataClass.WINDOW_WIDTH],[DataClass.Time[int(np.mean(temp1))], DataClass.Time[int(np.mean(temp1))]], 'g-', linewidth=3)
axarr_pos[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot([0, DataClass.WINDOW_WIDTH],[DataClass.Time[int(np.mean(temp2))], DataClass.Time[int(np.mean(temp2))]], 'b-', linewidth=3)
## PLOT VITESSES
plt.figure(f[2].number)
figNb+=1
for i in range(0, len(DataClass.UITrialNumber)):
t0 = indices_trial[2*i+1]
tf = indices_phase[0][4*i+3]- DataClass.time2line(1)
time_local = [ x - DataClass.Time[t0] for x in DataClass.Time[t0:tf]]
if DataClass.UIFinalChoice[0][i] == DataClass.UITargetPosC[i]:
axarr_vit[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(vitC[t0:tf], time_local,'g')
temp1.append(tf-t0)
elif DataClass.UIFinalChoice[0][i] == DataClass.UITargetPosF[i]:
axarr_vit[0][int(nb_trial/j_subplots), nb_trial%j_subplots].plot(vitC[t0:tf], time_local,'b')
temp2.append(tf-t0)
file_counter+=1
nb_trial+=1
###### FILES #####################################################################################################
# if cond=='ALONE':
# for k in range(0, nb_subjects):
# hist_vit[k] = [float(x)/float(np.sum(hist_vit[k])) for x in hist_vit[k]]
# tempdf = pandas.DataFrame(data={'SUBJ_NB':[k], 'SUBJ_NAME1':[subj_names[0]], 'SUBJ_NAME2': [subj_names[1]], 'EXP_COND':[cond], 'HIST':[hist_vit[k]]})
# DATA_HIST = DATA_HIST.append(tempdf,ignore_index=True)
# elif cond=='HFOP':
# hist_vit[2] = [float(x)/float(np.sum(hist_vit[2])) for x in hist_vit[2]]
# tempdf = pandas.DataFrame(data={'SUBJ_NB':[2], 'SUBJ_NAME1':[subj_names[0]], 'SUBJ_NAME2': [subj_names[1]], 'EXP_COND':[cond], 'HIST':[hist_vit[2]]})
# DATA_HIST = DATA_HIST.append(tempdf,ignore_index=True)
# elif cond=='HFO':
# for k in range(0, nb_subjects+1):
# hist_vit[k] = [float(x)/float(np.sum(hist_vit[k])) for x in hist_vit[k]]
# tempdf = pandas.DataFrame(data={'SUBJ_NB':[k], 'SUBJ_NAME1':[subj_names[0]], 'SUBJ_NAME2': [subj_names[1]], 'EXP_COND':[cond], 'HIST':[hist_vit[k]]})
# DATA_HIST = DATA_HIST.append(tempdf,ignore_index=True)
###### COND #####################################################################################################
###### EXPE #####################################################################################################
print DATA
print DATA_HIST
# for i in range(0, len(DATA_HIST['HIST'])):
# plt.figure()
# if(DATA_HIST['SUBJ_NB'][i]==0):
# plt.title(DATA_HIST['EXP_COND'][i] + ' : ' + DATA_HIST['SUBJ_NAME1'][i])
# elif(DATA_HIST['SUBJ_NB'][i]==1):
# plt.title(DATA_HIST['EXP_COND'][i] + ' : ' + DATA_HIST['SUBJ_NAME2'][i])
# elif(DATA_HIST['SUBJ_NB'][i]==2):
# plt.title(DATA_HIST['EXP_COND'][i] + ' : ' + DATA_HIST['SUBJ_NAME1'][i]+'+'+DATA_HIST['SUBJ_NAME2'][i])
# plt.plot(np.linspace(-0.75, 1.5, 101), DATA_HIST['HIST'][i])
date = time.gmtime(None)
date = str(date.tm_mday) + "-" + str(date.tm_mon) + "-" + str(date.tm_hour+2) + "-" + str(date.tm_min)
DATA.to_csv('~/Documents/Manip/DATA_POINTING_choices_'+date+'.csv')
DATA_HIST.to_csv('~/Documents/Manip/DATA_POINTING_histograms_'+date+'.csv')
plt.show(block='False')
def __init__(self, pof, b_verbose, b_detail, b_byfile, b_recur, b_exem,
ex_fo, ex_fi, sort, *args, **kwargs):
"""Builder gui"""
# Master gui
super().__init__(*args, **kwargs)
self.withdraw() # Hide GUI
self.iconbitmap(fr'{PATH_PICTURE}/icon.ico')
self.title('Pyline counter')
# Size and coordinate
w = 1200
h = 800
ws = self.winfo_screenwidth() # width of the screen
hs = self.winfo_screenheight() # height of the screen
x = int((ws / 2) - (w / 2))
y = int((hs / 2) - (h / 2))
self.geometry(f"{w}x{h}+{x}+{y}")
# Defaults attributes
self.la_th = Thread()
self.b_cancel = False
# Custom multi directory dialog
self.dlg = mdd.MultiDirDialog(None,
message="Select one or more "
"folders",
defaultPath=PATH_PROJECT,
agwStyle=mdd.DD_MULTIPLE
| mdd.DD_DIR_MUST_EXIST)
# Label / Buttons select pof
frame_pof = tk.Frame(self)
frame_pof.pack(anchor=tk.W, padx=2, pady=3)
tk.Label(frame_pof, text="Select").pack(side=tk.LEFT)
tk.Button(frame_pof, text="path",
command=self.button_browse_path).pack(side=tk.LEFT)
tk.Label(frame_pof, text="or").pack(side=tk.LEFT)
tk.Button(frame_pof, text="file",
command=self.button_browse_file).pack(side=tk.LEFT)
tk.Label(frame_pof, text=":").pack(side=tk.LEFT)
self.label_pof = tk.StringVar()
self.label_pof.trace('w', self.prerequisite_analysis)
tk.Entry(frame_pof, width=90,
textvariable=self.label_pof).pack(side=tk.LEFT)
# Checkbutton option
self.option = [
[
"verbose (-v) : Increases the level of verbosity for "
"debugging.",
tk.BooleanVar(value=b_verbose)
],
[
"detail (-d) : Display detail information (number of "
"Class/Decorator/Function/Docstring/Comment/Blank "
"line).",
tk.BooleanVar(value=b_detail)
],
[
"byfile (-b) : Display information by file (one "
"more line for the total).",
tk.BooleanVar(value=b_byfile)
],
[
"recursive (-r) : Search files in subfolders (path "
"only).",
tk.BooleanVar(value=b_recur)
],
[
"exclude_empty (-e) : Exclude empty files "
"from result.",
tk.BooleanVar(value=b_exem)
]
]
frame_option = tk.Frame(self)
frame_option.pack(anchor=tk.W)
for name, b_etat in self.option:
check = tk.Checkbutton(frame_option, text=name, variable=b_etat)
check.pack(anchor=tk.W)
# Option -o (exclude folder) and -i (exclude file)
self.option_ex_fo = tk.BooleanVar()
self.label_ex_fo = tk.StringVar()
self.option_ex_fi = tk.BooleanVar()
self.label_ex_fi = tk.StringVar()
l_ex = [[
self.option_ex_fo, self.label_ex_fo, self.lab_ex_fo,
self.button_ex_fo, self.checkbox_option_ex_fo, ex_fo,
"exclude_folder (-o) :", "Exclude folders",
"from analysis (recursive option must be enabled; regex "
"default pattern:'.*\\your_input\\.*'; delimiter:';') :", 65
],
[
self.option_ex_fi, self.label_ex_fi, self.lab_ex_fi,
self.button_ex_fi, self.checkbox_option_ex_fi, ex_fi,
"exclude_file (-i) :", "Exclude files",
"from analysis (path only; regex default pattern:"
"'^your_input$'; delimiter:';') :", 70
]]
for el in l_ex:
frame = tk.Frame(self)
frame.pack(anchor=tk.W)
el[1].trace('w', el[2])
tk.Checkbutton(frame, text=el[6],
variable=el[0]).pack(anchor=tk.W, side=tk.LEFT)
tk.Button(frame, text=el[7], command=el[3]).pack(side=tk.LEFT)
lab = tk.Label(frame, text=el[8])
lab.pack(side=tk.LEFT, expand=True)
lab.bind("<Button-1>", el[4])
tk.Entry(frame, width=el[9], textvariable=el[1]).pack(side=tk.LEFT)
el[1].set(el[5])
# Option -s (sort)
frame_sort = tk.Frame(self)
frame_sort.pack(anchor=tk.W)
self.option_sort = tk.BooleanVar()
self.select_sort = tk.StringVar()
self.select_sort.trace('w', self.str_sort)
tk.Checkbutton(frame_sort,
text="sort (-s) : Sort the "
"result by (byfile option must be "
"enabled) :",
variable=self.option_sort).pack(anchor=tk.W,
side=tk.LEFT)
combo_sort = ttk.Combobox(frame_sort,
width=8,
textvariable=self.select_sort,
state="readonly")
combo_sort.bind("<<ComboboxSelected>>", lambda e: frame_sort.focus())
combo_sort.config(values=("file", "nb", "class", "deco", "func", "doc",
"com", "blank", "_file", "_nb", "_class",
"_deco", "_func", "_doc", "_com", "_blank"))
combo_sort.pack(side=tk.LEFT)
self.select_sort.set(sort)
if not sort:
combo_sort.current(0)
self.option_sort.set(False)
# Button analysis and clear text result
frame_analysis = tk.Frame(self)
frame_analysis.pack(pady=(30, 0))
self.button_analysis = tk.Button(frame_analysis,
text="Start analysis",
command=self.button_sc_analysis)
self.button_clear = tk.Button(frame_analysis,
text="Clear result",
command=self.button_clear_result)
self.label_pof.set(pof) # Disable button analysis if empty
self.button_analysis.pack(side=tk.LEFT, padx=30)
self.button_clear.pack(side=tk.LEFT)
# Progressbar
frame_progress = tk.Frame(self)
frame_progress.pack(fill=tk.BOTH, pady=(15, 0))
self.progress_var = tk.DoubleVar()
self.progress_style = ttk.Style(self)
self.progress_style.layout( # add label in the layout
'text.Horizontal.TProgressbar',
[('Horizontal.Progressbar.trough', {
'children': [('Horizontal.Progressbar.pbar', {
'side': 'left',
'sticky': 'ns'
})],
'sticky':
'nswe'
}), ('Horizontal.Progressbar.label', {
'sticky': ''
})])
self.progress_style.configure( # set initial text
'text.Horizontal.TProgressbar',
text=PROGRESS_DEFAULT)
self.progress = ttk.Progressbar(frame_progress,
style='text.Horizontal'
'.TProgressbar',
variable=self.progress_var)
self.progress.pack(fill=tk.BOTH)
# Text result
self.text_scroll = GuiTextScrollCombo()
self.text_scroll.pack(fill=tk.BOTH, expand=True)
self.textvar_result = tk.StringVar()
self.textvar_result.trace('w', self.display_result)
self.textvar_result.set('') # Disable button clear
# Display GUI
self.update()
self.deiconify()
def test_lib_agw_multidirdialogCtor(self):
dlg = MDD.MultiDirDialog(self.frame,
title="Custom MultiDirDialog",
agwStyle=MDD.DD_MULTIPLE
| MDD.DD_DIR_MUST_EXIST)
def main():
# Our normal wxApp-derived class, as usual
app = wx.App(0)
dlg = MDD.MultiDirDialog(
None,
title="Custom MultiDirDialog",
defaultPath=
"/home/lucas/Documents/Manip/", # defaultPath="C:/Users/users/Desktop/",
agwStyle=MDD.DD_MULTIPLE | MDD.DD_DIR_MUST_EXIST)
if dlg.ShowModal() != wx.ID_OK:
print("You Cancelled The Dialog!")
dlg.Destroy()
paths = dlg.GetPaths()
dlg.Destroy()
app.MainLoop()
nbChoicesS1tot = []
nbChoicesR1tot = []
nbChoicesS2tot = []
nbChoicesR2tot = []
nameS1tot = []
nameS2tot = []
fileTypetot = []
expeNbtot = []
expe_nb = 0
for path in enumerate(paths):
directory = path[1].replace('Home directory', '/home/lucas')
print(directory)
file_names = os.listdir(directory)
file_names_HFO = [
x for x in file_names
if x.find('_HFO_') != -1 or x.find('_s_') != -1
]
file_names_HFOP = [
x for x in file_names
if x.find('_HFOP_') != -1 or x.find('_a_') != -1
]
file_names_HVP = [
x for x in file_names if x.find('_HRP_') != -1
or x.find('_HVP_') != -1 or x.find('_u_') != -1
]
file_names_KVP = [
x for x in file_names
if x.find('_KRP_') != -1 or x.find('_KVP_') != -1
]
file_names_ALONE = [
x for x in file_names
if x.find('_Alone_') != -1 or x.find('_w_') != -1
]
#
file_names = file_names_HFO + file_names_HFOP + file_names_HVP + file_names_KVP
nbChoicesS1 = []
nbChoicesR1 = []
nbChoicesS2 = []
nbChoicesR2 = []
nameS1 = []
nameS2 = []
fileType = []
expeNb = []
d = 0
for file in file_names:
file = directory + '/' + file
if file.find('~') != -1: # or f.find('trial_1') != -1:
d += 1
continue
DataClass = FileData(file)
DataClass.getDataFromFile()
DataClass.analyzeDominance()
expeNb.append(expe_nb)
fileType.append(DataClass.fileType)
nameS1.append(DataClass.SUBJECT_NAME1)
nameS2.append(DataClass.SUBJECT_NAME2)
if DataClass.fileType == 'HFOP' or DataClass.fileType == 'HFO' or DataClass.fileType == 'HFOP_mou':
nbChoicesS1.append(DataClass.nbChoices1)
nbChoicesS2.append(DataClass.nbChoices2)
nbChoicesR1.append(0)
nbChoicesR2.append(0)
elif DataClass.fileType == 'HVP' or DataClass.fileType == 'KVP':
nbChoicesS1.append(DataClass.nbChoicesH1)
nbChoicesR1.append(DataClass.nbChoicesR1)
nbChoicesS2.append(DataClass.nbChoicesH2)
nbChoicesR2.append(DataClass.nbChoicesR2)
print file, " analyzed ... "
expe_nb += 1
nbChoicesS1tot.extend(nbChoicesS1)
nbChoicesR1tot.extend(nbChoicesR1)
nbChoicesS2tot.extend(nbChoicesS2)
nbChoicesR2tot.extend(nbChoicesR2)
nameS1tot.extend(nameS1)
nameS2tot.extend(nameS2)
fileTypetot.extend(fileType)
expeNbtot.extend(expeNb)
data = pandas.DataFrame({
'EXPE': expeNb,
'TYPE': fileType,
'Name1': nameS1,
'Name2': nameS2,
'Choices1': nbChoicesS1,
'Choices2': nbChoicesS2,
'Robot1': nbChoicesR1,
'Robot2': nbChoicesR2
})
plt.figure(data['Name1'][0] + '+' + data['Name2'][1])
#HFOP
labels = data['Name1'][0], data['Name2'][0]
sizes = [
np.mean(data[data['TYPE'] == 'HFOP']['Choices1']),
np.mean(data[data['TYPE'] == 'HFOP']['Choices2'])
]
ax1 = plt.subplot(321)
ax1.pie(sizes,
labels=labels,
autopct='%1.1f%%',
colors=['blue', 'red'],
startangle=90)
ax1.axis('equal'
) # Equal aspect ratio ensures that pie is drawn as a circle.
#HFO
labels = data['Name1'][0], data['Name2'][0]
sizes = [
np.mean(data[data['TYPE'] == 'HFO']['Choices1']),
np.mean(data[data['TYPE'] == 'HFO']['Choices2'])
]
ax2 = plt.subplot(322)
ax2.pie(sizes,
labels=labels,
autopct='%1.1f%%',
colors=['blue', 'red'],
startangle=90)
ax2.axis('equal'
) # Equal aspect ratio ensures that pie is drawn as a circle.
#HVP1
labels = data['Name1'][0], 'Robot1'
sizes = [
np.mean(data[data['TYPE'] == 'HVP']['Choices1']),
np.mean(data[data['TYPE'] == 'HVP']['Robot1'])
]
ax3 = plt.subplot(323)
ax3.pie(sizes,
labels=labels,
autopct='%1.1f%%',
colors=['blue', 'green'],
startangle=90)
ax3.axis('equal'
) # Equal aspect ratio ensures that pie is drawn as a circle.
#HVP2
labels = data['Name2'][0], 'Robot2'
sizes = [
np.mean(data[data['TYPE'] == 'HVP']['Choices2']),
np.mean(data[data['TYPE'] == 'HVP']['Robot2'])
]
ax4 = plt.subplot(324)
ax4.pie(sizes,
labels=labels,
autopct='%1.1f%%',
colors=['red', 'green'],
startangle=90)
ax4.axis('equal'
) # Equal aspect ratio ensures that pie is drawn as a circle.
#KVP1
labels = data['Name1'][0], 'Robot1'
sizes = [
np.mean(data[data['TYPE'] == 'KVP']['Choices1']),
np.mean(data[data['TYPE'] == 'KVP']['Robot1'])
]
ax5 = plt.subplot(325)
ax5.pie(sizes,
labels=labels,
autopct='%1.1f%%',
colors=['blue', 'green'],
startangle=90)
ax5.axis('equal'
) # Equal aspect ratio ensures that pie is drawn as a circle.
#KVP2
labels = data['Name2'][0], 'Robot2'
sizes = [
np.mean(data[data['TYPE'] == 'KVP']['Choices2']),
np.mean(data[data['TYPE'] == 'KVP']['Robot2'])
]
ax6 = plt.subplot(326)
ax6.pie(sizes,
labels=labels,
autopct='%1.1f%%',
colors=['red', 'green'],
startangle=90)
ax6.axis('equal'
) # Equal aspect ratio ensures that pie is drawn as a circle.
datatot = pandas.DataFrame({
'EXPE': expeNbtot,
'TYPE': fileTypetot,
'Name1': nameS1tot,
'Name2': nameS2tot,
'Choices1': nbChoicesS1tot,
'Choices2': nbChoicesS2tot,
'Robot1': nbChoicesR1tot,
'Robot2': nbChoicesR2tot
})
date = time.gmtime(None)
date = str(date.tm_mday) + "-" + str(
date.tm_mon) + "-" + str(date.tm_hour + 2) + "-" + str(date.tm_min)
datatot.to_csv('/home/lucas/phri/lucas/fichiers_csv/data_AnDom_' + date +
'.csv')
plt.figure("Total")
#HFOP
labels = 'Sujet 1', 'Sujet 2'
sizes = [
np.mean(datatot[datatot['TYPE'] == 'HFOP']['Choices1']),
np.mean(datatot[datatot['TYPE'] == 'HFOP']['Choices2'])
]
ax1 = plt.subplot(321)
ax1.pie(sizes,
labels=labels,
autopct='%1.1f%%',
colors=['blue', 'red'],
startangle=90)
ax1.axis(
'equal') # Equal aspect ratio ensures that pie is drawn as a circle.
#HFO
labels = 'Sujet 1', 'Sujet 2'
sizes = [
np.mean(datatot[datatot['TYPE'] == 'HFO']['Choices1']),
np.mean(datatot[datatot['TYPE'] == 'HFO']['Choices2'])
]
ax2 = plt.subplot(322)
ax2.pie(sizes,
labels=labels,
autopct='%1.1f%%',
colors=['blue', 'red'],
startangle=90)
ax2.axis(
'equal') # Equal aspect ratio ensures that pie is drawn as a circle.
#HVP1
labels = 'Sujet 1', 'Robot 1'
sizes = [
np.mean(datatot[datatot['TYPE'] == 'HVP']['Choices1']),
np.mean(datatot[datatot['TYPE'] == 'HVP']['Robot1'])
]
ax3 = plt.subplot(323)
ax3.pie(sizes,
labels=labels,
autopct='%1.1f%%',
colors=['blue', 'green'],
startangle=90)
ax3.axis(
'equal') # Equal aspect ratio ensures that pie is drawn as a circle.
#HVP2
labels = 'Robot 2', 'Sujet 2'
sizes = [
np.mean(datatot[datatot['TYPE'] == 'HVP']['Robot2']),
np.mean(datatot[datatot['TYPE'] == 'HVP']['Choices2'])
]
ax4 = plt.subplot(324)
ax4.pie(sizes,
labels=labels,
autopct='%1.1f%%',
colors=['red', 'green'],
startangle=90)
ax4.axis(
'equal') # Equal aspect ratio ensures that pie is drawn as a circle.
#KVP1
labels = 'Sujet 1', 'Robot 1'
sizes = [
np.mean(datatot[datatot['TYPE'] == 'KVP']['Choices1']),
np.mean(datatot[datatot['TYPE'] == 'KVP']['Robot1'])
]
ax5 = plt.subplot(325)
ax5.pie(sizes,
labels=labels,
autopct='%1.1f%%',
colors=['blue', 'green'],
startangle=90)
ax5.axis(
'equal') # Equal aspect ratio ensures that pie is drawn as a circle.
#KVP2
labels = 'Robot 2', 'Sujet 2'
sizes = [
np.mean(datatot[datatot['TYPE'] == 'KVP']['Robot2']),
np.mean(datatot[datatot['TYPE'] == 'KVP']['Choices2'])
]
ax6 = plt.subplot(326)
ax6.pie(sizes,
labels=labels,
autopct='%1.1f%%',
colors=['red', 'green'],
startangle=90)
ax6.axis(
'equal') # Equal aspect ratio ensures that pie is drawn as a circle.
plt.show()
