Candlestick shadow is drawn after candlestick body

Hello,

in this example
http://matplotlib.org/examples/pylab_examples/finance_demo.html
there is a little display bug.
Candlestick shadows (vertical segment) should be drawn before candlestick body.
see http://en.wikipedia.org/wiki/Candlestick_chart

Kind regards

@c0indev3l

Looks like this could be a pretty accessible change. Are you interested in giving it a go, and I'lll happily review.

Cheers @c0indev3l!

@pelson

@pelson that's not as easy as expected...

I tried to modify _candlestick function
https://github.com/matplotlib/matplotlib/blob/master/lib/matplotlib/finance.py

My first idea was to return patches, lines instead of lines, patches
but it didn't worked

so I did a quite dirty fix...
I decomposed each shadow to 2 vline

There is probably a better way to do this...

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 = []
    for q in quotes: #[1:-1]:
        if ochl:
            t, open, close, high, low = q[:5]
        else:
            t, open, high, low, close = q[:5]

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

        vline = Line2D(
            xdata=(t, t), ydata=(low, lower),
            color='k',
            linewidth=0.5,
            antialiased=True,
        )

        vline2 = Line2D(
            xdata=(t, t), ydata=(higher, high),
            color='k',
            linewidth=0.5,
            antialiased=True,
        )

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

        patches.append(rect)
        lines.append(vline)
        lines.append(vline2)
        ax.add_patch(rect)
        ax.add_line(vline)
        ax.add_line(vline2)
    ax.autoscale_view()

    return lines, patches

That is the hard way to do it. Just change the zorder so that the shadow lines are behind the box.

Something like https://github.com/tacaswell/matplotlib/tree/fix_candlestick_zorder (which I have not tested, and still needs a unit test)

should, at the same time, make the color shadows modifiable ?

change

    vline = Line2D(
        xdata=(t, t), ydata=(low, lower),
        color='k',
        linewidth=0.5,
        antialiased=True,
    )

to

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

It could be useful to be able to set this when drawing using inverted colors (black background, white foreground)

@c0indev3l

@c0indev3l That sounds like a good idea. Could you put together a PR for each of these changes?

PR ? performance rating ?

Pull request.

ok... but I'm quite busy...

I also have an other comment about this function (when using a black and white color theme with inverted colors ie black background) it's quite problematic

we should also pass coloredgeup and coloredgedown parameter

def _candlestick(ax, quotes, width=0.2, colorup='g', colordown='r',                
                alpha=1.0, ochl=True, colorshadow='k', coloredgeup=None, coloredgedown=None):                

    """                
    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                

    """                
    if coloredgeup is None:                
        coloredgeup = colorup                

    if coloredgedown is None:                
        coloredgedown = colordown                

    OFFSET = width / 2.0                

    lines = []                
    patches = []                
    for q in quotes: #[1:-1]:                
        if ochl:                
            t, open, close, high, low = q[:5]                
        else:                
            t, open, high, low, close = q[:5]                

        if close >= open:                
            color = colorup                
            coloredge = coloredgeup                
            lower = open                
            higher = close                
            height = close - open                
        else:                
            color = colordown                
            coloredge = coloredgedown                
            lower = close                
            higher = open                
            height = open - close                

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

        vline2 = Line2D(                
            xdata=(t, t), ydata=(higher, high),                
            color=colorshadow,                
            linewidth=0.5,                
            antialiased=True,                
        )                

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

        patches.append(rect)                
        lines.append(vline)                
        lines.append(vline2)                
        ax.add_patch(rect)                
        ax.add_line(vline)                
        ax.add_line(vline2)                
    #ax.autoscale_view()                

    return lines, patches

That also looks like a good idea, but these things are much easier to review from a pull request (fork matplotlib on github, create a new branch with your changes, and you can use the website to create the PR against master from your branch)

Ok I will send a pull request this week. There is also some other problems.
Default colorup should be green (not black).
open and close are python command... they should be changed for 'opn' and 'cls' (it works but I don't think it's a good idea to keep open and close as variable

Changing internal variables is ok, changing the names of kwargs or the default value of anything is an api change and should be done very carefully.

@c0indev3l

@c0indev3l Are you still interested in working on this issue?

@c0indev3l

pushing to 1.4.x as @c0indev3l has gone silent.

@jdgd1

@jdgd1 If you have any time or expertise it will be an improvement.

candlestick edge color

@tacaswell

@tacaswell ok, I will help as much as I can. Let me know where to start.

@jdgd1

@jdgd1 For starters, can you review #5160 ?

@ssanderson is a dev at Quantopian who has expressed (very very) lose interest in also helping with the finance module, it is probably worth getting in touch with him.

A survey of what is in the finance module would be good to do. Are the functions we have actually useful to a 'typical' finance type anymore? Are there obvious functions we are missing? A major struggle with that package right now is that none of the core-devs do finance so we lack the domain expertise to answer these questions.

Related, I don't think we have any prose documentation for the finance module, turning some of the examples in to more proper tutorials might be worth doing.

There has been some discussion of splitting the finance module out of core mpl (into a mpl-finance repo in the matplotlib gh org). If we did this, then it could pick up a pandas dependency which would definitely help increase the relevance to current finance users. This may be something that the pandas folks would be willing to help with.

I know this is a daunting list and by no means expect you to tackle all of it, but just trying to make the point that this is a domain where there is significant opportunity to have a major impact.

@tacaswell

@tacaswell wow, you weren't kidding - that is quite the list. Will start with checking out #5160 and then trying to get in touch with @ssanderson. I've actually been spending a good bit of time lately working between Quantopian/zipline, so that could work out well.

Post those two things will start digging into the finance module and making my own list of what I think can go vs. what's missing.

@jdgd1

@jdgd1, @tacaswell hello!

@tacaswell

(@tacaswell I just realized I've owed you an email reply for like 3 months...sorry about that)

@ssanderson

@ssanderson Don't worry, that still leaves me way in the red in terms of net-emails-owed.

@twiecki

A couple notes on the discussion here:

I/we am/are interested in helping out with mpl.finance, but I'm not sure anyone has the bandwidth to make a sustained contribution right now. Zipline is basically being completely rewritten from the ground up on 2 different fronts right now, so we're stretched a bit thin.
I'm probably not any more qualified than the MPL devs to comment on things like how to display candlesticks properly, but I can at least help provide real-world user stories/issues from our user base. I suspect that our forums would also be an interesting place to ask for feedback/comments on this stuff.
Most of the interesting work we've done in financial visualization at Quantopian has been building visualizations for analyzing portfolio performance. @twiecki and co have been working on pyfolio, which is built primarily on top of pandas, matplotlib, and seaborn. I'm not sure what the right relationship would be between that project and mpl.finance.

@jdgd1

I only picked up python recently and I just started using matplotlib, but I can tell you these charts are looking quite nice and easy to handle (I used jfreechart before)

Things the finance modul could use are eg.
-hollow/filled candlesticks (tc2000 style) adding additional information to one candle
-easy subchart addition right into the chart itself or below for indicators
-easy access to daw into the chart itself eg. support/resistance lines etc

to make @jdgd1 list even longer ;-)

@tacaswell

@tacaswell @ssanderson +1 for mpl-finance as a separate repository with Numpy/Pandas as dependency.

@davidastephens

Pinging some people from PyData / Pandas-DataReader and others who might be interested in a Matplotlib / Numpy / Pandas / Finance plotting lib @davidastephens @bashtage @hayd @jorisvandenbossche

@campagnola

The scope of such a lib could be (or not) to be able to display "realtime" plot. PyQtGraph is nice for realtime plot so pinging also @campagnola

See

http://www.pyqtgraph.org/
http://stackoverflow.com/questions/24670856/the-fastest-way-to-add-a-new-data-bar-with-pyqtgraph

so far i use hecandlestick2_ohlc, and come across the same shadow line through the real body! this question has been put here almost 3 years and not solved!!

@genliu777

@genliu777 There is a quick resolving, use z-order as it had mentioned. It works for me without any side effect.
(By default lines have 2 and patches have 1 as z_order.
Of course, color of edges and shadows has not changed)

shadows, bodies = candlestick2_ohlc(ax, .... )
shadows.set_zorder(0)  # or 9
bodies.set_zorder(1)   # or 10 or so

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Candlestick shadow is drawn after candlestick body #2546

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pelson commented on Oct 28, 2013

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tacaswell commented on Oct 28, 2013

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