Ruby gem used to load, validate, and parse European Data Format files. Used for batch testing EDFs for errors. Ruby 2.6+ compatible.
Use gem install edfize to update Edfize to the latest stable
Use gem install edfize --pre to update Edfize to the latest prerelease
Use edfize test to test that EDFs stored in the current directory have a valid
format.
cd <edf-directory>
edfize test
A list of validations performed is:
- Expected Length Check: Compares the calculated size of the file based on signal sizes defined in the header with the actual file size. A failure may indicate corruption in the header (if the expected is less than the actual file size), or a partial/truncated file (if the expected is more than the actual file size).
- Reserved Area Checks: Check that reserved areas are blank. Non-blank reserved areas can indicate a sign of header or EDF file corruption.
Flags that can be added to the test command include:
--failing: Only display EDFs with failing tests--quiet: Suppress detailed failure descriptions that show the expected versus the actual result of the test
Use edfize run to print out signal header information for each EDF in the
current directory.
cd <edf-directory>
edfize run
Use edfize help to list available commands and descriptions for Edfize.
edfize help
Use edfize version to check the version of Edfize.
edfize version
This will update all EDFs in the current directory and subdirectories with a start date of 1st Jan 1985.
rewrite_signal_date.rb
# gem install edfize --no-document
# ruby rewrite_signal_date.rb
require "rubygems"
require "edfize"
CLIPPING_DATE = "01.01.85"
Edfize.edfs do |edf|
edf.update(start_date_of_recording: CLIPPING_DATE)
endThe Edfize gem now supports writing EDF+ files. You can create new EDF files or modify existing ones:
# Load an existing EDF file
edf = Edfize::Edf.new("input.edf")
# Write it to a new file (as continuous EDF+)
edf.write("output.edf", is_continuous: true)
# Write it as discontinuous EDF+
edf.write("output.edf", is_continuous: false)The write functionality automatically:
- Adds required EDF+ headers
- Ensures at least one EDF Annotations signal exists (required for EDF+)
- Properly formats all header fields
- Writes signal data in the correct binary format
The following Ruby file demonstrates how to make use of the Edfize gem to load EDF signals into arrays for analysis.
tutorial_01_load_edf_and_signals.rb
# Tutorial 01 - Load EDF and Signals
#
# gem install edfize --no-document
#
# ruby tutorial_01_load_edf_and_signals.rb
#
# The EDF exists at:
#
# https://sleepdata.org/datasets/shhs/files/edfs/shhs1?f=shhs1-200001.edf
#
require "rubygems"
require "edfize"
# Loads the file and reads the EDF Header
edf = Edfize::Edf.new("shhs1-200001.edf")
# Loads the data section of the EDF into Signal objects
edf.load_signals
# Print out information on the signals
puts "EDF #{edf.filename} contains the following #{edf.signals.count} signal#{"s" unless edf.signals.count == 1}:\n\n"
edf.signals.each do |signal|
puts "Signal"
puts " Label : #{signal.label}"
puts " Samples Per Data Record : #{signal.samples_per_data_record}"
puts " First 10 Physical Values : #{(signal.physical_values[0..10] + ["..."]).inspect}\n\n"
endWhen run, the code above will output the following:
EDF shhs1-200001.edf contains the following 14 signals:
Signal
Label : SaO2
Samples Per Data Record : 1
First 10 Physical Values : [95.31242847333486, 95.31242847333486, 95.31242847333486, 95.31242847333486, 95.31242847333486, 95.31242847333486, 95.31242847333486, 95.31242847333486, 94.14053559166858, 94.14053559166858, 94.14053559166858, "..."]
Signal
Label : H.R.
Samples Per Data Record : 1
First 10 Physical Values : [77.34416723887999, 77.34416723887999, 77.34416723887999, 76.56595712214848, 76.56595712214848, 76.56595712214848, 75.00190737773708, 75.00190737773708, 75.00190737773708, 75.00190737773708, 75.00190737773708, "..."]
Signal
Label : EEG(sec)
Samples Per Data Record : 125
First 10 Physical Values : [-4.411764705882348, 5.392156862745111, 2.4509803921568647, 0.49019607843136725, -0.49019607843136725, -10.294117647058826, 3.4313725490196134, 12.25490196078431, -1.470588235294116, -2.4509803921568647, -8.333333333333329, "..."]
Signal
Label : ECG
Samples Per Data Record : 125
First 10 Physical Values : [0.03431372549019618, 0.03431372549019618, 0.03431372549019618, 0.03431372549019618, 0.044117647058823595, 0.044117647058823595, 0.044117647058823595, 0.044117647058823595, 0.044117647058823595, 0.03431372549019618, 0.03431372549019618, "..."]
Signal
Label : EMG
Samples Per Data Record : 125
First 10 Physical Values : [12.622549019607845, 3.7990196078431353, -3.5539215686274517, -2.5735294117647065, 8.455882352941174, 1.5931372549019613, 9.436274509803923, -8.700980392156861, -2.5735294117647065, 13.112745098039213, -12.867647058823529, "..."]
Signal
Label : EOG(L)
Samples Per Data Record : 50
First 10 Physical Values : [28.921568627450966, 17.15686274509804, 25.0, 19.117647058823536, -5.392156862745097, -9.313725490196077, -0.49019607843136725, -1.470588235294116, 1.470588235294116, -1.470588235294116, 0.49019607843136725, "..."]
Signal
Label : EOG(R)
Samples Per Data Record : 50
First 10 Physical Values : [12.25490196078431, 1.470588235294116, 10.294117647058812, 5.392156862745111, 17.15686274509804, 18.137254901960773, 25.980392156862735, 32.84313725490196, 25.0, 26.960784313725497, 22.058823529411768, "..."]
Signal
Label : EEG
Samples Per Data Record : 125
First 10 Physical Values : [-2.4509803921568647, 1.470588235294116, -9.313725490196077, -6.372549019607845, -0.49019607843136725, -10.294117647058826, -12.25490196078431, -12.25490196078431, -7.352941176470594, 1.470588235294116, 6.372549019607845, "..."]
Signal
Label : THOR RES
Samples Per Data Record : 10
First 10 Physical Values : [0.207843137254902, 0.207843137254902, 0.15294117647058825, 0.0980392156862745, 0.03529411764705881, -0.0117647058823529, -0.050980392156862786, -0.08235294117647052, -0.10588235294117654, -0.1215686274509804, -0.13725490196078427, "..."]
Signal
Label : ABDO RES
Samples Per Data Record : 10
First 10 Physical Values : [0.30980392156862746, 0.24705882352941178, 0.16078431372549018, 0.06666666666666665, -0.0039215686274509665, -0.08235294117647052, -0.1607843137254903, -0.2078431372549019, -0.2313725490196079, -0.2549019607843137, -0.2705882352941176, "..."]
Signal
Label : POSITION
Samples Per Data Record : 1
First 10 Physical Values : [2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, "..."]
Signal
Label : LIGHT
Samples Per Data Record : 1
First 10 Physical Values : [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, "..."]
Signal
Label : NEW AIR
Samples Per Data Record : 10
First 10 Physical Values : [6.372549019607845, 6.372549019607845, 5.392156862745111, 3.4313725490196134, 7.35294117647058, 6.372549019607845, 8.333333333333343, 9.313725490196077, 6.372549019607845, 6.372549019607845, 7.35294117647058, "..."]
Signal
Label : OX stat
Samples Per Data Record : 1
First 10 Physical Values : [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, "..."]- Fork it ( https://github.com/sleepepi/edfize/fork )
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git checkout -b my-new-feature) - Commit your changes (
git commit -am 'Add some feature') - Push to the branch (
git push origin my-new-feature) - Create a new Pull Request