def test_get_close_price(asset, interval, since, until, recorder):
df = glassnode_model.get_close_price(asset, interval, since, until)
recorder.capture(df)
def display_btc_rainbow(
since: int,
until: int,
export: str = "",
external_axes: Optional[List[plt.Axes]] = None,
):
"""Displays bitcoin rainbow chart
[Price data from source: https://glassnode.com]
[Inspired by: https://blockchaincenter.net]
Parameters
----------
since : int
Initial date timestamp. Default is initial BTC timestamp: 1_325_376_000
until : int
Final date timestamp. Default is current BTC timestamp
external_axes : Optional[List[plt.Axes]], optional
External axes (1 axis is expected in the list), by default None
"""
df_data = get_close_price("BTC", "24h", since, until)
if df_data.empty:
return
# This plot has 1 axis
if not external_axes:
_, ax = plt.subplots(figsize=plot_autoscale(), dpi=cfgPlot.PLOT_DPI)
else:
if len(external_axes) != 1:
logger.error("Expected list of one axis item.")
console.print("[red]Expected list of one axis item./n[/red]")
return
(ax, ) = external_axes
d0 = datetime.strptime("2012-01-01", "%Y-%m-%d")
x = range((df_data.index[0] - d0).days, (df_data.index[-1] - d0).days + 1)
y0 = [
10**((2.90 * ln_x) - 19.463)
for ln_x in [np.log(val + 1400) for val in x]
]
y1 = [
10**((2.886 * ln_x) - 19.463)
for ln_x in [np.log(val + 1375) for val in x]
]
y2 = [
10**((2.872 * ln_x) - 19.463)
for ln_x in [np.log(val + 1350) for val in x]
]
y3 = [
10**((2.859 * ln_x) - 19.463)
for ln_x in [np.log(val + 1320) for val in x]
]
y4 = [
10**((2.8445 * ln_x) - 19.463)
for ln_x in [np.log(val + 1293) for val in x]
]
y5 = [
10**((2.8295 * ln_x) - 19.463)
for ln_x in [np.log(val + 1275) for val in x]
]
y6 = [
10**((2.815 * ln_x) - 19.463)
for ln_x in [np.log(val + 1250) for val in x]
]
y7 = [
10**((2.801 * ln_x) - 19.463)
for ln_x in [np.log(val + 1225) for val in x]
]
y8 = [
10**((2.788 * ln_x) - 19.463)
for ln_x in [np.log(val + 1200) for val in x]
]
ax.fill_between(df_data.index, y0, y1, color="red", alpha=0.7)
ax.fill_between(df_data.index, y1, y2, color="orange", alpha=0.7)
ax.fill_between(df_data.index, y2, y3, color="yellow", alpha=0.7)
ax.fill_between(df_data.index, y3, y4, color="green", alpha=0.7)
ax.fill_between(df_data.index, y4, y5, color="blue", alpha=0.7)
ax.fill_between(df_data.index, y5, y6, color="violet", alpha=0.7)
ax.fill_between(df_data.index, y6, y7, color="indigo", alpha=0.7)
ax.fill_between(df_data.index, y7, y8, color="purple", alpha=0.7)
ax.semilogy(df_data.index, df_data["v"].values)
ax.set_xlim(df_data.index[0], df_data.index[-1])
ax.set_title("Bitcoin Rainbow Chart")
ax.set_ylabel("Price ($)")
ax.legend(
[
"Bubble bursting imminent!!",
"SELL!",
"Everyone FOMO'ing....",
"Is this a bubble??",
"Still cheap",
"Accumulate",
"BUY!",
"Basically a Fire Sale",
"Bitcoin Price",
],
prop={"size": 8},
)
sample_dates = np.array(
[datetime(2012, 11, 28),
datetime(2016, 7, 9),
datetime(2020, 5, 11)])
sample_dates = mdates.date2num(sample_dates)
ax.vlines(x=sample_dates, ymin=0, ymax=10**5, color="grey")
for i, x in enumerate(sample_dates):
ax.text(x,
1,
f"Halving {i+1}",
rotation=-90,
verticalalignment="center")
ax.minorticks_off()
ax.yaxis.set_major_formatter(
matplotlib.ticker.FuncFormatter(lambda x, _: int(x) if x >= 1 else x))
ax.yaxis.set_major_locator(
matplotlib.ticker.LogLocator(base=100, subs=[1.0, 2.0, 5.0, 10.0]))
theme.style_primary_axis(ax)
if not external_axes:
theme.visualize_output()
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"rainbox",
df_data,
)
def display_btc_rainbow(since: int, until: int, export: str = ""):
"""Displays bitcoin rainbow chart
[Price data from source: https://glassnode.com]
[Inspired by: https://blockchaincenter.net]
Parameters
----------
since : int
Initial date timestamp. Default is initial BTC timestamp: 1_325_376_000
until : int
Final date timestamp. Default is current BTC timestamp
"""
df_data = get_close_price("BTC", "24h", since, until)
if df_data.empty:
print("Error in glassnode request\n")
else:
_, ax = plt.subplots(figsize=plot_autoscale(), dpi=cfgPlot.PLOT_DPI)
d0 = datetime.strptime("2012-01-01", "%Y-%m-%d")
x = range((df_data.index[0] - d0).days,
(df_data.index[-1] - d0).days + 1)
y0 = [
10**((2.90 * ln_x) - 19.463)
for ln_x in [np.log(val + 1400) for val in x]
]
y1 = [
10**((2.886 * ln_x) - 19.463)
for ln_x in [np.log(val + 1375) for val in x]
]
y2 = [
10**((2.872 * ln_x) - 19.463)
for ln_x in [np.log(val + 1350) for val in x]
]
y3 = [
10**((2.859 * ln_x) - 19.463)
for ln_x in [np.log(val + 1320) for val in x]
]
y4 = [
10**((2.8445 * ln_x) - 19.463)
for ln_x in [np.log(val + 1293) for val in x]
]
y5 = [
10**((2.8295 * ln_x) - 19.463)
for ln_x in [np.log(val + 1275) for val in x]
]
y6 = [
10**((2.815 * ln_x) - 19.463)
for ln_x in [np.log(val + 1250) for val in x]
]
y7 = [
10**((2.801 * ln_x) - 19.463)
for ln_x in [np.log(val + 1225) for val in x]
]
y8 = [
10**((2.788 * ln_x) - 19.463)
for ln_x in [np.log(val + 1200) for val in x]
]
ax.fill_between(df_data.index, y0, y1, color="red", alpha=0.7)
ax.fill_between(df_data.index, y1, y2, color="orange", alpha=0.7)
ax.fill_between(df_data.index, y2, y3, color="yellow", alpha=0.7)
ax.fill_between(df_data.index, y3, y4, color="green", alpha=0.7)
ax.fill_between(df_data.index, y4, y5, color="blue", alpha=0.7)
ax.fill_between(df_data.index, y5, y6, color="violet", alpha=0.7)
ax.fill_between(df_data.index, y6, y7, color="indigo", alpha=0.7)
ax.fill_between(df_data.index, y7, y8, color="purple", alpha=0.7)
ax.semilogy(df_data.index, df_data["v"].values, c="k", lw=1.2)
ax.set_xlim(df_data.index[0], df_data.index[-1])
ax.set_title("Bitcoin Rainbow Chart")
ax.set_xlabel("Time")
dateFmt = mdates.DateFormatter("%m/%d/%Y")
ax.set_ylabel("Price ($)")
ax.xaxis.set_major_formatter(dateFmt)
ax.tick_params(axis="x", labelrotation=45)
ax.legend(
[
"Bubble bursting imminent!!",
"SELL!",
"Everyone FOMO'ing....",
"Is this a bubble??",
"Still cheap",
"Accumulate",
"BUY!",
"Basically a Fire Sale",
"Bitcoin Price",
],
prop={"size": 6},
)
sample_dates = np.array([
datetime(2012, 11, 28),
datetime(2016, 7, 9),
datetime(2020, 5, 11)
])
sample_dates = mdates.date2num(sample_dates)
ax.vlines(x=sample_dates, ymin=0, ymax=10**5, color="grey")
for i, x in enumerate(sample_dates):
ax.text(x,
1,
f"Halving {i+1}",
rotation=-90,
verticalalignment="center")
ax.grid(alpha=0.2)
ax.minorticks_off()
ax.yaxis.set_major_formatter(
matplotlib.ticker.FuncFormatter(lambda x, _: int(x)
if x >= 1 else x))
ax.yaxis.set_major_locator(
matplotlib.ticker.LogLocator(base=100, subs=[1.0, 2.0, 5.0, 10.0]))
if gtff.USE_ION:
plt.ion()
plt.show()
print("")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"rainbox",
df_data,
)