diff --git a/config.json.sample b/config.json.sample
index 3917be3e..e404d961 100644
--- a/config.json.sample
+++ b/config.json.sample
@@ -34,7 +34,6 @@
"trailingbuypcnt": 0.5,
"telegramtradesonly": 0,
"granularity": "1hour",
- "enableml": 0,
"use_sell_fee": 1
}
},
@@ -73,7 +72,6 @@
"trailingbuypcnt": 0.5,
"telegramtradesonly": 0,
"granularity": "3600",
- "enableml": 0
}
},
"coinbasepro": {
@@ -111,7 +109,6 @@
"trailingbuypcnt": 0.5,
"telegramtradesonly": 0,
"granularity": "3600",
- "enableml": 0
}
},
"telegram": {
diff --git a/controllers/PyCryptoBot.py b/controllers/PyCryptoBot.py
index 0d6f8e0f..1a9ec4f1 100644
--- a/controllers/PyCryptoBot.py
+++ b/controllers/PyCryptoBot.py
@@ -910,17 +910,6 @@ def _notify(notification: str = "", level: str = "normal") -> None:
self.console_log.print(self.table_console)
self.table_console = Table(title=None, box=None, show_header=False, show_footer=False) # clear table
- if self.enableml:
- # Seasonal Autoregressive Integrated Moving Average (ARIMA) model (ML prediction for 3 intervals from now)
- if not self.is_sim:
- try:
- prediction = _technical_analysis.arima_model_prediction(int(self.granularity.to_integer / 60) * 3) # 3 intervals from now
- _notify(
- f"Seasonal ARIMA model predicts the closing self.price will be {str(round(prediction[1], 2))} at {prediction[0]} (delta: {round(prediction[1] - self.price, 2)})"
- )
- except Exception:
- pass
-
if self.state.last_action == "BUY":
# display support, resistance and fibonacci levels
if not self.is_sim:
@@ -2304,15 +2293,6 @@ def config_option_row_enum(
default_value=False,
arg_name="manualtradesonly",
)
- config_option_row_bool(
- "AI/ML Predictions",
- "enableml",
- "Enable AI / Machine Learning Predictions",
- break_below=False,
- store_invert=False,
- default_value=False,
- arg_name="predictions",
- )
config_option_row_str(
"Start Method",
"startmethod",
diff --git a/examples/create-graphs.py b/examples/create-graphs.py
index 646fba8c..1453abd2 100644
--- a/examples/create-graphs.py
+++ b/examples/create-graphs.py
@@ -17,5 +17,4 @@
# tradinggraphs.render_fibonacci_retracement(True)
# tradinggraphs.render_support_resistance(True)
# tradinggraphs.render_candle_sticks(30, True)
-# tradinggraphs.render_arima_model_prediction(1, True)
tradinggraphs.render_bollinger_bands()
diff --git a/models/BotConfig.py b/models/BotConfig.py
index 9312a990..74e241fa 100644
--- a/models/BotConfig.py
+++ b/models/BotConfig.py
@@ -121,7 +121,6 @@ def __init__(self, *args, **kwargs):
self.disabletelegram = False
self.disablelog = False
self.disabletracker = True
- self.enableml = False
self.websocket = False
self.exitaftersell = False
self.ignorepreviousbuy = True
@@ -424,7 +423,6 @@ def _parse_arguments(self):
parser.add_argument("--insufficientfundslogging", type=int, help="Enable insufficient funds logging")
parser.add_argument("--logbuysellinjson", type=int, help="Log buy and sell orders in a JSON file")
parser.add_argument("--manualtradesonly", type=int, help="Manual Trading Only (HODL)")
- parser.add_argument("--predictions", type=int, help="Enable AI / Machine Learning Predictions")
parser.add_argument("--startmethod", type=str, help="Bot start method ('scanner', 'standard', 'telegram')")
parser.add_argument("--recvwindow", type=int, help="Binance exchange API recvwindow, integer between 5000 and 60000")
parser.add_argument("--lastaction", type=str, help="Manually set the last action performed by the bot (BUY, SELL)")
diff --git a/models/config/default_parser.py b/models/config/default_parser.py
index 2fcb98a2..78255179 100644
--- a/models/config/default_parser.py
+++ b/models/config/default_parser.py
@@ -244,7 +244,6 @@ def config_option_date(
config_option_bool(option_name="insufficientfundslogging", option_default=False, store_name="enableinsufficientfundslogging", store_invert=False)
config_option_bool(option_name="logbuysellinjson", option_default=False, store_name="logbuysellinjson", store_invert=False)
config_option_bool(option_name="manualtradesonly", option_default=False, store_name="manual_trades_only", store_invert=False)
- config_option_bool(option_name="predictions", option_default=False, store_name="enableml", store_invert=False)
config_option_str(option_name="startmethod", option_default="standard", store_name="startmethod", valid_options=["scanner", "standard", "telegram"])
config_option_int(option_name="recvwindow", option_default=5000, store_name="recv_window", value_min=5000, value_max=60000)
config_option_str(option_name="lastaction", option_default=None, store_name="last_action", valid_options=["BUY", "SELL"])
diff --git a/pages/config.py b/pages/config.py
index 11f05da8..1509c43f 100644
--- a/pages/config.py
+++ b/pages/config.py
@@ -480,10 +480,6 @@
"label": "Disable Bot Logs",
"value": "disablelog",
},
- {
- "label": "Enable Machine Learning Messages",
- "value": "enableml",
- },
],
value=[1],
id="switches-extras",
diff --git a/views/TradingGraphs.py b/views/TradingGraphs.py
index 02c17bc2..cbfeddc9 100644
--- a/views/TradingGraphs.py
+++ b/views/TradingGraphs.py
@@ -302,36 +302,6 @@ def format_date(x, pos=None): # pylint: disable=unused-argument
if saveOnly is False:
plt.show()
- def render_seasonal_arima_model(self, saveFile="", saveOnly=False):
- """Render the seasonal ARIMA model
-
- Parameters
- ----------
- saveFile : str, optional
- Save the figure
- saveOnly : bool
- Save the figure without displaying it
- """
-
- fittedValues = self.technical_analysis.seasonal_arima_model_fitted_values()
-
- plt.plot(self.df["close"], label="original")
- plt.plot(fittedValues, color="red", label="fitted")
- plt.title("RSS: %.4f" % sum((fittedValues - self.df["close"]) ** 2))
- plt.legend()
- plt.ylabel("Price")
- plt.xticks(rotation=90)
- plt.tight_layout()
-
- try:
- if saveFile != "":
- plt.savefig(saveFile)
- except OSError:
- raise SystemExit(f"Unable to save: {saveFile}")
-
- if saveOnly is False:
- plt.show()
-
def render_sma_and_macd(self, saveFile="", saveOnly=False):
"""Render the self.price, SMA20, SMA50, and SMA200
@@ -369,72 +339,6 @@ def render_sma_and_macd(self, saveFile="", saveOnly=False):
if saveOnly is False:
plt.show()
- def render_arima_model_prediction(self, days=30, saveOnly=False):
- """Render the seasonal ARIMA model prediction
-
- Parameters
- ----------
- days : int
- Number of days to predict
- saveOnly : bool
- Save the figure without displaying it
- """
-
- # get dataframe from technical analysis object
- df = self.technical_analysis.get_df()
-
- if not isinstance(days, int):
- raise TypeError("Prediction days is not numeric.")
-
- if days < 1 or days > len(df):
- raise ValueError("Predication days is out of range")
-
- # extract market and granularity from trading dataframe
- market = df.iloc[0].market
- granularity = df.iloc[0].granularity
-
- results_ARIMA = self.technical_analysis.seasonal_arima_model()
-
- df = pd.DataFrame(self.df["close"])
- start_date = df.last_valid_index()
- end_date = start_date + timedelta(days=days)
- pred = results_ARIMA.predict(start=str(start_date), end=str(end_date), dynamic=True)
-
- fig, axes = plt.subplots(ncols=1, figsize=(12, 6)) # pylint: disable=unused-variable
- fig.autofmt_xdate()
- ax1 = plt.subplot(111)
- ax1.set_title("Seasonal ARIMA Model Prediction")
-
- date = pd.to_datetime(pred.index).to_pydatetime()
-
- pred_length = len(pred)
- # the evenly spaced plot indices
- # indices = np.arange(pred_length) # TODO: why is this here?
-
- def format_date(x, pos=None): # pylint: disable=unused-argument
- thisind = np.clip(int(x + 0.5), 0, pred_length - 1)
- return date[thisind].strftime("%Y-%m-%d %H:%M:%S")
-
- fig, ax = plt.subplots(ncols=1, figsize=(12, 6)) # pylint: disable=unused-variable
- fig.autofmt_xdate()
-
- ax = plt.subplot(111)
- ax.set_title("Seasonal ARIMA Model Prediction")
- ax.plot(pred, label="prediction", color="black")
- ax.xaxis.set_major_formatter(ticker.FuncFormatter(format_date))
-
- plt.xticks(rotation=90)
- plt.tight_layout()
-
- try:
- RichText.notify(f"creating: graphs/SAM_{market}_{str(granularity)}.png", self.app, "info")
- plt.savefig(f"graphs/SAM_{market}_{str(granularity)}.png", dpi=300)
- except OSError:
- raise SystemExit(f"Unable to save: graphs/SAM_{market}_{str(granularity)}.png")
-
- if saveOnly is False:
- plt.show()
-
def render_candle_stick_astral_pattern(self, period=30, saveOnly=False):
# get dataframe from technical analysis object
df = self.technical_analysis.get_df()
diff --git a/websvc/app/pages/pages.py b/websvc/app/pages/pages.py
index 8980e0a8..44279d35 100644
--- a/websvc/app/pages/pages.py
+++ b/websvc/app/pages/pages.py
@@ -450,32 +450,6 @@ def technical_analysis(exchange: str, market: str, g1, g2, g3) -> str:
adx14_6h_class = "table-danger"
adx14_6h_desc = "Weak Trend Up"
- def arima_predictions(even_rows: bool = True):
- results_ARIMA = ta.seasonal_arima_model()
- start_date = df_1h.last_valid_index()
- end_date = start_date + datetime.timedelta(days=3)
- arima_pred = results_ARIMA.predict(
- start=str(start_date), end=str(end_date), dynamic=True
- )
-
- if even_rows:
- arima_pred_rows = arima_pred.iloc[::2]
- else:
- arima_pred_rows = arima_pred.iloc[1::2]
-
- html = ""
- for index, pred in arima_pred_rows.items():
- html += f"""
-
- = ticker[1] else 'table-danger'}>
- | {index} |
- {pred} |
-
-
- """
-
- return html
-
return f"""
{header()}
@@ -955,7 +929,6 @@ def arima_predictions(even_rows: bool = True):
Time |
Prediction |
- {arima_predictions(True)}
@@ -964,7 +937,6 @@ def arima_predictions(even_rows: bool = True):
Time |
Prediction |
- {arima_predictions(False)}