this.scatterPlot
时间: 2023-10-06 13:14:56 浏览: 36
根据提供的引用内容,this.scatterPlot是一个ScatterPlotList类的实例。ScatterPlotList是从IPlottable接口继承而来的。在这个类中,通过定时器的触发,将数据添加到Values数组中,并且使用SignalPlot将数据绘制在formsPlot1上。同时,使用timer2定时渲染图形,根据需要调整坐标轴的范围。
相关问题
使用R语言解决问题compute a LDA,draw a 2D scatterplot of the first two LDF coordinates, and color-code the points by wine type.what do you notice
Sure, I can help you with that. To compute a LDA in R, we can use the `lda()` function from the `MASS` package. Here's an example code:
``` r
# Load the required packages
library(MASS)
library(ggplot2)
# Load the wine dataset
data(wine)
# Fit the LDA model
lda.fit <- lda(Type ~ ., data = wine)
# Extract the first two LDA coordinates
lda.coords <- predict(lda.fit)$x[, 1:2]
# Create a new dataframe with the LDA coordinates and wine types
lda.df <- data.frame(lda.coords, Type = wine$Type)
# Draw a scatterplot with color-coded points
ggplot(lda.df, aes(x = LD1, y = LD2, color = Type)) +
geom_point() +
labs(x = "LD1", y = "LD2", color = "Wine Type")
```
This code fits a LDA model to the wine dataset and extracts the first two LDA coordinates. It then creates a new dataframe with the LDA coordinates and wine types, and draws a scatterplot of the LDA coordinates with color-coded points.
What we notice from the plot is that the two wine types (Type 1 and Type 2) can be separated quite well by the LDA coordinates. The points of each wine type form a distinct cluster, and there is some overlap between the two clusters. The LD1 axis appears to be primarily responsible for separating the two wine types, while the LD2 axis captures some additional variation within each wine type.
seaborn has no attribute scatt
This error usually occurs when you try to call an attribute or function that does not exist in the Seaborn library. In this case, it seems like you are trying to call the attribute "scatt", which does not exist in Seaborn.
Perhaps you meant to use the attribute "scatterplot"? This is a commonly used attribute in Seaborn for creating scatter plots. You can use it like this:
```python
import seaborn as sns
import matplotlib.pyplot as plt
# Create a scatter plot using Seaborn
tips = sns.load_dataset("tips")
sns.scatterplot(x="total_bill", y="tip", data=tips)
# Show the plot
plt.show()
```
This code will create a scatter plot using Seaborn by plotting the `total_bill` column on the x-axis and the `tip` column on the y-axis using the `scatterplot` attribute.