async def fisher_command(ctx, ticker="", length="14", start="", end=""):
"""Displays chart with fisher transformation [Yahoo Finance]"""
try:
# Debug
if cfg.DEBUG:
print(f"!stocks.ta.fisher {ticker} {length} {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)
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.fisher("1440min", df_stock, length)
# Output Data
fig, axes = plt.subplots(2, 1, figsize=plot_autoscale(), dpi=PLOT_DPI)
ax = axes[0]
ax.set_title(f"{ticker} Fisher Transform")
ax.plot(df_stock.index, df_stock["Adj Close"].values, "k", lw=1)
ax.set_xlim(df_stock.index[0], df_stock.index[-1])
ax.set_ylabel("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,
label="Fisher",
)
ax2.plot(
df_ta.index,
df_ta.iloc[:, 1].values,
"fuchsia",
lw=2,
label="Signal",
)
ax2.set_xlim(df_stock.index[0], df_stock.index[-1])
ax2.axhspan(2, plt.gca().get_ylim()[1], facecolor="r", alpha=0.2)
ax2.axhspan(plt.gca().get_ylim()[0], -2, facecolor="g", alpha=0.2)
ax2.axhline(2, linewidth=3, color="r", ls="--")
ax2.axhline(-2, linewidth=3, color="g", ls="--")
ax2.grid(b=True, which="major", color="#666666", linestyle="-")
ax2.set_xlim(df_stock.index[0], df_stock.index[-1])
ax2.axhspan(2, plt.gca().get_ylim()[1], facecolor="r", alpha=0.2)
ax2.axhspan(plt.gca().get_ylim()[0], -2, facecolor="g", alpha=0.2)
ax2.axhline(2, linewidth=3, color="r", ls="--")
ax2.axhline(-2, linewidth=3, color="g", ls="--")
ax2.grid(b=True, which="major", color="#666666", linestyle="-")
ax2.set_yticks([-2, 0, 2])
ax2.set_yticklabels(["-2 STDEV", "0", "+2 STDEV"])
plt.gcf().autofmt_xdate()
fig.tight_layout(pad=1)
plt.legend()
plt.savefig("ta_fisher.png")
uploaded_image = gst_imgur.upload_image("ta_fisher.png",
title="something")
image_link = uploaded_image.link
if cfg.DEBUG:
print(f"Image URL: {image_link}")
title = "Stocks: Fisher-Transform " + 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_fisher.png")
await ctx.send(embed=embed)
except Exception as e:
embed = discord.Embed(
title="ERROR Stocks: Fisher-Transform",
colour=cfg.COLOR,
description=e,
)
embed.set_author(
name=cfg.AUTHOR_NAME,
icon_url=cfg.AUTHOR_ICON_URL,
)
await ctx.send(embed=embed)
async def fisher_command(ctx, ticker="", length="14", start="", end=""):
"""Displays chart with fisher transformation [Yahoo Finance]"""
try:
# Debug
if cfg.DEBUG:
logger.debug("!stocks.ta.fisher %s %s %s %s", ticker, length,
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 = int(length)
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.fisher(df_stock["High"], df_stock["Low"],
length)
dmin = df_ta.values.min()
dmax = df_ta.values.max()
# Output Data
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.Scatter(
name="Fisher",
x=df_ta.index,
y=df_ta.iloc[:, 0].values,
opacity=1,
),
row=2,
col=1,
)
fig.add_trace(
go.Scatter(
name="Signal",
x=df_ta.index,
y=df_ta.iloc[:, 1].values,
opacity=1,
),
row=2,
col=1,
)
fig.add_hrect(
y0=2,
y1=dmax,
fillcolor="red",
opacity=0.2,
layer="below",
line_width=0,
row=2,
col=1,
)
fig.add_hrect(
y0=-2,
y1=dmin,
fillcolor="green",
opacity=0.2,
layer="below",
line_width=0,
row=2,
col=1,
)
fig.add_hline(
y=-2,
fillcolor="green",
opacity=1,
layer="below",
line_width=3,
line=dict(color="green", dash="dash"),
row=2,
col=1,
)
fig.add_hline(
y=2,
fillcolor="red",
opacity=1,
layer="below",
line_width=3,
line=dict(color="red", 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"{ticker} Fisher Transform",
title_x=0.5,
yaxis_title="Stock Price ($)",
yaxis=dict(fixedrange=False, ),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
),
dragmode="pan",
legend=dict(yanchor="top", y=0.99, xanchor="left", x=0.01),
)
config = dict({"scrollZoom": True})
imagefile = "ta_fisher.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = random.randint(69, 69420)
fig.write_html(f"in/fisher_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/fisher_{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: Fisher-Transform " + 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: Fisher-Transform",
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 display_fisher(
ohlc: pd.DataFrame,
length: int = 14,
s_ticker: str = "",
export: str = "",
external_axes: Optional[List[plt.Axes]] = None,
):
"""Display Fisher Indicator
Parameters
----------
ohlc : pd.DataFrame
Dataframe of prices
length : int
Length of window
s_ticker : str
Ticker string
export : str
Format to export data
external_axes : Optional[List[plt.Axes]], optional
External axes (3 axes are expected in the list), by default None
"""
df_ta = momentum_model.fisher(ohlc["High"], ohlc["Low"], length)
plot_data = pd.merge(ohlc,
df_ta,
how="outer",
left_index=True,
right_index=True)
plot_data = reindex_dates(plot_data)
# This plot has 3 axes
if not external_axes:
_, axes = plt.subplots(2,
1,
sharex=True,
figsize=plot_autoscale(),
dpi=PLOT_DPI)
ax1, ax2 = axes
ax3 = ax2.twinx()
else:
if len(external_axes) != 3:
logger.error("Expected list of three axis items.")
console.print("[red]Expected list of 3 axis items./n[/red]")
return
ax1, ax2, ax3 = external_axes
ax1.set_title(f"{s_ticker} Fisher Transform")
ax1.plot(plot_data.index, plot_data["Adj Close"].values)
ax1.set_xlim(plot_data.index[0], plot_data.index[-1])
ax1.set_ylabel("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,
label="Fisher",
)
ax2.plot(
plot_data.index,
plot_data[df_ta.columns[1]].values,
label="Signal",
)
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(),
)
ax3.set_ylim(ax2.get_ylim())
ax3.axhspan(2, ax2.get_ylim()[1], facecolor=theme.down_color, alpha=0.2)
ax3.axhspan(ax2.get_ylim()[0], -2, facecolor=theme.up_color, alpha=0.2)
ax3.axhline(2, color=theme.down_color, ls="--")
ax3.axhline(-2, color=theme.up_color, ls="--")
theme.style_twin_axis(ax3)
ax2.set_yticks([-2, 0, 2])
ax2.set_yticklabels(["-2 STDEV", "0", "+2 STDEV"])
ax2.legend()
if external_axes is None:
theme.visualize_output()
export_data(
export,
os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
"fisher",
df_ta,
)
def view_fisher(s_ticker: str, s_interval: str, df_stock: pd.DataFrame,
length: int, export: str):
"""Display Fisher Indicator
Parameters
----------
s_ticker : str
Stock ticker
s_interval : str
Interval of stock data
df_stock : pd.DataFrame
Dataframe of prices
length : int
Length of window
export : str
Format to export data
"""
df_ta = momentum_model.fisher(s_interval, df_stock, length)
fig, axes = plt.subplots(2, 1, figsize=plot_autoscale(), dpi=PLOT_DPI)
ax = axes[0]
ax.set_title(f"{s_ticker} Fisher Transform")
if s_interval == "1440min":
ax.plot(df_stock.index, df_stock["Adj Close"].values, "k", lw=1)
else:
ax.plot(df_stock.index, df_stock["Close"].values, "k", lw=1)
ax.set_xlim(df_stock.index[0], df_stock.index[-1])
ax.set_ylabel("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,
label="Fisher",
)
ax2.plot(
df_ta.index,
df_ta.iloc[:, 1].values,
"fuchsia",
lw=2,
label="Signal",
)
ax2.set_xlim(df_stock.index[0], df_stock.index[-1])
ax2.axhspan(2, plt.gca().get_ylim()[1], facecolor="r", alpha=0.2)
ax2.axhspan(plt.gca().get_ylim()[0], -2, facecolor="g", alpha=0.2)
ax2.axhline(2, linewidth=3, color="r", ls="--")
ax2.axhline(-2, linewidth=3, color="g", ls="--")
ax2.grid(b=True, which="major", color="#666666", linestyle="-")
ax2.set_xlim(df_stock.index[0], df_stock.index[-1])
ax2.axhspan(2, plt.gca().get_ylim()[1], facecolor="r", alpha=0.2)
ax2.axhspan(plt.gca().get_ylim()[0], -2, facecolor="g", alpha=0.2)
ax2.axhline(2, linewidth=3, color="r", ls="--")
ax2.axhline(-2, linewidth=3, color="g", ls="--")
ax2.grid(b=True, which="major", color="#666666", linestyle="-")
ax2.set_yticks([-2, 0, 2])
ax2.set_yticklabels(["-2 STDEV", "0", "+2 STDEV"])
if gtff.USE_ION:
plt.ion()
plt.gcf().autofmt_xdate()
fig.tight_layout(pad=1)
plt.legend()
plt.show()
print("")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
"fisher",
df_ta,
)
def fisher_command(
ticker: str = "",
interval: int = 15,
past_days: int = 0,
length="14",
start="",
end="",
extended_hours: bool = False,
heikin_candles: bool = False,
news: bool = False,
):
"""Displays chart with fisher transformation [Yahoo Finance]"""
# Debug
if imps.DEBUG:
logger.debug(
"ta fisher %s %s %s %s %s %s %s %s %s",
ticker,
interval,
past_days,
length,
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 = int(length)
df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
if df_ta.empty:
raise Exception("No Data Found")
df_ta = df_ta.join(
momentum_model.fisher(df_stock["High"], df_stock["Low"], length))
# 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']} Fisher Transform</b>"
fig = plot["fig"]
idx = 6 if interval != 1440 else 11
dmin = df_ta.iloc[:, (idx + 1)].values.min()
dmax = df_ta.iloc[:, (idx + 1)].values.max()
fig.add_trace(
go.Scatter(
name="Fisher",
mode="lines",
x=df_ta.index,
y=df_ta.iloc[:, idx].values,
opacity=1,
),
row=2,
col=1,
)
fig.add_trace(
go.Scatter(
name="Signal",
mode="lines",
x=df_ta.index,
y=df_ta.iloc[:, (idx + 1)].values,
opacity=1,
),
row=2,
col=1,
)
fig.add_hrect(
y0=2,
y1=(dmax + 4),
fillcolor="red",
opacity=0.2,
layer="below",
line_width=0,
row=2,
col=1,
)
fig.add_hrect(
y0=-2,
y1=(dmin - 4),
fillcolor="green",
opacity=0.2,
layer="below",
line_width=0,
row=2,
col=1,
)
fig.add_hline(
y=-2,
fillcolor="green",
opacity=1,
layer="below",
line_width=3,
line=dict(color="green", dash="dash"),
row=2,
col=1,
)
fig.add_hline(
y=2,
fillcolor="red",
opacity=1,
layer="below",
line_width=3,
line=dict(color="red", 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=0.02,
title_font_size=14,
dragmode="pan",
)
imagefile = "ta_fisher.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: Fisher-Transform {ticker.upper()}",
"description": plt_link,
"imagefile": imagefile,
}