Commit f636f6ec authored by Alex Nunes's avatar Alex Nunes
Browse files

Minor changes to make sure there is a standard time unit(seconds) used across all tools 

 Changes to be committed:
	modified:   CHANGELOG.md
	modified:   README
	modified:   README.md
	modified:   conda.recipe/meta.yaml
	modified:   docs/conf.py
	modified:   docs/index.rst
	modified:   docs/notebooks/cohort_data.ipynb.rst
	modified:   docs/notebooks/filters.ipynb.rst
	modified:   py_notebooks/cohort_data.ipynb
	modified:   py_notebooks/filters.ipynb
	modified:   resonate/__init__.py
	modified:   resonate/cohorts.py
	modified:   setup.py
	modified:   tests/cohort_test.py
parent d2ce46c0

CHANGELOG.md

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@@ -4,6 +4,11 @@ All notable changes to this project will be documented in this file. 
The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)

and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html).



## [1.0.2]



### Changed

- All analysis and documentation now uses seconds and not minutes as a timedelta unit



## [1.0.1]



### Fixed

README

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@@ -45,7 +45,7 @@ OTN has developed a tool which will assist with filtering false detections. The 


This is a very simple tool. It will take an input file of detections and based on an input parameter will identify suspect detections. The suspect detections will be put into a dataframe which the user can examine. There will be enough information for each suspect detection for the user to understand why it was flagged. There is also enough information to be able to reference the detection in the original file if the user wants to see what was happening at the same time.



The input parameter is a time in minutes. We used 60 minutes as the default as this is what was used in Easton's code. This value can be changed by the user. The output contains a record for each detection for which there has been more than xx minutes since the previous detection (of that tag/animal) and more than the same amount of time until the next detection. It ignores which receiver the detection occurred at. That is all it does, nothing more and nothing less.

The input parameter is a time in minutes. We used 3600 seconds as the default as this is what was used in Easton's code. This value can be changed by the user. The output contains a record for each detection for which there has been more than xx minutes since the previous detection (of that tag/animal) and more than the same amount of time until the next detection. It ignores which receiver the detection occurred at. That is all it does, nothing more and nothing less.





Distance Matrix

README.md

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Original line number Diff line number Diff line
@@ -59,7 +59,7 @@ OTN has developed a tool which will assist with filtering false detections. The 


This is a very simple tool. It will take an input file of detections and based on an input parameter will identify suspect detections. The suspect detections will be put into a dataframe which the user can examine. There will be enough information for each suspect detection for the user to understand why it was flagged. There is also enough information to be able to reference the detection in the original file if the user wants to see what was happening at the same time.



The input parameter is a time in minutes. We used 60 minutes as the default as this is what was used in Easton's code. This value can be changed by the user. The output contains a record for each detection for which there has been more than xx minutes since the previous detection (of that tag/animal) and more than the same amount of time until the next detection. It ignores which receiver the detection occurred at. That is all it does, nothing more and nothing less.

The input parameter is a time in minutes. We used 3600 seconds as the default as this is what was used in Easton's code. This value can be changed by the user. The output contains a record for each detection for which there has been more than xx minutes since the previous detection (of that tag/animal) and more than the same amount of time until the next detection. It ignores which receiver the detection occurred at. That is all it does, nothing more and nothing less.





Distance Matrix

conda.recipe/meta.yaml

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package:

  name: resonate

  version: "1.0.1"

  version: "1.0.2"



source:

  git_rev: master

docs/conf.py

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@@ -76,9 +76,9 @@ copyright = u'2017 Ocean Tracking Network. All Rights Reserved.' 
# built documents.

#

# The short X.Y version.

version = 'v1.0.1'

version = 'v1.0.2'

# The full version, including alpha/beta/rc tags.

release = 'v1.0.1'

release = 'v1.0.2'



# The language for content autogenerated by Sphinx. Refer to documentation

# for a list of supported languages.