Function plots data with ggplot2 geom_line. Plot is returned as ggplot faced grid and is optimized for saving as facet, paginated PDF file.
mc_plot_line(
data,
filename = NULL,
sensors = NULL,
scale_coeff = NULL,
png_width = 1900,
png_height = 1900,
start_crop = NULL,
end_crop = NULL,
use_utc = TRUE,
localities = NULL,
facet = "locality",
color_by_logger = FALSE,
tag = NULL
)myClim object see myClim-package
output file name/path with the extension - supported formats are .pdf and .png (default NULL)
If NULL then the plot is displayed and can be returned into r environment but is not saved to file.
names of sensors; if NULL then all (default NULL) see names(mc_data_sensors)
scale coefficient for secondary axis (default NULL)
width for png output (default 1900)
height for png output (default 1900)
POSIXct datetime in UTC for crop data (default NULL)
POSIXct datetime in UTC for crop data (default NULL)
if FALSE, then the time shift from tz_offset metadata is used to correct
(shift) the output time-series (default TRUE)
In the Agg-format myClim object use_utc = FALSE is allowed only for steps shorter than one day. In myClim
the day nd longer time steps are defined by the midnight, but this represent whole day, week, month, year...
shifting daily, weekly, monthly... data (shift midnight) does not make sense in our opinion.
But when user need more flexibility, then myClim Raw-format
can be used, In Raw-format use_utc is not limited, user can shift an data without the restrictions.
See myClim-package
names of localities; if NULL then all (default NULL)
possible values (NULL, "locality", "physical")
facet = "locality" each locality is plotted (default)
in separate plot in R and separate row in PDF if filename.pdf is provided.
facet = "physical" sensors with identical physical (see mc_data_physical) are grouped together across localities.
facet = NULL, all localities and sensors (max 2 physicals, see details) are plotted in single plot
If TRUE, the color is assigned by logger to differentiate individual loggers (random colors) if false, the color is assigned by physical. (default FALSE)
hilight states with selected tag. (default NULL)
ggplot2 object
Saving as the PDF file is recommended, because the plot is optimized
to be paginate PDF (facet line plot is distributed to pages), each locality can be
represented by separate plot (facet = "locality") default, which is especially useful
for bigger data. When facet = NULL then single plot is returned showing all localities together.
When facet = physical sensors with identical physical units are grouped together across localities.
Maximal number of physical units (elements) of sensors to be plotted in one
plot is two. First element is related to primary and second to secondary y axis.
In case, there are multiple sensors with identical physical on one locality,
they are plotted together for facet = "locality" e.g., when you have
TMS_T1, TMS_T2, TMS_T3, Thermo_T, and VWC you get plot with 5 lines of different colors and
two y axes. Secondary y axes are scaled with calculation values * scale_coeff.
If scaling coefficient is NULL than function try to detects scale coefficient from
physical unit of sensors see mc_Physical. Scaling is useful when
plotting together e.g. temperature and moisture. For native myClim loggers
(TOMST, HOBO U-23) scaling coefficients are pre-defined.
For other cases when plotting two physicals together,
it is better to set scaling coefficients by hand.
tms.plot <- mc_filter(mc_data_example_agg, localities = "A6W79")
p <- mc_plot_line(tms.plot,sensors = c("TMS_T3","TMS_T1","TMS_moist"))
p <- p+ggplot2::scale_x_datetime(date_breaks = "1 week", date_labels = "%W")
p <- p+ggplot2::xlab("week")
p <- p+ggplot2::scale_color_manual(values=c("hotpink","pink", "darkblue"),name=NULL)
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.