|
|
@@ -1,254 +0,0 @@
|
|
|
-'''
|
|
|
-Creates .lst file for single wavelength TIFF files (pre-calculated RATIO) in the format used in Trondheim
|
|
|
-Author: Giovanni, Dec 2021, based on template in VIEW folder by Ajay
|
|
|
-
|
|
|
-Expected data structure:
|
|
|
- In the folder "01_DATA", each animal has a folder, e.g. "190815_h2_El",
|
|
|
- and located in that folder are all .tif files for that animal
|
|
|
- There is a sister folder "02_LISTS"
|
|
|
-
|
|
|
-Output:
|
|
|
- In the folder "02_LISTS":
|
|
|
- There will be a file Animal.lst.xlsx, e.g. "190815_h2_El.lst.xlsx"
|
|
|
- That file contains one line for each measurement.
|
|
|
-
|
|
|
-What to do next?
|
|
|
- In this file, change values that are global
|
|
|
- or insert a function that can extract odor name or concentration name from somewhere
|
|
|
-
|
|
|
- In the Animal.lst.xlsx file, correct/complete entries (e.g. odor names, odor concentrations)
|
|
|
- Make sure stimulus timing information is correct
|
|
|
-
|
|
|
-Why do I need a .lst.xlsx file?
|
|
|
- Load measurements in pyVIEW using this .lst file, so that stimulus information is correct
|
|
|
- For off-line analysis, information is taken from this file.
|
|
|
-
|
|
|
-Good to know:
|
|
|
- Information, where possible, is taken from the OME header of the incoming tif file.
|
|
|
- If that information is wrong, incomplete, or else, modify the code in:
|
|
|
- importers.py:P1DualWavelengthTIFSingleFileImporter:parse_metadata
|
|
|
-'''
|
|
|
-from view.python_core.measurement_list import MeasurementList
|
|
|
-from view.python_core.measurement_list.importers import get_importer_class
|
|
|
-from view.python_core.flags import FlagsManager
|
|
|
-from collections import OrderedDict
|
|
|
-import pandas as pd
|
|
|
-import logging
|
|
|
-import pathlib as pl
|
|
|
-
|
|
|
-logging.basicConfig(level=logging.INFO)
|
|
|
-
|
|
|
-# ------------------- Some parameters about experimental setup, data structure and output file type --------------------
|
|
|
-# 3 for single wavelength Till Photonics Measurements
|
|
|
-# 4 for two wavelength Till Photonics Measurements
|
|
|
-# 20 for Zeiss Confocal Measurements
|
|
|
-LE_loadExp = 33
|
|
|
-
|
|
|
-# Mother of all Folders of your dataset
|
|
|
-# On Windows, if you copy paths from the file explorer, make sure the string below is always of the form r"......"
|
|
|
-STG_MotherOfAllFolders = r"/Users/galizia/Nextcloud/VTK_2021/Bente_Test_2021"
|
|
|
-
|
|
|
-# path of the "Data" folder in VIEW organization containing the data
|
|
|
-# On Windows, if you copy paths from the file explorer, make sure the string below is always of the form r"......"
|
|
|
-STG_Datapath = r""
|
|
|
-
|
|
|
-# path of the "Lists" folder in VIEW organization containing the list files
|
|
|
-# On Windows, if you copy paths from the file explorer, make sure the string below is always of the form r"......"
|
|
|
-STG_OdorInfoPath = r""
|
|
|
-
|
|
|
-# Choose measurement list output extension among ".lst", ".lst.xlsx", ".settings.xlsx"
|
|
|
-# VIEW does not support writing .xls list files anymore (nonetheless, it can read them and revise/update them to .xlsx)
|
|
|
-measurement_output_extension = ".lst.xlsx"
|
|
|
-
|
|
|
-# ------------------- A dictionary containing default values for metadata.----------------------------------------------
|
|
|
-# ------------------- Only metadata included in this dictionary will be written ----------------------------------------
|
|
|
-# ----Note that columns of the output measeurement list files will have the same order as below.------------------------
|
|
|
-
|
|
|
-default_values = OrderedDict()
|
|
|
-
|
|
|
-default_values['Measu'] = 0 # unique identifier for each line, corresponds to item in TILL photonics log file
|
|
|
-
|
|
|
-default_values['Label'] = "none"
|
|
|
-default_values['Odour'] = 'odor?' # stimulus name, maybe extracted from label in the function "custom_func" below
|
|
|
-default_values['OConc'] = 0 # odor concentration, maybe extracted from label in the function "custom_func" below
|
|
|
-default_values['Analyze'] = -1 # whether to analyze in VIEWoff. Default 1
|
|
|
-
|
|
|
-default_values['Cycle'] = 0 # how many ms per frame
|
|
|
-default_values['DBB1'] = 'none' # file name of raw data
|
|
|
-default_values['UTC'] = 0 # recording time, extracted from file
|
|
|
-
|
|
|
-default_values['PxSzX'] = '0.0' # um per pixel, 1.5625 for 50x air objective, measured by Hanna Schnell July 2017 on Till vision system, with a binning of 8
|
|
|
-default_values['PxSzY'] = '0.0' # um per pixel, 1.5625 for 50x air objective, measured by Hanna Schnell July 2017 on Till vision system, with a binning of 8
|
|
|
-
|
|
|
-default_values['Lambda'] = 0 # wavelength of stimulus. In TILL, from .log file, In Zeiss LSM, from .lsm file
|
|
|
-
|
|
|
-# These will be automatically filed for LE_loadExp=4
|
|
|
-default_values['dbb2'] = 'none' # file name of raw data in dual wavelength recordings (FURA)
|
|
|
-# To include more columns, uncomment entries below and specify a default value.
|
|
|
-# #
|
|
|
-# block for first stimulus
|
|
|
-# default_values['StimON'] = -1 # stimulus onset, unit: frames, count starts at frame 1.
|
|
|
-# default_values['StimOFF'] = -1 # stimulus offset, unit: frames, count starts at frame 1.
|
|
|
-# default_values['StimLen'] = 0 # stimulus onset in ms from beginning - alternative to StimON
|
|
|
-# default_values['StimONms'] = -1 # stimulus length in ms - alternative to StimOFF
|
|
|
-# #
|
|
|
-# block for second stimulus
|
|
|
-# default_values['Stim2ON'] = 0 # stimulus onset, unit: frames, count starts at frame 1.
|
|
|
-# default_values['Stim2OFF'] = 0 # stimulus offset, unit: frames, count starts at frame 1.
|
|
|
-# default_values['Stim2Len'] = 0 # stimulus onset in ms from beginning - alternative to StimON
|
|
|
-# default_values['Stim2ONms'] = -1 # stimulus length in ms - alternative to StimOFF
|
|
|
-# #
|
|
|
-# default_values['Age'] = -1
|
|
|
-# default_values['Sex'] = 'o'
|
|
|
-# default_values['Side'] = 'none'
|
|
|
-# default_values['Comment'] = 'none'
|
|
|
-# #
|
|
|
-# default_values['MTime'] = 0
|
|
|
-# default_values['Control'] = 0
|
|
|
-# default_values['Pharma'] = 'none'
|
|
|
-# default_values['PhTime'] = 0
|
|
|
-# default_values['PhConc'] = 0
|
|
|
-# default_values['ShiftX'] = 0
|
|
|
-# default_values['ShiftY'] = 0
|
|
|
-# default_values['StimISI'] = 0
|
|
|
-# default_values['setting'] = 'none'
|
|
|
-# default_values['dbb3'] = 'none'
|
|
|
-# default_values['PosZ'] = 0
|
|
|
-# default_values['Countl'] = 0
|
|
|
-# default_values['slvFlip'] = 0
|
|
|
-# ----------------------------------------------------------------------------------------------------------------------
|
|
|
-
|
|
|
-# ----------------- A function used to modify list entries after automatic parsing of metadata -------------------------
|
|
|
-# ----------------- This function indicates what needs to be done for a row --------------------------------------------
|
|
|
-# ----------------- The same is internally applied to all rows of the measurement list----------------------------------
|
|
|
-
|
|
|
-
|
|
|
-def get_odorinfo_from_label(label):
|
|
|
- # format for file name (label) is:
|
|
|
-# odor_concentration_anything_else.tif
|
|
|
-# separating element is underscore
|
|
|
- # is the information for a concentration present? Detect "-"
|
|
|
- parts = label.split("_")
|
|
|
- if len(parts) > 1:
|
|
|
- odor = parts[0]
|
|
|
- concentration = parts[1]
|
|
|
- # in the case the name is odor_conc.tif:
|
|
|
- if concentration[-4:] == '.tif':
|
|
|
- concentration = concentration[:-4]
|
|
|
- else:
|
|
|
- odor = 'odor?'
|
|
|
- concentration = 'conc?'
|
|
|
- return [odor, concentration]
|
|
|
-
|
|
|
-
|
|
|
-def custom_func(list_row: pd.Series, animal_tag: str) -> pd.Series:
|
|
|
-
|
|
|
- # Examples:
|
|
|
- # list_row["StimON"] = 25
|
|
|
- # list_row["Odour"] = get_odor_from_label(list_row["Label"])
|
|
|
- # if list_row["Measu"]
|
|
|
- # get Odor from another file based on the value of <animal_tag> and list_row["Label"]
|
|
|
- list_row["StimONms"] = '3000'
|
|
|
- list_row["StimLen"] = '2000'
|
|
|
- list_row["Comment"] = 'create_measurement_list_bente'
|
|
|
- list_row["Line"] = 'ham'
|
|
|
-#extract odor and concentration from name
|
|
|
- (list_row["Odour"],list_row["OConc"]) = get_odorinfo_from_label(list_row["Label"])
|
|
|
-
|
|
|
- if list_row["Label"][-4:] == '.tif':
|
|
|
- list_row["Label"] = list_row["Label"][:-4]
|
|
|
-
|
|
|
- return list_row
|
|
|
-
|
|
|
-# ----------------------------------------------------------------------------------------------------------------------
|
|
|
-
|
|
|
-# ------------------ A function defining the criteria for excluding measurements ---------------------------------------
|
|
|
-# ------------------ Currently applicable only for tillvision setups ---------------------------------------------------
|
|
|
-
|
|
|
-
|
|
|
-def measurement_filter(s):
|
|
|
- # exclude blocks that have in the name "Snapshot" or "Delta"
|
|
|
- # or that do not have any "_"
|
|
|
- name = s["Label"]
|
|
|
- label_not_okay = name.count('Snapshot') > 0 or name.count('Delta') > 0 or name.count('_') < 1
|
|
|
- label_okay = not label_not_okay
|
|
|
-
|
|
|
- # exclude blocks with less than two frames or no calibration
|
|
|
- atleast_two_frames = False
|
|
|
- if type(s["Timing_ms"]) is str:
|
|
|
- if len(s["Timing_ms"].split(' ')) >= 2 and s["Timing_ms"] != "(No calibration available)":
|
|
|
- atleast_two_frames = True
|
|
|
-
|
|
|
- return label_okay and atleast_two_frames
|
|
|
-
|
|
|
-
|
|
|
-# ______________________________________________________________________________________________________________________
|
|
|
-
|
|
|
-
|
|
|
-# ------------------ names of columns that will be overwritten by old values -------------------------------------------
|
|
|
-# ------ these will only be used if a measurement list file with the same name as current output file exists -----------
|
|
|
-
|
|
|
-overwrite_old_values = ["Line", "PxSzX", "PxSzY", "Age", "Sex", "Prefer",
|
|
|
- "Comment", "Analyze", "Odour", "OConc"]
|
|
|
-
|
|
|
-# ______________________________________________________________________________________________________________________
|
|
|
-
|
|
|
-if __name__ == "__main__":
|
|
|
-
|
|
|
- # initialize a FlagsManager object with values specified above
|
|
|
- flags = FlagsManager()
|
|
|
- flags.update_flags({"STG_MotherOfAllFolders": STG_MotherOfAllFolders,
|
|
|
- "STG_OdorInfoPath": STG_OdorInfoPath,
|
|
|
- "STG_Datapath": STG_Datapath})
|
|
|
-
|
|
|
- # initialize importer
|
|
|
- importer_class = get_importer_class(LE_loadExp)
|
|
|
- importer = importer_class(default_values)
|
|
|
-
|
|
|
- # open a dialog for choosing raw data files
|
|
|
- # this returns a dictionary where keys are animal tags (STG_ReportTag) and
|
|
|
- # values are lists of associated raw data files
|
|
|
- animal_tag_raw_data_mapping = importer.ask_for_files(default_dir=flags["STG_Datapath"])
|
|
|
- # make sure some files were chosen
|
|
|
- assert len(animal_tag_raw_data_mapping) > 0, IOError("No files were chosen!")
|
|
|
-
|
|
|
- for animal_tag, raw_data_files in animal_tag_raw_data_mapping.items():
|
|
|
-
|
|
|
- # automatically parse metadata
|
|
|
- metadata_df = importer.import_metadata(raw_data_files=raw_data_files,
|
|
|
- measurement_filter=measurement_filter)
|
|
|
- # inform user if no usable measurements were found
|
|
|
- if metadata_df.shape[0] == 0:
|
|
|
- logging.info(f"No usable measurements we found among the files "
|
|
|
- f"chosen for the animal {animal_tag}. Not creating a list file")
|
|
|
- else:
|
|
|
- # create a new Measurement list object from parsed metadata
|
|
|
- measurement_list = MeasurementList.create_from_df(LE_loadExp=LE_loadExp,
|
|
|
- df=metadata_df)
|
|
|
-
|
|
|
- # apply custom modifications
|
|
|
- measurement_list.update_from_custom_func(custom_func=custom_func, animal_tag=animal_tag)
|
|
|
-
|
|
|
- # set anaylze to 0 if raw data files don't exist
|
|
|
- flags.update_flags({"STG_ReportTag": animal_tag})
|
|
|
- measurement_list.sanitize(flags=flags,
|
|
|
- data_file_extensions=importer.movie_data_extensions)
|
|
|
-
|
|
|
- # construct the name of the output file
|
|
|
- #AskAjay - what I am writing seems crude to me (Giovanni Dec 21)
|
|
|
- #Ajay: out_file = f"{flags.get_lst_file_stem()}{measurement_output_extension}"
|
|
|
- singlefilein = pl.Path(raw_data_files[0])
|
|
|
- #singlefilein could be:
|
|
|
- #'/Users/galizia/Nextcloud/VTK_2021/Bente_Test_2021/01_DATA/190815_h2_El/B_1.tif'
|
|
|
- #output should be:
|
|
|
- #'/Users/galizia/Nextcloud/VTK_2021/Bente_Test_2021/02_ANALYSIS/190815_h2_El.lst.xlsx'
|
|
|
- out_file = pl.Path(singlefilein.parent.parent.parent)
|
|
|
- out_file = pl.Path.joinpath(out_file, '02_LISTS' , singlefilein.parts[-2])
|
|
|
- out_file = f"{out_file}{measurement_output_extension}"
|
|
|
-
|
|
|
- # write measurement file to list
|
|
|
- measurement_list.write_to_list_file(lst_fle=out_file, columns2write=default_values.keys(),
|
|
|
- overwrite_old_values=overwrite_old_values)
|
|
|
-
|
|
|
-
|
|
|
-
|
Giovanni Galizia