ratify | Hapi plugin for validating the schema of path query | REST library
kandi X-RAY | ratify Summary
kandi X-RAY | ratify Summary
A Hapi plugin for validating the schema of path, query, request body, and response body params using JSON-schema
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QUESTION
What I want to do is combining a few different raster files of crop harvest (e.g. for soybean and maize) into one map. The legend should show two different colors for the crops. The data I will be using is this crop map data: http://www.earthstat.org/harvested-area-yield-175-crops/
But first I am trying to do this on a sample data set:
...ANSWER
Answered 2020-Nov-27 at 22:58It's not clear how you would like to combine these, though it would be straightforward to convert them to data frames to plot in ggplot:
QUESTION
I have the following reclassify & ratified rasters that I am trying to intercept/overlay/overlap to get a new one. The idea is to get a new overlayed raster from the interception areas of the rasters R1 and R2. Once done this, I would do zonal operations. Here the R1, R2, ED rasters.
...ANSWER
Answered 2020-Jan-13 at 04:40I think the answer in not clear at all, though I also think you already have the answer. Perhaps your main issue here is that you are working with relative large datasets and you do not manage to see what is going on at every stage.
So for the sake of simplicity I propose a smaller instance of your problem. Notice that when asking in stackoverflow this approach may be more useful to get help. As a matter of fact your files may be too heavey to download and use in some computers, avoiding people to get involved.
But let's go to the code.
QUESTION
All the files for this question are in the following git:
I am trying to plot a categorical map in leaflet with a categorical legend showing a character vector as labels:
Load the packagesfirst I load the required packages
...ANSWER
Answered 2019-Nov-30 at 15:14You can achieve that by exploiting the labFormat argument of addLegend.
The trick is using a transform function within labFormat to re-map the IDs of the RAT to the corresponding labels.
Something like this seems to work:
QUESTION
I have a raster in .tif format which I am trying to visualize in R using levelplot. Here is what I have done so far:
...ANSWER
Answered 2019-Nov-21 at 01:09Well, this is a bit tricky! First thing is loading raster and lattice libraries and then using lattice::levelplot for plotting categorical raster. However, you should be using rasterVis::levelplot for this purpose.
QUESTION
participated in the review for their constructive contributions, and to the international organizations. He urged them to continue to show solidarity with C™te dÕIvoire. In closing, he said that, more than ever, C™te dÕIvoire needed their support in order to attain its objectives ahead of 2020.
*II. Conclusions and/or recommendations*
127. The recommendations listed below enjoy the support of C™te dÕIvoire:
127.1 Consider the accession to core human rights instruments (Lesotho); and to other main international human rights treaties that it is not yet a party to (Philippines);
127.2 Make efforts towards the ratification of the OP-CAT (Chile);
127.3 Ratify the OP-CAT (Ghana, Tunisia), as recommended previously in 2009 (Czech Republic) and take policy measures to prevent torture and ill-treatment (Estonia);
ANSWER
Answered 2019-Nov-14 at 16:10text <- "participated in the review for their constructive contributions, and to the international organizations. He urged them to continue to show solidarity with C™te dÕIvoire. In closing, he said that, more than ever, C™te dÕIvoire needed their support in order to attain its objectives ahead of 2020.
*II. Conclusions and/or recommendations*
127. The recommendations listed below enjoy the support of C™te dÕIvoire:
127.1 Consider the accession to core human rights instruments (Lesotho); and to other main international human rights treaties that it is not yet a party to (Philippines);
127.2 Make efforts towards the ratification of the OP-CAT (Chile);
127.3 Ratify the OP-CAT (Ghana, Tunisia), as recommended previously in 2009 (Czech Republic) and take policy measures to prevent torture and ill-treatment (Estonia);"
QUESTION
I am parsing semi-structured text documents (sec filings) using beautifulsoup. The table I am looking for looks like this:
...ANSWER
Answered 2019-Jul-30 at 06:55You can use pandas to get it:
QUESTION
I would like to add some arrows to a categorical raster plot. Using Base R (on a non-ratified raster) as an example:
...ANSWER
Answered 2019-Jun-03 at 18:49You can solve it with layer and panel.arrows:
QUESTION
I have a RandomForest model trained with the caret package that contains both numeric and categorical predictors. I am attempting to use this trained model to make predictions on a new dataset that is a rasterStack containing one layer for each predictor. I have converted the categorical raster layer to a factor using the ratify function in the raster package, as well as added character strings corresponding to the training set syntax by adding a raster attribute table (RAT), but when I predict I am getting the following error:
ANSWER
Answered 2018-Feb-02 at 14:46The factor RasterLayer (Attribute Layer) seems to be (or be handled like) an ordered factor. So you just have to train the model with an ordered vector. You can achieve this changing one line:
QUESTION
I have received a .tif file alongside a .qml file containing information about the colour for each value (e.g. forest is green, clouds are black).
...ANSWER
Answered 2017-Oct-15 at 22:04I have committed changes in the code to solve this issue. Please, try the development version of the package:
QUESTION
I have a question similar to this one from 2014, which was answered but the datasets are no longer available and our original data structures differ. (I'm in crunch time and stumped, so if you're able to respond quickly I would greatly appreciate it!!)
Goal: use the type of bedrock as a covariate in a Point Process Model (ppm) in spatstat with mine locations in Connecticut.
Data: the files are available from this Dropbox folder. The rock data and CT poly outline comes from UConn Magic Library, and the mine data comes from the USGS Mineral Resources Data System.
Approach: I loaded some relevant packages and read in the shapefiles (and converted coords to match CT's system), and used the CT polygon as an owin object.
...ANSWER
Answered 2017-Apr-30 at 08:05Looking at your code you don't seem to be providing the field argument to rasterize.
From rasterize help:
fieldnumeric or character. The value(s) to be transferred. This can be a single number, or a vector of numbers that has the same length as the number of spatial features (points, lines, polygons). If x is a Spatial*DataFrame, this can be the column name of the variable to be transferred. If missing, the attribute index is used (i.e. numbers from 1 to the number of features). You can also provide a vector with the same length as the number of spatial features, or a matrix where the number of rows matches the number of spatial features
at this line:
litho1rast<-rasterize(litho1,ctmask)
you probably have to specify which column of the litho object to use in rasterization. Something like:
litho1rast<-rasterize(litho1,ctmask, field = "LITHO1")
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