soil | friendly Agent-based Social Simulator

Sorry for the messy codebase. I am new to C++.

I'm trying to tie a loop and function together. (1) A moisture sensor and (2) a servo to turn a lever on and off based on moisture.

I'm receiving an error that 'servo' cannot be used as a function. I've tried changing servo to some other name. I'm not using servo anywhere else, such as a variable, so that doesn't seem like the issue.

Does anyone have any other advice?

I want to add a column days to a dataset with some conditions. For each soil there should be nine rows in the days column. The first two rows (0 and 4) should be the value from the SS Period. The value for the days 10-66 should be the N in Period and the ES in Period should be the last days.

This is a very bad explanation I know, but I think perhaps it makes sense by looking at the expected_df dataset.

All help is very much appreciated!

can someone help me to detect the issue of my searchbox. I made a searchbox in javascript that proofs the input with a defined keyword list. If a word is matching, then the "HARMI-SOIL 8.0/15 Result Box" should show up, if it does not match the Result Box should stay hidden (display:none).

My Issue is that after typing in a matching word and klicking enter, the Result Box does not show up. Javascript tells me the word are not matching, even though they should. Just when I click on the cross (x) and deleting the input the Result Box shows up and Javascript tells me the words are matching. I am grateful about any hint. Thank you very much!

I am trying to parse a JSON response. I cannot use the VBA-JSON library. I need to check to see if a nested array is empty or null. I keep getting this error:

Example JSON:

When I enter 4, it shows Living_room2 not defined, how can I let it jump to another def form first def.Code is below, appreciate if you can help.

So, for room_attic, how can I let option A show different things when you have a different condition, like, when you have cheese you can throw in it when you have a ball of string, you can use it, and then come back two different results. And how to make an option one time, like after you pick up the ball of string, and when you go back to def_living room, it will not show again string information.

I'm displaying linear regression models in plots using the ggpmisc package. I only want the regression line, p-value and r2-value to be showed in the plot if the p-value is less than 0.2. @Ricardo Semião e Castro helped me (thanks!) with a great code, however it only works sometimes. Whether it works or not depends on the number of regression models that meet the P<0.2 criteria. Any ideas as how to make the code so that it works both when 0, 1 or 2 models have P-values below P?

Here is the code:

So I have this code and it should check if the value in the column: friction_number is above 1 than it should print "gravel" for all the cells in which thats the case. I tried working with functions but then the order couldn't be the way it needs to be. my code:

So I have a point cloud or a 3D grid, each grid contains the following data (features/attributes): Grid type (building, tree, grass, soil, or blank). But then space type "Buildings" has sub-attributes such as conductivity and reflective values. Besides, the attributes of the cells there are a couple of individual other attributes that apply to the whole data set, examples of these attributes are wind speed, temperature,....etc. I would like to know what Deep learning algorithm would be helpful to predict the values of air temperature in each grid cell (in the x, y direction only) based on the 3d attributes I explained above. Also, what would be the best way to prepare a pipeline for this?. The goal is to predict air temperate values when I feed the trained model a data set that has geometric model info, the wind direction, and the wind speed)

Here is an example image of 300 images I have ( have the images, and I have a data set of all the attributes of each grid cell, and the air temperature value). The image is modeled inside a cube of 60x60x60 cells, when a cell contains a building the space type is set to a "building", when a cell has air the space type is set to "blank" and so on...., as I mentioned, each "building" cell contains additional sub-attributes. The values I'm trying to predict are values of air temperature at each BLANK cell (around buildings) at an x,y plane (let's say at height z=2), in this image, the x,y plane is the colored plane. I have the values in numbers, not just colored planes.

Also here is a small portion of the data I have and the results (y values = air temp).