🧹 only parse f16 & update tests

Author: jvdd

plotly_resampler/figure_resampler/figure_resampler_interface.py

@@ -18,7 +18,6 @@
 from uuid import uuid4
 from collections import namedtuple
 
-import orjson
 import dash
 import numpy as np
 import pandas as pd
@@ -293,6 +292,7 @@ def _check_update_trace_data(
                 hf_series, hf_trace_data["max_n_samples"]
             )
             # Also parse the data types to an orjson compatible format
+            # Note this can be removed once orjson supports f16
             trace["x"] = self._parse_dtype_orjson(s_res.index)
             trace["y"] = self._parse_dtype_orjson(s_res.values)
             # todo -> first draft & not MP safe
@@ -702,15 +702,6 @@ def _parse_get_trace_props(
                 except ValueError:
                     hf_y = hf_y.astype("str")
 
-            msg = (
-                "Plotly-Resampler its aggregator functions do not support the float128"
-                + " dtype, so please consider casting your data to float64\n."
-                + " If you have an eligible usecase where float128 still is necessary,"
-                + " please consider making an issue on GitHub."
-            )
-            assert hf_x.dtype != np.float128, msg
-            assert hf_y.dtype != np.float128, msg
-
             assert len(hf_x) == len(hf_y), "x and y have different length!"
         else:
             self._print(f"trace {trace['type']} is not a high-frequency trace")
@@ -1296,16 +1287,9 @@ def _parse_dtype_orjson(series: np.ndarray) -> np.ndarray:
         # NOTE:
         #    * float16 and float128 aren't supported with latest orjson versions (3.8.1)
         #    * this method assumes that the it will not get a float128 series
+        # -> this method can be removed if orjson supports float16
         if series.dtype in [np.float16]:
             return series.astype(np.float32)
-
-        # orjson < 3.8.0 encoding cannot encode with int16 & uint16 dtype
-        elif series.dtype in [np.int16, np.uint16]:
-            major_v, minor_v = list(map(int, orjson.__version__.split(".")))[:2]
-            if major_v < 3 or major_v == 3 and minor_v < 8:
-                if series.dtype == np.uint16:
-                    return series.astype("uint32")
-                return series.astype(np.int32)
         return series
 
     @staticmethod

tests/test_figure_resampler.py

@@ -102,6 +102,7 @@ def test_add_trace_not_resampling(float_series):
     )
 
 def test_various_dtypes(float_series):
+    # List of dtypes supported by orjson >= 3.8
     valid_dtype_list = [
         np.bool_,
         # ---- uints
@@ -115,29 +116,33 @@ def test_various_dtypes(float_series):
         np.int32,
         np.int64,
         # -------- floats
-        np.float16,
+        np.float16,  # currently not supported by orjson
         np.float32,
         np.float64,
     ]
     for dtype in valid_dtype_list:
         fig = FigureResampler(go.Figure(), default_n_shown_samples=1000)
+        # nb. datapoints > default_n_shown_samples
         fig.add_trace(
             go.Scatter(name="float_series"),
             hf_x=float_series.index,
             hf_y=float_series.astype(dtype),
-            limit_to_view=True,
         )
+        fig.full_figure_for_development()
 
-    invalid_dtype_list = [ np.float128 ]
+    # List of dtypes not supported by orjson >= 3.8
+    invalid_dtype_list = [ np.float16 ]
     for invalid_dtype in invalid_dtype_list:
         fig = FigureResampler(go.Figure(), default_n_shown_samples=1000)
-        with pytest.raises(AssertionError):
+        # nb. datapoints < default_n_shown_samples
+        with pytest.raises(TypeError):  
+            # if this test fails -> orjson supports f16 => remove casting frome code
             fig.add_trace(
                 go.Scatter(name="float_series"),
-                hf_x=float_series.index,
-                hf_y=float_series.astype(invalid_dtype),
-                limit_to_view=True,
+                hf_x=float_series.index[:500],
+                hf_y=float_series.astype(invalid_dtype)[:500],
             )
+            fig.full_figure_for_development()
 
 def test_max_n_samples(float_series):
     s = float_series[:5000]