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https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
24e86d762a
- Updated BBWN, BBWP, CCV, CV, CVI, EWMA, GKV, HLV, HV, Jvolty, JVOLTYN, MASSI, NATR, RSV, RV, RVI, TR, UI, VOV, VR, YZV indicators with documentation links. - Added documentation links for Aberration, Acceleration Bands, Andrews' Pitchfork, Adaptive Price Zone, ATR Bands, Bollinger Bands, Center of Gravity, Donchian Channels, Decay Min-Max Channel, Detrended Synthetic Price, EACP, EBSW, HOMOD, Jurik Volatility Bands, Keltner Channel, MA Envelope, Min-Max Channel, Price Channel, Regression Channels, Standard Deviation Channel, Stoller Average Range Channel, Super Trend Bands, Ultimate Bands, Ultimate Channel, VWAP Bands, and VWAP with Standard Deviation Bands.
42 lines
1.5 KiB
Plaintext
42 lines
1.5 KiB
Plaintext
// The MIT License (MIT)
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// © mihakralj
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//@version=6
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indicator("Median", "MEDIAN", overlay=false, precision=8)
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//@function Calculates the median of a series over a lookback period.
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//@param src series float Input data series.
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//@param len simple int Lookback period (must be > 0).
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//@returns series float The median of the series over the period, or na if insufficient valid data.
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median(series float src, simple int len) =>
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if len <= 0
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runtime.error("Length must be greater than 0")
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var array<float> values_in_window = array.new_float(0)
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array.clear(values_in_window) // Clear from previous bar's calculation
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for i = 0 to len - 1
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val = src[i]
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if not na(val)
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array.push(values_in_window, val)
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int n = array.size(values_in_window)
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float result = na
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if n > 0
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array.sort(values_in_window) // Sort the array
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if n % 2 == 1 // Odd number of elements
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result := array.get(values_in_window, n / 2)
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else // Even number of elements
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float mid1 = array.get(values_in_window, n / 2 - 1)
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float mid2 = array.get(values_in_window, n / 2)
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result := (mid1 + mid2) / 2.0
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result
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// ---------- Main loop ----------
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// Inputs
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i_source = input.source(close, "Source")
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i_length = input.int(14, "Period", minval=1)
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// Calculation
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median_value = median(i_source, i_length)
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// Plot
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plot(median_value, "Median", color=color.new(color.orange, 0, color=color.yellow, linewidth=2), linewidth=2)
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