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Remove remaining CustomModel references

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This commit is contained in:
Matthias 2022-07-23 16:06:46 +02:00
parent 62f7606d2c
commit 8a3cffcd1b
4 changed files with 7 additions and 13 deletions
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12
docs/freqai.md
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@ -166,7 +166,7 @@ config setup includes:
Features are added by the user inside the `populate_any_indicators()` method of the strategy
by prepending indicators with `%` and labels are added by prepending `&`.
There are some important components/structures that the user *must* include when building their feature set.
As shown below, `with self.model.bridge.lock:` must be used to ensure thread safety - especially when using third
As shown below, `with self.freqai.lock:` must be used to ensure thread safety - especially when using third
party libraries for indicator construction such as TA-lib.
Another structure to consider is the location of the labels at the bottom of the example function (below `if set_generalized_indicators:`).
This is where the user will add single features and labels to their feature set to avoid duplication from
@ -191,7 +191,7 @@ various configuration parameters which multiply the feature set such as `include
:coin: the name of the coin which will modify the feature names.
"""
with self.model.bridge.lock:
with self.freqai.lock:
if informative is None:
informative = self.dp.get_pair_dataframe(pair, tf)
@ -370,7 +370,6 @@ for each pair, for each backtesting window within the bigger `--timerange`.
The Freqai strategy requires the user to include the following lines of code in the strategy:
```python
from freqtrade.freqai.strategy_bridge import CustomModel
def informative_pairs(self):
whitelist_pairs = self.dp.current_whitelist()
@ -385,9 +384,6 @@ The Freqai strategy requires the user to include the following lines of code in
informative_pairs.append((pair, tf))
return informative_pairs
def bot_start(self):
self.model = CustomModel(self.config)
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
self.freqai_info = self.config["freqai"]
@ -400,7 +396,7 @@ The Freqai strategy requires the user to include the following lines of code in
# the target mean/std values for each of the labels created by user in
# `populate_any_indicators()` for each training period.
dataframe = self.model.bridge.start(dataframe, metadata, self)
dataframe = self.freqai.start(dataframe, metadata, self)
return dataframe
```
@ -648,7 +644,7 @@ below this value. An example usage in the strategy may look something like:
dataframe["do_predict"],
dataframe["target_upper_quantile"],
dataframe["target_lower_quantile"],
) = self.model.bridge.start(dataframe, metadata, self)
) = self.freqai.start(dataframe, metadata, self)
return dataframe

1
freqtrade/templates/FreqaiExampleStrategy.py
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@ -19,7 +19,6 @@ class FreqaiExampleStrategy(IStrategy):
"""
Example strategy showing how the user connects their own
IFreqaiModel to the strategy. Namely, the user uses:
self.model = CustomModel(self.config)
self.freqai.start(dataframe, metadata)
to make predictions on their data. populate_any_indicators() automatically

6
tests/freqai/conftest.py
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@ -76,7 +76,7 @@ def get_freqai_live_analyzed_dataframe(mocker, freqaiconf):
strategy = get_patched_freqai_strategy(mocker, freqaiconf)
exchange = get_patched_exchange(mocker, freqaiconf)
strategy.dp = DataProvider(freqaiconf, exchange)
freqai = strategy.model.bridge
freqai = strategy.freqai
freqai.live = True
freqai.dk = FreqaiDataKitchen(freqaiconf, freqai.dd)
timerange = TimeRange.parse_timerange("20180110-20180114")
@ -91,7 +91,7 @@ def get_freqai_analyzed_dataframe(mocker, freqaiconf):
exchange = get_patched_exchange(mocker, freqaiconf)
strategy.dp = DataProvider(freqaiconf, exchange)
strategy.freqai_info = freqaiconf.get("freqai", {})
freqai = strategy.model.bridge
freqai = strategy.freqai
freqai.live = True
freqai.dk = FreqaiDataKitchen(freqaiconf, freqai.dd)
timerange = TimeRange.parse_timerange("20180110-20180114")
@ -107,7 +107,7 @@ def get_ready_to_train(mocker, freqaiconf):
exchange = get_patched_exchange(mocker, freqaiconf)
strategy.dp = DataProvider(freqaiconf, exchange)
strategy.freqai_info = freqaiconf.get("freqai", {})
freqai = strategy.model.bridge
freqai = strategy.freqai
freqai.live = True
freqai.dk = FreqaiDataKitchen(freqaiconf, freqai.dd)
timerange = TimeRange.parse_timerange("20180110-20180114")

1
tests/strategy/strats/freqai_test_strat.py
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@ -16,7 +16,6 @@ class freqai_test_strat(IStrategy):
"""
Example strategy showing how the user connects their own
IFreqaiModel to the strategy. Namely, the user uses:
self.model = CustomModel(self.config)
self.freqai.start(dataframe, metadata)
to make predictions on their data. populate_any_indicators() automatically