Mark’s functions for sharing across projects

Note: This file is automatically generated. Please do not edit manually.

Last Updated 2020-01-28 by Adam Lu

Instructions for syncing this directory to your local machine:

# Add this directory as a submodule:
git submodule add https://github.com/blabuva/Marks_Functions.git

# Update the submodule in the future
git submodule foreach git pull origin master

There are 2 MATLAB scripts in this directory:

adamSetPath.m: Add directories to search path for required functions across servers
anal_params.m:
analyzeCI_mark_Lise.m: function [bigdata] = analyzeCI_mark_Lise(alldata, si, timeC)
analyzeCI_mark.m:
analyze_the_new_stuff.m:
appendTextFileUpdate.m: save(‘/home/mark/matlab_temp_variables/records’) ;
atf_extractor_BARRETT.m: ccc
atf_extractor_BARRETT_peaks.m: ccc
atf_extractor_BARRETT_starts.m: ccc
atf_extractor_BRANDON.m: ccc
atf_extractor.m: ccc
awesoCrunch.m:
awesolater.m:
baseline_extracellular_recordings.m:
beeper.m:
beeps.m:
big_question.m: putvar(proceed) ;
binBurstySpikes.m: save(‘/home/mark/matlab_temp_variables/tableData’)
bin_line_maker.m:
bin_the_spikes.m: this function bins detected spikes found in all_data
brainImage.m:
brainImageModelCells2.m:
brainImageModelCells3.m:
brainImageModelCells.m:
burst_finder.m:
ccc.m: ccc.m
CCIBgrades.m:
chop_data_to_window_abf.m: clear all
chop_data_to_window.m:
chop_data_to_window_xsg.m:
color_list.m:
confInterval95.m: mark’s function that calculates the 95% confidence intervals
confplot_mark.m: CONFPLOT Linear plot with continuous confidence/error boundaries.
convertMyOscillationPNGs.m: save(‘/home/mark/matlab_temp_variables/conversion’)
data_reducer.m:
define_binsize.m:
define_burst_isi_2.m:
define_burst_isi.m:
define_display_window_abf.m: function [start_index, end_index, start_time, baseline_duration] = define_display_window(time_column)
define_display_window.m: Make GUI using ‘inputdlg’ matlab function so that user can define start &
define_lowpass.m:
define_oscillation_isi_2.m:
define_spike_threshold.m:
drawSomeAwesome.m: performs population analyses
eat.m:
extract_XL.m:
filter_out_already_analyzed.m:
find_me_a_max.m:
find_undies.m:
get_colormap.m:
getDataFromExcel.m: get numbers from excel file
get_event_frequency.m:
get_imaging_movie.m: pn = ‘/home/mark/peter_movies/’ ;
getMyLetters.m:
get_peters_mat.m: for i = 1:size(onsets,2) ;
get_single_EEG_file_data_column.m:
get_single_EEG_file.m:
get_single_EEG_file_time_column_dan.m:
get_single_EEG_file_time_column.m:
getThemBurstSpikes.m: save(‘/home/mark/matlab_temp_variables/theMMAAATT’)
have_matlab_email_me2.m:
have_matlab_email_meERROR.m:
have_matlab_email_me.m:
inputdlg_restrict_search.m:
interface_spike_detecta_2.m: Have user define threshold
interface_spike_detecta_3.m: Have user define threshold
interface_spike_detecta_4.m: Have user define threshold
interface_spike_detecta.m: convert detected spike indicies into spike times
katie_colormap.m:
katies_means_file_selector.m:
linux_command_permissions.m: function that changes permissions
lunch.m: reset random number generator so it works in compiled version
makeAWSfolders.m:
make_cmap.m:
make_colors.m:
make_filename_path_from_ephus.m: make figure name
makeMarkMemLogFile.m:
make_mini_analysis_figs.m: clean up dump directory (i.e. create it if it doesn’t exist. remove existing pdfs if it does exist)
make_mini_analysis_figs_PASSES.m: subplot and figure counters are required because the main skeleton calls up this funtion twice. The second time needs to take up where the first stopped.
make_mini_analysis_figs_PASS_REJECTS.m: subplot and figure counters are required because the main skeleton calls up this funtion twice. The second time needs to take up where the first stopped.
make_mini_analysis_figs_REJECTS.m: subplot and figure counters are required because the main skeleton calls up this funtion twice. The second time needs to take up where the first stopped.
make_my_figure_fit_EEG2.m: x_width = 200 ;
make_my_figure_fit_EEG3.m:
make_my_figure_fit_EEG_continuous.m:
make_my_figure_fit_EEG_interface.m: x_width = 200 ;
make_my_figure_fit_EEG.m:
make_my_figure_fit_horizontal.m:
make_my_figure_fit_HW.m:
make_my_figure_fit_katie.m: width = 16;
make_my_figure_fit.m:
makeMyMfileNames.m: varargin - ‘OldName’: old data structure must be a nonempty structure default == []
make_some_bursts2.m:
make_some_bursts.m: get rid of singlets
make_sub_plots_abf.m: This function plots each sweep as an individual subplot. It also plots
make_sub_plots.m: This function plots each sweep as an individual subplot. It also plots
make_sub_plots_no_stim.m: This function plots each sweep as an individual subplot. It also plots
make_sub_plots_with_stim.m: This function plots each sweep as an individual subplot. It also plots
makeTextFileUpdate.m:
make_time_column.m: Create a time column in sec from either a sampling rate (Hz) or a sampling interval (usec) and the number of samples (obsolete, use create_time_vectors instead)
markFFT.m: function [f,mx,maxF,powmaxF] = markFFT(data,Fs)
MARKonlineOmight.m: add skipper for debugging purposes
marksMemoryFunction.m: save(‘/home/mark/matlab_temp_variables/mm’)
marksTimeStamp.m:
mattExample.m:
meanerize_data.m: max_big_bins = find_me_a_max(all_FFTs, pump_on) ; KEEP THIS
mean_this_stuff.m:
moveMyOscillationFiles.m: save(‘/home/mark/matlab_temp_variables/conversion’)
nik_oscillation_maker.m: clear all
osc_finder.m: clear all
osc_finder_old.m: function start_stop_times = osc_finder(data, leading_ISI)
osc_gatherer.m:
oscillation_selector.m: clear all
pclamp_file_maker_atf.m: ccc
pclamp_file_maker_CaImaging_detectedtoo.m: ccc
pclamp_file_maker_CaImaging_detectedtoo_sifted.m: ccc
pclamp_file_maker_CaImaging.m: ccc
pclamp_file_maker.m: load(‘plamp_maker_data’)
pdf_concater.m: temp_dir = directory holding pdfs that you want to concatenate
peak_detecta.m: This function finds peaks (e.g. biggest synaptic response) within the data.
peterstuff.m:
placePlot.m:
plot_filtered_data_and_spikes_and_bins2.m:
plot_filtered_data_and_spikes_and_bins_and_bursts.m:
plot_filtered_data_and_spikes_and_bins.m:
plot_filtered_data_set2.m: Have user define low pass specs
plot_filtered_data_set_and_spikes2.m: make temp folder to hold pdfs
plot_filtered_data_set_and_spikes3.m: make temp folder to hold pdfs
plot_filtered_data_set_and_spikes.m: unpack all_data
plot_filtered_data_set.m:
plot_original_data_set_interface2.m: make temp folder to hold pdfs
plot_original_data_set_interface_filt.m:
plot_original_data_set_interface.m: Determine rms for sweeps
questdlg_mark2.m: QUESTDLG Question dialog box.
questdlg_mark.m: QUESTDLG Question dialog box.
replot_and_request_abf2.m: this function asks the user if the new window is acceptable. The
replot_and_request_abf.m: This function calculates the indicies for the start/end times according
replot_and_request_filt_abf.m: This function calculates the indicies for the start/end times according
replot_and_request.m: This function calculates the indicies for the start/end times according
replot_and_request_xsg.m: This function calculates the indicies for the start/end times according
retrofit_analysis_params.m: ccc
saveSpace.m:
saveTheWork.m:
scott_main_peter.m: function output_data = scott_main_mark(data, timeC) ; % gui_selections, timeC)
seconds_to_dayshoursminssecs.m: secs = 865000 ;
see_whats_been_analyzed.m:
sexAgeCmap.m: save(‘/media/markX/matlab_temp_variables/sexAges’)
sexAge.m:
temp_pdf_folder_maker.m: make temp folder to hold pdfs
turn_gap_free_into_sweeps.m:
unixcommander2.m:
unixcommander.m:
update_whats_been_analyzed.m:
user_windows_for_combining_data.m:
xldata_restricter.m: get column numbers for relevant data
zof_mark_band.m: data is a vector of samples
zof_mark_high.m: data is a vector of samples
zof_mark.m: Uses a Butterworth filter twice to filter data (each column is a vector of samples)