如何在Julia中将多维数组传递到函数中？_Julia

如何在Julia中将多维数组传递到函数中？

julia

如何在Julia中将多维数组传递到函数中？,julia,Julia,我仍在学习语言Julia，但是，我正在编写一个种群模型，描述100个蚊子亚种群的动态。我有很多不同的函数，但我认为错误在于传递给我的主函数 xf = XLSX.readxlsx("C:/Scriptie_mosquitoes/knmi_csv.xlsx") sh = xf["knmi_csv"] temperature = sh["B3:B368"] precip = sh["F3:F368"] subpopulation_amount = 100 imat_list = zeros(subp

我仍在学习语言Julia，但是，我正在编写一个种群模型，描述100个蚊子亚种群的动态。我有很多不同的函数，但我认为错误在于传递给我的主函数

xf = XLSX.readxlsx("C:/Scriptie_mosquitoes/knmi_csv.xlsx")
sh = xf["knmi_csv"]
temperature = sh["B3:B368"]
precip = sh["F3:F368"]

subpopulation_amount = 100
imat_list = zeros(subpopulation_amount,length(temperature))
adul_list = zeros(subpopulation_amount,length(temperature))
egg_list = zeros(subpopulation_amount,length(temperature))
diaegg_list = zeros(subpopulation_amount,length(temperature))

imat_list[1] = 100.0
adul_list[1] = 1000.0
egg_list[1] = 100.0
diaegg_list[1] = 100.0

for counter = 1:subpopulation_amount
    u = Normal()
    temp_change = rand(u)
    tempa = temperature .+ temp_change

    e = Normal()
    precip_change = rand(e)

    main(counter,tempa,precip,precip_change,imat_list[:],adul_list[:],egg_list[:],diaegg_list[:])
end

这是显示的错误

julia> for counter = 1:subpopulation_amount
           u = Normal()
           temp_change = rand(u)
           tempa = temperature .+ temp_change
               e = Normal()
                   precip_change = rand(e)
           main(counter,tempa,precip,precip_change,imat_list,adul_list,egg_list,diaegg_list)
           end
ERROR: UndefVarError: Point2f0 not defined
Stacktrace:
 [1] newImmaturetoAdult(::Float64) at .\REPL[1137]:9
 [2] main(::Int64, ::Array{Float64,2}, ::Array{Any,2}, ::Float64, ::Array{Float64,2}, ::Array{Float64,2}, ::Array{Float64,2}, ::Array{Float64,2}) at .\REPL[1158]:10
 [3] top-level scope at .\REPL[1187]:7

如果你们愿意帮助我，我将非常感激。任何事都能帮上忙。谢谢

我也将在下面添加整个代码

using Statistics
using Plots
using JuliaDB
using XLSX
using Distributions
using Random

# Possible struct for climaticfactors per day
struct Climaticfactors
    temperature
    precipiation
    evaporation
    photoperiod
end

# First function written, describes the development rate of larvae to adults. on Temperature
# function developRate(temp)
#     # function 
#     develop = (-1/225)*(temp-25)^2+1

#     # Check if development is not negative 
#     if develop < 0 
#         develop = 0 
#         return develop
#     else 
#         return develop
#     end
# end

# Linear segments between the data points. The function finds the percentage of larvae growing up on temperature
function newImmaturetoAdult(temp)
    # Data point from literature 
    x = [5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0]
    y = [0.0, 0.0, 50.0, 77.5, 76.3, 67.5, 2.5, 0.0]

    # Loop that goes through all possible temperatures
    for i in 1:length(x)-1

        # If in the temperature falls between a segment find that point
        if temp >= x[i] && temp <= x[i+1]
            a = LineSegment(Point2f0(x[i], y[i]), Point2f0(x[i+1], y[i+1]))
            b = LineSegment(Point2f0(temp,0.0),Point2f0(temp,100.0))
            j = intersects(a,b)
            c = j[2]

            # Returning the percentage  
            return c[2]

        # Temperatures do nothing 
        elseif temp>40.0 || temp<5.0
            return 0.0 
        end
    end
end

# Same technique as before but with egg to larvae on temperature
function eggtolarvea(temp)

    # Data from literature 
    x = [5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0]
    y = [4.4, 4.0, 8.2, 66.9, 49.2, 51.4, 10, 0.0]
    for i in 1:(length(x)-1)
        if temp >= x[i] && temp <= x[i+1]
            a = LineSegment(Point2f0(x[i], y[i]), Point2f0(x[i+1], y[i+1]))
            b = LineSegment(Point2f0(temp,0.0),Point2f0(temp,100.0))
            j = intersects(a,b)
            c = j[2]
            return c[2]

        elseif temp>40.0 || temp<5.0
            return 0.0 
        end
    end
end

# function humidityindex(temp, precip...)
#     moist_effect = 0
#     temp_effect = 0 
#     for i in 1:size(precip)
#         moist_effect += ((precip[i]/100) * (1-(i/10)))
#         temp_effect -= ((temp[i]/25) * (1-(i/10)))
#     end

#     effect = temp_effect + moist_effect
#     return effect 
# end  

function diapauserate(day)
    y = 0.045*day - 10.75
end 

# Egg_population dynamics 
function eggpop(hatch,effect,diarate,egg_pop, adult_pop)
    # if eggs don't hatch do nothing
    if hatch == 0 
        egg_pop *= 0.8
    end

    if effect > 0
        tot = adult_pop * 10
        dia_pop = tot * diarate
        egg_pop = tot - dia_pop
    else 
        tot = adult_pop * 4
        dia_pop = tot * diarate
        egg_pop = tot - dia_pop
    end 

    return dia_pop, egg_pop
end

# Larvae population dynamics 
function immaturepop(develop_rate, hatch, immature_pop, egg_pop)
    # Hatch encreases larvae population 
    if hatch == 0 
        change = immature_pop * develop_rate 
        immature_pop -= change
    else 
        change = immature_pop * develop_rate 
        immature_pop -= change
        immature_pop += egg_pop * hatch
    end

    return immature_pop
end

# Adult population dynamics
function adultpop(develop_rate,immature_pop,adult_pop)
    # New adults 
    change = immature_pop * develop_rate
    adult_pop = adult_pop + change
    # Survival of 80%
    adult_pop *= 0.95
    return adult_pop
end

# Main 
function main(counter,temperature,precip, precip_change,imat_list,adul_list,egg_list,diaegg_list)
    # Iterating through temperature data (year)
    for i in 2:1:length(temperature);
        # Only from 10 march to 30 september mosquito season, otherwise diapause 
        if i >= 69 && i <= 273;
            # temperatures in 1 degrees celcius 
            temp = temperature[i] / 10;

            # Development and hatch values in 0.02 values 
            develop = newImmaturetoAdult(temp) / 100;
            # println(develop)
            hatch = eggtolarvea(temp) / 100;
            # println(hatch)
            # Moist_index
            evap = collect(1:1:7);
            precipi = collect(1:1:7);

            for j in 1:7
                t = temperature[-j+i];
                evap[j]= t;
                p = precip[-j+i];
                precipi[j] = p;
            end

            moist_effect = 0;
            temp_effect = 0; 
            for h in 1:length(precipi)
                moist_effect += ((precipi[h]/100.0) * (1.0-(h/10.0)));
                temp_effect -= ((evap[h]/200.0) * (1.0-(h/10.0)));
            end
            effect = temp_effect + moist_effect + precip_change;  

            if diapauserate(i) <= 0
                diarate = 0 ;
            elseif diapauserate(i) >= 1  
                diarate = 1; 
            else 
                diarate = diapauserate(i);
            end

            egg = eggpop(hatch,effect,diarate, egg_list[counter,i-1],adul_list[counter,i-1]);
            egg_list[counter, i] = egg[2]
            diaegg_list[counter, i] = egg[1]
            # Changing and adding eggpop

            # Changing and adding immature pop
            ima = immaturepop(develop, hatch, imat_list[counter,i], egg_list[counter,i-1]);
            imat_list[counter,i] = ima

            # Changing and adding adult pop
            adu = adultpop(develop, imat_list[counter,i-1], adul_list[counter,i]);
            adul_list[counter,i] = adu

        # from 30 september keep egg_level the same but larvae and adult decreasing 
        elseif i > 273 && i < 365
            egg_list[counter,i] = egg_list[counter,i-1]/1.1
            diaegg_list[counter,i] = diaegg_list[counter,i-1]
            imat_list[counter,i] = imat_list[counter,i-1]/1.1
            adul_list[counter,i] = adul_list[counter,i-1]/1.1

        else i > 0 && i < 69
            egg_list[counter,i] = egg_list[counter,i-1]
            diaegg_list[counter,i] = diaegg_list[counter,i-1]
            imat_list[counter,i] = imat_list[counter,i-1]
            adul_list[counter,i] = adul_list[counter,i-1]
        end

    end
end

# using Distributions, Random 
# Random.seed!(123)
# td = Truncated(Normal(0, 0.05),-5,5)
# x = rand(td, 10000000)'

# using Distributions
# using Random
# Random.seed!(123)
# d = Normal()
# x = rand(d, 100)

# Importing KNMI data 
xf = XLSX.readxlsx("C:/Scriptie_mosquitoes/knmi_csv.xlsx")
sh = xf["knmi_csv"]
temperature = sh["B3:B368"]
precip = sh["F3:F368"]

# Starting values 
# imat_list = collect(1.0:1:length(temperature));
# adul_list = collect(1.0:1:length(temperature));
# egg_list = collect(1.0:1:length(temperature));
# diaegg_list = collect(1.0:1:length(temperature));

subpopulation_amount = 100

imat_list = zeros(subpopulation_amount,length(temperature))
adul_list = zeros(subpopulation_amount,length(temperature))
egg_list = zeros(subpopulation_amount,length(temperature))
diaegg_list = zeros(subpopulation_amount,length(temperature))

imat_list[1] = 100.0
adul_list[1] = 1000.0
egg_list[1] = 100.0
diaegg_list[1] = 100.0

for counter = 1:subpopulation_amount
    u = Normal()
    temp_change = rand(u)
    tempa = temperature .+ temp_change

    e = Normal()
    precip_change = rand(e)

    main(counter,tempa,precip,precip_change,imat_list,adul_list,egg_list,diaegg_list)
end



# # Visualizing 
# populaties = [imat_list, adul_list]
# x = 1:1:length(temperature)
# p1 = plot(x,populaties, title= "Populatie niveaus", label = ["ImmaturePopulatie" "AdultPopulatie"], lw = 3)
# plot(p1)
# # plot(x,egg_list, title="Egg population")

# egg_popu = [egg_list, diaegg_list]
# p2 = plot(x,egg_popu, title="Egg populations", label=["Eggpop" "DiaeggPop"])

# plot(p1,p2, layout=(2,1), legend=true)

使用统计信息
使用绘图
使用JuliaDB
使用XLSX
使用分布
使用随机
#每日气候因子的可能结构
结构气候因子
温度
沉淀
蒸发
光周期
结束
#首先写函数，描述幼虫到成虫的发育速度。在温度上
#功能开发（临时）
##功能
#发展=（-1/225）*（temp-25）^2+1
##检查发展是否为负
#如果发展<0
#发展=0
#回归发展
#否则
#回归发展
#结束
#结束
#数据点之间的直线段。该函数用于查找在温度下生长的幼虫的百分比
函数newImagentoDult（温度）
#资料来源于文献
x=[5.0,10.0,15.0,20.0,25.0,30.0,35.0,40.0]
y=[0.0,0.0,50.0,77.5,76.3,67.5,2.5,0.0]
#通过所有可能温度的回路
对于1中的i：长度（x）-1
#如果温度在一段之间下降，找到该点
如果temp>=x[i]&&temp 40.0 | | temp=x[i]&&temp 40.0 | | temp您忘记导入定义Point2f0
的包：
using GeometryTypes

顺便说一句，您的struct
s应具有字段类型-由于性能原因，切勿使用非类型的struct
s
此外，要生成正态分布的数字，请使用randn（）。
还值得注意的是，在定义分布参数（如Normal（）
）时，只需执行一次即可，然后即可重用对象。
您忘记导入定义Point2f0
的包：
using GeometryTypes

顺便说一句，您的struct
s应具有字段类型-由于性能原因，切勿使用非类型的struct
s
此外，要生成正态分布的数字，请使用randn（）。
还值得注意的是，在定义分布参数（如Normal（）
时，只需执行一次即可，然后即可重用对象。
感谢您的回答！添加“使用几何类型”后，最后一个问题得到了解决。然而，现在我有一个错误，我不知道如何修复```谢谢你的回答！添加“使用几何类型”后，最后一个问题得到了解决。然而，现在我有一个错误，我不知道如何修复```