示例#1
0
async def macd_command(ctx,
                       ticker="",
                       fast="12",
                       slow="26",
                       signal="9",
                       start="",
                       end=""):
    """Displays chart with moving average convergence/divergence [Yahoo Finance]"""

    try:

        # Debug
        if cfg.DEBUG:
            print(
                f"!stocks.ta.macd {ticker} {fast} {slow} {signal} {start} {end}"
            )

        # Check for argument
        if ticker == "":
            raise Exception("Stock ticker is required")

        if start == "":
            start = datetime.now() - timedelta(days=365)
        else:
            start = datetime.strptime(start, cfg.DATE_FORMAT)

        if end == "":
            end = datetime.now()
        else:
            end = datetime.strptime(end, cfg.DATE_FORMAT)

        if not fast.lstrip("-").isnumeric():
            raise Exception("Number has to be an integer")
        fast = float(fast)
        if not slow.lstrip("-").isnumeric():
            raise Exception("Number has to be an integer")
        slow = float(slow)
        if not signal.lstrip("-").isnumeric():
            raise Exception("Number has to be an integer")
        signal = float(signal)

        ticker = ticker.upper()
        df_stock = discordbot.helpers.load(ticker, start)
        if df_stock.empty:
            raise Exception("Stock ticker is invalid")

        # Retrieve Data
        df_stock = df_stock.loc[(df_stock.index >= start)
                                & (df_stock.index < end)]

        df_ta = momentum_model.macd("1440min", df_stock, fast, slow, signal)

        # Output Data
        fig, axes = plt.subplots(2, 1, figsize=plot_autoscale(), dpi=PLOT_DPI)
        ax = axes[0]
        ax.set_title(f"{ticker} MACD")
        ax.plot(df_stock.index, df_stock["Adj Close"].values, "k", lw=2)
        ax.set_xlim(df_stock.index[0], df_stock.index[-1])
        ax.set_ylabel("Share Price ($)")
        ax.grid(b=True, which="major", color="#666666", linestyle="-")

        ax2 = axes[1]
        ax2.plot(df_ta.index, df_ta.iloc[:, 0].values, "b", lw=2)
        ax2.plot(df_ta.index, df_ta.iloc[:, 2].values, "r", lw=2)
        ax2.bar(df_ta.index, df_ta.iloc[:, 1].values, color="g")
        ax2.legend(
            [
                f"MACD Line {df_ta.columns[0]}",
                f"Signal Line {df_ta.columns[2]}",
                f"Histogram {df_ta.columns[1]}",
            ],
            loc="upper left",
        )
        ax2.set_xlim(df_stock.index[0], df_stock.index[-1])
        ax2.grid(b=True, which="major", color="#666666", linestyle="-")

        plt.gcf().autofmt_xdate()
        fig.tight_layout(pad=1)

        plt.savefig("ta_macd.png")
        uploaded_image = gst_imgur.upload_image("ta_cci.png",
                                                title="something")
        image_link = uploaded_image.link
        if cfg.DEBUG:
            print(f"Image URL: {image_link}")
        title = "Stocks: Moving-Average-Convergence-Divergence " + ticker
        embed = discord.Embed(title=title, colour=cfg.COLOR)
        embed.set_author(
            name=cfg.AUTHOR_NAME,
            icon_url=cfg.AUTHOR_ICON_URL,
        )
        embed.set_image(url=image_link)
        os.remove("ta_macd.png")

        await ctx.send(embed=embed)

    except Exception as e:
        embed = discord.Embed(
            title="ERROR Stocks: Moving-Average-Convergence-Divergence",
            colour=cfg.COLOR,
            description=e,
        )
        embed.set_author(
            name=cfg.AUTHOR_NAME,
            icon_url=cfg.AUTHOR_ICON_URL,
        )

        await ctx.send(embed=embed)
示例#2
0
def macd_command(ticker="",
                 fast="12",
                 slow="26",
                 signal="9",
                 start="",
                 end=""):
    """Displays chart with moving average convergence/divergence [Yahoo Finance]"""

    # Debug
    if cfg.DEBUG:
        # pylint: disable=logging-too-many-args
        logger.debug(
            "ta-macd %s %s %s %s %s %s",
            ticker,
            fast,
            slow,
            signal,
            start,
            end,
        )

    # Check for argument
    if ticker == "":
        raise Exception("Stock ticker is required")

    if start == "":
        start = datetime.now() - timedelta(days=365)
    else:
        start = datetime.strptime(start, cfg.DATE_FORMAT)

    if end == "":
        end = datetime.now()
    else:
        end = datetime.strptime(end, cfg.DATE_FORMAT)

    if not fast.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    fast = float(fast)
    if not slow.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    slow = float(slow)
    if not signal.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    signal = float(signal)

    ticker = ticker.upper()
    df_stock = helpers.load(ticker, start)
    if df_stock.empty:
        raise Exception("Stock ticker is invalid")

    # Retrieve Data
    df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]

    df_ta = momentum_model.macd(df_stock["Adj Close"], fast, slow, signal)
    trace_name = df_ta.columns[0].replace("_", " ")

    fig = make_subplots(
        rows=2,
        cols=1,
        shared_xaxes=True,
        vertical_spacing=0.07,
        row_width=[0.5, 0.6],
    )
    fig.add_trace(
        go.Scatter(
            name=ticker,
            x=df_stock.index,
            y=df_stock["Adj Close"].values,
            line=dict(color="#fdc708", width=2),
            opacity=1,
            showlegend=False,
        ),
        row=1,
        col=1,
    )
    fig.add_trace(
        go.Bar(
            name="MACD Histogram",
            x=df_ta.index,
            y=df_ta.iloc[:, 1].values,
            opacity=1,
        ),
        row=2,
        col=1,
    )
    fig.add_trace(
        go.Scatter(
            mode="lines",
            name="MACD Line",
            x=df_ta.index,
            y=df_ta.iloc[:, 0].values,
            opacity=1,
        ),
        row=2,
        col=1,
    )
    fig.add_trace(
        go.Scatter(
            mode="lines",
            name="Signal Line",
            x=df_ta.index,
            y=df_ta.iloc[:, 2].values,
            opacity=1,
        ),
        row=2,
        col=1,
    )
    fig.update_layout(
        margin=dict(l=0, r=20, t=30, b=20),
        template=cfg.PLT_TA_STYLE_TEMPLATE,
        colorway=cfg.PLT_TA_COLORWAY,
        title=f"{ticker} {trace_name}",
        title_x=0.3,
        yaxis_title="Stock Price ($)",
        yaxis=dict(fixedrange=False, ),
        xaxis=dict(
            rangeslider=dict(visible=False),
            type="date",
        ),
        dragmode="pan",
        legend=dict(orientation="h",
                    yanchor="bottom",
                    y=1.02,
                    xanchor="right",
                    x=1),
    )
    config = dict({"scrollZoom": True})
    imagefile = "ta_macd.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if cfg.INTERACTIVE:
        html_ran = helpers.uuid_get()
        fig.write_html(f"in/macd_{html_ran}.html", config=config)
        plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/macd_{html_ran}.html)"

    fig.update_layout(
        width=800,
        height=500,
    )

    imagefile = helpers.image_border(imagefile, fig=fig)

    return {
        "title": f"Stocks: Moving-Average-Convergence-Divergence {ticker}",
        "description": plt_link,
        "imagefile": imagefile,
    }
示例#3
0
def macd_command(
    ticker="",
    interval: int = 15,
    past_days: int = 0,
    fast="12",
    slow="26",
    signal="9",
    start="",
    end="",
    extended_hours: bool = False,
    heikin_candles: bool = False,
    news: bool = False,
):
    """Displays chart with moving average convergence/divergence [Yahoo Finance]"""

    # Debug
    if imps.DEBUG:
        # pylint: disable=logging-too-many-args
        logger.debug(
            "ta macd %s %s %s %s %s %s %s %s %s %s %s",
            ticker,
            interval,
            past_days,
            fast,
            slow,
            signal,
            start,
            end,
            extended_hours,
            heikin_candles,
            news,
        )

    # Check for argument
    if ticker == "":
        raise Exception("Stock ticker is required")

    # Retrieve Data
    df_stock, start, end, bar_start = load_candle.stock_data(
        ticker=ticker,
        interval=interval,
        past_days=past_days,
        extended_hours=extended_hours,
        start=start,
        end=end,
        heikin_candles=heikin_candles,
    )

    if df_stock.empty:
        raise Exception("No Data Found")

    if not fast.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    fast = int(fast)
    if not slow.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    slow = int(slow)
    if not signal.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    signal = int(signal)

    df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]

    if df_ta.empty:
        raise Exception("No Data Found")

    ta_data = momentum_model.macd(df_stock["Adj Close"], fast, slow, signal)
    df_ta = df_ta.join(ta_data)

    # Output Data
    if interval != 1440:
        df_ta = df_ta.loc[(df_ta.index >= bar_start) & (df_ta.index < end)]
    df_ta = df_ta.fillna(0.0)

    plot = load_candle.candle_fig(
        df_ta,
        ticker,
        interval,
        extended_hours,
        news,
        bar=bar_start,
        int_bar=interval,
        rows=2,
        cols=1,
        shared_xaxes=True,
        vertical_spacing=0.07,
        row_width=[0.4, 0.6],
        specs=[[{"secondary_y": True}], [{"secondary_y": False}]],
    )
    title = f"<b>{plot['plt_title']} MACD {fast} {slow} {signal}</b>"
    fig = plot["fig"]
    idx = 6 if interval != 1440 else 11

    fig.add_trace(
        go.Bar(
            name="MACD Histogram",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 1)].values,
            opacity=(plot["bar_opacity"] + 0.3),
            marker_color="#d81aea",
        ),
        row=2,
        col=1,
        secondary_y=False,
    )
    fig.add_trace(
        go.Scatter(
            name="MACD Line",
            mode="lines",
            x=df_ta.index,
            y=df_ta.iloc[:, idx].values,
            opacity=0.8,
            line=dict(color="#00e6c3"),
        ),
        row=2,
        col=1,
        secondary_y=False,
    )
    fig.add_trace(
        go.Scatter(
            name="Signal Line",
            mode="lines",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 2)].values,
            opacity=1,
            line=dict(color="#9467bd"),
        ),
        row=2,
        col=1,
        secondary_y=False,
    )
    fig.update_layout(
        margin=dict(l=0, r=0, t=50, b=20),
        template=imps.PLT_TA_STYLE_TEMPLATE,
        colorway=imps.PLT_TA_COLORWAY,
        title=title,
        title_x=0.02,
        title_font_size=14,
        dragmode="pan",
    )
    imagefile = "ta_macd.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if imps.INTERACTIVE:
        plt_link = imps.inter_chart(fig, imagefile, callback=False)

    fig.update_layout(
        width=800,
        height=500,
    )

    imagefile = imps.image_border(imagefile, fig=fig)

    return {
        "title": f"Stocks: Moving-Average-Convergence-Divergence {ticker.upper()}",
        "description": plt_link,
        "imagefile": imagefile,
    }
def view_macd(
    s_ticker: str,
    s_interval: str,
    df_stock: pd.DataFrame,
    n_fast: int,
    n_slow: int,
    n_signal: int,
    export: str,
):
    """Plot MACD signal

    Parameters
    ----------
    s_ticker : str
        Stock ticker
    s_interval : str
        Interval of data
    df_stock : pd.DataFrame
        Dataframe of prices
    n_fast : int
        Fast period
    n_slow : int
        Slow period
    n_signal : int
        Signal period
    export : str
        Format to export data
    """
    df_ta = momentum_model.macd(s_interval, df_stock, n_fast, n_slow, n_signal)

    fig, axes = plt.subplots(2, 1, figsize=plot_autoscale(), dpi=PLOT_DPI)
    ax = axes[0]
    ax.set_title(f"{s_ticker} MACD")
    if s_interval == "1440min":
        ax.plot(df_stock.index, df_stock["Adj Close"].values, "k", lw=2)
    else:
        ax.plot(df_stock.index, df_stock["Close"].values, "k", lw=2)
    ax.set_xlim(df_stock.index[0], df_stock.index[-1])
    ax.set_ylabel("Share Price ($)")
    ax.grid(b=True, which="major", color="#666666", linestyle="-")

    ax2 = axes[1]
    ax2.plot(df_ta.index, df_ta.iloc[:, 0].values, "b", lw=2)
    ax2.plot(df_ta.index, df_ta.iloc[:, 2].values, "r", lw=2)
    ax2.bar(df_ta.index, df_ta.iloc[:, 1].values, color="g")
    ax2.legend(
        [
            f"MACD Line {df_ta.columns[0]}",
            f"Signal Line {df_ta.columns[2]}",
            f"Histogram {df_ta.columns[1]}",
        ],
        loc="upper left",
    )
    ax2.set_xlim(df_stock.index[0], df_stock.index[-1])
    ax2.grid(b=True, which="major", color="#666666", linestyle="-")

    if gtff.USE_ION:
        plt.ion()

    plt.gcf().autofmt_xdate()
    fig.tight_layout(pad=1)

    plt.show()
    print("")
    export_data(
        export,
        os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
        "macd",
        df_ta,
    )
示例#5
0
def display_macd(
    series: pd.Series,
    n_fast: int = 12,
    n_slow: int = 26,
    n_signal: int = 9,
    s_ticker: str = "",
    export: str = "",
    external_axes: Optional[List[plt.Axes]] = None,
):
    """Plot MACD signal

    Parameters
    ----------
    series : pd.Series
        Values to input
    n_fast : int
        Fast period
    n_slow : int
        Slow period
    n_signal : int
        Signal period
    s_ticker : str
        Stock ticker
    export : str
        Format to export data
    external_axes : Optional[List[plt.Axes]], optional
        External axes (2 axes are expected in the list), by default None
    """
    df_ta = momentum_model.macd(series, n_fast, n_slow, n_signal)
    plot_data = pd.merge(series,
                         df_ta,
                         how="outer",
                         left_index=True,
                         right_index=True)
    plot_data = reindex_dates(plot_data)

    # This plot has 2 axes
    if external_axes is None:
        _, (ax1, ax2) = plt.subplots(2,
                                     1,
                                     figsize=plot_autoscale(),
                                     sharex=True,
                                     dpi=PLOT_DPI)
    else:
        if len(external_axes) != 2:
            logger.error("Expected list of two axis items.")
            console.print("[red]Expected list of 2 axis items./n[/red]")
            return
        ax1, ax2 = external_axes

    ax1.set_title(f"{s_ticker} MACD")
    ax1.plot(plot_data.index, plot_data.iloc[:, 1].values)
    ax1.set_xlim(plot_data.index[0], plot_data.index[-1])
    ax1.set_ylabel("Share Price ($)")
    theme.style_primary_axis(
        ax1,
        data_index=plot_data.index.to_list(),
        tick_labels=plot_data["date"].to_list(),
    )

    ax2.plot(plot_data.index, plot_data.iloc[:, 2].values)
    ax2.plot(plot_data.index,
             plot_data.iloc[:, 4].values,
             color=theme.down_color)
    ax2.bar(
        plot_data.index,
        plot_data.iloc[:, 3].values,
        width=theme.volume_bar_width,
        color=theme.up_color,
    )
    ax2.legend([
        f"MACD Line {plot_data.columns[2]}",
        f"Signal Line {plot_data.columns[4]}",
        f"Histogram {plot_data.columns[3]}",
    ])
    ax2.set_xlim(plot_data.index[0], plot_data.index[-1])
    theme.style_primary_axis(
        ax2,
        data_index=plot_data.index.to_list(),
        tick_labels=plot_data["date"].to_list(),
    )

    if external_axes is None:
        theme.visualize_output()

    export_data(
        export,
        os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
        "macd",
        df_ta,
    )
示例#6
0
async def macd_command(ctx,
                       ticker="",
                       fast="12",
                       slow="26",
                       signal="9",
                       start="",
                       end=""):
    """Displays chart with moving average convergence/divergence [Yahoo Finance]"""

    try:

        # Debug
        if cfg.DEBUG:
            # pylint: disable=logging-too-many-args
            logger.debug(
                "!stocks.ta.macd %s %s %s %s %s %s",
                ticker,
                fast,
                slow,
                signal,
                start,
                end,
            )

        # Check for argument
        if ticker == "":
            raise Exception("Stock ticker is required")

        if start == "":
            start = datetime.now() - timedelta(days=365)
        else:
            start = datetime.strptime(start, cfg.DATE_FORMAT)

        if end == "":
            end = datetime.now()
        else:
            end = datetime.strptime(end, cfg.DATE_FORMAT)

        if not fast.lstrip("-").isnumeric():
            raise Exception("Number has to be an integer")
        fast = float(fast)
        if not slow.lstrip("-").isnumeric():
            raise Exception("Number has to be an integer")
        slow = float(slow)
        if not signal.lstrip("-").isnumeric():
            raise Exception("Number has to be an integer")
        signal = float(signal)

        ticker = ticker.upper()
        df_stock = discordbot.helpers.load(ticker, start)
        if df_stock.empty:
            raise Exception("Stock ticker is invalid")

        # Retrieve Data
        df_stock = df_stock.loc[(df_stock.index >= start)
                                & (df_stock.index < end)]

        df_ta = momentum_model.macd(df_stock["Adj Close"], fast, slow, signal)
        trace_name = df_ta.columns[0].replace("_", " ")

        fig = make_subplots(
            rows=2,
            cols=1,
            shared_xaxes=True,
            vertical_spacing=0.07,
            row_width=[0.5, 0.6],
        )
        fig.add_trace(
            go.Scatter(
                name=ticker,
                x=df_stock.index,
                y=df_stock["Adj Close"].values,
                line=dict(color="#fdc708", width=2),
                opacity=1,
                showlegend=False,
            ),
            row=1,
            col=1,
        )
        fig.add_trace(
            go.Bar(
                name="MACD Histogram",
                x=df_ta.index,
                y=df_ta.iloc[:, 1].values,
                opacity=1,
            ),
            row=2,
            col=1,
        )
        fig.add_trace(
            go.Scatter(
                mode="lines",
                name="MACD Line",
                x=df_ta.index,
                y=df_ta.iloc[:, 0].values,
                opacity=1,
            ),
            row=2,
            col=1,
        )
        fig.add_trace(
            go.Scatter(
                mode="lines",
                name="Signal Line",
                x=df_ta.index,
                y=df_ta.iloc[:, 2].values,
                opacity=1,
            ),
            row=2,
            col=1,
        )
        fig.update_layout(
            margin=dict(l=0, r=20, t=30, b=20),
            template=cfg.PLT_TA_STYLE_TEMPLATE,
            colorway=cfg.PLT_TA_COLORWAY,
            title=f"{ticker} {trace_name}",
            title_x=0.3,
            yaxis_title="Stock Price ($)",
            yaxis=dict(fixedrange=False, ),
            xaxis=dict(
                rangeslider=dict(visible=False),
                type="date",
            ),
            dragmode="pan",
            legend=dict(orientation="h",
                        yanchor="bottom",
                        y=1.02,
                        xanchor="right",
                        x=1),
        )
        config = dict({"scrollZoom": True})
        imagefile = "ta_macd.png"

        # Check if interactive settings are enabled
        plt_link = ""
        if cfg.INTERACTIVE:
            html_ran = random.randint(69, 69420)
            fig.write_html(f"in/macd_{html_ran}.html", config=config)
            plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/macd_{html_ran}.html)"

        fig.update_layout(
            width=800,
            height=500,
        )
        fig.write_image(imagefile)

        img = Image.open(imagefile)
        print(img.size)
        im_bg = Image.open(cfg.IMG_BG)
        h = img.height + 240
        w = img.width + 520

        # Paste fig onto background img and autocrop background
        img = img.resize((w, h), Image.ANTIALIAS)
        x1 = int(0.5 * im_bg.size[0]) - int(0.5 * img.size[0])
        y1 = int(0.5 * im_bg.size[1]) - int(0.5 * img.size[1])
        x2 = int(0.5 * im_bg.size[0]) + int(0.5 * img.size[0])
        y2 = int(0.5 * im_bg.size[1]) + int(0.5 * img.size[1])
        img = img.convert("RGB")
        im_bg.paste(img, box=(x1 - 5, y1, x2 - 5, y2))
        im_bg.save(imagefile, "PNG", quality=100)
        image = Image.open(imagefile)
        image = autocrop_image(image, 0)
        image.save(imagefile, "PNG", quality=100)

        image = disnake.File(imagefile)

        print(f"Image {imagefile}")
        if cfg.DEBUG:
            logger.debug("Image: %s", imagefile)
        title = "Stocks: Moving-Average-Convergence-Divergence " + ticker
        embed = disnake.Embed(title=title,
                              description=plt_link,
                              colour=cfg.COLOR)
        embed.set_image(url=f"attachment://{imagefile}")
        embed.set_author(
            name=cfg.AUTHOR_NAME,
            icon_url=cfg.AUTHOR_ICON_URL,
        )
        os.remove(imagefile)

        await ctx.send(embed=embed, file=image)

    except Exception as e:
        embed = disnake.Embed(
            title="ERROR Stocks: Moving-Average-Convergence-Divergence",
            colour=cfg.COLOR,
            description=e,
        )
        embed.set_author(
            name=cfg.AUTHOR_NAME,
            icon_url=cfg.AUTHOR_ICON_URL,
        )

        await ctx.send(embed=embed, delete_after=30.0)
示例#7
0
def display_macd(
    values: pd.Series,
    n_fast: int = 12,
    n_slow: int = 26,
    n_signal: int = 9,
    s_ticker: str = "",
    export: str = "",
):
    """Plot MACD signal

    Parameters
    ----------
    values : pd.DataFrame
        Values to input
    n_fast : int
        Fast period
    n_slow : int
        Slow period
    n_signal : int
        Signal period
    s_ticker : str
        Stock ticker
    export : str
        Format to export data
    """
    df_ta = momentum_model.macd(values, n_fast, n_slow, n_signal)

    fig, axes = plt.subplots(2, 1, figsize=plot_autoscale(), dpi=PLOT_DPI)
    ax = axes[0]
    ax.set_title(f"{s_ticker} MACD")
    ax.plot(values.index, values.values, "k", lw=2)
    ax.set_xlim(values.index[0], values.index[-1])
    ax.set_ylabel("Share Price ($)")
    ax.grid(b=True, which="major", color="#666666", linestyle="-")

    ax2 = axes[1]
    ax2.plot(df_ta.index, df_ta.iloc[:, 0].values, "b", lw=2)
    ax2.plot(df_ta.index, df_ta.iloc[:, 2].values, "r", lw=2)
    ax2.bar(df_ta.index, df_ta.iloc[:, 1].values, color="g")
    ax2.legend(
        [
            f"MACD Line {df_ta.columns[0]}",
            f"Signal Line {df_ta.columns[2]}",
            f"Histogram {df_ta.columns[1]}",
        ],
        loc="upper left",
    )
    ax2.set_xlim(values.index[0], values.index[-1])
    ax2.grid(b=True, which="major", color="#666666", linestyle="-")

    if gtff.USE_ION:
        plt.ion()

    plt.gcf().autofmt_xdate()
    fig.tight_layout(pad=1)

    plt.show()
    console.print("")
    export_data(
        export,
        os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
        "macd",
        df_ta,
    )