Fix importing json templates

Author: polakowo

MANIFEST.in

@@ -0,0 +1 @@
+recursive-include vectorbt/templates *.json

setup.py

@@ -5,14 +5,17 @@
 
 setup(
     name='vectorbt',
-    version='0.15.1',
+    version='0.15.2',
     description='Python library for backtesting and analyzing trading strategies at scale',
     author='Oleg Polakow',
     author_email='[email protected]',
     long_description=long_description,
     long_description_content_type="text/markdown",
     url='https://github.com/polakowo/vectorbt',
     packages=find_packages(),
+    package_data={
+        'vectorbt': ['templates/*.json']
+    },
     install_requires=[
         'numpy', 
         'pandas',

tests/test_generic.py

@@ -8,6 +8,8 @@
 from vectorbt.generic import nb
 from vectorbt.generic.drawdowns import Drawdowns
 
+seed = 42
+
 day_dt = np.timedelta64(86400000000000)
 
 df = pd.DataFrame({
@@ -186,6 +188,34 @@ def test_split_into_ranges(self):
         with pytest.raises(Exception) as e_info:
             df.vbt.split_into_ranges(start_idxs=[0, 1], end_idxs=[2, 4])
 
+    def test_shuffle(self):
+        pd.testing.assert_series_equal(
+            df['a'].vbt.shuffle(seed=seed),
+            pd.Series(
+                np.array([2.0, np.nan, 3.0, 1.0, 4.0]),
+                index=df['a'].index,
+                name=df['a'].name
+            )
+        )
+        np.testing.assert_array_equal(
+            df['a'].vbt.shuffle(seed=seed).values,
+            nb.shuffle_1d_nb(df['a'].values, seed=seed)
+        )
+        pd.testing.assert_frame_equal(
+            df.vbt.shuffle(seed=seed),
+            pd.DataFrame(
+                np.array([
+                    [2., 2., 2.],
+                    [np.nan, 4., 1.],
+                    [3., 3., 2.],
+                    [1., np.nan, 1.],
+                    [4., 1., np.nan]
+                ]),
+                index=df.index,
+                columns=df.columns
+            )
+        )
+
     @pytest.mark.parametrize(
         "test_value",
         [-1, 0., np.nan],

tests/test_signals.py

@@ -50,34 +50,6 @@ def test_freq(self):
         assert pd.Series([False, True]).vbt.signals(freq='3D').wrapper.freq == day_dt * 3
         assert pd.Series([False, True]).vbt.signals(freq=np.timedelta64(4, 'D')).wrapper.freq == day_dt * 4
 
-    def test_shuffle(self):
-        pd.testing.assert_series_equal(
-            sig['a'].vbt.signals.shuffle(seed=seed),
-            pd.Series(
-                np.array([False, False, False, True, True]),
-                index=sig['a'].index,
-                name=sig['a'].name
-            )
-        )
-        np.testing.assert_array_equal(
-            sig['a'].vbt.signals.shuffle(seed=seed).values,
-            nb.shuffle_1d_nb(sig['a'].values, seed=seed)
-        )
-        pd.testing.assert_frame_equal(
-            sig.vbt.signals.shuffle(seed=seed),
-            pd.DataFrame(
-                np.array([
-                    [False, False, False],
-                    [False, True, False],
-                    [False, False, False],
-                    [True, False, False],
-                    [True, True, True]
-                ]),
-                index=sig.index,
-                columns=sig.columns
-            )
-        )
-
     @pytest.mark.parametrize(
         "test_n",
         [1, 2, 3, 4, 5],

vectorbt/base/accessors.py

@@ -65,11 +65,11 @@ def empty(cls, shape, fill_value=np.nan, **kwargs):
         return pd.DataFrame(np.full(shape, fill_value), **kwargs)
 
     @classmethod
-    def empty_like(cls, other, fill_value=np.nan):
+    def empty_like(cls, other, fill_value=np.nan, **kwargs):
         """Generate an empty Series/DataFrame like `other` and fill with `fill_value`."""
         if checks.is_series(other):
-            return cls.empty(other.shape, fill_value=fill_value, index=other.index, name=other.name)
-        return cls.empty(other.shape, fill_value=fill_value, index=other.index, columns=other.columns)
+            return cls.empty(other.shape, fill_value=fill_value, index=other.index, name=other.name, **kwargs)
+        return cls.empty(other.shape, fill_value=fill_value, index=other.index, columns=other.columns, **kwargs)
 
     # ############# Index and columns ############# #
 
@@ -336,10 +336,10 @@ def concat(self_or_cls, *others, keys=None, broadcast_kwargs={}):
             objs = (self_or_cls._obj,) + others
         broadcasted = reshape_fns.broadcast(*objs, **broadcast_kwargs)
         broadcasted = tuple(map(reshape_fns.to_2d, broadcasted))
-        concatenated = pd.concat(broadcasted, axis=1, keys=keys)
-        if np.all(concatenated.columns == 0):
-            concatenated.columns = pd.RangeIndex(start=0, stop=len(concatenated.columns), step=1)
-        return concatenated
+        out = pd.concat(broadcasted, axis=1, keys=keys)
+        if not isinstance(out.columns, pd.MultiIndex) and np.all(out.columns == 0):
+            out.columns = pd.RangeIndex(start=0, stop=len(out.columns), step=1)
+        return out
 
     def apply_and_concat(self, ntimes, *args, apply_func=None, to_2d=False, keys=None, **kwargs):
         """Apply `apply_func` `ntimes` times and concatenate the results along columns.

vectorbt/generic/accessors.py

@@ -74,6 +74,7 @@
 
 
 @add_nb_methods([
+    nb.shuffle_nb,
     nb.fillna_nb,
     nb.fshift_nb,
     nb.diff_nb,

vectorbt/generic/nb.py

@@ -17,6 +17,28 @@
 from vectorbt.generic.enums import DrawdownStatus, drawdown_dt
 
 
+@njit(cache=True)
+def shuffle_1d_nb(a, seed=None):
+    """Shuffle each column in `a`.
+
+    Specify `seed` to make output deterministic."""
+    if seed is not None:
+        np.random.seed(seed)
+    return np.random.permutation(a)
+
+
+@njit(cache=True)
+def shuffle_nb(a, seed=None):
+    """2-dim version of `shuffle_1d_nb`."""
+    if seed is not None:
+        np.random.seed(seed)
+    out = np.empty_like(a, dtype=a.dtype)
+
+    for col in range(a.shape[1]):
+        out[:, col] = np.random.permutation(a[:, col])
+    return out
+
+
 @njit(cache=True)
 def prepend_1d_nb(a, n, value):
     """Prepend value `n` times."""

vectorbt/settings.py

@@ -12,7 +12,7 @@
 
 import numpy as np
 import json
-import os
+import pkgutil
 
 from vectorbt.utils.config import Config
 
@@ -60,17 +60,13 @@
 """
 
 # Templates
-with open(os.path.join(os.path.dirname(__file__), 'templates/light.json')) as json_file:
-    light_template = Config(json.load(json_file))
-    """_"""
+light_template = Config(json.loads(pkgutil.get_data(__name__, "templates/light.json")))
 
-    __pdoc__['light_template'] = "Light template."
+__pdoc__['light_template'] = "Light template."
 
-with open(os.path.join(os.path.dirname(__file__), 'templates/dark.json')) as json_file:
-    dark_template = Config(json.load(json_file))
-    """_"""
+dark_template = Config(json.loads(pkgutil.get_data(__name__, "templates/dark.json")))
 
-    __pdoc__['dark_template'] = "Dark template."
+__pdoc__['dark_template'] = "Dark template."
 
 # Layout
 layout = Config(

vectorbt/signals/accessors.py

@@ -50,7 +50,6 @@
 
 
 @add_nb_methods([
-    nb.shuffle_nb,
     nb.fshift_nb,
 ], module_name='vectorbt.signals.nb')
 class Signals_Accessor(Generic_Accessor):
@@ -90,7 +89,7 @@ def empty(cls, *args, fill_value=False, **kwargs):
         2020-01-05  False  False  False
         ```
         """
-        return Generic_Accessor.empty(*args, fill_value=fill_value, **kwargs)
+        return Generic_Accessor.empty(*args, fill_value=fill_value, dtype=bool, **kwargs)
 
     @classmethod
     def empty_like(cls, *args, fill_value=False, **kwargs):
@@ -116,7 +115,7 @@ def empty_like(cls, *args, fill_value=False, **kwargs):
         2020-01-05  False  False  False
         ```
         """
-        return Generic_Accessor.empty_like(*args, fill_value=fill_value, **kwargs)
+        return Generic_Accessor.empty_like(*args, fill_value=fill_value, dtype=bool, **kwargs)
 
     # ############# Signal generation ############# #
 

vectorbt/signals/nb.py

@@ -145,28 +145,6 @@ def generate_enex_nb(shape, entry_wait, exit_wait, entry_choice_func_nb,
 # ############# Random ############# #
 
 
-@njit(cache=True)
-def shuffle_1d_nb(a, seed=None):
-    """Shuffle each column in `a`.
-
-    Specify `seed` to make output deterministic."""
-    if seed is not None:
-        np.random.seed(seed)
-    return np.random.permutation(a)
-
-
-@njit(cache=True)
-def shuffle_nb(a, seed=None):
-    """2-dim version of `shuffle_1d_nb`."""
-    if seed is not None:
-        np.random.seed(seed)
-    out = np.empty_like(a, dtype=np.bool_)
-
-    for col in range(a.shape[1]):
-        out[:, col] = np.random.permutation(a[:, col])
-    return out
-
-
 @njit(cache=True)
 def rand_choice_nb(from_i, to_i, col, n):
     """`choice_func_nb` to randomly pick `n` values from range `[from_i, to_i)`.