example_scripts/example_calc_s_freq.R
In vbaliga/pathviewR: Wrangle, Analyze, and Visualize Animal Movement Data
## Last updated 2020/07/16 by ERP
########################## Not fully worked out yet
## The calc_vis_angle function references the position_width and position_height
## variables of raw motive data files and require the following arguments:
## gnd_plane - at baseline, this indicates the vertical distance
## between the bottom of the "V" and the height of the grounding tool.
## Following raw data processing using the utility functions, it must
## indicate the vertical distance between the bottom of the "V" and the
## height of the perches. An incorrect gnd_plane for a given tunnel set up
## may calculate negative visual angles (as if the bird is flying outside the
## tunnel). gnd_plane should be reported in the same units as position_width
## and position_height (typically in meters).
##
## stim_param_pos AND stim_param_neg - these reflects the
## size of the visual stimulus displayed on either side of the tunnel.
## E.g. positive screens displays 10cm wide bars: stim_param_pos = 0.1.
##
## vertex_angle - this is included in the calc_vis_angle_mod
## functions and it represents the acute angle each screen creates with a
## vertical axis. It is also equal to the angle of the "V" divided by 2.
## It's reported in degrees and is converted to radians so that it works with
## the trig functions.
##
## simplify_output - if set to TRUE, this limits output variables to
## vis_angle_pos_deg and vis_angle_neg_deg
### NOTE: Perhaps these arguments can eventually be supplied or referenced
### from within each file's metadata.
### 7.14.2020 - perhaps gnd_plane, stim_param_pos, stim_param_neg, and
### vertx_angle instead these can be referenced from the data frame itself
### after the user has used insert_treatments.
## The first several sections of this example simply run through the importing
## and cleaning pipeline to generate an object that calc_vis_angle can apply to.
##### Load packages #####
library(ggplot2)
library(magrittr)
##### Source scripts #####
## First define the directory to inspect
scripts_path <- "./R/"
## calc_vis_angle functions now included in this path
## Now list all the .R files
scripts_list <- list.files(path = scripts_path,
pattern = "*.R",
full.names = TRUE,
recursive = TRUE
)
## Using a for() loop instead of lapply() because the latter produces messages
## we don't need.
for (i in 1:length(scripts_list)) {
source(scripts_list[i])
}
##### Working with motive objects #####
# Lets try an examples using the all in one function (import_and_clean_viewr)
##### All in one function #####
jul_29_path <- './inst/extdata/pathviewr_motive_example_data.csv'
jul_29_all_defaults <-
jul_29_path %>% import_and_clean_viewr()
## or we could use the utility functions in sequence
##### Utility functions in sequence #####
## default arguments used for every step to see if the product mirrors the all
## in one function output
##### Data import #####
jul_29 <- read_motive_csv('./inst//extdata/pathviewr_motive_example_data.csv')
##### Rename axes #####
jul_29 <- relabel_viewr_axes(jul_29,
tunnel_length = "_z",
tunnel_width = "_x",
tunnel_height = "_y",
real = "_w")
##### Gather data #####
jul_29_gathered <- gather_tunnel_data(jul_29)
##### Trim outliers #####
jul_29_trimmed <- trim_tunnel_outliers(jul_29_gathered)
##### Rotate tunnel #####
jul_29_rotated <-
jul_29_trimmed %>% rotate_tunnel()
##### Select X percent #####
jul_29_selected <-
jul_29_rotated %>% select_x_percent()
##### Separate trajectories #####
jul_29_labeled <-
jul_29_selected %>% separate_trajectories()
##### Keep full trajectories #####
jul_29_full <-
jul_29_labeled %>% get_full_trajectories()
identical(jul_29_all_defaults, jul_29_full)
## curently false as import_and_clean_viewr includes velocity calculations
################ calc_vis_angle #############
## For an experiment with the ground plane set 50cm above the bottom of a 45 degree
## "V" and sine-wave gratings with a period of 10cm displayed on either side of
## the tunnel, the following arguments would be used.
## NOTE: in this case, the position of the grounding tool was unknown and
## therefore gnd_plane is estimated as the height of the perches from the base
## of the "V".
full45 <- calc_vis_angle(jul_29_all_defaults,
gnd_plane = 0.5,
stim_param_pos = 0.1,
stim_param_neg = 0.1,
vertex_angle = 45,
simplify_output = FALSE)
View(full45)
## This produces 10 additional variables in the dataframe based on the math
## internal to calc_vis_angle.
## Use simplify_output = TRUE to output only the degrees of visual angle on the
## positive and negative sides of the tunnel
simp45 <- calc_vis_angle(jul_29_all_defaults,
gnd_plane = 0.5,
stim_param_pos = 0.1,
stim_param_neg = 0.1,
vertex_angle = 45,
simplify_output = TRUE)
View(simp45)
## calc_vis_angle can accomodate different tunnel vertex angles and now
## calculates mind_dist correctly even when the bird is flying far from the
## center line.
## NOTE: This data was collected at vertex_angle = 45 so changing this argument
## is not something a user would want to do. But let's see how it affects the
## values and distribution of angles in the tunnel.
full60 <- calc_vis_angle(jul_29_all_defaults,
gnd_plane = 0.5,
stim_param_pos = 0.1,
stim_param_neg = 0.1,
vertex_angle = 60,
simplify_output = FALSE)
View(full60)
###### Visualizing the calculated angles by position in the tunnel #####
## Plot position in cross section of the tunnel and color points by
## vis_angle_pos_deg
ggplot(full45, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_pos_deg),
shape = 1, size = 3)
# greater visual angles closer to positive (right) side of the tunnel
## Now for vertex_angle = 60
ggplot(full60, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_pos_deg),
shape = 1, size = 3)
# flipping between the graphs you can see a subtle shift in the distribution of
# angles.
## In response to VBB comments:
#### _VBB_suggestions_2 #####
## These plots are awesome! Easy to make sense of them.
##
## One feature that would also be helpful would be to add a visualization of
## the tunnel itself, which would require inferring the coordinates of the
## tunnel. I think we can reasonably approximate some of this using the
## inputs from calc_vis_angle() alone.
## Here's what we assume:
## - With gnd_plane = 0.5, we assume the vertex is at -0.5 on the height
## axis. Therefore the vertex is located at (0, -0.5) for (width, height);
## ignoring length for now.
## - With vertex_angle = 45, we assume the vertex angle (duh).
## - It may not be feasible to know the height of the tunnel, i.e. where
## on the position_height axis the walls actually end. So, I suggest we
## use position_height = 0 as a first-pass approximation. Therefore, the
## two topmost points of the tunnel walls will be at (?, 0) and (-?, 0),
## for the positive and negative side, respectively (again, ignore length)
## So, with those conditions, it's time for some SohCahToa:
## For the positive side:
## tan(deg_2_rad(45/2)) = x / 0.5
## 0.5 * tan(deg_2_rad(45/2)) = x
## 0.2071068 = x
## Therefore, the topmost point on the positive side is at (0.207, 0)
## Since the tunnel is assumed symmetric about width = 0, the topmost
## point on the neg side is (-0.207,0).
## And for fun, the length of the hypotenuse, h, (i.e. the length of the
## walls themselves) is:
## cos(deg_2_rad(45/2)) = 0.5 / h
## h = 0.5 / cos(deg_2_rad(45/2))
## h = 0.5411961
## As a check:
sqrt((0.2071068 ^2) + (0.5^2)) ## equates to 0.5411961
## Also if we use the three points (two topmost and vertex), we should
## be able to back-calculate the vertex angle to confirm it is ~45
get_2d_angle(x1 = -0.2071, ## (x1, y1) is topmost on negative side
y1 = 0,
x2 = 0, ## (x2, y2) is vertex
y2 = -0.5,
x3 = 0.2071, ## (x3, y3) is topmost on positive side
y3 = 0)
## I get 44.99867, which is basically 45. So this all seems to work.
## Yoinking the vis_angle_pos_deg plot and adding walls:
ggplot(full45, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_pos_deg),
shape = 1, size = 3) +
geom_segment(aes(x = 0, ## POSITIVE SIDE FIRST
y = -0.5,
xend = 0.207,
yend = 0)) +
geom_segment(aes(x = 0, ## NEGATIVE SIDE
y = -0.5,
xend = -0.207,
yend = 0))
## Judging by this visualization, I think either the vertex angle is
## actually greater than 45 (i.e. the "V" is wider than 45deg) or the
## ground plane placement should be lower.
## Is it worth re-measuring the tunnel in lab?
## Related to all this, the information of tunnel coordinates can be
## inferred from user inputs to cal_vis_angle. I think it would be
## nice to add these coordinates in as attributes to the object. That
## way, successive pathviewr functions can make use of these info, and
## also they will be available if the user wants to add them to a plot.
## Also, do you mind if we rename gnd_plane? We are using the ground
## plane as an approximator of the vertex location. So if we are to
## make things more generic (i.e. for other users) we could opt to
## rename this as vertex_height, vertex_relative_height, or something
## along those lines?
#### ERP response ####
## I like the idea of visualizing the tunnel walls with this plot!
## gnd_plane = 0.5 is only an estimate of the true distance between
## the height of the perches and the vertex. It's definitely worth
## measuring the tunnel again to make it's accurate. I can do that
## next time I go to the lab.
## The TV model dimensions are ~ 1.46m length x 0.83m height. Angled
## at 45 degree meaning the top corners are:
0.83 * cos(pi/4) # vertical distance from (0, 0) = 0.5869m
## gnd_plane = 0.5, therefore the height is +0.0869m w.r.t the perches
0.83 * sin(pi/4) # horizontal distance from (0, 0) is also 0.5869m (duhh
## vertex_angle = 45) therefore the top corners are:
## top right = (0.5869, 0.0869)
## top left = (-0.5869, 0.0869)
## checking the angles...
get_2d_angle(x1 = -0.5869, ## (x1, y1) is topmost on negative side
y1 = 0.0869,
x2 = 0, ## (x2, y2) is vertex
y2 = -0.5,
x3 = 0.5869, ## (x3, y3) is topmost on positive side
y3 = 0.0869)
## shows the tunnel angles at 90 degree which is correct since vertex_angle is
## the angle of the "V" divided by 2 (stupid system I know but we'll chat
## about it)
## Let's plot it out again with the walls included
ggplot(full45, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_neg_deg),
shape = 1, size = 3) +
geom_segment(aes(x = 0, ## POSITIVE SIDE FIRST
y = -0.5,
xend = 0.5869,
yend = 0.0869)) +
geom_segment(aes(x = 0, ## NEGATIVE SIDE
y = -0.5,
xend = -0.5869,
yend = 0.0869))
ggplot(full45, aes(x = position_length, y = position_height)) +
geom_point(aes(color = vis_angle_pos_deg),
shape = 1, size = 3) +
geom_segment(aes(x = 0, ## POSITIVE SIDE FIRST
y = -0.5,
xend = 0.5869,
yend = 0.0869)) +
geom_segment(aes(x = 0, ## NEGATIVE SIDE
y = -0.5,
xend = -0.5869,
yend = 0.0869))
## I think this looks reasonably close to the true scenario of flights in
## the tunnel but again, it all depends on how close the estimate of
## gnd_plane = 0.5 is to the correct measurement.
## With gnd_plane = 0.4 the result is...
gnd40 <- calc_vis_angle(jul_29_all_defaults,
gnd_plane = 0.4,
stim_param_pos = 0.1,
stim_param_neg = 0.1,
vertex_angle = 45,
simplify_output = TRUE)
ggplot(gnd40, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_neg_deg),
shape = 1, size = 3) +
geom_segment(aes(x = 0, ## POSITIVE SIDE FIRST
y = -0.4,
xend = 0.5869,
yend = 0.1869)) +
geom_segment(aes(x = 0, ## NEGATIVE SIDE
y = -0.4,
xend = -0.5869,
yend = 0.1869))
## this also looks reasonable.. The correct measurement is probably
## somewhere between 0.4 and 0.5.
## Either way, it's probably in our best interest to include gnd_plane
## (or whatever name we end up using) in the insert_treatments() function
## and call it automatically within calc_vis_angle so the user doesn't
## need to worry about this.
## Now coloring points by vis_angle_neg_deg
ggplot(full45, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_neg_deg),
shape = 1, size = 3)
# greater visual angles closer to negative (left) side of the tunnel
## And now for vertex_angle = 60
ggplot(full60, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_neg_deg),
shape = 1, size = 3)
# angain a subtle shift in distribution of angles
## Perhaps we're interested in the sum of the visual angles percieved by the
## bird
full45$vis_angle_sum <- full45$vis_angle_pos_deg + full45$vis_angle_neg_deg
ggplot(full45, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_sum),
shape = 1, size = 3)
# largest visual angles at the bottom of the tunnel
## Top view of the tunnel
## vis_angle_pos_deg
ggplot(full45, aes(x = position_length, y = position_width)) +
geom_point(aes(color = vis_angle_pos_deg),
shape = 1, size = 3)
## vis_angle_neg_deg
ggplot(full45, aes(x = position_length, y = position_width)) +
geom_point(aes(color = vis_angle_neg_deg),
shape = 1, size = 3)
## vis_angle_sum
ggplot(full45, aes(x = position_length, y = position_width)) +
geom_point(aes(color = vis_angle_sum),
shape = 1, size = 3)
# This view is not very helpful for displaying the sum because height is an
# important factor
############## Next Steps #############
## 1. Set gnd_plane automatically by using the distance from the bottom of the
## "V" to (0,0,0) by referencing something within rotate_tunnel().
##
## 2. Set vertex_angle and stim_param arguments from an insert_treatments()
## function elsewhere in the pipeline.
##
## ## suggestion from VBB -- maybe these two would be good to add as
## ## attributes, rather than as columns, since each is a constant and
## ## therefore it may be annoying to have them as columns running the
## ## length of the tibble? In any case, I agree -- insert_treatments()
## ## would be a very logical place to add this stuff in.
##
## ** external to calc_vis_angle - include ordientation coordinates in
## plots such that each point represents position and head orientation
##
## 3. Include head orientation to calculate visual angles based on where the
## bird is actually looking rather than assuming a fixed gaze.
## This one could take a while I'm still wrapping my head around quaternions.
##
## 4. Figure out how to visualize or otherwise use the visual angles calculated
## from these functions.
## - I believe this variable can be the nucleus with which to design
## functions that more accurately estimate optic flow by calculating how it
## changes over time in various dimensions, i.e. how it increases or
## decreases with the bird's movements.
## See rough work below where I'm trying to calculate these running changes.
## Perhaps a simple derivative function could be used rather than diff() as
## it reduces the number of data points by 1 and then can't be plotted with
## time_sec.
## Testing area for calc_vis_angle uses in optic flow calculations
expansion_pos <- diff(full45$vis_angle_pos_deg)/diff(full45$time_sec)
expansion_neg <- diff(full45$vis_angle_neg_deg)/diff(full45$time_sec)
plot(expansion_pos, expansion_neg)
ang <- diff(full45$vis_angle_pos_deg)
time <- diff(full45$time_sec)
vecsum <- sqrt(full45$position_width^2 +
full45$position_length^2 +
full45$position_height^2)
vel <- diff(vecsum)
plot(full45$time_sec, vel)
plot(full45$position_width,
full45$vis_angle_neg_deg,
col = 'red')
points(full45$position_width,
full45$vis_angle_pos_deg,
col = 'blue')
plot(full45$position_height,
full45$vis_angle_pos_deg)
product <- full45$position_height * full45$position_width
plot(product,
full45$vis_angle_pos_deg,
col = 'red')
points(product,
full45$vis_angle_neg_deg,
col = 'blue')
plot(full45$position_width,
full45$position_height)
plot(full45$frame,
full45$vis_angle_neg_deg,
col = full45$traj_id)
vbaliga/pathviewR documentation built on March 16, 2023, 4:13 p.m.
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## Last updated 2020/07/16 by ERP
########################## Not fully worked out yet
## The calc_vis_angle function references the position_width and position_height
## variables of raw motive data files and require the following arguments:
## gnd_plane - at baseline, this indicates the vertical distance
## between the bottom of the "V" and the height of the grounding tool.
## Following raw data processing using the utility functions, it must
## indicate the vertical distance between the bottom of the "V" and the
## height of the perches. An incorrect gnd_plane for a given tunnel set up
## may calculate negative visual angles (as if the bird is flying outside the
## tunnel). gnd_plane should be reported in the same units as position_width
## and position_height (typically in meters).
##
## stim_param_pos AND stim_param_neg - these reflects the
## size of the visual stimulus displayed on either side of the tunnel.
## E.g. positive screens displays 10cm wide bars: stim_param_pos = 0.1.
##
## vertex_angle - this is included in the calc_vis_angle_mod
## functions and it represents the acute angle each screen creates with a
## vertical axis. It is also equal to the angle of the "V" divided by 2.
## It's reported in degrees and is converted to radians so that it works with
## the trig functions.
##
## simplify_output - if set to TRUE, this limits output variables to
## vis_angle_pos_deg and vis_angle_neg_deg
### NOTE: Perhaps these arguments can eventually be supplied or referenced
### from within each file's metadata.
### 7.14.2020 - perhaps gnd_plane, stim_param_pos, stim_param_neg, and
### vertx_angle instead these can be referenced from the data frame itself
### after the user has used insert_treatments.
## The first several sections of this example simply run through the importing
## and cleaning pipeline to generate an object that calc_vis_angle can apply to.
##### Load packages #####
library(ggplot2)
library(magrittr)
##### Source scripts #####
## First define the directory to inspect
scripts_path <- "./R/"
## calc_vis_angle functions now included in this path
## Now list all the .R files
scripts_list <- list.files(path = scripts_path,
pattern = "*.R",
full.names = TRUE,
recursive = TRUE
)
## Using a for() loop instead of lapply() because the latter produces messages
## we don't need.
for (i in 1:length(scripts_list)) {
source(scripts_list[i])
}
##### Working with motive objects #####
# Lets try an examples using the all in one function (import_and_clean_viewr)
##### All in one function #####
jul_29_path <- './inst/extdata/pathviewr_motive_example_data.csv'
jul_29_all_defaults <-
jul_29_path %>% import_and_clean_viewr()
## or we could use the utility functions in sequence
##### Utility functions in sequence #####
## default arguments used for every step to see if the product mirrors the all
## in one function output
##### Data import #####
jul_29 <- read_motive_csv('./inst//extdata/pathviewr_motive_example_data.csv')
##### Rename axes #####
jul_29 <- relabel_viewr_axes(jul_29,
tunnel_length = "_z",
tunnel_width = "_x",
tunnel_height = "_y",
real = "_w")
##### Gather data #####
jul_29_gathered <- gather_tunnel_data(jul_29)
##### Trim outliers #####
jul_29_trimmed <- trim_tunnel_outliers(jul_29_gathered)
##### Rotate tunnel #####
jul_29_rotated <-
jul_29_trimmed %>% rotate_tunnel()
##### Select X percent #####
jul_29_selected <-
jul_29_rotated %>% select_x_percent()
##### Separate trajectories #####
jul_29_labeled <-
jul_29_selected %>% separate_trajectories()
##### Keep full trajectories #####
jul_29_full <-
jul_29_labeled %>% get_full_trajectories()
identical(jul_29_all_defaults, jul_29_full)
## curently false as import_and_clean_viewr includes velocity calculations
################ calc_vis_angle #############
## For an experiment with the ground plane set 50cm above the bottom of a 45 degree
## "V" and sine-wave gratings with a period of 10cm displayed on either side of
## the tunnel, the following arguments would be used.
## NOTE: in this case, the position of the grounding tool was unknown and
## therefore gnd_plane is estimated as the height of the perches from the base
## of the "V".
full45 <- calc_vis_angle(jul_29_all_defaults,
gnd_plane = 0.5,
stim_param_pos = 0.1,
stim_param_neg = 0.1,
vertex_angle = 45,
simplify_output = FALSE)
View(full45)
## This produces 10 additional variables in the dataframe based on the math
## internal to calc_vis_angle.
## Use simplify_output = TRUE to output only the degrees of visual angle on the
## positive and negative sides of the tunnel
simp45 <- calc_vis_angle(jul_29_all_defaults,
gnd_plane = 0.5,
stim_param_pos = 0.1,
stim_param_neg = 0.1,
vertex_angle = 45,
simplify_output = TRUE)
View(simp45)
## calc_vis_angle can accomodate different tunnel vertex angles and now
## calculates mind_dist correctly even when the bird is flying far from the
## center line.
## NOTE: This data was collected at vertex_angle = 45 so changing this argument
## is not something a user would want to do. But let's see how it affects the
## values and distribution of angles in the tunnel.
full60 <- calc_vis_angle(jul_29_all_defaults,
gnd_plane = 0.5,
stim_param_pos = 0.1,
stim_param_neg = 0.1,
vertex_angle = 60,
simplify_output = FALSE)
View(full60)
###### Visualizing the calculated angles by position in the tunnel #####
## Plot position in cross section of the tunnel and color points by
## vis_angle_pos_deg
ggplot(full45, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_pos_deg),
shape = 1, size = 3)
# greater visual angles closer to positive (right) side of the tunnel
## Now for vertex_angle = 60
ggplot(full60, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_pos_deg),
shape = 1, size = 3)
# flipping between the graphs you can see a subtle shift in the distribution of
# angles.
## In response to VBB comments:
#### _VBB_suggestions_2 #####
## These plots are awesome! Easy to make sense of them.
##
## One feature that would also be helpful would be to add a visualization of
## the tunnel itself, which would require inferring the coordinates of the
## tunnel. I think we can reasonably approximate some of this using the
## inputs from calc_vis_angle() alone.
## Here's what we assume:
## - With gnd_plane = 0.5, we assume the vertex is at -0.5 on the height
## axis. Therefore the vertex is located at (0, -0.5) for (width, height);
## ignoring length for now.
## - With vertex_angle = 45, we assume the vertex angle (duh).
## - It may not be feasible to know the height of the tunnel, i.e. where
## on the position_height axis the walls actually end. So, I suggest we
## use position_height = 0 as a first-pass approximation. Therefore, the
## two topmost points of the tunnel walls will be at (?, 0) and (-?, 0),
## for the positive and negative side, respectively (again, ignore length)
## So, with those conditions, it's time for some SohCahToa:
## For the positive side:
## tan(deg_2_rad(45/2)) = x / 0.5
## 0.5 * tan(deg_2_rad(45/2)) = x
## 0.2071068 = x
## Therefore, the topmost point on the positive side is at (0.207, 0)
## Since the tunnel is assumed symmetric about width = 0, the topmost
## point on the neg side is (-0.207,0).
## And for fun, the length of the hypotenuse, h, (i.e. the length of the
## walls themselves) is:
## cos(deg_2_rad(45/2)) = 0.5 / h
## h = 0.5 / cos(deg_2_rad(45/2))
## h = 0.5411961
## As a check:
sqrt((0.2071068 ^2) + (0.5^2)) ## equates to 0.5411961
## Also if we use the three points (two topmost and vertex), we should
## be able to back-calculate the vertex angle to confirm it is ~45
get_2d_angle(x1 = -0.2071, ## (x1, y1) is topmost on negative side
y1 = 0,
x2 = 0, ## (x2, y2) is vertex
y2 = -0.5,
x3 = 0.2071, ## (x3, y3) is topmost on positive side
y3 = 0)
## I get 44.99867, which is basically 45. So this all seems to work.
## Yoinking the vis_angle_pos_deg plot and adding walls:
ggplot(full45, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_pos_deg),
shape = 1, size = 3) +
geom_segment(aes(x = 0, ## POSITIVE SIDE FIRST
y = -0.5,
xend = 0.207,
yend = 0)) +
geom_segment(aes(x = 0, ## NEGATIVE SIDE
y = -0.5,
xend = -0.207,
yend = 0))
## Judging by this visualization, I think either the vertex angle is
## actually greater than 45 (i.e. the "V" is wider than 45deg) or the
## ground plane placement should be lower.
## Is it worth re-measuring the tunnel in lab?
## Related to all this, the information of tunnel coordinates can be
## inferred from user inputs to cal_vis_angle. I think it would be
## nice to add these coordinates in as attributes to the object. That
## way, successive pathviewr functions can make use of these info, and
## also they will be available if the user wants to add them to a plot.
## Also, do you mind if we rename gnd_plane? We are using the ground
## plane as an approximator of the vertex location. So if we are to
## make things more generic (i.e. for other users) we could opt to
## rename this as vertex_height, vertex_relative_height, or something
## along those lines?
#### ERP response ####
## I like the idea of visualizing the tunnel walls with this plot!
## gnd_plane = 0.5 is only an estimate of the true distance between
## the height of the perches and the vertex. It's definitely worth
## measuring the tunnel again to make it's accurate. I can do that
## next time I go to the lab.
## The TV model dimensions are ~ 1.46m length x 0.83m height. Angled
## at 45 degree meaning the top corners are:
0.83 * cos(pi/4) # vertical distance from (0, 0) = 0.5869m
## gnd_plane = 0.5, therefore the height is +0.0869m w.r.t the perches
0.83 * sin(pi/4) # horizontal distance from (0, 0) is also 0.5869m (duhh
## vertex_angle = 45) therefore the top corners are:
## top right = (0.5869, 0.0869)
## top left = (-0.5869, 0.0869)
## checking the angles...
get_2d_angle(x1 = -0.5869, ## (x1, y1) is topmost on negative side
y1 = 0.0869,
x2 = 0, ## (x2, y2) is vertex
y2 = -0.5,
x3 = 0.5869, ## (x3, y3) is topmost on positive side
y3 = 0.0869)
## shows the tunnel angles at 90 degree which is correct since vertex_angle is
## the angle of the "V" divided by 2 (stupid system I know but we'll chat
## about it)
## Let's plot it out again with the walls included
ggplot(full45, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_neg_deg),
shape = 1, size = 3) +
geom_segment(aes(x = 0, ## POSITIVE SIDE FIRST
y = -0.5,
xend = 0.5869,
yend = 0.0869)) +
geom_segment(aes(x = 0, ## NEGATIVE SIDE
y = -0.5,
xend = -0.5869,
yend = 0.0869))
ggplot(full45, aes(x = position_length, y = position_height)) +
geom_point(aes(color = vis_angle_pos_deg),
shape = 1, size = 3) +
geom_segment(aes(x = 0, ## POSITIVE SIDE FIRST
y = -0.5,
xend = 0.5869,
yend = 0.0869)) +
geom_segment(aes(x = 0, ## NEGATIVE SIDE
y = -0.5,
xend = -0.5869,
yend = 0.0869))
## I think this looks reasonably close to the true scenario of flights in
## the tunnel but again, it all depends on how close the estimate of
## gnd_plane = 0.5 is to the correct measurement.
## With gnd_plane = 0.4 the result is...
gnd40 <- calc_vis_angle(jul_29_all_defaults,
gnd_plane = 0.4,
stim_param_pos = 0.1,
stim_param_neg = 0.1,
vertex_angle = 45,
simplify_output = TRUE)
ggplot(gnd40, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_neg_deg),
shape = 1, size = 3) +
geom_segment(aes(x = 0, ## POSITIVE SIDE FIRST
y = -0.4,
xend = 0.5869,
yend = 0.1869)) +
geom_segment(aes(x = 0, ## NEGATIVE SIDE
y = -0.4,
xend = -0.5869,
yend = 0.1869))
## this also looks reasonable.. The correct measurement is probably
## somewhere between 0.4 and 0.5.
## Either way, it's probably in our best interest to include gnd_plane
## (or whatever name we end up using) in the insert_treatments() function
## and call it automatically within calc_vis_angle so the user doesn't
## need to worry about this.
## Now coloring points by vis_angle_neg_deg
ggplot(full45, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_neg_deg),
shape = 1, size = 3)
# greater visual angles closer to negative (left) side of the tunnel
## And now for vertex_angle = 60
ggplot(full60, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_neg_deg),
shape = 1, size = 3)
# angain a subtle shift in distribution of angles
## Perhaps we're interested in the sum of the visual angles percieved by the
## bird
full45$vis_angle_sum <- full45$vis_angle_pos_deg + full45$vis_angle_neg_deg
ggplot(full45, aes(x = position_width, y = position_height)) +
geom_point(aes(color = vis_angle_sum),
shape = 1, size = 3)
# largest visual angles at the bottom of the tunnel
## Top view of the tunnel
## vis_angle_pos_deg
ggplot(full45, aes(x = position_length, y = position_width)) +
geom_point(aes(color = vis_angle_pos_deg),
shape = 1, size = 3)
## vis_angle_neg_deg
ggplot(full45, aes(x = position_length, y = position_width)) +
geom_point(aes(color = vis_angle_neg_deg),
shape = 1, size = 3)
## vis_angle_sum
ggplot(full45, aes(x = position_length, y = position_width)) +
geom_point(aes(color = vis_angle_sum),
shape = 1, size = 3)
# This view is not very helpful for displaying the sum because height is an
# important factor
############## Next Steps #############
## 1. Set gnd_plane automatically by using the distance from the bottom of the
## "V" to (0,0,0) by referencing something within rotate_tunnel().
##
## 2. Set vertex_angle and stim_param arguments from an insert_treatments()
## function elsewhere in the pipeline.
##
## ## suggestion from VBB -- maybe these two would be good to add as
## ## attributes, rather than as columns, since each is a constant and
## ## therefore it may be annoying to have them as columns running the
## ## length of the tibble? In any case, I agree -- insert_treatments()
## ## would be a very logical place to add this stuff in.
##
## ** external to calc_vis_angle - include ordientation coordinates in
## plots such that each point represents position and head orientation
##
## 3. Include head orientation to calculate visual angles based on where the
## bird is actually looking rather than assuming a fixed gaze.
## This one could take a while I'm still wrapping my head around quaternions.
##
## 4. Figure out how to visualize or otherwise use the visual angles calculated
## from these functions.
## - I believe this variable can be the nucleus with which to design
## functions that more accurately estimate optic flow by calculating how it
## changes over time in various dimensions, i.e. how it increases or
## decreases with the bird's movements.
## See rough work below where I'm trying to calculate these running changes.
## Perhaps a simple derivative function could be used rather than diff() as
## it reduces the number of data points by 1 and then can't be plotted with
## time_sec.
## Testing area for calc_vis_angle uses in optic flow calculations
expansion_pos <- diff(full45$vis_angle_pos_deg)/diff(full45$time_sec)
expansion_neg <- diff(full45$vis_angle_neg_deg)/diff(full45$time_sec)
plot(expansion_pos, expansion_neg)
ang <- diff(full45$vis_angle_pos_deg)
time <- diff(full45$time_sec)
vecsum <- sqrt(full45$position_width^2 +
full45$position_length^2 +
full45$position_height^2)
vel <- diff(vecsum)
plot(full45$time_sec, vel)
plot(full45$position_width,
full45$vis_angle_neg_deg,
col = 'red')
points(full45$position_width,
full45$vis_angle_pos_deg,
col = 'blue')
plot(full45$position_height,
full45$vis_angle_pos_deg)
product <- full45$position_height * full45$position_width
plot(product,
full45$vis_angle_pos_deg,
col = 'red')
points(product,
full45$vis_angle_neg_deg,
col = 'blue')
plot(full45$position_width,
full45$position_height)
plot(full45$frame,
full45$vis_angle_neg_deg,
col = full45$traj_id)
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