raw_detections

An example dataset of real acoustic telemetry detections of fish at several
receivers within the California Central Valley from 2021. These detections
have not been processed to remove false positives.

datasets

Analyze telemetry datasets generalized to allow
any technology. The filtering steps check for false positives caused by
reflected transmissions from surfaces and false pings from other noise
generating equipment. The filters are based on JSATS filtering algorithms
found in package 'filteRjsats' <https://CRAN.R-project.org/package=filteRjsats>
but have been generalized to allow the user to define many of the filtering
variables. Additionally, this package contains scripts used to help identify
an optimal maximum blanking period as defined in Capello et al (2015)
<doi:10.1371/journal.pone.0134002>. The functions were written according to
their manuscript description, but have not been reviewed by the authors for
accuracy. It is included here as is, without warranty.

Taylor Spaulding

telemetR

Filter and Analyze Generalised Telemetry Data from Organisms

raw_detections function

## `raw_detections`
A data frame with 55,736 rows and 3 columns:<dl>
 <dt>serial</dt>
<dd>The serial number of the detecting receiver</dd> <dt>local_time</dt>
<dd>the local time of the detection (tz = America/Los_Angeles)</dd> <dt>tag_id</dt>
<dd>The hexadecimal acoustic tag ID code</dd>
</dl>

Format

Unfiltered detection data — raw_detections

## `raw_detections`
A data frame with 55,736 rows and 3 columns:<dl>
 <dt>serial</dt>
<dd>The serial number of the detecting receiver</dd>

 <dt>local_time</dt>
<dd>the local time of the detection (tz = America/Los_Angeles)</dd>

 <dt>tag_id</dt>
<dd>The hexadecimal acoustic tag ID code</dd>


</dl>

raw_detections: Unfiltered detection data

Description

Usage

Arguments

Format