cu_vwap_ind added

setup.py

@@ -2,7 +2,7 @@ from setuptools import setup, find_packages
 
 setup(
     name='ttools',
-    version='0.1.9',
+    version='0.2.0',
     packages=find_packages(),
     install_requires=[
         'vectorbtpro',

tests/vbt-anchored.py

@@ -1,3 +1,6 @@
-import ttools
+import ttools as tts
+
+#ttools.AnchoredIndicator("talib:MOM")
+
+from ttools import cu_vwap_ind
 
-#ttools.AnchoredIndicator("talib:MOM")

ttools/__init__.py

@@ -1 +1,2 @@
-from .vbtutils import AnchoredIndicator, create_mask_from_window, isrising, isfalling
+from .vbtutils import AnchoredIndicator, create_mask_from_window, isrising, isfalling
+from .vbtindicators import cu_vwap_ind

ttools/vbtindicators.py

@@ -0,0 +1,56 @@
+import numpy as np
+from numba import jit
+import vectorbtpro as vbt
+from vectorbtpro import _typing as tp
+from vectorbtpro.base.wrapping import ArrayWrapper
+from vectorbtpro.utils.template import RepFunc
+
+def substitute_anchor(wrapper: ArrayWrapper, anchor: tp.Optional[tp.FrequencyLike]) -> tp.Array1d:
+    """Substitute reset frequency by group lens. It is array of number of elements of each group."""
+    if anchor is None:
+        return np.array([wrapper.shape[0]])
+    return wrapper.get_index_grouper(anchor).get_group_lens()
+
+@jit(nopython=True)
+def vwap_cum(high, low, close, volume, group_lens):
+    #anchor based grouping - prepare group indexes
+    group_end_idxs = np.cumsum(group_lens)
+    group_start_idxs = group_end_idxs - group_lens
+
+    #prepare output
+    out = np.full(volume.shape, np.nan, dtype=np.float_)
+
+    hlcc4 = (high + low + close + close) / 4
+
+    #iterate over groups
+    for group in range(len(group_lens)):
+        from_i = group_start_idxs[group]
+        to_i = group_end_idxs[group]
+        nom_cumsum = 0
+        denum_cumsum = 0
+        #for each group do this (it is just np.cumsum(hlcc4 * volume) / np.sum(volume) iteratively)
+        for i in range(from_i, to_i):
+            nom_cumsum += volume[i] * hlcc4[i]
+            denum_cumsum += volume[i]
+            if denum_cumsum == 0:
+                out[i] = np.nan
+            else:
+                out[i] = nom_cumsum / denum_cumsum
+    return out
+
+#cumulative anchored vwap on HLCC4 price
+cu_vwap_ind = vbt.IF(
+    class_name='CUVWAP',
+    input_names=['high', 'low', 'close', 'volume'],
+    param_names=['anchor'],
+    output_names=['vwap']
+).with_apply_func(vwap_cum,
+                takes_1d=True,
+                param_settings=dict(
+                    anchor=dict(template=RepFunc(substitute_anchor)),
+                ),
+                anchor="D",
+                )
+
+#vwap_cum = vwap_ind.run(s12_data.high, s12_data.low, s12_data.close, s12_data.volume, anchor="min")
+vbt.IF.register_custom_indicator(cu_vwap_ind)