maxent | Maximum Entropy Modeling Toolkit for Python and C | CSV Processing library
kandi X-RAY | maxent Summary
kandi X-RAY | maxent Summary
This package provides a Conditional Maximum Entropy Modeling Toolkit for Python and C++. The library is written in C++ and has been tested under various GNU/Linux, BSD, and Windows systems. The Python extension module works for Python3. The original project website hosted at homepages.inf.ed.ac.uk is long gone. Please visit the mirror courtesy of Wayback Machine for more information.
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Trending Discussions on maxent
QUESTION
I have nine raster layers (.tif) and each needs to have the same extent, resolution and CRS in order to work in Maxent. I have tried converting each layer to the same CRS and translating them to .asc format in QGIS. After that I tried to resample the layers in R to match one of the layers, but this resulted in errors, such as that the extents do not overlap. My question is how do I match all these layers in order to proceed with Maxent and also to use the 'stack' function in R?
Here is the zip-file with the rasters: https://drive.google.com/file/d/1lle95SPdQ7FyQSbFoFvmAzyuO2HUt7-L/view?usp=sharing
...ANSWER
Answered 2022-Feb-23 at 15:26So the initial problem is to set the crs using the 'crs' function from the raster package (I haven't used the new terra package yet). Then you need to reproject into the same crs. The next step is to resample the rasters so they all have the same cell resolution and size. Last you can put them in a stack. I was in a rush, so I didn't comment very well, but let me know if you have questions. The last point is the bedrock file. You'll need to use QGIS or another program to georeference it first. Try to find a map with a known projection that looks similar to it.
QUESTION
I have a plot with 5 lines that are dashed, 5 that are solid. This is correctly displaying in the plot. However, using the following code, the legend shows all line to be solid. I find this strange, because the legend is showing the correct variation in the line size, which is formatted in the same way. I tried replacing "Factorlevel" = "solid" by "Factorlevel" = 1, but this didn't work either.
Please see reproducible example below my code
...ANSWER
Answered 2021-Nov-11 at 01:14You may use theme(legend.key.size = unit(0.5, "in")) to increase size of legend, that have enough space to dashed line looks like dashed.
QUESTION
I am running this piece of code:
...ANSWER
Answered 2021-Apr-26 at 22:20You can’t smooth binary or categorical variables, only continuous ones.
You can create and interaction between a smooth and a categorical variable, and you could use random effects “smooths” for categorical variables. But you can’t just smooth binary or categorical variables. You would need to arrange for biomod to include those variables as linear factor terms. If you codes them as 0,1 then R, biomod, and mgcv will think those variables are numeric. Make sure they are coerced to be factors and then retry.
QUESTION
I'm sorry to ask the repeatedly answered question but I just couldn't solve this relating to my specific case, maybe I'm missing something. The error is E/RecyclerView: No adapter attached; skipping layout and I'm not sure, is the problem with an adapter I set or the RecyclerView per se? Also, I was following a tutorial and this was the code that was presented.
(I tried brining the initRecyclerView() into the main onCreateView but no luck. Some answers say to set an empty adapter first and notify it with the changes later but I don't know how to do that.)
This is my HomeFragment:
ANSWER
Answered 2021-Apr-14 at 10:37Ok, it's normal you have this message because in your code, you' ll do this :
QUESTION
I am trying to create a classifier using NLTK, however, I believe that I have a problem in the format of my data that I cannot get over.
My data looks like this:
...ANSWER
Answered 2021-Apr-07 at 23:22From the documentation:
train(train_toks, algorithm=None, trace=3, encoding=None, labels=None, gaussian_prior_sigma=0, **cutoffs)
Parameters train_toks (list) – Training data, represented as a list of pairs, the first member of which is a featureset, and the second of which is a classification label.
Your tuples need to have the first element be a dict that "map[s] strings to either numbers, booleans or strings" then you need to have your second element be the classification label.
QUESTION
I am running the StanfordCoreNLP server through my docker container. Now I want to access it through my python script.
Github repo I'm trying to run: https://github.com/swisscom/ai-research-keyphrase-extraction
I ran the command which gave me the following output:
...ANSWER
Answered 2020-Oct-07 at 08:08As seen in the log, your service is listening to port 9000 inside the container. However, from outside you need further information to be able to access it. Two pieces of information that you need:
- The IP address of the container
- The external port that docker exports this 9000 to the outside (by default docker does not export locally open ports).
To get the IP address you need to use docker inspect, for example via
QUESTION
I am evaluating OpenNLP for use as a document categorizer. I have a sanitized training corpus with roughly 4k files, in about 150 categories. The documents have many shared, mostly irrelevant words - but many of those words become relevant in n-grams, so I'm using the following parameters:
...ANSWER
Answered 2020-Aug-25 at 21:58Well, the answer to this one did not come from the direction in which the question was asked. It turns out that there was a code sample in the OpenNLP documentation that was wrong, and no amount of parameter tuning would have solved it. I've submitted a jira to the project so it should be resolved; but for those who make their way here before then, here's the rundown:
Documentation (wrong):
QUESTION
I have a rasterbrick containing daily time series and temperature data (summarised below). How can I create a single raster layer from this rasterbrick showing average number of days (per year) where temperature is <0?
...ANSWER
Answered 2020-Jul-09 at 00:09When asking an R question always include a minimal, self-contained, reproducible example (creating one is also the best approach to answering your own questions!). For example
QUESTION
I'm trying to tokenizer long sentences:
...ANSWER
Answered 2020-May-28 at 11:44Using tidyr + purrr gets you there. map will create a nested output which you can bring to a higher level with unnest from tidyr.
QUESTION
I'm have built a couple of species distribution models using sdm:sdm() From these I make predictions using raster::predict() and sdm::ensemble() based on widget input data in a shiny app. (Note that raster::predict() also loads the sdm package automatically if it detects a sdm object). The application works locally, but not on the server shiny.io.
I have stripped he server.R script down and added one element at the time until the error occurs, and that seems to be when either of these functions are run. The error log return
Warning: Error in <-: replacement has length zero
If I move the predict/ensemble function outside of the renderPlot() part of server.R it also returns:
Error in m[i] <- .self$whichMethod(m[i]) : replacement has length zero
I have traced this error to here but have not found anything that indicates why the app should work locally and not on the server. I tried removing all mentions of maxent models as this requires a modification of the local library by adding a maxent.jar file to the dismo/java/ folder. This did not affect anything. I have also updated all essential packages and redeployed.
The shiny script as pasted below and you'll find additional needed files here here and here.
...ANSWER
Answered 2020-May-13 at 05:51library(sdm) doesn't, like the other packages, tell the virtuell server to install it's dependencies. This package relies on a command sdm::install_all() for this. This command doesn't work in shiny, but did this instead:
Start a new R session (sdm unattached)
library(sdm)
Then do something like predict(myModel, ...)
This causes R to load all dependencies, which are then printed in the console. I added these to the top of the server.R file:
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