关于k Line Chart (k线图)

K Line Chart

python实现k线图的代码，之前找过matplotlib中文文档但是画k线图的finance方法已经弃用了。所以自己在网上搜寻一下加上改编，很好的实现出k线图，

代码如下：__main__

# conding:utf-8
# 导入聚宽函数库
from jqdatasdk import *
import pandas as pd
import matplotlib.pyplot as plt
from KLineChart.mpl_finance import plt_KLineChart
import os

'''
:param fields 字符串list, 默认是None(表示['open', 'close', 'high', 'low', 'volume', 'money']这几个标准字段),
      支持以下属性 ['open', 'close', 'low', 'high', 'volume', 'money', 'factor', 'high_limit', 'low_limit', 'avg', 'pre_close', 'paused']
:param skip_paused 是否跳过不交易日期
'''
auth('your ID','your password')

fields = ['open', 'close', 'high', 'low', 'volume', 'money']
stock_code = ['600519.XSHG','000001.XSHE','IC9999.CCFX']
data = get_price(stock_code,start_date='2018-1-1',end_date='2018-8-29',frequency='1d',fields=fields,skip_paused=False)
k,m,n = data.shape
# print(k,m,n)
for i in range(n):
    Data = data.iloc[:,:,i]
    plt_KLineChart(Data,stock_code[i],step=20,fontSize=14)
plt.show()

# 数据保存
# os.mkdir('data/中国银行.xlsx')
# data.to_excel(r'./data/中国银行.xlsx')
# sql.to_excel()
# print(data.shape)

这下我们需要导入自定义函数：from mpl_finance import plt_KLineChart

"""
A collection of functions for analyzing and plotting
financial data.   User contributions welcome!
"""
from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors as mcolors
from matplotlib.collections import LineCollection, PolyCollection
from matplotlib.lines import TICKLEFT, TICKRIGHT, Line2D
from matplotlib.patches import Rectangle
from matplotlib.transforms import Affine2D

from six.moves import xrange, zip

def plot_day_summary_oclh(ax, quotes, ticksize=3,
                          colorup='k', colordown='r'):
    """Plots day summary
        Represent the time, open, close, high, low as a vertical line
        ranging from low to high.  The left tick is the open and the right
        tick is the close.
    Parameters
    ----------
    ax : `Axes`
        an `Axes` instance to plot to
    quotes : sequence of (time, open, close, high, low, ...) sequences
        data to plot.  time must be in float date format - see date2num
    ticksize : int
        open/close tick marker in points
    colorup : color
        the color of the lines where close >= open
    colordown : color
        the color of the lines where close <  open
    Returns
    -------
    lines : list
        list of tuples of the lines added (one tuple per quote)
    """
    return _plot_day_summary(ax, quotes, ticksize=ticksize,
                             colorup=colorup, colordown=colordown,
                             ochl=True)

def plot_day_summary_ohlc(ax, quotes, ticksize=3,
                          colorup='k', colordown='r'):
    """Plots day summary
        Represent the time, open, high, low, close as a vertical line
        ranging from low to high.  The left tick is the open and the right
        tick is the close.
    Parameters
    ----------
    ax : `Axes`
        an `Axes` instance to plot to
    quotes : sequence of (time, open, high, low, close, ...) sequences
        data to plot.  time must be in float date format - see date2num
    ticksize : int
        open/close tick marker in points
    colorup : color
        the color of the lines where close >= open
    colordown : color
        the color of the lines where close <  open
    Returns
    -------
    lines : list
        list of tuples of the lines added (one tuple per quote)
    """
    return _plot_day_summary(ax, quotes, ticksize=ticksize,
                             colorup=colorup, colordown=colordown,
                             ochl=False)

def _plot_day_summary(ax, quotes, ticksize=3,
                      colorup='k', colordown='r',
                      ochl=True):
    """Plots day summary
        Represent the time, open, high, low, close as a vertical line
        ranging from low to high.  The left tick is the open and the right
        tick is the close.
    Parameters
    ----------
    ax : `Axes`
        an `Axes` instance to plot to
    quotes : sequence of quote sequences
        data to plot.  time must be in float date format - see date2num
        (time, open, high, low, close, ...) vs
        (time, open, close, high, low, ...)
        set by `ochl`
    ticksize : int
        open/close tick marker in points
    colorup : color
        the color of the lines where close >= open
    colordown : color
        the color of the lines where close <  open
    ochl: bool
        argument to select between ochl and ohlc ordering of quotes
    Returns
    -------
    lines : list
        list of tuples of the lines added (one tuple per quote)
    """
    # unfortunately this has a different return type than plot_day_summary2_*
    lines = []
    for q in quotes:
        if ochl:
            t, open, close, high, low = q[:5]
        else:
            t, open, high, low, close = q[:5]

        if close >= open:
            color = colorup
        else:
            color = colordown

        vline = Line2D(xdata=(t, t), ydata=(low, high),
                       color=color,
                       antialiased=False,  # no need to antialias vert lines
                       )

        oline = Line2D(xdata=(t, t), ydata=(open, open),
                       color=color,
                       antialiased=False,
                       marker=TICKLEFT,
                       markersize=ticksize,
                       )

        cline = Line2D(xdata=(t, t), ydata=(close, close),
                       color=color,
                       antialiased=False,
                       markersize=ticksize,
                       marker=TICKRIGHT)

        lines.extend((vline, oline, cline))
        ax.add_line(vline)
        ax.add_line(oline)
        ax.add_line(cline)

    ax.autoscale_view()

    return lines

def candlestick_ochl(ax, quotes, width=0.2, colorup='k', colordown='r',
                     alpha=1.0):
    """
    Plot the time, open, close, high, low as a vertical line ranging
    from low to high.  Use a rectangular bar to represent the
    open-close span.  If close >= open, use colorup to color the bar,
    otherwise use colordown
    Parameters
    ----------
    ax : `Axes`
        an Axes instance to plot to
    quotes : sequence of (time, open, close, high, low, ...) sequences
        As long as the first 5 elements are these values,
        the record can be as long as you want (e.g., it may store volume).
        time must be in float days format - see date2num
    width : float
        fraction of a day for the rectangle width
    colorup : color
        the color of the rectangle where close >= open
    colordown : color
         the color of the rectangle where close <  open
    alpha : float
        the rectangle alpha level
    Returns
    -------
    ret : tuple
        returns (lines, patches) where lines is a list of lines
        added and patches is a list of the rectangle patches added
    """
    return _candlestick(ax, quotes, width=width, colorup=colorup,
                        colordown=colordown,
                        alpha=alpha, ochl=True)

def plt_KLineChart(data,stockCode,step=20,fontSize=13,figsize=(12,6)):

    '''
    :param data: type for DataFrame
    :param stockCode: stock code
    :param step: xticks step
    :param fontSize: font size
    :param figsize: window size
    :return:
    '''

    prices = data[['open', 'high', 'low', 'close']]

    fig = plt.figure(figsize=figsize)
    ax = fig.add_axes([0.06, 0.15, 0.9, 0.75])   # margin_left margin_bottom width height
    candlestick_ohlc(ax, prices, width=0.5, colorup='r', colordown='b')

    dataIndex = [str(i).split(' ')[0] for i in data.iloc[::step, :].index]
    location = list(range(0,len(data.iloc[:,0]),step))
    plt.xticks(location,dataIndex,rotation=45)

    font_size = {'size': fontSize}
    plt.ylabel('prices',font_size)
    plt.title('stock：%s'%(stockCode),font_size)
    plt.rcParams['font.sans-serif'] = ['SimHei']  # 设置字体为SimHei显示中文
    plt.rcParams['axes.unicode_minus'] = False  # 设置正常显示符号

def candlestick_ohlc(ax, quotes, width=0.2, colorup='k', colordown='r',
                     alpha=1.0):
    """
    Plot the time, open, high, low, close as a vertical line ranging
    from low to high.  Use a rectangular bar to represent the
    open-close span.  If close >= open, use colorup to color the bar,
    otherwise use colordown
    Parameters
    ----------
    ax : `Axes`
        an Axes instance to plot to
    quotes : sequence of (time, open, high, low, close, ...) sequences
        As long as the first 5 elements are these values,
        the record can be as long as you want (e.g., it may store volume).
        time must be in float days format - see date2num
    width : float
        fraction of a day for the rectangle width
    colorup : color
        the color of the rectangle where close >= open
    colordown : color
         the color of the rectangle where close <  open
    alpha : float
        the rectangle alpha level
    Returns
    -------
    ret : tuple
        returns (lines, patches) where lines is a list of lines
        added and patches is a list of the rectangle patches added
    """
    return _candlestick(ax, quotes, width=width, colorup=colorup,
                        colordown=colordown,
                        alpha=alpha, ochl=False)

def _candlestick(ax, quotes, width=0.2, colorup='k', colordown='r',
                 alpha=1.0, ochl=True):
    """
    Plot the time, open, high, low, close as a vertical line ranging
    from low to high.  Use a rectangular bar to represent the
    open-close span.  If close >= open, use colorup to color the bar,
    otherwise use colordown
    Parameters
    ----------
    ax : `Axes`
        an Axes instance to plot to
    quotes : sequence of quote sequences
        data to plot.  time must be in float date format - see date2num
        (time, open, high, low, close, ...) vs
        (time, open, close, high, low, ...)
        set by `ochl`
    width : float
        fraction of a day for the rectangle width
    colorup : color
        the color of the rectangle where close >= open
    colordown : color
         the color of the rectangle where close <  open
    alpha : float
        the rectangle alpha level
    ochl: bool
        argument to select between ochl and ohlc ordering of quotes
    Returns
    -------
    ret : tuple
        returns (lines, patches) where lines is a list of lines
        added and patches is a list of the rectangle patches added
    """

    OFFSET = width / 2.0

    lines = []
    patches = []
    quotes = np.column_stack([list(range(len(quotes))), quotes])
    for q in quotes:
        if ochl:
            t, open, close, high, low = q[:5]
        else:
            t, open, high, low, close = q[:5]

        if close >= open:
            color = colorup
            lower = open
            height = close - open
        else:
            color = colordown
            lower = close
            height = open - close

        vline = Line2D(
            xdata=(t, t), ydata=(low, high),
            color=color,
            linewidth=0.5,
            antialiased=True,
        )

        rect = Rectangle(
            xy=(t - OFFSET, lower),
            width=width,
            height=height,
            facecolor=color,
            edgecolor=color,
        )
        rect.set_alpha(alpha)

        lines.append(vline)
        patches.append(rect)
        ax.add_line(vline)
        ax.add_patch(rect)
    ax.autoscale_view()

    return lines, patches

def _check_input(opens, closes, highs, lows, miss=-1):
    """Checks that *opens*, *highs*, *lows* and *closes* have the same length.
    NOTE: this code assumes if any value open, high, low, close is
    missing (*-1*) they all are missing
    Parameters
    ----------
    ax : `Axes`
        an Axes instance to plot to
    opens : sequence
        sequence of opening values
    highs : sequence
        sequence of high values
    lows : sequence
        sequence of low values
    closes : sequence
        sequence of closing values
    miss : int
        identifier of the missing data
    Raises
    ------
    ValueError
        if the input sequences don't have the same length
    """

    def _missing(sequence, miss=-1):
        """Returns the index in *sequence* of the missing data, identified by
        *miss*
        Parameters
        ----------
        sequence :
            sequence to evaluate
        miss :
            identifier of the missing data
        Returns
        -------
        where_miss: numpy.ndarray
            indices of the missing data
        """
        return np.where(np.array(sequence) == miss)[0]

    same_length = len(opens) == len(highs) == len(lows) == len(closes)
    _missopens = _missing(opens)
    same_missing = ((_missopens == _missing(highs)).all() and
                    (_missopens == _missing(lows)).all() and
                    (_missopens == _missing(closes)).all())

    if not (same_length and same_missing):
        msg = ("*opens*, *highs*, *lows* and *closes* must have the same"
               " length. NOTE: this code assumes if any value open, high,"
               " low, close is missing (*-1*) they all must be missing.")
        raise ValueError(msg)

def plot_day_summary2_ochl(ax, opens, closes, highs, lows, ticksize=4,
                           colorup='k', colordown='r'):
    """Represent the time, open, close, high, low,  as a vertical line
    ranging from low to high.  The left tick is the open and the right
    tick is the close.
    Parameters
    ----------
    ax : `Axes`
        an Axes instance to plot to
    opens : sequence
        sequence of opening values
    closes : sequence
        sequence of closing values
    highs : sequence
        sequence of high values
    lows : sequence
        sequence of low values
    ticksize : int
        size of open and close ticks in points
    colorup : color
        the color of the lines where close >= open
    colordown : color
         the color of the lines where close <  open
    Returns
    -------
    ret : list
        a list of lines added to the axes
    """

    return plot_day_summary2_ohlc(ax, opens, highs, lows, closes, ticksize,
                                  colorup, colordown)

def plot_day_summary2_ohlc(ax, opens, highs, lows, closes, ticksize=4,
                           colorup='k', colordown='r'):
    """Represent the time, open, high, low, close as a vertical line
    ranging from low to high.  The left tick is the open and the right
    tick is the close.
    *opens*, *highs*, *lows* and *closes* must have the same length.
    NOTE: this code assumes if any value open, high, low, close is
    missing (*-1*) they all are missing
    Parameters
    ----------
    ax : `Axes`
        an Axes instance to plot to
    opens : sequence
        sequence of opening values
    highs : sequence
        sequence of high values
    lows : sequence
        sequence of low values
    closes : sequence
        sequence of closing values
    ticksize : int
        size of open and close ticks in points
    colorup : color
        the color of the lines where close >= open
    colordown : color
         the color of the lines where close <  open
    Returns
    -------
    ret : list
        a list of lines added to the axes
    """

    _check_input(opens, highs, lows, closes)

    rangeSegments = [((i, low), (i, high)) for i, low, high in
                     zip(xrange(len(lows)), lows, highs) if low != -1]

    # the ticks will be from ticksize to 0 in points at the origin and
    # we'll translate these to the i, close location
    openSegments = [((-ticksize, 0), (0, 0))]

    # the ticks will be from 0 to ticksize in points at the origin and
    # we'll translate these to the i, close location
    closeSegments = [((0, 0), (ticksize, 0))]

    offsetsOpen = [(i, open) for i, open in
                   zip(xrange(len(opens)), opens) if open != -1]

    offsetsClose = [(i, close) for i, close in
                    zip(xrange(len(closes)), closes) if close != -1]

    scale = ax.figure.dpi * (1.0 / 72.0)

    tickTransform = Affine2D().scale(scale, 0.0)

    colorup = mcolors.to_rgba(colorup)
    colordown = mcolors.to_rgba(colordown)
    colord = {True: colorup, False: colordown}
    colors = [colord[open < close] for open, close in
              zip(opens, closes) if open != -1 and close != -1]

    useAA = 0,  # use tuple here
    lw = 1,  # and here
    rangeCollection = LineCollection(rangeSegments,
                                     colors=colors,
                                     linewidths=lw,
                                     antialiaseds=useAA,
                                     )

    openCollection = LineCollection(openSegments,
                                    colors=colors,
                                    antialiaseds=useAA,
                                    linewidths=lw,
                                    offsets=offsetsOpen,
                                    transOffset=ax.transData,
                                    )
    openCollection.set_transform(tickTransform)

    closeCollection = LineCollection(closeSegments,
                                     colors=colors,
                                     antialiaseds=useAA,
                                     linewidths=lw,
                                     offsets=offsetsClose,
                                     transOffset=ax.transData,
                                     )
    closeCollection.set_transform(tickTransform)

    minpy, maxx = (0, len(rangeSegments))
    miny = min([low for low in lows if low != -1])
    maxy = max([high for high in highs if high != -1])
    corners = (minpy, miny), (maxx, maxy)
    ax.update_datalim(corners)
    ax.autoscale_view()

    # add these last
    ax.add_collection(rangeCollection)
    ax.add_collection(openCollection)
    ax.add_collection(closeCollection)
    return rangeCollection, openCollection, closeCollection

def candlestick2_ochl(ax, opens, closes, highs, lows, width=4,
                      colorup='k', colordown='r',
                      alpha=0.75):
    """Represent the open, close as a bar line and high low range as a
    vertical line.
    Preserves the original argument order.
    Parameters
    ----------
    ax : `Axes`
        an Axes instance to plot to
    opens : sequence
        sequence of opening values
    closes : sequence
        sequence of closing values
    highs : sequence
        sequence of high values
    lows : sequence
        sequence of low values
    width : int
        size of open and close ticks in points
    colorup : color
        the color of the lines where close >= open
    colordown : color
        the color of the lines where close <  open
    alpha : float
        bar transparency
    Returns
    -------
    ret : tuple
        (lineCollection, barCollection)
    """

    return candlestick2_ohlc(ax, opens, highs, lows, closes, width=width,
                             colorup=colorup, colordown=colordown,
                             alpha=alpha)

def candlestick2_ohlc(ax, opens, highs, lows, closes, width=4,
                      colorup='k', colordown='r',
                      alpha=0.75):
    """Represent the open, close as a bar line and high low range as a
    vertical line.
    NOTE: this code assumes if any value open, low, high, close is
    missing they all are missing
    Parameters
    ----------
    ax : `Axes`
        an Axes instance to plot to
    opens : sequence
        sequence of opening values
    highs : sequence
        sequence of high values
    lows : sequence
        sequence of low values
    closes : sequence
        sequence of closing values
    width : int
        size of open and close ticks in points
    colorup : color
        the color of the lines where close >= open
    colordown : color
        the color of the lines where close <  open
    alpha : float
        bar transparency
    Returns
    -------
    ret : tuple
        (lineCollection, barCollection)
    """

    _check_input(opens, highs, lows, closes)

    delta = width / 2.
    barVerts = [((i - delta, open),
                 (i - delta, close),
                 (i + delta, close),
                 (i + delta, open))
                for i, open, close in zip(xrange(len(opens)), opens, closes)
                if open != -1 and close != -1]

    rangeSegments = [((i, low), (i, high))
                     for i, low, high in zip(xrange(len(lows)), lows, highs)
                     if low != -1]

    colorup = mcolors.to_rgba(colorup, alpha)
    colordown = mcolors.to_rgba(colordown, alpha)
    colord = {True: colorup, False: colordown}
    colors = [colord[open < close]
              for open, close in zip(opens, closes)
              if open != -1 and close != -1]

    useAA = 0,  # use tuple here
    lw = 0.5,  # and here
    rangeCollection = LineCollection(rangeSegments,
                                     colors=colors,
                                     linewidths=lw,
                                     antialiaseds=useAA,
                                     )

    barCollection = PolyCollection(barVerts,
                                   facecolors=colors,
                                   edgecolors=colors,
                                   antialiaseds=useAA,
                                   linewidths=lw,
                                   )

    minx, maxx = 0, len(rangeSegments)
    miny = min([low for low in lows if low != -1])
    maxy = max([high for high in highs if high != -1])

    corners = (minx, miny), (maxx, maxy)
    ax.update_datalim(corners)
    ax.autoscale_view()

    # add these last
    ax.add_collection(rangeCollection)
    ax.add_collection(barCollection)
    return rangeCollection, barCollection

def volume_overlay(ax, opens, closes, volumes,
                   colorup='k', colordown='r',
                   width=4, alpha=1.0):
    """Add a volume overlay to the current axes.  The opens and closes
    are used to determine the color of the bar.  -1 is missing.  If a
    value is missing on one it must be missing on all
    Parameters
    ----------
    ax : `Axes`
        an Axes instance to plot to
    opens : sequence
        a sequence of opens
    closes : sequence
        a sequence of closes
    volumes : sequence
        a sequence of volumes
    width : int
        the bar width in points
    colorup : color
        the color of the lines where close >= open
    colordown : color
        the color of the lines where close <  open
    alpha : float
        bar transparency
    Returns
    -------
    ret : `barCollection`
        The `barrCollection` added to the axes
    """

    colorup = mcolors.to_rgba(colorup, alpha)
    colordown = mcolors.to_rgba(colordown, alpha)
    colord = {True: colorup, False: colordown}
    colors = [colord[open < close]
              for open, close in zip(opens, closes)
              if open != -1 and close != -1]

    delta = width / 2.
    bars = [((i - delta, 0), (i - delta, v), (i + delta, v), (i + delta, 0))
            for i, v in enumerate(volumes)
            if v != -1]

    barCollection = PolyCollection(bars,
                                   facecolors=colors,
                                   edgecolors=((0, 0, 0, 1),),
                                   antialiaseds=(0,),
                                   linewidths=(0.5,),
                                   )

    ax.add_collection(barCollection)
    corners = (0, 0), (len(bars), max(volumes))
    ax.update_datalim(corners)
    ax.autoscale_view()

    # add these last
    return barCollection

def volume_overlay2(ax, closes, volumes,
                    colorup='k', colordown='r',
                    width=4, alpha=1.0):
    """
    Add a volume overlay to the current axes.  The closes are used to
    determine the color of the bar.  -1 is missing.  If a value is
    missing on one it must be missing on all
    nb: first point is not displayed - it is used only for choosing the
    right color
    Parameters
    ----------
    ax : `Axes`
        an Axes instance to plot to
    closes : sequence
        a sequence of closes
    volumes : sequence
        a sequence of volumes
    width : int
        the bar width in points
    colorup : color
        the color of the lines where close >= open
    colordown : color
        the color of the lines where close <  open
    alpha : float
        bar transparency
    Returns
    -------
    ret : `barCollection`
        The `barrCollection` added to the axes
    """

    return volume_overlay(ax, closes[:-1], closes[1:], volumes[1:],
                          colorup, colordown, width, alpha)

def volume_overlay3(ax, quotes,
                    colorup='k', colordown='r',
                    width=4, alpha=1.0):
    """Add a volume overlay to the current axes.  quotes is a list of (d,
    open, high, low, close, volume) and close-open is used to
    determine the color of the bar
    Parameters
    ----------
    ax : `Axes`
        an Axes instance to plot to
    quotes : sequence of (time, open, high, low, close, ...) sequences
        data to plot.  time must be in float date format - see date2num
    width : int
        the bar width in points
    colorup : color
        the color of the lines where close1 >= close0
    colordown : color
        the color of the lines where close1 <  close0
    alpha : float
         bar transparency
    Returns
    -------
    ret : `barCollection`
        The `barrCollection` added to the axes
    """

    colorup = mcolors.to_rgba(colorup, alpha)
    colordown = mcolors.to_rgba(colordown, alpha)
    colord = {True: colorup, False: colordown}

    dates, opens, highs, lows, closes, volumes = list(zip(*quotes))
    colors = [colord[close1 >= close0]
              for close0, close1 in zip(closes[:-1], closes[1:])
              if close0 != -1 and close1 != -1]
    colors.insert(0, colord[closes[0] >= opens[0]])

    right = width / 2.0
    left = -width / 2.0

    bars = [((left, 0), (left, volume), (right, volume), (right, 0))
            for d, open, high, low, close, volume in quotes]

    sx = ax.figure.dpi * (1.0 / 72.0)  # scale for points
    sy = ax.bbox.height / ax.viewLim.height

    barTransform = Affine2D().scale(sx, sy)

    dates = [d for d, open, high, low, close, volume in quotes]
    offsetsBars = [(d, 0) for d in dates]

    useAA = 0,  # use tuple here
    lw = 0.5,  # and here
    barCollection = PolyCollection(bars,
                                   facecolors=colors,
                                   edgecolors=((0, 0, 0, 1),),
                                   antialiaseds=useAA,
                                   linewidths=lw,
                                   offsets=offsetsBars,
                                   transOffset=ax.transData,
                                   )
    barCollection.set_transform(barTransform)

    minpy, maxx = (min(dates), max(dates))
    miny = 0
    maxy = max([volume for d, open, high, low, close, volume in quotes])
    corners = (minpy, miny), (maxx, maxy)
    ax.update_datalim(corners)
    # print 'datalim', ax.dataLim.bounds
    # print 'viewlim', ax.viewLim.bounds

    ax.add_collection(barCollection)
    ax.autoscale_view()

    return barCollection

def index_bar(ax, vals,
              facecolor='b', edgecolor='l',
              width=4, alpha=1.0, ):
    """Add a bar collection graph with height vals (-1 is missing).
    Parameters
    ----------
    ax : `Axes`
        an Axes instance to plot to
    vals : sequence
        a sequence of values
    facecolor : color
        the color of the bar face
    edgecolor : color
        the color of the bar edges
    width : int
        the bar width in points
    alpha : float
       bar transparency
    Returns
    -------
    ret : `barCollection`
        The `barrCollection` added to the axes
    """

    facecolors = (mcolors.to_rgba(facecolor, alpha),)
    edgecolors = (mcolors.to_rgba(edgecolor, alpha),)

    right = width / 2.0
    left = -width / 2.0

    bars = [((left, 0), (left, v), (right, v), (right, 0))
            for v in vals if v != -1]

    sx = ax.figure.dpi * (1.0 / 72.0)  # scale for points
    sy = ax.bbox.height / ax.viewLim.height

    barTransform = Affine2D().scale(sx, sy)

    offsetsBars = [(i, 0) for i, v in enumerate(vals) if v != -1]

    barCollection = PolyCollection(bars,
                                   facecolors=facecolors,
                                   edgecolors=edgecolors,
                                   antialiaseds=(0,),
                                   linewidths=(0.5,),
                                   offsets=offsetsBars,
                                   transOffset=ax.transData,
                                   )
    barCollection.set_transform(barTransform)

    minpy, maxx = (0, len(offsetsBars))
    miny = 0
    maxy = max([v for v in vals if v != -1])
    corners = (minpy, miny), (maxx, maxy)
    ax.update_datalim(corners)
    ax.autoscale_view()

    # add these last
    ax.add_collection(barCollection)
    return barCollection

K线图函数：plt_KLineChart