async def adx_command(ctx,
ticker="",
length="14",
scalar="100",
drift="1",
start="",
end=""):
"""Displays chart with average directional movement index [Yahoo Finance]"""
try:
# Debug
if cfg.DEBUG:
print(
f"!stocks.ta.adx {ticker} {length} {scalar} {drift} {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 length.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
length = float(length)
if not scalar.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
scalar = float(scalar)
if not drift.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
drift = float(drift)
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 = trend_indicators_model.adx("1440min", df_stock, length, scalar,
drift)
# Output Data
fig, ax = plt.subplots(2, 1, figsize=plot_autoscale(), dpi=PLOT_DPI)
ax0 = ax[0]
ax0.plot(df_stock.index, df_stock["Close"].values, "k", lw=2)
ax0.set_title(f"Average Directional Movement Index (ADX) on {ticker}")
ax0.set_xlim(df_stock.index[0], df_stock.index[-1])
ax0.set_ylabel("Share Price ($)")
ax0.grid(b=True, which="major", color="#666666", linestyle="-")
ax1 = ax[1]
ax1.plot(df_ta.index, df_ta.iloc[:, 0].values, "b", lw=2)
ax1.plot(df_ta.index, df_ta.iloc[:, 1].values, "g", lw=1)
ax1.plot(df_ta.index, df_ta.iloc[:, 2].values, "r", lw=1)
ax1.set_xlim(df_stock.index[0], df_stock.index[-1])
ax1.axhline(25, linewidth=3, color="k", ls="--")
ax1.legend(
[
f"ADX ({df_ta.columns[0]})",
f"+DI ({df_ta.columns[1]})",
f"- DI ({df_ta.columns[2]})",
],
loc="upper left",
)
ax1.set_xlabel("Time")
ax1.grid(b=True, which="major", color="#666666", linestyle="-")
ax1.set_ylim([0, 100])
fig.tight_layout()
plt.gcf().autofmt_xdate()
plt.savefig("ta_adx.png")
uploaded_image = gst_imgur.upload_image("ta_adx.png",
title="something")
image_link = uploaded_image.link
if cfg.DEBUG:
print(f"Image URL: {image_link}")
title = "Stocks: Average-Directional-Movement-Index " + 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_adx.png")
await ctx.send(embed=embed)
except Exception as e:
embed = discord.Embed(
title="ERROR Stocks: Average-Directional-Movement-Index",
colour=cfg.COLOR,
description=e,
)
embed.set_author(
name=cfg.AUTHOR_NAME,
icon_url=cfg.AUTHOR_ICON_URL,
)
await ctx.send(embed=embed)
def display_adx(
ohlc: pd.DataFrame,
length: int = 14,
scalar: int = 100,
drift: int = 1,
s_ticker: str = "",
export: str = "",
external_axes: Optional[List[plt.Axes]] = None,
):
"""Plot ADX indicator
Parameters
----------
ohlc : pd.DataFrame
Dataframe with OHLC price data
length : int
Length of window
scalar : int
Scalar variable
drift : int
Drift variable
s_ticker : str
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 = trend_indicators_model.adx(
high_values=ohlc["High"],
low_values=ohlc["Low"],
close_values=ohlc["Adj Close"],
length=length,
scalar=scalar,
drift=drift,
)
plot_data = pd.merge(ohlc, df_ta, how="outer", left_index=True, right_index=True)
plot_data = reindex_dates(plot_data)
# This plot has 2 axes
if not external_axes:
_, axes = plt.subplots(
2, 1, sharex=True, figsize=plot_autoscale(), dpi=PLOT_DPI
)
ax1, ax2 = axes
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.plot(plot_data.index, plot_data["Close"].values)
ax1.set_title(f"Average Directional Movement Index (ADX) on {s_ticker}")
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[df_ta.columns[0]].values)
ax2.plot(plot_data.index, plot_data[df_ta.columns[1]].values, color=theme.up_color)
ax2.plot(
plot_data.index, plot_data[df_ta.columns[2]].values, color=theme.down_color
)
ax2.set_xlim(plot_data.index[0], plot_data.index[-1])
ax2.axhline(25, ls="--")
ax2.legend(
[
f"ADX ({df_ta.columns[0]})",
f"+DI ({df_ta.columns[1]})",
f"-DI ({df_ta.columns[2]})",
]
)
ax2.set_ylim([0, 100])
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"),
"adx",
df_ta,
)
def display_adx(
df_stock: pd.DataFrame,
length: int = 14,
scalar: int = 100,
drift: int = 1,
s_ticker: str = "",
export: str = "",
):
"""Plot ADX indicator
Parameters
----------
df_stock
Dataframe of prices
length : int
Length of window
scalar : int
Scalar variable
drift : int
Drift variable
s_ticker : str
Ticker
export: str
Format to export data
"""
df_ta = trend_indicators_model.adx(
high_values=df_stock["High"],
low_values=df_stock["Low"],
close_values=df_stock["Adj Close"],
length=length,
scalar=scalar,
drift=drift,
)
fig, ax = plt.subplots(2, 1, figsize=plot_autoscale(), dpi=PLOT_DPI)
ax0 = ax[0]
ax0.plot(df_stock.index, df_stock["Close"].values, "k", lw=2)
ax0.set_title(f"Average Directional Movement Index (ADX) on {s_ticker}")
ax0.set_xlim(df_stock.index[0], df_stock.index[-1])
ax0.set_ylabel("Share Price ($)")
ax0.grid(b=True, which="major", color="#666666", linestyle="-")
ax1 = ax[1]
ax1.plot(df_ta.index, df_ta.iloc[:, 0].values, "b", lw=2)
ax1.plot(df_ta.index, df_ta.iloc[:, 1].values, "g", lw=1)
ax1.plot(df_ta.index, df_ta.iloc[:, 2].values, "r", lw=1)
ax1.set_xlim(df_stock.index[0], df_stock.index[-1])
ax1.axhline(25, linewidth=3, color="k", ls="--")
ax1.legend(
[
f"ADX ({df_ta.columns[0]})",
f"+DI ({df_ta.columns[1]})",
f"- DI ({df_ta.columns[2]})",
],
loc="upper left",
)
ax1.set_xlabel("Time")
ax1.grid(b=True, which="major", color="#666666", linestyle="-")
ax1.set_ylim([0, 100])
if gtff.USE_ION:
plt.ion()
fig.tight_layout()
plt.gcf().autofmt_xdate()
plt.show()
console.print("")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
"adx",
df_ta,
)
async def adx_command(ctx,
ticker="",
length="14",
scalar="100",
drift="1",
start="",
end=""):
"""Displays chart with average directional movement index [Yahoo Finance]"""
try:
# Debug
if cfg.DEBUG:
# pylint: disable=logging-too-many-args
logger.debug(
"!stocks.ta.adx %s %s %s %s %s",
ticker,
length,
scalar,
drift,
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 length.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
length = float(length)
if not scalar.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
scalar = float(scalar)
if not drift.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
drift = float(drift)
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 = trend_indicators_model.adx(
df_stock["High"],
df_stock["Low"],
df_stock["Adj Close"],
length,
scalar,
drift,
)
# Output Data
leg_adx = df_ta.columns[0].replace("_", " ")
neg_di = df_ta.columns[1].replace("_", " ")
pos_di = df_ta.columns[2].replace("_", " ")
fig = make_subplots(
rows=2,
cols=1,
shared_xaxes=True,
vertical_spacing=0.07,
row_width=[0.5, 0.5],
)
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,
),
row=1,
col=1,
)
fig.add_trace(
go.Scatter(
mode="lines",
name=f"ADX ({leg_adx})",
x=df_ta.index,
y=df_ta.iloc[:, 0].values,
opacity=1,
line=dict(width=2),
),
row=2,
col=1,
)
fig.add_trace(
go.Scatter(
mode="lines",
name=f"+DI ({pos_di})",
x=df_ta.index,
y=df_ta.iloc[:, 1].values,
opacity=1,
line=dict(width=1),
),
row=2,
col=1,
)
fig.add_trace(
go.Scatter(
mode="lines",
name=f"- DI ({neg_di})",
x=df_ta.index,
y=df_ta.iloc[:, 2].values,
opacity=1,
line=dict(width=1),
),
row=2,
col=1,
)
fig.add_hline(
y=25,
fillcolor="grey",
opacity=1,
layer="below",
line_width=3,
line=dict(color="grey", dash="dash"),
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"Average Directional Movement Index (ADX) on {ticker}",
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_adx.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = random.randint(69, 69420)
fig.write_html(f"in/adx_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/adx_{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 = f"Stocks: Average-Directional-Movement-Index {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: Average-Directional-Movement-Index",
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)
def adx_command(
ticker="",
interval: int = 15,
past_days: int = 0,
length="14",
scalar="100",
drift="1",
start="",
end="",
extended_hours: bool = False,
heikin_candles: bool = False,
news: bool = False,
):
"""Displays chart with average directional movement index [Yahoo Finance]"""
# Debug
if imps.DEBUG:
# pylint: disable=logging-too-many-args
logger.debug(
"ta adx %s %s %s %s %s %s %s %s %s %s %s",
ticker,
interval,
past_days,
length,
scalar,
drift,
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 length.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
length = float(length)
if not scalar.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
scalar = float(scalar)
if not drift.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
drift = float(drift)
df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
if df_ta.empty:
raise Exception("No Data Found")
ta_data = trend_indicators_model.adx(
df_stock["High"],
df_stock["Low"],
df_stock["Adj Close"],
length,
scalar,
drift,
)
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']} Average Directional Movement Index</b>"
fig = plot["fig"]
idx = 6 if interval != 1440 else 11
fig.add_trace(
go.Scatter(
name=f"ADX ({length})",
mode="lines",
x=df_ta.index,
y=df_ta.iloc[:, idx].values,
opacity=1,
line=dict(width=2),
),
secondary_y=False,
row=2,
col=1,
)
fig.add_trace(
go.Scatter(
name=f"+DI ({length})",
mode="lines",
x=df_ta.index,
y=df_ta.iloc[:, (idx + 1)].values,
opacity=1,
line=dict(width=1),
),
secondary_y=False,
row=2,
col=1,
)
fig.add_trace(
go.Scatter(
name=f"-DI ({length})",
mode="lines",
x=df_ta.index,
y=df_ta.iloc[:, (idx + 2)].values,
opacity=1,
line=dict(width=1),
),
secondary_y=False,
row=2,
col=1,
)
fig.add_hline(
y=25,
fillcolor="grey",
opacity=1,
layer="below",
line_width=3,
line=dict(color="grey", dash="dash"),
row=2,
col=1,
)
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=0.01,
title_font_size=12,
dragmode="pan",
)
imagefile = "ta_adx.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: Average-Directional-Movement-Index {ticker.upper()}",
"description": plt_link,
"imagefile": imagefile,
}