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fix: single track plots for ATL08 variables #408

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fix: single track plots for ATL08 variables #408

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f40226b
fix: single track plots for ATL08 variables
tsutterley May 30, 2024
f8b9c50
Update ipysliderule.py
tsutterley Jun 3, 2024
4b8c918
add function to get version for a short_name
tsutterley Jun 25, 2024
9bc76ee
numpy 2.0 deprecated `np.float_`
tsutterley Jun 25, 2024
2a5f604
make draw control a map object attribute
tsutterley Jun 25, 2024
0444799
save sliderule crs metadata as json in parquet output
tsutterley Jun 25, 2024
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19 changes: 19 additions & 0 deletions clients/python/sliderule/earthdata.py
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Original file line number Diff line number Diff line change
Expand Up @@ -471,6 +471,25 @@ def __stac_search(provider, short_name, collections, polygons, time_start, time_
# return geojson dictionary
return geojson

#
# Get Version from DATASETS
#
def __get_version(short_name):

# check parameters
if short_name == None:
raise sliderule.FatalError("Must supply short name to CMR query")
elif short_name not in DATASETS:
raise sliderule.FatalError("Must supply a supported dataset: " + short_name)

# attempt to fill in version
version = DATASETS[short_name]["version"]
if version == None:
raise sliderule.FatalError("Unable to determine version for CMR query")

# return version string (cannot be None)
return version

#
# Get Provider from DATASETS
#
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8 changes: 5 additions & 3 deletions clients/python/sliderule/io.py
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Original file line number Diff line number Diff line change
Expand Up @@ -262,7 +262,7 @@ def attributes_encoder(attr):
if isinstance(attr, (np.int_, np.intc, np.intp, np.int8, np.int16, np.int32,
np.int64, np.uint8, np.uint16, np.uint32, np.uint64)):
return int(attr)
elif isinstance(attr, (np.float_, np.float16, np.float32, np.float64)):
elif isinstance(attr, (np.float16, np.float32, np.float64)):
return float(attr)
elif isinstance(attr, (np.ndarray)):
return attr.tolist()
Expand Down Expand Up @@ -482,8 +482,10 @@ def to_parquet(gdf, filename, **kwargs):
)
# output metadata
output = {}
# remove request polygon from output parameters
if 'poly' in kwargs['parameters']:
kwargs['parameters'].pop('poly')
# for each adjustable sliderule parameter
[kwargs['parameters'].pop(p) for p in ['poly']]
for p,val in kwargs['parameters'].items():
# try to convert the parameter if available
try:
Expand All @@ -492,7 +494,7 @@ def to_parquet(gdf, filename, **kwargs):
pass
# save CRS to JSON
crs = pyproj.CRS.from_string(kwargs['crs'])
output['crs'] = crs.to_string()
output['crs'] = crs.to_json_dict()
# save each region following GeoJSON specification
output['type'] = 'FeatureCollection'
output['features'] = []
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79 changes: 40 additions & 39 deletions clients/python/sliderule/ipysliderule.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2026,17 +2026,17 @@ def __init__(self, projection, **kwargs):
# keep track of cursor position
self.map.on_interaction(self.handle_interaction)
# add control for drawing polygons or bounding boxes
draw_control = ipyleaflet.DrawControl(polyline={},circlemarker={},
self.draw_control = ipyleaflet.DrawControl(polyline={},circlemarker={},
edit=False)
shapeOptions = {'color':kwargs['color'],'fill_color':kwargs['color']}
draw_control.rectangle = dict(shapeOptions=shapeOptions,
self.draw_control.rectangle = dict(shapeOptions=shapeOptions,
metric=['km','m'])
draw_control.polygon = dict(shapeOptions=shapeOptions,
self.draw_control.polygon = dict(shapeOptions=shapeOptions,
allowIntersection=False, showArea=True, metric=['km','m'])
# create regions
self.regions = []
draw_control.on_draw(self.handle_draw)
self.map.add(draw_control)
self.draw_control.on_draw(self.handle_draw)
self.map.add(self.draw_control)
# initialize data and colorbars
self.geojson = None
self.tooltip = None
Expand Down Expand Up @@ -2949,22 +2949,22 @@ def plot(self, **kwargs):
if (cycle < kwargs['cycle_start']):
continue
# reduce data frame to RGT, ground track and cycle
atl06 = self._gdf[
gdf = self._gdf[
(self._gdf['rgt'] == RGT) &
(self._gdf['gt'] == GT) &
(self._gdf['cycle'] == cycle)]
if not any(atl06[column].values):
if not any(gdf[column].values):
continue
# set index to along-track distance
atl06['x_atc'] -= kwargs['x_offset']
atl06.set_index('x_atc', inplace=True)
gdf['x_atc'] -= kwargs['x_offset']
gdf.set_index('x_atc', inplace=True)
# plot reduced data frame
l, = ax.plot(atl06.index.values,
atl06[column].values,
l, = ax.plot(gdf.index.values,
gdf[column].values,
marker='.', lw=0, ms=1.5)
# create legend element for cycle
if (kwargs['legend_label'] == 'date'):
label = atl06.index[0].strftime('%Y-%m-%d')
label = gdf.index[0].strftime('%Y-%m-%d')
elif (kwargs['legend_label'] == 'cycle'):
label = f'Cycle {cycle:0.0f}'
# append handle to legend
Expand All @@ -2977,76 +2977,77 @@ def plot(self, **kwargs):
elif (kwargs['kind'] == 'scatter'):
# extract orbital cycle parameters
cycle = int(kwargs['cycle'])
if (kwargs['data_type'] == 'atl03'):
data_type = kwargs['data_type']
if (data_type == 'atl03'):
# reduce entered data frame to RGT, ground track and cycle
atl03 = self._gdf[(self._gdf['rgt'] == RGT) &
gdf = self._gdf[(self._gdf['rgt'] == RGT) &
(self._gdf['track'] == self.PT(GT)) &
(self._gdf['pair'] == self.LR(GT)) &
(self._gdf['cycle'] == cycle)]
# set index to along-track distance
atl03['segment_dist'] += atl03['x_atc']
atl03['segment_dist'] -= kwargs['x_offset']
atl03.set_index('segment_dist', inplace=True)
if (kwargs['data_type'] == 'atl03') and (kwargs['classification'] == 'atl08'):
gdf['segment_dist'] += gdf['x_atc']
gdf['segment_dist'] -= kwargs['x_offset']
gdf.set_index('segment_dist', inplace=True)
if (data_type == 'atl03') and (kwargs['classification'] == 'atl08'):
# noise, ground, canopy, top of canopy, unclassified
colormap = np.array(['c','b','limegreen','g','y'])
classes = ['noise','ground','canopy','top of canopy','unclassified']
sc = ax.scatter(atl03.index.values, atl03["height"].values,
c=colormap[atl03["atl08_class"].values.astype('i')],
sc = ax.scatter(gdf.index.values, gdf[column].values,
c=colormap[gdf["atl08_class"].values.astype('i')],
s=1.5, rasterized=True)
# append handles to legend
for i,lab in enumerate(classes):
handle = matplotlib.lines.Line2D([0], [0],
color=colormap[i], lw=6, label=lab)
legend_handles.append(handle)
elif (kwargs['data_type'] == 'atl03') and (kwargs['classification'] == 'yapc'):
sc = ax.scatter(atl03.index.values,
atl03["height"].values,
c=atl03["yapc_score"],
elif (data_type == 'atl03') and (kwargs['classification'] == 'yapc'):
sc = ax.scatter(gdf.index.values,
gdf[column].values,
c=gdf["yapc_score"],
cmap=kwargs['cmap'],
s=1.5, rasterized=True)
plt.colorbar(sc)
elif (kwargs['data_type'] == 'atl03') and (kwargs['classification'] == 'atl03'):
elif (data_type == 'atl03') and (kwargs['classification'] == 'atl03'):
# background, buffer, low, medium, high
colormap = np.array(['y','c','b','g','m'])
confidences = ['background','buffer','low','medium','high']
# reduce data frame to photon classified for surface
atl03 = atl03[atl03["atl03_cnf"] >= 0]
sc = ax.scatter(atl03.index.values, atl03["height"].values,
c=colormap[atl03["atl03_cnf"].values.astype('i')],
gdf = gdf[gdf["atl03_cnf"] >= 0]
sc = ax.scatter(gdf.index.values, gdf[column].values,
c=colormap[gdf["atl03_cnf"].values.astype('i')],
s=1.5, rasterized=True)
# append handles to legend
for i,lab in enumerate(confidences):
handle = matplotlib.lines.Line2D([0], [0],
color=colormap[i], lw=6, label=lab)
legend_handles.append(handle)
elif (kwargs['data_type'] == 'atl03'):
elif (data_type == 'atl03'):
# plot all available ATL03 points as gray
sc = ax.scatter(atl03.index.values, atl03["height"].values,
sc = ax.scatter(gdf.index.values, gdf[column].values,
c='0.4', s=0.5, rasterized=True)
# append handle to legend
handle = matplotlib.lines.Line2D([0], [0],
color='0.4', lw=6, label='ATL03')
legend_handles.append(handle)
# plot ATL06-SR segments for cycle and track
if (kwargs['data_type'] == 'atl06'):
atl06 = self._gdf[
# plot ATL06-SR or ATL08-SR segments for cycle and track
if data_type in ('atl06','atl08'):
gdf = self._gdf[
(self._gdf['rgt'] == RGT) &
(self._gdf['gt'] == GT) &
(self._gdf['cycle'] == cycle)]
# set index to along-track distance
atl06['x_atc'] -= kwargs['x_offset']
atl06.set_index('x_atc', inplace=True)
gdf['x_atc'] -= kwargs['x_offset']
gdf.set_index('x_atc', inplace=True)
# plot reduced data frame
sc = ax.scatter(atl06.index.values,
atl06["h_mean"].values,
sc = ax.scatter(gdf.index.values,
gdf[column].values,
c='red', s=2.5, rasterized=True)
handle = matplotlib.lines.Line2D([0], [0],
color='red', lw=6, label='ATL06-SR')
color='red', lw=6, label=f'{data_type.upper()}-SR')
legend_handles.append(handle)
# add axes labels
ax.set_xlabel('Along-Track Distance [m]')
ax.set_ylabel('Height (m)')
ax.set_ylabel(f'SlideRule {column}')
# add title
if kwargs['title']:
ax.set_title(kwargs['title'])
Expand Down
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