优化PineScript效率：数组计算与绘图性能提升求助

我写了一段Pine Script代码，用来统计RSI（14周期）四舍五入后各数值（0-100）的出现次数，再绘制对应线条。但当前代码极度冗长，运行效率极低，还经常崩溃。我知道只在最新K线计算能节省算力，但没找到实现方法。尝试用循环+数组来简化代码，但多次尝试都失败了，只能保留冗长版本。

原冗长代码 #

freq_50 = ta.cum(math.round(ta.rsi(close, 14)) == 50 ? 1 : 0)
freq_49 = ta.cum(math.round(ta.rsi(close, 14)) == 49 ? 1 : 0)
// 从100到0依次定义所有freq变量

ratio_sort = array.from(freq_100, freq_99, freq_98, freq_97, freq_96, freq_95, freq_94, freq_93, freq_92, freq_91, freq_90,
   freq_89, freq_88, freq_87, freq_86, freq_85, freq_84, freq_83, freq_82, freq_81, freq_80, freq_79, freq_78, freq_77,
   freq_76, freq_75, freq_74, freq_73, freq_72, freq_71, freq_70, freq_69, freq_68, freq_67, freq_66, freq_65, freq_64,
   freq_63, freq_62, freq_61, freq_60, freq_59, freq_58, freq_57, freq_56, freq_55, freq_54, freq_53, freq_52, freq_51,
   freq_50, freq_49, freq_48, freq_47, freq_46, freq_45, freq_44, freq_43, freq_42, freq_41, freq_40, freq_39, freq_38,
   freq_37, freq_36, freq_35, freq_34, freq_33, freq_32, freq_31, freq_30, freq_29, freq_28, freq_27, freq_26, freq_25,
   freq_24, freq_23, freq_22, freq_21, freq_20, freq_19, freq_18, freq_17, freq_16, freq_15, freq_14, freq_13, freq_12,
   freq_11, freq_10, freq_9, freq_8, freq_7, freq_6, freq_5, freq_4, freq_3, freq_2, freq_1, freq_0)
ratio_max = array.max(ratio_sort, 0)

line_50 = line.new(0, array.percentile_linear_interpolation(ratio_rank, 50), bar_index, array.percentile_linear_interpolation(ratio_rank, 50))
line.set_x1(line_50, bar_index + (math.round(ratio_max) - math.round(freq_50)))
line.set_x2(line_50, bar_index + math.round(ratio_max))
line.delete(line_50[1])

line_49 = line.new(0, array.percentile_linear_interpolation(ratio_rank, 49), bar_index, array.percentile_linear_interpolation(ratio_rank, 49))
line.set_x1(line_49, bar_index + (math.round(ratio_max) - math.round(freq_49)))
line.set_x2(line_49, bar_index + math.round(ratio_max))
line.delete(line_49[1])
// 再次从100到0依次绘制所有线条

我的尝试（无线条显示） #

lineArr = array.new_line()

ratio_max = math.max(array.percentile_linear_interpolation(ta.rsi(close, 14), 0), array.percentile_linear_interpolation(ta.rsi(close, 14), 100))

if barstate.isconfirmed
    for i = 100 to 0
        freq = ta.cum(math.round(ta.rsi(close, 14)) == i ? 1 : 0)
        line_var = line.new(bar_index, array.percentile_linear_interpolation(ta.rsi(close, 14), i), bar_index + math.round(freq), array.percentile_linear_interpolation(ta.rsi(close, 14), i))
        array.push(lineArr, line_var)

for i = 1 to array.size(lineArr) - 1
    line.delete(array.get(lineArr, i))

for i = 0 to array.size(lineArr) - 1
    line_var = array.get(lineArr, i)
    line.set_x1(line_var, bar_index)
    line.set_x2(line_var, bar_index + math.round(line.get_x2(line_var) - bar_index))

优化后的解决方案 #

//@version=5
indicator("RSI频次统计与线条绘制", overlay=false)

// 计算当前RSI四舍五入值
rsi_val = math.round(ta.rsi(close, 14))

// 初始化频次数组，存储0-100的出现次数（仅初始化一次）
var freq_array = array.new_int(101, 0)

// 仅在K线确认时更新频次，避免重复计算
if barstate.isconfirmed
    // 确保RSI值在合法范围内，防止数组越界
    if rsi_val >= 0 and rsi_val <= 100
        array.set(freq_array, rsi_val, array.get(freq_array, rsi_val) + 1)

// 计算最大频次
ratio_max = array.max(freq_array)

// 存储线条的数组，仅初始化一次
var line_array = array.new_line(101)

// 循环更新0-100对应的线条
for i = 0 to 100
    freq = array.get(freq_array, i)
    // 获取当前RSI数值对应的Y轴位置
    y_val = array.percentile_linear_interpolation(ta.rsi(close, 14), i)
    
    current_line = array.get(line_array, i)
    // 线条不存在则创建，存在则直接更新位置
    if na(current_line)
        current_line = line.new(bar_index, y_val, bar_index + math.round(freq), y_val, color=color.gray)
        array.set(line_array, i, current_line)
    else
        line.set_x1(current_line, bar_index + math.round(ratio_max - freq))
        line.set_x2(current_line, bar_index + math.round(ratio_max))

核心优化点 #

• 数组替代单独变量：用一个数组存储0-100所有RSI值的频次，彻底删除冗余的变量定义代码。
• 限制计算时机：仅在barstate.isconfirmed时更新频次，避免每根K线重复计算，大幅节省算力。
• 复用线条对象：初始化一次线条数组，后续仅更新线条位置，而非反复创建/删除线条，避免资源过载导致崩溃。
• 边界值校验：增加RSI值的范围检查，防止数组越界错误。

内容的提问来源于stack exchange，提问作者Oxelo