remove remaining collar voltage code from core library

ecoscope/io/utils.py

@@ -25,29 +25,6 @@ def pack_columns(dataframe: pd.DataFrame, columns: typing.List):
     return dataframe
 
 
-def extract_voltage(s: typing.Dict):
-    """
-    Extracts voltage from different source-provider in EarthRanger
-    Parameters
-    ----------
-    s: typing.Dict
-
-    Returns
-    -------
-    typing.Any
-
-    """
-    additional = s["extra__observation_details"] or {}
-    voltage = additional.get("battery", None)  # savannah tracking
-    if not voltage:
-        voltage = additional.get("mainVoltage", None)  # vectronics
-    if not voltage:
-        voltage = additional.get("batt", None)  # AWT
-    if not voltage:
-        voltage = additional.get("power", None)  # Followit
-    return voltage
-
-
 def download_file(url, path, overwrite_existing=False, chunk_size=1024, **request_kwargs):
     r = requests.get(url, stream=True, **request_kwargs)
 

ecoscope/plotting/__init__.py

@@ -1,7 +1,6 @@
 from ecoscope.plotting.plot import (
     EcoPlotData,
     add_seasons,
-    collar_event_timeline,
     ecoplot,
     mcp,
     nsd,
@@ -12,7 +11,6 @@
 __all__ = [
     "EcoPlotData",
     "add_seasons",
-    "collar_event_timeline",
     "ecoplot",
     "mcp",
     "nsd",

ecoscope/plotting/plot.py

@@ -1,18 +1,10 @@
-import logging
-import os
-import uuid
-
 import numpy as np
 import pandas as pd
 import plotly.graph_objs as go
 import shapely
 from plotly.subplots import make_subplots
 from sklearn.neighbors import KernelDensity
 
-from ecoscope.io.utils import extract_voltage
-
-logger = logging.getLogger(__name__)
-
 
 class EcoPlotData:
     def __init__(self, grouped, x_col="x", y_col="y", groupby_style=None, **style):
@@ -158,42 +150,6 @@ def add_seasons(fig, season_df):
     return fig
 
 
-def collar_event_timeline(relocations, collar_events):
-    fig = go.FigureWidget()
-
-    ys = [0]
-    if not collar_events.empty:
-        times = collar_events["time"].to_list()
-        times.append(relocations["fixtime"][-1])
-        xs = [[times[i]] * 3 + [times[i + 1]] for i in range(len(collar_events))]
-        ys = [[0, i + 1, 0, 0] for i in range(len(collar_events))]
-        colors = collar_events["colors"]
-
-        for x, y, color in zip(xs, ys, colors):
-            fig.add_trace(go.Scatter(x=x, y=y, line_color=color))
-            fig.update_layout(
-                annotations=[
-                    go.layout.Annotation(x=row.time, y=i, text=f"{row.event_type}<br>{row.time.date()}")
-                    for i, (_, row) in enumerate(collar_events.iterrows(), 1)
-                ]
-            )
-
-    x = relocations.fixtime
-    y = np.full(len(x), np.max(ys) / 10)
-    fig.add_trace(go.Scatter(x=x, y=y, line_color="rgb(0,0,255)", mode="markers", marker_size=1))
-
-    fig.update_layout(
-        margin_l=0,
-        margin_r=0,
-        margin_t=0,
-        margin_b=15,
-        yaxis_visible=False,
-        showlegend=False,
-    )
-
-    return fig
-
-
 def mcp(relocations):
     relocations = relocations.to_crs(relocations.estimate_utm_crs())
 

notebooks/01. IO/EarthRanger_IO.ipynb

@@ -23,7 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
@@ -644,9 +644,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "spatial_feature = er_io.get_spatial_feature(\n",
-    "                            spatial_feature_id=\"8868718f-0154-45bf-a74d-a66706ef958f\"\n",
-    "                          )\n",
+    "spatial_feature = er_io.get_spatial_feature(spatial_feature_id=\"8868718f-0154-45bf-a74d-a66706ef958f\")\n",
     "spatial_feature"
    ]
   },
@@ -663,9 +661,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "spatial_features = er_io.get_spatial_features_group(\n",
-    "                             spatial_features_group_id=\"15698426-7e0f-41df-9bc3-495d87e2e097\"\n",
-    "                           )\n",
+    "spatial_features = er_io.get_spatial_features_group(spatial_features_group_id=\"15698426-7e0f-41df-9bc3-495d87e2e097\")\n",
     "spatial_features"
    ]
   },