//@version=5

indicator('Linear Regression Channel', overlay = true, max_lines_count = 3)

// ---------------------------------------------------------------------------------------------------------------------}

// 𝙐𝙎𝙀𝙍 𝙄𝙉𝙋𝙐𝙏𝙎

// ---------------------------------------------------------------------------------------------------------------------{

bool bands      = input.bool(true, "Plot Linear Regression Bands", group = "Settings Bands")

int window      = input.int(150, "Length", group = "Settings Bands")

float devlen_b  = input.float(3., "Deviation Linear Regression Bands",step=0.1, group = "Settings Bands")

bool channel    = input.bool(false, "Plot Linear Regression Channel", group = "Settings Channel")

int window1     = input.int(150, "Channel Length", group = "Settings Channel")

float devlen1   = input.float(1., "Deviation Linear Regression Channel",step=0.1, group = "Settings Channel")

bool channel1   = input.bool(false, "Plot Future Projection of linear regression", group = "Future Projection Channel")

bool arr_dirc   = input.bool(false, "Plot Arrow Direction", group = "Future Projection Channel")

int window2     = input.int(50, "Length", group = "Future Projection Channel")

float devlen2   = input.float(1., "Deviation Future Projection Regression Channel",step=0.1, group = "Future Projection Channel")

// Define colors for up, down, and mid lines

color col_dn      = #f01313

color col_up      = color.aqua

color col_mid     = color.yellow

color gray        = color.gray

color fg_col      = chart.fg_color

// Regression Channel Arrays Line

var reglines  = array.new_line(3)

var reglines_ = array.new_line(3)

// ---------------------------------------------------------------------------------------------------------------------}

// 𝙄𝙉𝘿𝙄𝘾𝘼𝙏𝙊𝙍 𝘾𝘼𝙇𝘾𝙐𝙇𝘼𝙏𝙄𝙊𝙉𝙎

// ---------------------------------------------------------------------------------------------------------------------{

//@function linear_regression

//@description Calculates linear regression coefficients for a given source and window.

//@param src  (series float) The data series on which linear regression is calculated.

//@param window  (int) The number of bars to use in the calculation.

//@returns the intercept slope, Deviation, end of the channel.

linear_regression(src, window) =>

    sum_x = 0.0

    sum_y = 0.0

    sum_xy = 0.0

    sum_x_sq = 0.0

    // Calculate sums

    for i = 0 to window - 1 by 1

        sum_x += i + 1

        sum_y += src[i]

        sum_xy += (i + 1) * src[i]

        sum_x_sq += math.pow(i + 1, 2)

    // Calculate linear regression coefficients

    slope     = (window * sum_xy - sum_x * sum_y) / (window * sum_x_sq - math.pow(sum_x, 2))

    intercept = (sum_y - slope * sum_x) / window

    y1 = intercept  + slope * (window - 1)

    dev = 0.0

    for i = 0 to window - 1

        dev := dev + math.pow(src[i] - (slope * (window - i) + intercept), 2)

    dev := math.sqrt(dev/window)

    [intercept, y1, dev, slope]

[y2, y1, dev, slope] = linear_regression(close, window)

[y2_, y1_, dev_, slope_] = linear_regression(close, window1)

[y2__, y1__, dev__, slope__] = linear_regression(close, window2)

// Linear Regression Channel Lines

series float mid     = y2 + slope

series float upper   = mid  + ta.rma(high - low, window) * devlen_b

series float lower   = mid  - ta.rma(high - low, window) * devlen_b

// Returns True for window length period

isAllowed = (last_bar_index - bar_index < window1)

// ---------------------------------------------------------------------------------------------------------------------}

// 𝙑𝙄𝙎𝙐𝘼𝙇𝙄𝙕𝘼𝙏𝙄𝙊𝙉

// ---------------------------------------------------------------------------------------------------------------------{

// Plot upper, lower, and mid lines if channel is not enabled

p_u = plot(upper, color = bands and channel ? na : bands ? gray : na, linewidth = 2)

p_l = plot(lower, color = bands and channel ? na : bands ? gray : na, linewidth = 2)

p_m = plot(mid,   color = bands and channel ? na : bands ? gray : na)

// Fill areas between upper/mid and lower/mid lines

fill(p_u, p_m, mid, upper, na, bands and channel ? na : bands ? color.new(col_up, 80) : na)

fill(p_m, p_l, lower, mid,     bands and channel ? na : bands ? color.new(col_dn, 80) : na, na)

if barstate.islast and channel

    for i = 0 to 2

        array.set(reglines, i,

             line.new(x1 = bar_index - (window1 - 1),

                     y1 = y1_ + dev_ * devlen1 * (i - 1),

                     x2 = bar_index,

                     y2 = y2_ + dev_ * devlen1 * (i - 1),

                     color = color.gray,

                     style = i % 2 == 1 ? line.style_dashed : line.style_solid,

                     width = 2,

                     extend = extend.none)

                     )

    linefill.new(array.get(reglines, 1), array.get(reglines, 2), color = color.new(col_up, 90))

    linefill.new(array.get(reglines, 1), array.get(reglines, 0), color = color.new(col_dn, 90))

if barstate.islast and channel1

    for i = 0 to 2

        array.set(reglines_, i,

             line.new(x1 = bar_index - (window2 - 1),

                     y1 = y1__ + dev__ * devlen2 * (i - 1),

                     x2 = bar_index,

                     y2 = y2__ + dev__ * devlen2 * (i - 1),

                     color = color.gray,

                     style = i % 2 == 1 ? line.style_dotted : line.style_dashed,

                     width = 1,

                     extend = extend.right)

                     )              

    linefill.new(array.get(reglines_, 1), array.get(reglines_, 2), color = color.new(col_up, 95))

    linefill.new(array.get(reglines_, 1), array.get(reglines_, 0), color = color.new(col_dn, 95))

if arr_dirc

    l1 = label.new(chart.point.from_index(bar_index, hl2 > y2__ ? high : low),

             text = hl2 > y2__ ? "⇗" : hl2 < y2__ ? "⇘" : "⇒",

             textcolor = hl2 > y2__ ? col_up : hl2 < y2__ ? col_dn : gray,

             color = color(na),

             size = size.huge,

             style =  label.style_label_left

             )    

    label.delete(l1[1])

// Bar Heat Map

b_c = (close - lower) / (upper - lower)

b_c := b_c > 1 ? 1 : b_c < 0 ? 0 : b_c

bar_color = channel ?

     (isAllowed ?

         (b_c <= 0.5 ? color.from_gradient(b_c, 0, 0.5, col_up, col_mid) : color.from_gradient(b_c, 0.5, 1, col_mid, col_dn))

         : na)

     : (b_c >= 0.5 ? color.from_gradient(b_c, 0.5, 1, col_mid, col_up) : color.from_gradient(b_c, 0, 0.5, col_dn, col_mid))

plotcandle(open, high, low, close,

             title = "Bar HeatMap",

               color = bar_color,

                 wickcolor = bar_color,

                  bordercolor = bar_color

                     )

barcolor(bar_color)

// Conditions for crossovers

condition1 = bands and channel ? na : bands ? ta.pivotlow(3, 3) and close < lower : na

condition2 = bands and channel ? na : bands ? ta.pivothigh(3, 3) and close > upper: na

// Plot markers for channel break outs

plotchar(condition1, "", "◆", size=size.tiny, location=location.belowbar, color = col_up)

plotchar(condition2, "", "◆", size=size.tiny, location=location.abovebar, color = col_dn)

// ---------------------------------------------------------------------------------------------------------------------}