Datetime range

README.md

@@ -179,13 +179,6 @@ The paper about the plotly-resampler toolkit itself (preprint): https://arxiv.or
   code: https://github.com/predict-idlab/MinMaxLTTB
 
 
-
-## Future work 🔨
-
-- [x] Support `.add_traces()` (currently only `.add_trace` is supported)
-- [x] Support `hf_color` and `hf_markersize`, see [#148](https://github.com/predict-idlab/plotly-resampler/pull/148)
-- [x] Integrate with [tsdownsample](https://github.com/predict-idlab/tsdownsample) :racehorse:
-
 <br>
 
 ---

plotly_resampler/aggregation/plotly_aggregator_parser.py

@@ -38,7 +38,7 @@ def to_same_tz(
             return None
         elif reference_tz is not None:
             if ts.tz is not None:
-                assert ts.tz.zone == reference_tz.zone
+                assert ts.tz.__str__() == reference_tz.__str__()
                 return ts
             else:  # localize -> time remains the same
                 return ts.tz_localize(reference_tz)

tests/test_figure_resampler.py

@@ -7,6 +7,7 @@
 import multiprocessing
 import subprocess
 import time
+from datetime import timedelta
 from typing import List
 
 import numpy as np
@@ -124,12 +125,16 @@ def test_various_dtypes(float_series):
         np.float64,
     ]
     for dtype in valid_dtype_list:
+        if np.issubdtype(dtype, np.unsignedinteger):
+            fsv = float_series.astype("int").astype(dtype)
+        else:
+            fsv = float_series.astype(dtype)
         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),
+            hf_x=fsv.index,
+            hf_y=fsv,
         )
         fig.full_figure_for_development()
 
@@ -627,6 +632,50 @@ def test_set_hfx_tz_aware_series():
     assert all(fr.hf_data[0]["x"] == pd.DatetimeIndex(df.timestamp))
 
 
+def test_tz_xaxis_range():
+    # test related to issue 212 - github.com/predict-idlab/plotly-resampler/issues/212
+    n = 50_000
+    s = pd.Series(
+        index=pd.date_range("2020-01-01", periods=n, freq="1min", tz="UTC"),
+        data=23 + np.random.randn(n),
+    )
+
+    fig = go.Figure(
+        layout=go.Layout(
+            title=dict(
+                text="AirT test timeseries",
+                y=0.98,
+                x=0.5,
+                xanchor="center",
+                yanchor="top",
+            ),
+            xaxis=dict(title="Time", type="date"),
+            yaxis=dict(title="Air Temp (ºC)", range=[20, 30], fixedrange=True),
+            template="seaborn",
+            margin=dict(l=50, r=50, t=50, b=50, pad=5),
+            showlegend=True,
+        )
+    )
+
+    fr = FigureResampler(fig, verbose=True, default_n_shown_samples=2000)
+    fr.add_trace(go.Scattergl(name="AirT", mode="markers"), hf_x=s.index, hf_y=s)
+    fr.add_trace(go.Scattergl(name="AirT", mode="markers", x=s.index, y=s))
+
+    fr.add_vline(x=s.index[0])
+    fr.add_vline(x=s.index[-1])
+
+    start = s.index[0] - timedelta(hours=48)
+    end = s.index[-1] + timedelta(hours=48)
+
+    fr.update_xaxes(range=[start, end])
+
+    # verify whether the update was performed correctly
+    out = fr.construct_update_data({"xaxis.range[0]": start, "xaxis.range[1]": end})
+    assert len(out) == 3
+    assert len(out[1]["x"]) == 2000
+    assert len(out[2]["x"]) == 2000
+
+
 def test_datetime_hf_x_no_index():
     df = pd.DataFrame(
         {"timestamp": pd.date_range("2020-01-01", "2020-01-02", freq="1s")}