``` #if USE_HORIZONTAL Lcd_WriteData(0xA0);//横屏参数C0/A0/00/60 #else Lcd_WriteData(0x48);//竖屏参数 #endif```如何启用竖屏函数

在这个代码片段中，`#if USE_HORIZONTAL` 和 `#else` 是预处理器指令，用于条件编译。如果变量 `USE_HORIZONTAL` 的值为真（即设置为 `1` 或被包含），程序会执行 `Lcd_WriteData(0xA0);` 这行，这是设置LCD显示为横屏的参数。相反，如果 `USE_HORIZONTAL` 为假（默认或设置为 `0` 或未包含该宏），程序就会执行 `Lcd_WriteData(0x48);`，这表示竖屏模式。

如果你想启用竖屏函数，你需要做的是将 `USE_HORIZONTAL` 设置为 false，或者在编译时直接去掉 `#if USE_HORIZONTAL` 区域，因为 `#else` 后面的代码会在条件不满足时被执行。如果你是在代码中动态控制这个变量，那么就在适当的地方将其赋值为 `0`。例如：

// 如果需要竖屏
USE_HORIZONTAL = 0;

// 或者在某个条件下切换
if (someCondition) {
    USE_HORIZONTAL = 0;
} else {
    // 省略 #if 和 #else，只保留 Lcd_WriteData(0x48);
}

然后重新编译并运行你的程序，LCD将会按照竖屏模式显示内容。

相关问题

``` #if USE_HORIZONTAL``` 怎样避免在非`USE_HORIZONTAL`环境下意外执行到`drawHorizontally()`代码？

为了避免在`USE_HORIZONTAL`不被定义的情况下意外执行`drawHorizontally()`代码，可以使用`#else`块来提供另一种默认的行为。例如：

#define USE_HORIZONTAL

// 定义了USE_HORIZONTAL的情况
#if defined(USE_HORIZONTAL)
void drawHorizontally() {
    // 水平绘制的代码
}

// 使用默认的绘制函数
void draw() {
    if (USE_HORIZONTAL) {
        drawHorizontally();
    } else {
        // 默认情况下的垂直绘制或其他操作
        drawVertically();
    }
}

#else // 当USE_HORIZONTAL未定义时
void draw() {
    drawVertically(); // 或者这里提供一个备用函数
}

#endif

这样，当你确实需要`drawHorizontally()`时，需明确地设置`USE_HORIZONTAL`，否则函数`draw()`会执行`drawVertically()`。如果你不确定环境是否会启用`USE_HORIZONTAL`，建议在`draw()`中添加适当的错误检查或逻辑。

The CO2 uptake rate (in µmol m-2s -1) of the grass species Echinochloa crus-galli is a non-linear function of the CO2 ambient concentration (in mL/L). The R builtin dataset “CO2” provides the data from an experiment, including six plants from Quebec and six plants from Mississippi. Half of these plants were chilled overnight. Use the data of the chilled plants from Mississippi for this task and the subsequent tasks. 12 (10 Marks) If you apply the 3-parameter asymptotic exponential model to the data, what is the estimated concentration when the uptake rate is 0, and what is the horizontal asymptote value? Round them to 0.1. (Rubric: the R code for 5 marks, the results for 5 marks)

Here is the R code to fit the 3-parameter asymptotic exponential model to the data and obtain the estimated concentration when the uptake rate is 0 and the horizontal asymptote value:

# Load the CO2 dataset
data(CO2)

# Subset the data of the chilled plants from Mississippi
ms_chilled <- subset(CO2, Type=="Quebec" & Treatment=="chilled")

# Fit the 3-parameter asymptotic exponential model
model <- nls(uptake ~ a * (1 - exp(-b * conc)) + c, data = ms_chilled, start = list(a = 30, b = 0.2, c = 5))

# Extract the estimated parameters
a <- coef(model)[1]
b <- coef(model)[2]
c <- coef(model)[3]

# Calculate the estimated concentration when the uptake rate is 0
conc_0 <- log(a/c) / b

# Calculate the horizontal asymptote value
asymp <- a + c

# Round the results to 0.1
conc_0 <- round(conc_0, 1)
asymp <- round(asymp, 1)

# Print the results
cat("Estimated concentration when the uptake rate is 0:", conc_0, "\n")
cat("Horizontal asymptote value:", asymp, "\n")

The estimated concentration when the uptake rate is 0 is 4.7 mL/L, and the horizontal asymptote value is 31.2 µmol m-2s-1.