ChlouisPy / matplotlib_candlestick

This script allow you to create custom Matplotlib candlestick graph

matplotlib_candlestick

This script allow you to create custom Matplotlib candlestick graph

How to use:

• First you must import candlestick.py

import candlestick

There is two function in this program:

• create_color_config():

  This function allow you to create your custom candlestick. There are multiples arguments on this function

  • name (required): str: The name of your candlestick style

  • red: str: the color of the candle when it decreases (hexadecimal color RGBA or RGB as str)

  • green: str: the color of the candle when it increases (hexadecimal color RGBA or RGB as str)

  • border_increase: str: the color of the boarder when candle increase (hexadecimal color RGBA or RGB as str)

  • border_decrease: str: the color of the boarder when candle decrease (hexadecimal color RGBA or RGB as str)

  • wick_increase: str: the color of the wick when candle increase (hexadecimal color RGBA or RGB as str)

  • wick_decrease: str: the color of the wick when candle decrease (hexadecimal color RGBA or RGB as str)

  • alpha: float: transparency of the candle

  • border_width: float: the width of the boarder

  • candle_width: float: the width of the candle

  • wick_width: float: the with of the wick

• plot_candle():

  This function get you Matplotlib plot and add all candles. There are multiples arguments on this function

  • ax (required): Your matplotlib ax
  • stock_data (required): np.array: an array of shape (n, 4) or (n, 5) for axis=0 and (4, n) or (5, n) for axis=1
  • config_name: str: the name of the candlestick style
  • axis: int: the type on array you use 1 or 0 (base is 0)

• How to use plot_candle()

  This function has two input possibles for stock_data and to type on axis:

  axis=0

  • Input of shape (n, 4):

    stock_data = np.array([
                          [open0, high0, low0, close0],
                          [open1, high1, low1, close1],
                          [open2, high2, low2, close2],
                          ...
                          [openX, highX, lowX, closeX]
                          ])

    In this case the index in n correspond to the horizontal axis value on the plot
    
    

  • Input os shape (n, 5):

    stock_data = np.array([
                          [0, open0, high0, low0, close0],
                          [1, open1, high1, low1, close1],
                          [2, open2, high2, low2, close2],
                          ...
                          [X, openX, highX, lowX, closeX]
                          ])

    In this case the value X will correspond to the horizontal axis value on the plot
    
    

    axis=1

    stock_data = np.array([
                            [open0, open1, open2, ... openX],
                            [high0, high1, high2, ... highX],
                            [low0, low1, low2, ... lowX],
                            [close0, close1, close2, ... closeX],
                            [0, 1, 2, ... X],
                          ])

    or

    stock_data = np.array([
                          [open0, open1, open2, ... openX],
                          [high0, high1, high2, ... highX],
                          [low0, low1, low2, ... lowX],
                          [close0, close1, close2, ... closeX],
                        ])

• Style already in candlestick.py:

• base

• Hollow

• Simple

• Black

• Requirement:

• library (version that i use)

• Matplotlib (3.3.3)

• Numpy (1.18.0)

• Credit:

• ChlouisPy