fix missing link to seewave::meanspec

R/excess_attenuation.R

@@ -11,7 +11,7 @@
 #' @return Object 'X' with an additional column,  'excess.attenuation', containing the computed excess attenuation values (in dB).
 #' @export
 #' @name excess_attenuation
-#' @details Excess attenuation is the amplitude loss of a sound in excess due to spherical spreading (observed attenuation - expected attenuation). With every doubling of distance, sounds attenuate with a 6 dB loss of amplitude (Morton, 1975; Marten & Marler, 1977). Any additional loss of amplitude results in energy loss in excess of that expected to occur with distance via spherical spreading. So it represents power loss due to additional factors like vegetation or atmospheric conditions (Wiley & Richards, 1978). Low values indicate little additional attenuation. The goal of the function is to measure the excess attenuation on sounds in which a reference playback has been re-recorded at increasing distances. The 'sound.id' column must be used to indicate which sounds belonging to the same category (e.g. song-types). The function will then compare each sound type to the corresponding reference sound. Two approaches for computing excess attenuation are provided (see 'type' argument).
+#' @details Excess attenuation is the amplitude loss of a sound in excess due to spherical spreading (observed attenuation - expected attenuation). With every doubling of distance, sounds attenuate with a 6 dB loss of amplitude (Morton, 1975; Marten & Marler, 1977). Any additional loss of amplitude results in energy loss in excess of that expected to occur with distance via spherical spreading. So it represents power loss due to additional factors like vegetation or atmospheric conditions (Wiley & Richards, 1978). Low values indicate little additional attenuation. The goal of the function is to measure the excess attenuation on sounds in which a reference playback has been re-recorded at increasing distances. The 'sound.id' column must be used to indicate which sounds belonging to the same category (e.g. song-types). The function will then compare each sound type to the corresponding reference sound. Two approaches for computing excess attenuation are provided (see 'type' argument). NAs will be returned if one of the envelopes is completely flat (e.g. no variation in amplitude).
 #' @examples {
 #'   # load example data
 #'   data("test_sounds_est")

R/internal_functions.R

@@ -1177,6 +1177,10 @@
         )$y
     }
 
+    # add little variation if all values ar the same so measurements can be taken on in (like envelope correlation)
+    if (all(nv == nv[1]))
+      nv[1] <- nv[1] + 0.0001
+
     return(nv)
   }
 
@@ -1256,12 +1260,11 @@
       )
   }
 
-
-  sig_env <-   if (!rms)
+  # convert into envelope using warbleR if no rms
+  sig_env <- if (!rms)
     mean(warbleR::envelope(x = clp@left)) else
       seewave::rms(warbleR::envelope(x = clp@left))
 
-
   return(sig_env)
 }
 
@@ -1320,6 +1323,9 @@
       ea <- (-20 * log10(sig_env_REF / X$sig_env[y])) - (20 * log10(1 / dist_SIG))
   }
 
+  if (is.infinite(ea))
+    ea <- NA
+
   return(ea)
 }
 
@@ -1549,7 +1555,11 @@
 
         # get RMS for signal
         sig_rms <- seewave::rms(warbleR::envelope(signal[, 1]))
-
+
+        # convert to 0.0001 if sig_rms is 0 to avoid errors in SNR measurements
+        if (sig_rms == 0)
+          sig_rms <- 0.0001
+
         # cut ambient noise before sound
         noise1 <-
           seewave::cutw(noise_sig,
@@ -1559,6 +1569,11 @@
 
         # get RMS for background noise
         bg_rms <- seewave::rms(warbleR::envelope(noise1[, 1]))
+
+        # convert to 0.0001 if bg_rms is 0 to avoid errors in SNR measurements
+        if (bg_rms == 0)
+          bg_rms <- 0.0001
+
       }
     } else {
       sig_rms <- NA

R/signal_to_noise_ratio.R

@@ -23,7 +23,7 @@
 #' with the signal-to-noise ratio values (in dB).
 #' @export
 #' @name signal_to_noise_ratio
-#' @details Signal-to-noise ratio (SNR) measures sound amplitude level in relation to ambient noise. Noise is measured on the background noise immediately before the test sound. A general margin in which ambient noise will be measured must be specified. Alternatively, a selection of ambient noise can be used as reference (see 'noise.ref' argument). When margins overlap with another sound nearby, SNR will be inaccurate, so margin length should be carefully considered. Any SNR less than or equal to one suggests background noise is equal to or overpowering the sound. The function will measure signal-to-noise ratio within the supplied frequency range (e.g. bandpass) of the reference signal ('bottom.freq' and 'top.freq' columns in 'X') by default (that is, when \code{bp = 'freq.range'}.
+#' @details Signal-to-noise ratio (SNR) measures sound amplitude level in relation to ambient noise. Noise is measured on the background noise immediately before the test sound. A general margin in which ambient noise will be measured must be specified. Alternatively, a selection of ambient noise can be used as reference (see 'noise.ref' argument). When margins overlap with another sound nearby, SNR will be inaccurate, so margin length should be carefully considered. Any SNR less than or equal to one suggests background noise is equal to or overpowering the sound. The function will measure signal-to-noise ratio within the supplied frequency range (e.g. bandpass) of the reference signal ('bottom.freq' and 'top.freq' columns in 'X') by default (that is, when \code{bp = 'freq.range'}. SNR can be ~0 when both tail and signal have very low amplitude.
 #' @examples {
 #'   # load example data
 #'   data("test_sounds_est")
@@ -86,6 +86,7 @@ signal_to_noise_ratio <-
         path = path,
         header = TRUE
       )$sample.rate
+
 
     # adjust wl based on hop.size
     wl <- .adjust_wl(wl, X, hop.size, path)
@@ -118,7 +119,7 @@ signal_to_noise_ratio <-
     }
 
     # 'mar' is needed when not using equal duration
-    if (!eq.dur & is.null(mar)) {
+    if (!eq.dur & is.null(mar) & noise.ref == "adjacent") {
       .stop("'mar' must be supplied when 'eq.dur = FALSE'")
     }
 

R/spcc.R

@@ -69,7 +69,7 @@ spcc <-
     comp_mat <- cbind(X$.sgnl.temp, X$reference)
 
     # remove NA rows
-    comp_mat <- comp_mat[stats::complete.cases(comp_mat),]
+    comp_mat <- comp_mat[stats::complete.cases(comp_mat), , drop = FALSE]
 
 
     # save previous warbleR options

R/tail_to_signal_ratio.R

@@ -21,7 +21,7 @@
 #' with the tail-to-signal ratio values (in dB).
 #' @export
 #' @name tail_to_signal_ratio
-#' @details Tail-to-signal ratio (TSR) measures the ratio of power in the tail of reverberations to that in the test sound. A general margin in which reverberation tail will be measured must be specified. The function will measure TSR within the supplied frequency range (e.g. bandpass) of the reference sound ('bottom.freq' and 'top.freq' columns in 'X'). Two methods for computing reverberations are provided (see 'tsr.formula' argument). Note that 'tsr.formula' 2 is not equivalent to the original description of TSR in Dabelsteen et al. (1993) and  is better referred to as tail-to-noise ratio. Tail-to-signal ratio values are typically negative as signals tend to have higher power than that in the reverberating tail.
+#' @details Tail-to-signal ratio (TSR) measures the ratio of power in the tail of reverberations to that in the test sound. A general margin in which reverberation tail will be measured must be specified. The function will measure TSR within the supplied frequency range (e.g. bandpass) of the reference sound ('bottom.freq' and 'top.freq' columns in 'X'). Two methods for computing reverberations are provided (see 'tsr.formula' argument). Note that 'tsr.formula' 2 is not equivalent to the original description of TSR in Dabelsteen et al. (1993) and  is better referred to as tail-to-noise ratio. Tail-to-signal ratio values are typically negative as signals tend to have higher power than that in the reverberating tail. TSR can be ~0 when both tail and signal have very low amplitude.
 #' @examples {
 #'   # load example data
 #'
@@ -195,10 +195,17 @@ tail_to_signal_ratio <- function(X,
         # sound (or noise) RMS
         sig_RMS <- seewave::rms(sig.env)
 
-        # get reference ambient noise RMS
+        # convert to 0.0001 if sig_RMS is 0 to avoid errors in STR measurements
+        if (sig_RMS == 0)
+          sig_RMS <- 0.0001
 
+        # get reference ambient noise RMS
         tail_RMS <- seewave::rms(tail.env)
 
+        # convert to 0.0001 if tail_RMS is 0 to avoid errors in STR measurements
+        if (tail_RMS == 0)
+          tail_RMS <- 0.0001
+
         # Calculate tail.to.signal ratio
         str <- tail_RMS / sig_RMS
 

vignettes/align_test_sounds.Rmd

@@ -68,9 +68,10 @@ opts_chunk$set(fig.align = "center",
 
 <img src="baRulho_sticker.png" alt="baRulho sticker" align="right" width = "25%" height="25%"/>
 
-
 This vignette shows deals with two things: how to create synthetic sounds for playback experiments and how to align re-recorded sounds to their reference once playback has been conducted. Here is some terms that will be used in this vignettes and throughout the package.
 
+&nbsp;
+
 <div class="alert alert-info">
 
 <font size="5">Glossary</font> 

vignettes/quantify_degradation.Rmd

@@ -560,7 +560,7 @@ sc
 
 ### Noise profiles
 
-The function `noise_profile()` allows to estimate the frequency spectrum of ambient noise. This can be done on extended selection tables (using the segments containing no sound) or over entire sound files in the working directory (or path supplied). The function uses \code{\link[seewave]{meanspec}} internally to calculate frequency spectra. The following code measures the ambient noise profile for the recordings at distance >= 5m on the example extended selection table:
+The function `noise_profile()` allows to estimate the frequency spectrum of ambient noise. This can be done on extended selection tables (using the segments containing no sound) or over entire sound files in the working directory (or path supplied). The function uses the seewave function `meanspec()` internally to calculate frequency spectra. The following code measures the ambient noise profile for the recordings at distance >= 5m on the example extended selection table:
 
 ```{r, eval = TRUE}