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library(mosaicCalc)

## Loading required package: mosaic

## Registered S3 method overwritten by 'mosaic':
##   method                           from   
##   fortify.SpatialPolygonsDataFrame ggplot2

## 
## The 'mosaic' package masks several functions from core packages in order to add 
## additional features.  The original behavior of these functions should not be affected by this.

## 
## Attaching package: 'mosaic'

## The following objects are masked from 'package:dplyr':
## 
##     count, do, tally

## The following object is masked from 'package:Matrix':
## 
##     mean

## The following object is masked from 'package:ggplot2':
## 
##     stat

## The following objects are masked from 'package:stats':
## 
##     binom.test, cor, cor.test, cov, fivenum, IQR, median, prop.test,
##     quantile, sd, t.test, var

## The following objects are masked from 'package:base':
## 
##     max, mean, min, prod, range, sample, sum

## Loading required package: mosaicCore

## 
## Attaching package: 'mosaicCore'

## The following objects are masked from 'package:dplyr':
## 
##     count, tally

## 
## Attaching package: 'mosaicCalc'

## The following object is masked from 'package:stats':
## 
##     D

slice_plot(3 * x^2 - 4 ~ x, domain(x = range(-10, 10)))

library(mosaicCalc)
m = 1
b = 20
slice_plot(m * x + b ~ x, domain(x = range(0, 10)))

perubahan dari kode program bisa kita lkukan dengan merubah nilai variabel m, variabel m bisa diisi dengan nol maka bisa menentukan grafik tersebut lurus atau stabil contoh

library (mosaicCalc)
m = 1
b = 2
slice_plot(m * x^3 + b ~ x, domain(x = range(-10, 10)))

library(mosaicCalc)
A = 100
slice_plot( A * x ^ 2 ~ x, domain(x = range(-2, 3)))

A = 5
slice_plot( A * x ^ 2 ~ x,  domain(x = range(0, 3)),  color="red" )

slice_plot( cos(t) ~ t, domain(t = range(0,4*pi) ))

library(mosaicCalc)
g  <- makeFun(2*x^2 - 5*x + 2 ~ x)
slice_plot(g(x) ~ x , domain(x = range(-2, 3)))

g(x = 2)

## [1] 0

## [1] 0
g(x = 5)

## [1] 27

## [1] 27

library(mosaicCalc)
g(x = 2)

## [1] 0

## [1] 0
g(x = 5)

## [1] 27

## [1] 27

Housing= read.csv("http://www.mosaic-web.org/go/datasets/Income-Housing.csv")
Housing

##   Income IncomePercentile CrimeProblem AbandonedBuildings IncompleteBathroom
## 1   3914                5         39.6               12.6                2.6
## 2  10817               15         32.4               10.0                3.3
## 3  21097               30         26.7                7.1                2.3
## 4  34548               50         23.9                4.1                2.1
## 5  51941               70         21.4                2.3                2.4
## 6  72079               90         19.9                1.2                2.0
##   NoCentralHeat ExposedWires AirConditioning TwoBathrooms MotorVehicle
## 1          32.3          5.5            52.3         13.9         57.3
## 2          34.7          5.0            55.4         16.9         82.1
## 3          28.1          2.4            61.7         24.8         91.7
## 4          21.4          2.1            69.8         39.6         97.0
## 5          14.9          1.4            73.9         51.2         98.0
## 6           9.6          1.0            76.7         73.2         99.0
##   TwoVehicles ClothesWasher ClothesDryer Dishwasher Telephone
## 1        17.3          57.8         37.5       16.5      68.7
## 2        34.3          61.4         38.0       16.0      79.7
## 3        56.4          78.6         62.0       25.8      90.8
## 4        75.3          84.4         75.2       41.6      96.5
## 5        86.6          92.8         88.9       58.2      98.3
## 6        92.9          97.1         95.6       79.7      99.5
##   DoctorVisitsUnder7 DoctorVisits7To18 NoDoctorVisitUnder7 NoDoctorVisit7To18
## 1                3.6               2.6                13.7               31.2
## 2                3.7               2.6                14.9               32.0
## 3                3.6               2.1                13.8               31.4
## 4                4.0               2.3                10.4               27.3
## 5                4.0               2.5                 7.7               23.9
## 6                4.7               3.1                 5.3               17.5

Housing [1: 3,1:5,]

##   Income IncomePercentile CrimeProblem AbandonedBuildings IncompleteBathroom
## 1   3914                5         39.6               12.6                2.6
## 2  10817               15         32.4               10.0                3.3
## 3  21097               30         26.7                7.1                2.3

Housing$IncomePercentile

## [1]  5 15 30 50 70 90

names(Housing)

##  [1] "Income"              "IncomePercentile"    "CrimeProblem"       
##  [4] "AbandonedBuildings"  "IncompleteBathroom"  "NoCentralHeat"      
##  [7] "ExposedWires"        "AirConditioning"     "TwoBathrooms"       
## [10] "MotorVehicle"        "TwoVehicles"         "ClothesWasher"      
## [13] "ClothesDryer"        "Dishwasher"          "Telephone"          
## [16] "DoctorVisitsUnder7"  "DoctorVisits7To18"   "NoDoctorVisitUnder7"
## [19] "NoDoctorVisit7To18"

gf_point(ClothesDryer ~ NoDoctorVisitUnder7, data = Housing )

gf_point(ClothesDryer ~ ClothesDryer, data = Housing )

gf_point( 
  CrimeProblem ~ Income, data=Housing ) %>%
  slice_plot(
     40 - Income/2000 ~ Income, color = "red")

gf_point( 
  CrimeProblem ~ Income, data=Housing ) %>%
  slice_plot(
    55 - Income/2000 ~ Income, color = "blue")

gf_point( 
 AbandonedBuildings ~ Income, data=Housing ) %>%
  slice_plot(
    15 - Income/2500 ~ Income, color = "purple")

gf_point( 
  ClothesDryer ~ NoDoctorVisitUnder7, data = Housing) %>%
  slice_plot(
    15 - Income/2000 ~ Income, color = "green")

gf_point( 
  NoCentralHeat ~ Income, data = Housing) %>%
  slice_plot(
    75 - Income/2000 ~ Income, color = "yellow")

contour_plot(
  sin(2*pi*t/10) ~ t & x, 
  domain(t = range(0,20), x = range(0,10)))

## Warning in contour_plot(sin(2 * pi * t/10) ~ t & x, domain(t = range(0, : No
## dependence of function on y variable. Contour labels may be misplaced.

contour_plot(
  sin(4*pi*t/32)*exp(-.4*x) ~ t & x, 
  domain(t = range(0,15), x = range(0,10)))

contour_plot( 
  sin(2*pi*t/10)*exp(-.2*x) ~ t & x, 
  domain(t=0:20, x=0:10))

interactive_plot(
   sin(2*pi*t/10)*exp(-.5*x) ~ t & x, 
   domain(t = 0:20, x = 0:10))

DAFTAR PUSTAKA

https://dtkaplan.github.io/RforCalculus/index.html?fbclid=IwAR1d_WcAeawvUaBnLKlkRoO2sV4b-6nRX0eNR3DT457DKN7NJV8NV0giSLo

bab2 Fungsi grafik

2022-09-27

Including Plots