Adam’s functions for sharing across projects

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

Last Updated 2020-10-09 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/Adams_Functions.git

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

There are 2 MATLAB scripts in this directory:

abf2mat.m: Converts .abf files to .mat files with time vector (in ms) included
addpath_custom.m: Add a folder to MATLAB path only if is not already on the path
addvar_as_rowname.m: Adds a column to a table in the beginning and as row name
addvars_custom.m: Adds a column to a table, matching rows if necessary
adjust_edges.m: Update histogram bin edges according to specific parameters
adjust_peaks.m: Adjusts peak indices and values given approximate peak indices
adjust_window_to_bounds.m: Adjusts a time window so that it is within specific bounds
align_subplots.m: Aligns subplots in a figure
align_vectors_by_index.m: Aligns vectors by an index from each vector
all_data_files.m: Looks for data files in a directory according to either extensionUser or going through a list of possibleExtensions
all_dependent_files.m: Prints all dependent files used by a given MATLAB script/function
all_fields.m: Get all field values and names of a structure that satisfies specific conditions in cell arrays
all_file_bases.m: Returns all the file bases in a given directory (optionally recursive) that matches a prefix, keyword, suffix or extension
all_files.m: Returns all the files in a given directory (optionally recursive) that matches a prefix, keyword, suffix or extension
all_ordered_pairs.m: Generates a cell array of all ordered pairs of elements/indices, one from each vector
all_slice_bases.m: Retrieves all unique slice bases from the data files in the directory
all_subdirs.m: Returns all the subdirectories in a given directory
all_swd_sheets.m: Returns all files ending with ‘_SWDs.csv’ under a directory recursively
alternate_elements.m: Alternate elements between two vectors to create a single vector
analyze_adicht.m: Read in the data from the .adicht file
analyzeCI.m: Analyzes current-injection protocols (legacy, please use parse_current_family.m instead)
analyze_cobalt.m: Clear workspace
annotation_in_plot.m: A wrapper function for the annotation() function that accepts x and y values normalized to the axes
append_str_to_varnames.m: Appends a string to all variable names in a table
apply_iteratively.m: Applies a function iteratively to an array until it becomes a non-cell array result
apply_or_return.m: Applies a function if a condition is true, or return the original argument(s)
apply_over_cells.m: Apply a function that usually takes two equivalent arguments over all contents of a cell array
apply_to_all_cells.m: Applies a function to inputs, separately to each cell if a inputs is a cell array
apply_to_all_subdirs.m: Apply the same function (must have ‘Directory’ as a parameter) to all subdirectories
apply_to_nonnan_part.m: Applies a function to just the non-NaN part of a vector
archive_dependent_scripts.m: Archive all dependent scripts of a function
argfun.m: Applies a function to each input argument
arglist2struct.m: Converts an argument list to a scalar structure
array_fun.m: Applies cellfun or arrayfun based on the input type, or use parfor if not already in a parallel loop
atf2sheet.m: Converts .atf text file(s) to a spreadsheet file(s) (type specified by the ‘SheetType’ argument)
boltzmann.m: Computes the sigmoidal Boltzmann function
cell2num.m: This is the reverse of num2cell, replacing empty entries with NaNs
char2rgb.m: Converts a color string to an rgb value
check_and_collapse_identical_contents.m: Checks if a cell array or array has identical contents and collapse it to one copy of the content
check_dir.m: Checks if needed directory(ies) exist and creates them if not
check_fullpath.m: Checks whether a path or paths exists and prints message if not
check_subdir.m: Checks if needed subdirectory(ies) exist in parentDirectory
check_within_bounds.m: Checks whether all values are within bounds and print the ones that aren’t
choose_random_values.m: Chooses random values from bounds
choose_stimulation_type.m: Chooses the stimulation type based on the response type
clc2_analyze.m: Analyzes all CLC2 data
clcf.m: clcf.m
cleanup_parcluster.m: Cleans up parallel cluster, removing all jobs that contain crash dump files
collapse_identical_vectors.m: Collapses identical vectors into a single one
color_index.m: Find the colormap index for a given value with boundaries set by edges
combine_abf_data.m: Combine data from many .abf files and return a structure
combine_data_from_same_slice.m: Combines data across multiple .abf files for each slice in the input folder (or for a particular slice)
combine_looped_params.m: TODO
combine_multiunit_data.m: Combines data across multiple .abf files (using multiunit data defaults) for each slice in the input folder (or for a particular slice)
combine_param_tables.m: Combine parameter tables with a ‘Value’ column and row names as parameters
combine_phase_numbers.m: Combines (possibly multiple) phase number vectors into a single vector
combine_strings.m: Constructs a final string based on optional substrings and/or Name-Value pairs
combine_swd_resp_data.m: Parses and concatenates SWD and resp files from different source data .atf and .mat files
combine_swd_sheets.m: Combines all files ending with ‘_SWDs.csv’ and with ‘_piece’ in the name under a directory
combine_sweeps.m: Combines sweeps that begin with expLabel in dataDirectory under dataMode
combine_variables_across_tables.m: Combines measures across different tables
compare_events_pre_post_stim.m: Binary file /home/Matlab/Adams_Functions/compare_events_pre_post_stim.m matches
compile_mod_files.m: Compiles NEURON .mod files
compile_script.m: Compiles a MATLAB script/function
compute_activation_profile.m: Computes the percent of activated cells in the network over time
compute_all_pulse_responses.m: Filter and extract all pulse response and compute features
compute_and_plot_all_responses.m: Computes and plots all pulse responses with stimulus
compute_and_plot_average_response.m: Computes and plots an average pulse response with its stimulus
compute_and_plot_concatenated_trace.m: Computes and plots concatenated traces from parsed ABF file results
compute_and_plot_values_online.m: Computes and plots a value whenever a new .abf file is completed
compute_autocorrelogram.m: Computes an autocorrelogram and compute the oscillatory index and period from an array of event times
compute_average_psc_trace.m: Compute the “average PSC trace”
compute_average_pulse_response.m: Computes an average pulse response as well as its features
compute_average_trace.m: Computes the average of traces that are not necessarily the same length
compute_axis_limits.m: Computes x or y axis limits from data (works also for a range [min(data), max(data)])
compute_baseline_noise.m: Computes the baseline noise from a set of data vectors, time vectors and baseline windows
compute_bins.m: Computes bin counts and edges from a vector
compute_centers_from_edges.m: Computes bin centers from bin edges
compute_combined_data.m: Average data according column numbers to average and to a grouping vector
compute_combined_trace.m: Computes a combined trace from a set of traces
compute_default_signal2noise.m: Computes a default signal-to-noise ratio
compute_default_sweep_info.m: Computes default windows, noise, weights and errors
compute_derivative_trace.m: Computes the derivative trace dy/dx from x and y, using the midpoints of x as new x
compute_elcurr.m: Computes electrode current from conductance & voltage
compute_eRev.m: Computes the reversal potential of a channel that passes monovalent ions using the GHK voltage equation
compute_gabab_conductance.m: Computes a the conductance over time for a GABAB-IPSC
compute_gpas.m: Computes the passive conductance (gpas, in S/cm^2) from input resistance and surface area
compute_grouped_histcounts.m: Computes bin counts and edges from grouped data
compute_IMax_GHK.m: Computes the maximum current [mA/cm^2] using the GHK current equation
compute_index_boundaries.m: Computes boundary values for indices of different groups, assuming the groups are all consecutive in the array
compute_initial_slopes.m: Computes the average initial slope from a current pulse response
compute_lts_errors.m: Computes low-threshold spike errors for single neuron data
compute_maximum_numel.m: Given a list of arrays, compute the maximum number of elements
compute_maximum_trace.m: Computes the maximum of traces that are not necessarily the same length
compute_minimum_trace.m: Computes the minimum of traces that are not necessarily the same length
compute_oscillation_duration.m: Computes the oscillation duration in seconds from an interface recording abf file
compute_pairwise_differences.m: Computes pairwise differences of vectors
compute_peak_decay.m: Computes the peak decays
compute_peak_halfwidth.m: Computes the half widths for peaks
compute_phase_average.m: Computes the average of values over the last of a phase
compute_population_average.m: Computes the population mean and confidence intervals from a table or time table
compute_psth.m: Computes a peri-stimulus time histogram
compute_relative_event_times.m: Computes the relative event times from event times and stimulus times
compute_relative_time.m: Computes time(s) relative to limits from indice(s)
compute_relative_value.m: Computes value(s) relative to limits
compute_residuals.m: Computes residual vector(s) from simulated and recorded vectors
compute_rms_error.m: Computes the root mean squared error(s) given one or two sets of vectors
compute_rms_Gaussian.m: Compute the root-mean-square level of the “Gaussian part” of a data vector
compute_running_windows.m: Computes running windows based on time vectors
compute_sampling_interval.m: Computes sampling intervals from time vectors
compute_sampsizepwr.m: Computes the sample size needed, the statistical power or the alternative hypothesis parameter from either raw data or estimated parameters
compute_sigfig.m: Returns the number of significant figures from a number (numeric or string)
compute_single_neuron_errors.m: Computes the average total error for a single neuron
compute_slope.m: Computes the slope given two vectors and two indices
compute_spectrogram.m: Computes a spectrogram
compute_spike_density.m: Computes the spike density from spike times and overlapping bins
compute_spike_frequency.m: Computes the spike frequency for sets of spike indices given a sampling interval
compute_spike_histogram.m: Computes a spike histogram, detect bursts and compute the oscillation duration
compute_stats.m: Computes a statistic of vector(s) possibly restricted by endpoint(s)
compute_surface_area.m: Computes the surface area(s) (cm^2) of cylindrical compartmental model cell(s) based on lengths (um) and diameters (um)
compute_sweep_errors.m: Computes all errors for single neuron data
compute_time_average.m: Computes the time average of a value vector over time window(s)
compute_time_constant.m: Computes the time constant of vector(s) with a single peak
compute_time_window.m: Computes time windows from time vectors and given time end points
compute_total_current.m: Computes the total current across all compartments from current densities, lengths and diameters of each compartment
compute_value_boundaries.m: Computes boundaries for values based on a grouping vector
compute_weighted_average.m: Computes a weighted average value (root-mean-square by default)
construct_and_check_abfpath.m: Constructs the full path to a .abf file and checks whether it exists
construct_and_check_fullpath.m: Constructs the full path to the file or directory and checks whether it exists
construct_fullpath.m: Constructs full path(s) based on file/directory name(s) and optional directory, suffixes or extension
convert_sheettype.m: Converts all spreadsheets to desired sheettype (all .xlsx and .xls files to .csv files by default)
convert_to_char.m: Converts other data types to character arrays or a cell array of character arrays
convert_to_rank.m: Creates a positive integer array from an array showing the ranks of each element
convert_to_samples.m: Converts time(s) from a time unit to samples based on a sampling interval in the same time unit
convert_units.m: Converts numeric values from one units to another
copy_into.m: Copies source directories and files into a destination folder
copyvars.m: Copies variable 1 of a table to variable 2 of the same table
correct_unbalanced_bridge.m: Shifts a current pulse response to correct the unbalanced bridge
count_A_each_C.m: Counts the number of (A)s in each (C) based on the number of (A)s in each (B) and the number of (B)s in each (C)
count_events.m: Counts events before and after stimulation
count_frames.m: Count the number of frames in a video file
count_samples.m: Counts the number of samples whether given an array or a cell array
count_strings.m: Count the number of strings
count_vectors.m: Counts the number of vectors whether given an array or a cell array
create_average_time_vector.m: Creates an average time vector from a set of time vectors
create_colormap.m: Returns colorMap based on the number of colors requested
create_default_endpoints.m: Constructs default endpoints from number of samples
create_default_grouping.m: Creates numeric grouping vectors and grouping labels from data, counts or original non-numeric grouping vectors
create_empty_frames.m: Creates an empty MATLAB movie frames
create_empty_match.m: Creates an empty array that matches a given array
create_error_for_nargin.m: Creates an error text for not having enough input arguments
create_grouping_by_vectors.m: Creates a grouping array that matches input by putting all elements of a vector into the same group
create_indices.m: Creates indices from endpoints (starting and ending indices)
create_input_file.m: Create an input spreadsheet file from data file names in a directory based on default parameters
create_label_from_sequence.m: Creates a single label from a sequence of integers with an optional prefix or suffix
create_labels_from_numbers.m: Creates a cell array of labels from an array of numbers with an optional prefix or suffix
create_latex_string.m: Creates a LaTeX string from an equation used for fitting
create_logical_array.m: Creates a logical array from indices for true and dimensions
create_looped_params.m: Construct parameters to change for each trial from loopMode, pNames, pIsLog, pMin, pMax, pInc
create_new_mscript.m: Creates a new MATLAB script starting from a function template
create_pleth_EEG_movies.m: Creates a synced movie from a .wmv file and a Spike2-exported .mat file in the current directory
create_plot_movie.m: Creates a plot movie from a given figure with traces
create_power_tables.m: Creates power tables
create_pulse.m: Creates a pulse vector
create_pulse_train_series.m: Creates a pulse train series (a theta burst stimulation by default)
create_row_labels.m: Creates row labels for table(s)
create_shifted_vectors.m: Creates shifted vectors based on values to shift
create_simulation_output_filenames.m: Creates simulation output file names
create_subdir_copy_files.m: Creates subdirectories and copies figure files
create_subplots.m: Creates subplots with maximal fit
create_synced_movie_trace_plot_movie.m: Creates a plot movie showing a movie and a trace in synchrony
create_time_stamp.m: Creates a time stamp (default format yyyymmddTHHMM)
create_time_vectors.m: Creates time vector(s) in seconds from number(s) of samples and other optional arguments
create_trace_plot_movie.m: Creates a plot movie for traces
create_waveform_train.m: Creates a waveform train from a waveform, a frequency, and a total duration
crosscorr_profile.m: data: each channel is a column
current_injection_create_sim_commands.m: Generates simulation commands to be read by NEURON from a table of simulation parameters
current_injection_create_sim_params.m: Generates a table of simulation parameters from table(s) of neuron parameters
current_injection_run_and_analyze.m: Runs and analyzes “one iteration” of NEURON simulations (once for each of the sweeps)
decide_on_colormap.m: Decides on the color map to use
decide_on_filebases.m: Create filebases if empty, or extract file bases
decide_on_geom_params.m: Standardizes geometric parameters
decide_on_parpool.m: Creates or modifies a parallel pool object
decide_on_video_object.m: Decide on the video object given path or object
detect_spikes_current_clamp.m: Detects spikes from a current clamp recording
detect_spikes_multiunit.m: Detects spikes from a multiunit recording
distribute_balls_into_boxes.m: Returns the ways and number of ways to distribute identical/discrete balls into identical/discrete boxes
dlmwrite_with_header.m: Write a comma-separated value file with given header
error_unrecognized.m: Throws an error for unrecognized string
estimate_passive_params.m: Estimates passive parameters from fitted coefficients, current pulse amplitude and some constants
estimate_resting_potential.m: Estimates the resting membrane potential (mV) and the input resistance (MOhm) from holding potentials and holding currents
examine_figure_objects.m: Examines figure objects
extract_channel.m: Extracts vectors of a given type from a .abf file
extract_columns.m: Extracts columns from arrays or a cell array of arrays
extract_common_directory.m: Extracts the common parent directory of a cell array of file paths
extract_common_prefix.m: Extracts the common prefix of a cell array of strings
extract_common_suffix.m: Extracts the common suffix of a cell array of strings
extract_distinct_fileparts.m: Extracts distinct file parts (removes common parent directory, common prefix and common suffix)
extract_elements.m: Extracts elements from vectors using a certain mode (‘first’, ‘last’, ‘min’, ‘max’)
extract_fields.m: Extracts field(s) from an array of structures/tables/objects or a cell array of structures/tables/objects
extract_fileparts.m: Extracts directories, bases, extensions, distinct parts or the common directory from file paths, treating any path without an extension as a directory
extract_frame_times.m: Extracts all the frame start times in a video file
extractFrom.m: Extract the part of string(s) from a starting substring
extract_fullpaths.m: Extracts full paths from a files structure array
extract_in_order.m: Reorganizes a set of vectors by the first vectors, the second vectors, … and so on
extract_looped_params.m: Extracts parameters that were looped in the simulation from loopedparams.mat
extract_parameter_value_pairs.m: Extracts parameter-value pairs from an argument list and return remaining
extract_param_values.m: Extracts parameter values as structure(s)
extract_substrings.m: Extracts substring(s) from strings
extract_subvectors.m: Extracts subvectors from vectors, given either endpoints, value windows or a certain align mode (‘leftAdjust’, ‘rightAdjust’)
extract_vars.m: Extracts variable(s) (column(s)) from a table
files2contents.m: Replaces file names with file contents in a cell array of strings
fill_markers.m: Fills markers if any for the current axes
filter_and_extract_pulse_response.m: Filters and extracts pulse response(s) from a .abf file
find_closest.m: Finds the element(s) in numeric vector(s) closest to target(s)
find_custom.m: Same as find() but takes custom parameter-value pairs
find_directional_events.m: Find all directional events in a data vector
find_first_deviant.m: Finds the index of the first deviant from preceding peers in a time series
find_first_jump.m: Finds the index of the first jump in a time series
find_first_match.m: Returns the first matching index and match in an array for candidate(s)
find_initial_slopes.m: Find all initial slopes from a set of current pulse responses
find_in_list.m: Returns all indices of a candidate in a list
find_in_strings.m: Returns all indices of a particular string (could be represented by substrings) in a list of strings
find_matching_files.m: Finds matching files from file strings
find_nearest_multiple.m: Finds the nearest integer multiple of base to target and the distance to between it and target
find_nearest_odd.m: Returns the nearest odd integer to real number(s)
find_passive_params.m: Extract passive parameters from both the rising and falling phase of a current pulse response
find_pulse_endpoints.m: Returns the start and end indices of the first pulse from vector(s)
find_pulse_response_endpoints.m: Returns the start and end indices of the first pulse response (from pulse start to 20 ms after pulse ends by default) from vector(s)
find_troughs_from_peaks.m: Finds troughs of a vector in between given peak indices
find_window_endpoints.m: Returns the start and end indices of a time window in a time vector
find_zeros.m: Find the indices where the vectors are closest to zero
first_matching_field.m: Extracts the first matching field/variable/property of a structure/table/property from a list of candidate names
fit_2exp.m: Fits a double exponential curve to data
fit_and_estimate_passive_params.m: Uses a given pulse width and amplitude to fit and estimate passive parameters from a current pulse response
fitdist_initial_slopes.m: Fits initial slope distributions
fit_gaussians_and_refine_threshold.m: Fits data to Gaussian mixture models and finds the optimal number of components
fit_IEI.m: Fit IEI data to curves
fit_kernel.m: Fits a kernel distribution to a data vector and determine the two primary peaks, the threshold and the void and spacing parameters
fit_logIEI.m: Fit log(IEI) logData to curves
fit_pulse_response.m: Estimate short and long pulse response parameters from a double exponential fit to the rising/falling phase of a pulse response
fit_setup_2exp.m: Constructs a fittype object and set initial conditions and bounds for a double exponential equation form
fit_setup_first_order_response.m: Constructs a fittype object and set initial conditions and bounds for a first order response equation form
force_column_cell.m: Transforms a row cell array or a non-cell array to a column cell array of non-cell vectors
force_column_vector.m: Transform row vector(s) or array(s) to column vector(s)
force_data_as_matrix.m: Forces data values as a numeric matrix where each group is a column and each row is a sample
force_logical.m: Forces any numeric binary array to become a logical array
force_matrix.m: Forces vectors into a non-cell array matrix
force_row_cell.m: Transforms a column cell array or a non-cell array to a row cell array of non-cell vectors
force_row_vector.m: Transform column vector(s) or array(s) to row vector(s)
force_string_end.m: Force the string to end with a certain substring
force_string_start.m: Force the string to start with a certain substring
freqfilter.m: Uses a Butterworth filter twice to filter data by a frequency band (each column is a vector of samples)
get_idxEnd.m: Get the index of the end of an event
get_matlab_year.m: Returns the year of current MATLAB version
get_var_name.m: Returns a variable’s name as a string
Glucose_analyze.m: Analyzes all Glucose paper oscillations data
has_same_attributes.m: Returns all row indices that have the same attributes (column values) combination as a given set of row names
histg.m: HISTG ‘Grouped’ univariate histogram
histproperties.m: Computes the area, edges of the histogram for given data array
hold_off.m: Holds off based on previous status
hold_on.m: Holds on and returns previous status
hpc_test_matlab_figures.m: Test whether MATLAB figures can be suppressed on a high performance computing server
hpc_test_matlab_unix_neuron.m: Tests whether MATLAB can call NEURON with the unix command
hpc_test_parallel_matlab_figures.m: Set up parallel pool and run hpc_test_matlab_figures.m on Rivanna
hpc_test_parallel_matlab_unix_neuron.m: Tests whether MATLAB can call NEURON with the unix command under parallel loop on a high performance computing server
identify_bursts.m: Identify bursts from a list of directional events
identify_channels.m: Assigns voltage, current or conductance to each channel (2nd dim) in abfdata
identify_CI_protocol.m: Identifies whether a set of current vectors is a current injection protocol, and if so, what the range of the current injection is
identify_eLFP_protocol.m: Identifies whether a .abf file or a set of current vectors follows an eLFP protocol
identify_gabab_protocol.m: Identifies whether a .abf file or a set of voltage vectors follows a GABA-B IPSC protocol
identify_repetitive_pulses.m: Identifies whether a set of vectors are repetitive pulses
increment_editbox.m: Increment or decrement editbox value based on direction
intersect_over_cells.m: Apply the intersect function over all contents of a cell array
isaninteger.m: Returns whether each element of an array is an integer
isbinaryarray.m: Returns whether the input is a binary array
isbinaryscalar.m: Returns whether an input is a binary scalar (may be empty)
iscellnonvector.m: Returns whether an input is a cell array of non-cell vectors (may be empty)
iscellnumeric.m: Returns whether an input is a cell array of numeric arrays
iscellnumericvector.m: Returns whether an input is a cell array of numeric vectors (may be empty)
iscellvector.m: Returns whether an input is a cell array of vectors (may be empty)
is_contained_in.m: Checks whether all elements of the first set are elements of the second set and print the ones that aren’t
isemptycell.m: Returns whether each cell of a cell array is empty; if not a cell array, same as isempty()
isemptystruct.m: Returns whether a structure has no fields
is_field.m: Tests whether a name is a field (in the general sense) in a structure/table/object
isfigtype.m: Check whether a string or each string in a cell array is a valid figure type accepted by saveas()
is_in_parallel.m: Checks whether in a parfor loop
islegendlocation.m: Check whether a string or each string in a cell array is a valid legend location or ‘suppress’ or ‘auto’
islinestyle.m: Check whether a string or each string in a cell array is a valid line style accepted by plot() or line()
islog2scale.m: Converts whether is log-scaled (a Boolean) to a string (‘log’ or ‘linear’)
is_matching_string.m: Returns whether each element in a list of strings matches a candidate
ismatch.m: Returns whether each element in a list matches a candidate
ismember_custom.m: Returns whether a particular candidate is a member of a list
isnumericvector.m: Returns whether an input is a numeric vector (may be empty)
isnum.m: Returns whether the input is numeric in the general sense (numeric, logical, datetime or duration)
is_on_path.m: Returns whether folder(s) are on the MATLAB path
is_out_of_range.m: Check if any of the value(s) are out of range
is_overlapping.m: Returns whether a set of time windows are overlapping
ispositiveintegerarray.m: Returns whether an input is a positive integer array
ispositiveintegerscalar.m: Returns whether an input is a positive integer scalar
ispositiveintegervector.m: Returns whether an input is a positive integer vector
ispositivescalar.m: Returns whether an input is a positive scalar
ispositivevector.m: Returns whether an input is a positive vector
is_row_in_table.m: Returns whether a row name is an existing row in a table
issheettype.m: Check whether a string or each string in a cell array is a valid spreadsheet type accepted by readtable()
istext.m: Returns whether the input is a character array, a string array or a cell array of character arrays
istype.m: Check whether a string or each string in a cell array is a valid type specified by validTypes
is_var_in_table.m: Returns whether a variable name is an existing column in a table
linscale.m: Creates scaled values between base and target based on a linear scale
load_examples.m: Loads example data structures for testing
locate_dir.m: Locate the first directory that exists out of a list of candidates
locate_functionsdir.m: Locate the first shared functions directory that exists
log_arraytext.m: Create a text file that logs the array information
log_matfile.m: Print variables in a MATfile to a comma-separated-value file
logscale.m: Creates scaled values between base and target based on a log scale
lower_first_char.m: Converts the first character of each string to lower case
m3ha_append_lts_properties.m: Generates vectors of peak features restricted to those with LTS
m3ha_choose_heterogeneous_population.m: m3ha_choose_heterogeneous_population.m
m3ha_compare_and_plot_across_conditions.m: Plot activation/inactivation and I-V curves across conditions
m3ha_compare_and_plot_across_IC2.m: Plot activation/inactivation and I-V curves across initial conditions
m3ha_compare_and_plot_across_IC.m: Plot activation/inactivation and I-V curves across initial conditions
m3ha_compare_dclamp_analysis_versions.m: Used to find and copy traces with new stats such as peak classifications, LTS peak times and spikes per peak
m3ha_compare_neuronparams2.m: compare graphs across different sets of NEURON parameters
m3ha_compare_neuronparams.m: compare graphs across different sets of NEURON parameters
m3ha_compare_sse.m: m3ha_compare_sse.m
m3ha_compute_and_compare_lts_statistics.m: Computes statistics for LTS features and compares across (NOT FINISHED)
m3ha_compute_and_plot_all_IV2.m: Plot I-V curves of all currents together
m3ha_compute_and_plot_all_IV.m: Plot I-V curves of all currents together
m3ha_compute_and_plot_geometry2.m: Plot the geometry of the cell
m3ha_compute_and_plot_geometry.m: Plot the geometry of the cell
m3ha_compute_and_plot_IA2.m: Plot activation/inactivation curves for the T-type calcium current
m3ha_compute_and_plot_IA.m: Plot activation/inactivation curves for the T-type calcium current
m3ha_compute_and_plot_Ih2.m: Plot activation/inactivation curves for the T-type calcium current
m3ha_compute_and_plot_Ih.m: Plot activation/inactivation curves for the T-type calcium current
m3ha_compute_and_plot_IKir2.m: Plot activation/inactivation curves for the T-type calcium current
m3ha_compute_and_plot_IKir.m: Plot activation/inactivation curves for the T-type calcium current
m3ha_compute_and_plot_INaP2.m: Plot activation/inactivation curves for the T-type calcium current
m3ha_compute_and_plot_INaP.m: Plot activation/inactivation curves for the T-type calcium current
m3ha_compute_and_plot_IT2.m: Plot activation/inactivation curves for the T-type calcium current
m3ha_compute_and_plot_IT.m: Plot activation/inactivation curves for the T-type calcium current
m3ha_compute_and_plot_statistics_addendum.m: m3ha_compute_and_plot_statistics_addendum.m
m3ha_compute_and_plot_statistics.m: Plot bar graphs for LTS and burst statistics
m3ha_compute_and_plot_violin.m: Computes the statistics for and plots 2D violin plots
m3ha_compute_fixed_params.m: Compute fixed parameters that are used in the model
m3ha_compute_gabab_ipsc.m: Computes and plots difference GABA-B IPSC waveforms
m3ha_compute_hinf_IA.m: Compute the steady state value of the inactivation gating variable of IA
m3ha_compute_hinf_INaP.m: Compute the steady state value of the inactivation gating variable of INaP
m3ha_compute_hinf_IT.m: Compute the steady state value of the inactivation gating variable of IT
m3ha_compute_m1inf_IA.m: Compute the steady state value of the activation gating variable of IA
m3ha_compute_m2inf_IA.m: Compute the steady state value of the activation gating variable of IA
m3ha_compute_minf_Ih.m: Compute the steady state value of the activation gating variable of Ih
m3ha_compute_minf_IKir.m: Compute the steady state value of the activation gating variable of IKir
m3ha_compute_minf_INaP.m: Compute the steady state value of the activation gating variable of INaP
m3ha_compute_minf_IT.m: Compute the steady state value of the activation gating variable of IT
m3ha_compute_statistics.m: Computes LTS and burst statistics for some indices (indOfInterest) in ltsOnsetTimeEachSwp, spikesPerLtsEachSwp, burstOnsetTimeEachSwp & spikesPerBurst
m3ha_compute_tauh1_IA.m: Compute the time constant for the inactivation gating variable of IA
m3ha_compute_tauh2_IA.m: Compute the time constant for the inactivation gating variable of IA
m3ha_compute_tauh_INaP.m: Compute the time constant for the inactivation gating variable of INaP
m3ha_compute_tauh_IT.m: Compute the time constant for the inactivation gating variable of IT
m3ha_compute_taum_IA.m: Compute the time constant for the activation gating variable of IA
m3ha_compute_taum_Ih.m: Compute the time constant for the activation gating variable of IT
m3ha_compute_taum_IT.m: Compute the time constant for the activation gating variable of IT
m3ha_correct_unbalanced_bridge.m: Fix current pulse response traces that may have out-of-balance bridges
m3ha_create_cell_info_table.m: Creates a table of cell information from the sweep information table
m3ha_decide_on_plot_vars.m: Decides on the error and parameters to plot
m3ha_decide_on_sweep_weights.m: Set default weights for fitting for the GAT blockade project
m3ha_decide_on_ylimits.m: Decides on the y axis limits based on the measure title
m3ha_determine_row_conditions.m: Determine the conditions for each row
m3ha_estimate_passive_params.m: Estimates passive parameters for each cell from dclamp data recorded by Mark & Christine
m3ha_extract_candidate_label.m: Extracts the cell name from strings but ignores anything before filesep
m3ha_extract_cell_name.m: Extracts the cell name from strings but ignores anything before filesep
m3ha_extract_component_errors.m: Extracts component errors from an error table
m3ha_extract_iteration_string.m: Extracts the iteration string from strings
m3ha_extract_sweep_name.m: Extracts the sweep name from strings but ignores anything before filesep
m3ha_find_all_dependent_scripts.m: Hard-coded parameters
m3ha_find_decision_point.m: Finds the indices for the decision points in the
m3ha_find_files_to_take_out.m: Returns all the file names of files to take out from .png files in ‘TAKE_OUT_*’ folders of a special cases directory
m3ha_find_ind_to_fit.m: Finds indices of fnrow in dclampdatalog_take4.mat that will be used for fitting (legacy, please use m3ha_select_sweeps.m instead)
m3ha_find_ipsc_peak.m: Finds time of current peak from a an inhibitory current trace (must be negative current) (legacy, please use parse_ipsc.m instead)
m3ha_find_ipsc_start_from_conductance.m: Finds time of current application from a series of conductance vectors (legacy, please use parse_ipsc.m instead)
m3ha_find_ipsc_start_from_current.m: Finds time of current application from a series of current vectors (legacy, please use parse_ipsc.m instead)
m3ha_find_lts.m: Find, plot and classify the most likely low-threshold spike (LTS) candidate in a voltage trace (legacy, please use parse_lts.m instead)
m3ha_find_lts_many_sweeps.m: Calls m3ha_find_lts.m for many voltage traces (legacy, please use parse_lts.m instead)
m3ha_find_special_cases.m: Looks for special cases and put traces in corresponding folder
m3ha_fminsearch3.m: Applies the Nelder-Mead simplex algorithm to optimize parameters (modified version of fminsearch for the m3ha project)
m3ha_histograms_across_cells.m: Plots histograms across cells for single neuron fitting
m3ha_import_raw_traces.m: Imports raw traces from .mat files in the m3ha format
m3ha_initial_slopes.m: Computes and plots histograms of slopes right after current pulse start and end
m3ha_load_gabab_ipsc_params.m: Loads GABA-B IPSC parameters
m3ha_load_sweep_info.m: Loads sweep info (default is m3ha_locate_homedir/data_dclamp/take4/dclampdatalog_take4.csv)
m3ha_locate_homedir.m: Locate the first home directory that exists for the GAT blockade project
m3ha_log_errors_params.m: Log errors and parameter values
m3ha_network_analyze_spikes.m: Analyzes .spi files in a directory
m3ha_network_autocorrelogram.m: Shows an m3ha_network_autocorrelogram for each set of neurons (each .spi file in the infolder)
m3ha_network_change_params.m: Change parameter values in a parameters table
m3ha_network_copy_pngs.m: Hard-coded parameters
m3ha_network_define_actmode.m: Determine what cells are stimulated in each activation mode
m3ha_network_launch.m: Launches NEURON with simulation commands and plot output figures
m3ha_network_plot_essential.m: Plots essential traces from special cells in the network
m3ha_network_plot_gabab.m: Compare evoked GABAB activation curves against the recorded GABAB IPSC
m3ha_network_plot_oscillations.m: Shows a swarm plot for each set of neurons (each .spi file in the infolder)
m3ha_network_raster_plot.m: Shows a spike raster plot and compute numActive, latency, oscDur, nSpikes, actDur, actVel for each set of neurons (each .spi file in the inFolder)
m3ha_network_show_net.m: Shows network topology for each network (each .syn file in the inFolder)
m3ha_network_single_neuron.m: Shows single neuron traces for different neurons or for different properties in the same neuron
m3ha_network_tuning_curves.m: Shows a tuning curve for numActive, latency, oscDur, for each parameter changed
m3ha_network_tuning_maps.m: Shows a tuning map for numActive, latency, oscDur, for each parameter changed
m3ha_network_update_dependent_params.m: Update dependent parameters for particular experiments
m3ha_neuron_choose_best_params.m: Chooses among candidates the NEURON parameters that fits a cell’s data the best
m3ha_neuron_create_default_params.m: Creates the default NEURON parameters table
m3ha_neuron_create_initial_params.m: Creates initial NEURON parameters for each cell recorded in dynamic clamp experiments
m3ha_neuron_create_new_initial_params.m: Creates a new set of NEURON parameters based on information in the previous parameters table
m3ha_neuron_create_sim_commands.m: Generates simulation commands to be read by NEURON from a table of simulation parameters
m3ha_neuron_create_sim_params.m: Generates a table of simulation parameters from table(s) of neuron parameters
m3ha_neuron_run_and_analyze.m: Runs and analyzes “one iteration” of NEURON simulations (once for each of the sweeps)
m3ha_optimizer_4compgabab.m: OPTIMIZER Passes parameters to NEURON (which runs simulations and saves
m3ha_optimizergui_4compgabab.m: OPTIMIZERGUI The GUI interface for OPTIMIZER.m, which runs NEURON
m3ha_organize_sweep_indices.m: Organize sweep indices by g incr, pharm conditions for each cell
m3ha_oscillations_analyze.m: m3ha_oscillations_analyze.m
m3ha_parse_dclamp_data.m: m3ha_parse_dclamp_data.m
m3ha_parse_mat.m: Parses and loads a set of matfiles for the GAT blockade project
m3ha_parse_sweep_settings.m: Counts total number of usable cells, sets and sweeps, generate filenames and record sweep properties
m3ha_pfiles2csv.m: Converts the old m3ha .p files to spreadsheet files
m3ha_phase_plane_analysis.m: Plots phase planes from an m3ha .mat file
m3ha_plot_bar3.m: Plots 3-dimensional bar plots from a statistics table returned by m3ha_compute_statistics.m
m3ha_plot_correlations.m: Plot Correlation diagrams for data that will be used for fitting
m3ha_plot_example_jitter.m: m3ha_plot_example_jitter.m
m3ha_plot_figure02.m: m3ha_plot_figure02.m
m3ha_plot_figure03.m: m3ha_plot_figure03.m
m3ha_plot_figure04.m: m3ha_plot_figure04.m
m3ha_plot_figure05.m: m3ha_plot_figure05.m
m3ha_plot_figure08.m: m3ha_plot_figure08.m
m3ha_plot_grouped_scatter.m: Plots grouped scatter plots from a statistics table returned by m3ha_compute_statistics.m
m3ha_plot_histograms_refine_threshold.m: Plot histograms for sweep information & passive fit results that will be used for fitting
m3ha_plot_simulated_traces.m: Plots simulated traces from single neuron output files
m3ha_plot_traces_mat.m: Plot traces from mat file
m3ha_plot_violin.m: Plots violin plots from a statistics table returned by m3ha_compute_statistics.m
m3ha_rank_neurons.m: function [output1] = m3ha_rank_neurons (reqarg1, varargin)
m3ha_resave_sweeps.m: Extracts .abf data and resave as .mat file in the m3ha format
m3ha_select_cells.m: Selects cells with sweeps to use for all pharm-gIncr pairs
m3ha_select_raw_traces.m: Select raw traces to import for specific cells
m3ha_select_sweeps.m: Selects file bases and row indices in swpInfo that will be used
m3ha_simulate_population.m: function [output1] = m3ha_simulate_population (reqarg1, varargin)
m3ha_specs_for_datamode.m: Specifications depending on dataMode for the GAT blockade project
m3ha_test_phase_plane_analysis.m: m3ha_test_phase_plane_analysis.m
m3ha_test_sweep.m: m3ha_test_sweep.m
m3ha_trace_comparison.m: m3ha_trace_comparison.m
m3ha_xolotl_create_neuron.m: Creates a xolotl object for a 3-compartment neuron based on a parameters table
m3ha_xolotl_plot.m: Plots the simulation results from a xolotl object against recorded data
m3ha_xolotl_test.m: m3ha_xolotl_test
mat2sheet.m: Converts .mat files to a spreadsheet file(s) (type specified by the ‘SheetType’ argument)
match_and_combine_vectors.m: Match vectors and combine into an array
match_array_counts.m: Matches a set of arrays to another set of arrays so that they have equal number of arrays
match_column_count.m: Expands or truncates an array to match a given number of columns (dimension #2)
match_dimensions.m: Reshapes or expands an array to match given dimensions
match_format_vector_sets.m: Matches two sets of vectors so that they are both cell arrays of the same number of column vectors
match_format_vectors.m: Match the format of individual vectors by making them all column vectors with the same length
match_positions.m: Finds element(s) of an array that matches the positions of elements in a second list
match_reciprocals.m: Check reciprocals, make them column vectors and generate the reciprocal if empty
match_row_count.m: Expands or truncates an array to match a given number of rows (dimension #1)
match_time_info.m: Match time vector(s) with sampling interval(s) and number(s) of samples
match_time_points.m: Interpolates data (containing a time column) to match the time points of a new time vector
match_vector_count.m: Expands or truncates a vector set to match a given number of vectors
medianfilter.m: Applies a median filter to vectors
merge_structs.m: Merges two scalar structures
metabolismR01_extrapolate_burst_probability.m: Extrapolates burst probability values for A-Drug from GAT1 data
metabolismR01_lactate_regression.m: metabolismR01_lactate_regression.m
metabolismR01_plot_chevrons.m: metabolismR01_plot_chevrons.m
metabolismR01_power_analysis.m: metabolismR01_power_analysis.m
minEASE_combine_events.m: Convert info from Excel file into a structure for GUI
minEASE_compute_plot_average_psc.m: Computes and plots averaged Type I, II & III PSC traces
minEASE_detect_gapfree_events.m: Spontaneous EPSC/IPSC detector and classifyer
minEASE_examine_gapfree_events.m: Examine detected events and allow additions and deletions
minEASE_extract_from_output_filename.m: Extracts information from a minEASE output filename
minEASE_filter_events.m: Filter events and compute inter-event intervals based on criteria
minEASE_filter_output.m: Filter the combined output from a minEASE output directory
minEASE_gui_examine_events.m: A graphic user interface for examining detected events
minEASE_load_output.m: Load the output and relevant parameters from a minEASE output directory into an output structure
minEASE.m: Detect synaptic events
minEASE_plot_gapfree_events.m: Plots all detected events
minEASE_read_params.m: Convert info from Excel file into a structure for GUI
modify_table.m: Modify (possibly only parts of) a table by applying a specific function
movingaveragefilter.m: Applies a moving average filter to vectors
my_closereq.m: Close request function that displays a question dialog box
nan_except.m: Make vectors all NaNs except for selected indices
nanstderr.m: Calculate the standard error of the mean excluding NaN values
normalize_by_initial_value.m: Normalize value(s) by the initial value(s) provided, or store initial value(s) if the latter is empty
outer_product.m: Returns the outer product of two vectors (could be cell arrays)
parse_abf.m: Loads and parses an abf file
parse_all_abfs.m: Parses all abf files in the directory
parse_all_multiunit.m: Runs the parse_multiunit function on all slices in the present working directory
parse_all_swds.m: Parses all Assyst, Sayli and manual SWD files in the current directory
parse_assyst_swd.m: Parse spike-wave-discharge (SWD) event info from an Assyst.txt file
parse_atf_swd.m: Parse spike-wave-discharge (SWD) event info from .atf file or converted .csv file
parse_current_family.m: From a family of current injections, detect current pulse times and amplitudes, detect spikes for each voltage response, and compute spike frequencies
parse_file_or_directory.m: Parses whether the argument is a file or a directory
parse_fitobject.m: Extract information from a cfit or sfit object
parse_gas_trace.m: Parses gas traces
parse_iox.m: Parses a .iox.txt file and return a pulse table
parse_ipsc.m: Finds time of current start and peak from a an inhibitory post-synaptic current trace (must be negative current)
parse_laser_trace.m: Parses laser traces
parse_lts.m: Finds, plots and classifies the most likely low-threshold spike (LTS) candidate in a voltage trace
parse_multiunit.m: Parses multiunit recordings: detect spikes, computes spike histograms and autocorrelograms
parse_peaks.m: Parses peaks for one vector
parse_phase_info.m: Parses phase-related information from parameter and readout values
parse_pleth_trace.m: Parses pleth traces
parse_psd.m: Parses the power spectral density and compute peak frequencies of a data vector
parse_pulse.m: Parses pulse widths, endpoints, amplitudes for vector(s) containing a pulse
parse_pulse_response.m: Parses pulse response widths, endpoints, amplitudes for vector(s) containing a pulse response
parse_repetitive_pulses.m: Parses repetitive pulses
parse_spike2_mat.m: Parses a Spike2-exported MATLAB file
parse_stim.m: Detects the index and time of stimulation start from pulse vectors
parse_xolotl_object.m: Parses a xolotl object
piecelinspace.m: Generates a piece-wise linear vector from nodes and number of points
play_frames.m: TODO: Play frames as a movie
plot_all_abfs.m: Plots all abf files in a directory
plot_all_GABA_B.m: plot_all_GABA_B.m
plot_and_save_boxplot.m: Plots a box plot from a grouped vector according to group
plot_and_save_histogram.m: Plots and saves a stacked histogram for a vector and color code according to class
plot_arrow.m: Draws an arrow from pointFrom to pointTo
plot_autocorrelogram.m: Plots an autocorrelation function from the results of compute_autocorrelogram.m
plot_ball_stick.m: Plots a ball-and-stick model
plot_bar.m: Plots a bar graph (grouped or not) with or without confidence intervals
plot_calcium_imaging_traces.m: Plots calcium imaging traces
plot_cfit_pulse_response.m: Plots data along with the fitted curve
plot_chevron_bar_inset.m: Plots a bar plot comparing against the first group
plot_chevron.m: Plots a Chevron (paired comparison) plot from data
plot_correlation_coefficient.m: Plots the correlation coefficient between x and y data
plot_EEG.m: Plots EEG traces from .abf file(s) or all .abf files in a directory
plot_ellipse.m: Plot an ellipse that may be oblique
plot_error_bar.m: Plots error bar(s)
plot_fitted_traces.m: Plots individual fitted traces
plot_frame.m: Plots a specific movie frame
plot_grouped_histogram.m: Plots a grouped histogram
plot_grouped_jitter.m: Plots a jitter plot colored by group from data (uses plotSpread)
plot_grouped_scatter.m: Plot a grouped scatter plot with 95% confidence ellipses
plot_histogram.m: Plots a histogram labelling out of range values differently
plot_horizontal_line.m: Plots horizontal line(s)
plot_horizontal_shade.m: Plots a shaded area at specific y values, either between specific x values or extend to the current x-axis limits
plot_measures.m: Plots all measures of interest across slices
plot_pdf.m: Plots scaled pdf fit of data X and return vectors for the plots
plot_psth.m: Plots a peri-stimulus time histogram
plot_pulse.m: Plots pulses, marks the parsed endpoints and displays total number of sweeps
plot_pulse_response.m: Plots pulse responses, marks the parsed baseline and steady state bounds
plot_pulse_response_with_stimulus.m: Plots a pulse response with its stimulus
plot_raster.m: Make a raster plot from a cell array of event time arrays
plot_raw_multiunit.m: Plots the raw data from parsed multiunit data
plot_relative_events.m: Binary file /home/Matlab/Adams_Functions/plot_relative_events.m matches
plot_repetitive_protocols.m: Computes features for each file according to protocol type
plot_scale_bar.m: Plots a scale bar for x and/or y axis based on the current axis limits
plot_selected.m: Plots selected values
plot_signals.m: Plots signals (TO BE MERGED WITH plot_traces.m)
plot_small_chevrons.m: Plots two chevron tables
plot_spectrogram.m: Plots the magnitude of the spectrogram data computed by compute_spectrogram.m
plot_spectrogram_multiunit.m: Plots spectrograms from parsed multiunit data
plot_spike_density_multiunit.m: Plots a spike density plot from parsed multiunit data
plot_spike_histogram.m: Plots a spike histogram from the results of compute_spike_histogram.m
plot_struct.m: Plot all fields in a structure array as tuning curves
plot_swd_histogram.m: Plots SWD start times in a histogram
plot_swd_raster.m: Compares all SWD start times in a directory as a raster plot
plot_table.m: Plots variables (columns) in a table
plot_table_parallel.m: Plots the variables in a table in separate subplots
plot_traces_abf.m: Takes an abf file and plots all traces
plot_traces_EEG.m: Plots EEG traces from a .abf file
plot_traces.m: Plots traces all in one place, overlapped or in parallel
plot_traces_spike2_mat.m: Plots traces from a Spike2-exported .mat file
plot_tuning_curve.m: Plot 1-dimensional tuning curve(s), can include confidence intervals or test p values
plot_tuning_map.m: Plot a 2-dimensional tuning map
plot_vertical_line.m: Plots vertical line(s)
plot_vertical_shade.m: Plots a shaded area at specific x values, either between specific y values or extend to the current y-axis limits
plot_violin.m: Plots a violin (unpaired comparison) plot from data
plot_window_boundaries.m: Plots window boundaries as separating lines, duration bars or background shades
print_and_show_message.m: Print to standard output and show message box at the same time
print_cellstr.m: Prints and returns a string for the contents stored in a cell array
print_help.m: Prints and returns the documentation for a specific function
print_next_in_csv.m: What to print next in a csv file
print_or_show_message.m: Either print a message in standard output or show a message box
print_structure.m: Display all fields of a structure recursively
read_adicht.m: Reads in a .adicht file (from LabChart)
read_data_atf.m: Reads the data table from an Axon Text File formatted text file (.atf)
read_frames.m: Reads all frames from a video file
read_lines_from_file.m: Reads line(s) from a file
read_matching_sheets.m: Loads spreadsheets with matching strings before given suffixes (incomplete)
read_neuron_outputs.m: Loads .out files created by NEURON into a cell array
read_params.m: Loads parameters from file(s) into a table
read_swd_sheet.m: Read in an SWD table from a spreadsheet file
read_swd_sheets.m: Loads SWD tables from SWD spreadsheets
read_timetable.m: Reads a time table from a spreadsheet file
regroup_cell_of_cells.m: Regroup a cell array of cell arrays of numeric vectors
relative_std.m: Computes the relative standard deviation (%)
remove_empty.m: Removes empty elements from an array
remove_non_axes.m: Removes axes that are titles or labels
remove_outliers.m: Removes outliers from a data matrix and return a new matrix
renamevars_custom.m: Rename variable(s) in a table
rescale_vec.m: Rescale a vector (vec1) to be in the same ballpark as another vector (vec2),
restore_fields.m: Set each field specified in varargin to previous values from the field strcat(field, ‘_prev’)
restrict_values.m: Restrict values
rmfield_custom.m: Removes field(s) from a structure array only if the field(s) exists
run_neuron.m: Runs NEURON using a .hoc file and a cell array of simulation commands/files
save_all_figtypes.m: Save figures using all figure types provided
save_all_zooms.m: Save a figure in various zoom windows
save_params.m: Saves parameters to a file
select_similar_values.m: Selects values that are within a certain percentage range of the mean
set_axes_properties.m: Decides on the axes handle and sets axes properties
set_default_flag.m: Sets the default flag if empty according to an optional auxFlag
set_fields_zero.m: Set each field specified in varargin to zero and store previous values in a new field strcat(field, ‘_prev’)
set_figure_properties.m: Decides on the figure handle and sets figure properties
set_visible_off.m: Set the ‘Visible’ property of object(s) to ‘off’
sld2ometiff.m: Converts each SlideBook file to a directory of OME-TIFF files
solve_function_at_value.m: Solves x for f(x) at a specific value (default is zero)
spike2Mat2Text.m: Converts a Spike2-exported .mat file to a text file (.atf, .txt or .csv)
sscanf_full.m: Same as sscanf but treats unmatched parts as whitespace (does not stop until end of string)
stderr.m: Calculate the standard error of the mean
struct2arglist.m: Converts a scalar structure to an argument list
struct2mat.m: Saves each variable in a structure as a variable in a MAT-file and create a logHeader and a logVariables
struct2sheet.m: Converts a structure array into a table and write it to a spreadsheet
structofstruct2structarray.m: Converts a structure of structures to a structure array
structs2vecs.m: Converts a cell array of structs with equal numbers of fields to a column cell array of row vectors or cell arrays
suptitle_custom.m: SUPTITLE puts a title above all subplots.
suptitle.m: SUPTITLE puts a title above all subplots.
test_difference.m: Performs the appropriate test between groups based on the normality
test_normality.m: Test whether each set of values is normally distributed
test_passive_fit.m: Tests passive fitting
test_var_difference.m: Tests whether groups are different for each measured variable
transform_vectors.m: Transform vectors by a binary operation
transpose_table.m: Transposes a table (make row names variable names and vice versa)
trim_nans.m: Removes leading and trailing NaNs from vector(s)
union_over_cells.m: Apply the union function over all contents of a cell array
unique_custom.m: Returns the unique values in x, optionally without NaN
unique_groups.m: Retrieves the unique groups and counts the number in each group
update_figure_for_corel.m: Update figure to be journal-friendly (ready for CorelDraw)
update_file_base_in_matfiles.m: Updates slice bases in .mat files to match the file name if changed
update_neuron_scripts.m: Updates NEURON scripts from one directory to another and change to the latter directory
update_param_values.m: Updates a parameters table with new values
update_slice_bases.m: Updates slice bases to file bases for all slice data .mat files in a directory
updatevars.m: Replace a variable in a table or add it if it doesn’t exist
validate_string.m: Validate whether a string is an element of a cell array of valid strings
vec2array.m: Convert a vector to an array with dimensions given by dims using linear indexing (obsolete, use reshape() instead)
vec2cell.m: Reorganize a vector or array into a cell array of partial vectors/arrays according to class
vecfun.m: Apply a function to each vector (each column of an array or each element of a cell array of vectors)
vertcat_spreadsheets.m: Combine spreadsheets using readtable, vertcat, then writetable
write_data_atf.m: Writes a data matrix to an Axon Text File formatted text file (.atf)
write_frames.m: Write frames to a file
write_timetable.m: Writes a time table to a spreadsheet file
xolotl_add_current_injection.m: Adds a current injection to a xolotl object, just the first compartment by default
xolotl_add_current_pulse.m: Adds a current pulse to the first compartment of a xolotl object
xolotl_add_holding_current.m: Adds a holding current to a xolotl object
xolotl_add_voltage_clamp.m: Adds a voltage clamp to the first compartment of a xolotl object
xolotl_compartment_index.m: Returns the index of the compartment or the first compartment by default
xolotl_create_model_howard.m: Creates a xolotl model based on Howard et al
xolotl_create_model_soplata.m: Creates a xolotl model based on Soplata et al
xolotl_estimate_holding_current.m: Estimates the holding current necessary to match a certain holding potential
xolotl_set_simparams.m: Runs a simulation on a xolotl object
xolotl_simulate.m: Simulates and returns output
ZG_compute_IEI_thresholds.m: Compute all possible inter-event interval thresholds from the data within an all_output directory
ZG_extract_all_data.m: Extract each cell and concatenate sweeps into a single file under a subdirectory of its own
ZG_extract_all_IEIs.m: Extract all the inter-event intervals from a directory containing multiple minEASE output subdirectories
ZG_extract_IEI_thresholds.m: Extract/compute inter-event-interval distribution thresholds, separating events from spikes
ZG_fit_IEI_distributions.m: Fit inter-event-interval distributions and log distributions
ZG_plot_grouped_scatter.m: Plot and save a grouped scatter plot with 95% confidence ellipses