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Geomedian notebook #1148

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2e4221d
Geomedian notebook
margaretharrison Nov 7, 2023
005ec26
update GeoMAD with latest version
JM-GA Jun 14, 2024
36a24fe
update tests to use new GeoMAD products
JM-GA Jun 17, 2024
2a6975f
update export netcdf notebook with new GeoMAD
JM-GA Jun 17, 2024
edd03c5
Merge branch 'develop' into geomedian
JM-GA Jun 18, 2024
cb424ef
Update setup_test_datacube.sh
JM-GA Jun 18, 2024
38c1177
Update setup_test_datacube.sh
JM-GA Jun 18, 2024
e2d0fa4
Update setup_test_datacube.sh
JM-GA Jun 18, 2024
bf1ce5d
Update to new c3 grid path rows
JM-GA Jun 18, 2024
555e3e9
Update loading_data notebook to use new GeoMAD
JM-GA Jun 18, 2024
c3651fc
update plotting notebook with new GeoMAD
JM-GA Jun 20, 2024
02ed2dc
Update parallel processing notebook with new GeoMAD
JM-GA Jun 21, 2024
b4b992a
update Animated_timeseries with new GeoMAD
JM-GA Jun 21, 2024
09d81c7
Update DEA_Intertidal with new GeoMAD
JM-GA Jun 21, 2024
6025419
Update DEA_GeoMAD.ipynb
JM-GA Jun 21, 2024
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3,492 changes: 1,911 additions & 1,581 deletions Beginners_guide/04_Loading_data.ipynb
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5,912 changes: 3,055 additions & 2,857 deletions Beginners_guide/05_Plotting.ipynb
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1,770 changes: 987 additions & 783 deletions Beginners_guide/09_Parallel_processing_with_Dask.ipynb
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1,007 changes: 1,007 additions & 0 deletions DEA_products/DEA_GeoMAD.ipynb
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491 changes: 246 additions & 245 deletions DEA_products/DEA_Intertidal.ipynb
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4,733 changes: 2,407 additions & 2,326 deletions How_to_guides/Animated_timeseries.ipynb
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739 changes: 369 additions & 370 deletions How_to_guides/Exporting_NetCDFs.ipynb
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42 changes: 21 additions & 21 deletions Tests/setup_test_datacube.sh
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Expand Up @@ -20,7 +20,7 @@ for metadata_yaml in $(find ./dea-config/product_metadata -name '*.yaml'); do
done

# Index products we care about for dea-notebooks
for prod_def_yaml in $(find ./dea-config/products -name '*.yaml' -regex '.*\(ga_ls7e_nbart_gm_cyear_3\|ga_ls8c_nbart_gm_cyear_3\|ga_ls_fc_3\|ga_ls_wo_3\|ga_ls_wo_fq_cyear_3\|ga_ls_landcover_class_cyear_2\|high_tide_comp_20p\|low_tide_comp_20p\|ga_s2am_ard_3\|ga_s2bm_ard_3\|ga_ls5t_ard_3\|ga_ls7e_ard_3\|ga_ls8c_ard_3\|ga_ls9c_ard_3\|ga_ls_mangrove_cover_cyear_3\|ga_s2ls_intertidal_cyear_3\).*'); do
for prod_def_yaml in $(find ./dea-config/products -name '*.yaml' -regex '.*\(ga_ls7e_gm_cyear_3\|ga_ls8cls9c_gm_cyear_3\|ga_ls_fc_3\|ga_ls_wo_3\|ga_ls_wo_fq_cyear_3\|ga_ls_landcover_class_cyear_2\|high_tide_comp_20p\|low_tide_comp_20p\|ga_s2am_ard_3\|ga_s2bm_ard_3\|ga_ls5t_ard_3\|ga_ls7e_ard_3\|ga_ls8c_ard_3\|ga_ls9c_ard_3\|ga_ls_mangrove_cover_cyear_3\|ga_s2ls_intertidal_cyear_3\).*'); do
datacube product add $prod_def_yaml
done

Expand All @@ -35,26 +35,26 @@ s3-to-dc 's3://dea-public-data/derivative/ga_s2ls_intertidal_cyear_3/1-0-0/x080/
s3-to-dc 's3://dea-public-data/derivative/ga_ls_mangrove_cover_cyear_3/3-0-0/x33/y39/*/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls_mangrove_cover_cyear_3'

# Index GeoMAD
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x08/y27/2018--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x08/y27/2019--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x08/y27/2020--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x49/y24/2017--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls7e_nbart_gm_cyear_3/3-0-0/x49/y23/2015--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls7e_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls7e_nbart_gm_cyear_3/3-0-0/x49/y24/2015--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls7e_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x49/y23/2013--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x49/y23/2014--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x49/y23/2016--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x49/y23/2017--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x49/y24/2013--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x49/y24/2014--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x49/y24/2015--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x49/y24/2016--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x38/y19/2017--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x38/y19/2018--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x38/y19/2016--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x38/y19/2015--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x38/y19/2019--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8c_nbart_gm_cyear_3/3-0-0/x38/y19/2020--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8c_nbart_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x67/y39/2017--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x67/y38/2013--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x67/y38/2014--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x67/y38/2016--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x67/y38/2017--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x67/y39/2013--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x67/y39/2014--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x67/y39/2015--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x67/y39/2016--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x56/y34/2017--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x56/y34/2018--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x56/y34/2016--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x56/y34/2015--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x56/y34/2019--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x56/y34/2020--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x26/y42/2018--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x26/y42/2019--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls8cls9c_gm_cyear_3/4-0-0/x26/y42/2020--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls8cls9c_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls7e_gm_cyear_3/4-0-0/x67/y38/2015--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls7e_gm_cyear_3'
s3-to-dc 's3://dea-public-data/derivative/ga_ls7e_gm_cyear_3/4-0-0/x67/y39/2015--P1Y/*.odc-metadata.yaml' --no-sign-request --skip-lineage 'ga_ls7e_gm_cyear_3'

# Index FC
s3-to-dc 's3://dea-public-data/derivative/ga_ls_fc_3/2-5-0/096/084/1993/10/30/*.json' --no-sign-request --skip-lineage --stac 'ga_ls_fc_3'
Expand Down
126 changes: 126 additions & 0 deletions Tools/dea_tools/app/geomedian.py
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@@ -0,0 +1,126 @@
"""
Geomedian widget: generates an interactive visualisation of
the geomedian summary statistic.
"""

# Load modules
import ipywidgets as widgets
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import xarray as xr
from odc.algo import xr_geomedian

def run_app():

"""
An interactive app that allows users to visualise the difference between the median and geomedian time-series summary statistics. By modifying the red-green-blue values of three timesteps for a given pixel, the user changes the output summary statistics.

This allows a visual representation of the difference through the output values, RGB colour, as well as showing values plotted as a vector on a 3-dimensional space.

Last modified: December 2021
"""

# Define the red-green-blue sliders for timestep 1
p1r = widgets.IntSlider(description='Red', max=255, value=58)
p1g = widgets.IntSlider(description='Green', max=255, value=153)
p1b = widgets.IntSlider(description='Blue', max=255, value=68)

# Define the red-green-blue sliders for timestep 2
p2r = widgets.IntSlider(description='Red', max=255, value=208)
p2g = widgets.IntSlider(description='Green', max=255, value=221)
p2b = widgets.IntSlider(description='Blue', max=255, value=203)

# Define the red-green-blue sliders for timestep 3
p3r = widgets.IntSlider(description='Red', max=255, value=202)
p3g = widgets.IntSlider(description='Green', max=255, value=82)
p3b = widgets.IntSlider(description='Blue', max=255, value=33)

# Define the median calculation for the timesteps
def f(p1r, p1g, p1b, p2r, p2g, p2b, p3r, p3g, p3b):
print('Red Median = {}'.format(np.median([p1r, p2r, p3r])))
print('Green Median = {}'.format(np.median([p1g, p2g, p3g])))
print('Blue Median = {}'.format(np.median([p1b, p2b, p3b])))

# Define the geomedian calculation for the timesteps
def g(p1r, p1g, p1b, p2r, p2g, p2b, p3r, p3g, p3b):
print('Red Geomedian = {:.2f}'.format(xr_geomedian(xr.Dataset({"red": (("x", "y", "time"), [[[np.float32(p1r), np.float32(p2r), np.float32(p3r)]]]), "green": (("x", "y", "time"), [[[np.float32(p1g), np.float32(p2g), np.float32(p3g)]]]), "blue": (("x", "y", "time"), [[[np.float32(p1b), np.float32(p2b), np.float32(p3b)]]])})).red.values.ravel()[0]))
print('Green Geomedian = {:.2f}'.format(xr_geomedian(xr.Dataset({"red": (("x", "y", "time"), [[[np.float32(p1r), np.float32(p2r), np.float32(p3r)]]]), "green": (("x", "y", "time"), [[[np.float32(p1g), np.float32(p2g), np.float32(p3g)]]]), "blue": (("x", "y", "time"), [[[np.float32(p1b), np.float32(p2b), np.float32(p3b)]]])})).green.values.ravel()[0]))
print('Blue Geomedian = {:.2f}'.format(xr_geomedian(xr.Dataset({"red": (("x", "y", "time"), [[[np.float32(p1r), np.float32(p2r), np.float32(p3r)]]]), "green": (("x", "y", "time"), [[[np.float32(p1g), np.float32(p2g), np.float32(p3g)]]]), "blue": (("x", "y", "time"), [[[np.float32(p1b), np.float32(p2b), np.float32(p3b)]]])})).blue.values.ravel()[0]))

# Define the Timestep 1 box colour
def h(p1r, p1g, p1b):
fig1, axes1 = plt.subplots(figsize=(2,2))
fig1 = plt.imshow([[(p1r, p1g, p1b)]])
axes1.set_title('Timestep 1')
axes1.axis('off')
plt.show(fig1)

# Define the Timestep 2 box colour
def hh(p2r, p2g, p2b):
fig2, axes2 = plt.subplots(figsize=(2,2))
fig2 = plt.imshow([[(p2r, p2g, p2b)]])
axes2.set_title('Timestep 2')
axes2.axis('off')
plt.show(fig2)

# Define the Timestep 3 box colour
def hhh(p3r, p3g, p3b):
fig3, axes3 = plt.subplots(figsize=(2,2))
fig3 = plt.imshow([[(p3r, p3g, p3b)]])
axes3.set_title('Timestep 3')
axes3.axis('off')
plt.show(fig3)

# Define the Median RGB colour box
def i(p1r, p1g, p1b, p2r, p2g, p2b, p3r, p3g, p3b):
fig4, axes4 = plt.subplots(figsize=(3,3))
fig4 = plt.imshow([[(int(np.median([p1r, p2r, p3r])), int(np.median([p1g, p2g, p3g])), int(np.median([p1b, p2b, p3b])))]])
axes4.set_title('Median RGB - All timesteps')
axes4.axis('off')
plt.show(fig4)

# Define the Geomedian RGB colour box
def ii(p1r, p1g, p1b, p2r, p2g, p2b, p3r, p3g, p3b):
fig5, axes5 = plt.subplots(figsize=(3,3))
fig5 = plt.imshow([[(int(xr_geomedian(xr.Dataset({"red": (("x", "y", "time"), [[[np.float32(p1r), np.float32(p2r), np.float32(p3r)]]]), "green": (("x", "y", "time"), [[[np.float32(p1g), np.float32(p2g), np.float32(p3g)]]]), "blue": (("x", "y", "time"), [[[np.float32(p1b), np.float32(p2b), np.float32(p3b)]]])})).red.values.ravel()[0]), int(xr_geomedian(xr.Dataset({"red": (("x", "y", "time"), [[[np.float32(p1r), np.float32(p2r), np.float32(p3r)]]]), "green": (("x", "y", "time"), [[[np.float32(p1g), np.float32(p2g), np.float32(p3g)]]]), "blue": (("x", "y", "time"), [[[np.float32(p1b), np.float32(p2b), np.float32(p3b)]]])})).green.values.ravel()[0]), int(xr_geomedian(xr.Dataset({"red": (("x", "y", "time"), [[[np.float32(p1r), np.float32(p2r), np.float32(p3r)]]]), "green": (("x", "y", "time"), [[[np.float32(p1g), np.float32(p2g), np.float32(p3g)]]]), "blue": (("x", "y", "time"), [[[np.float32(p1b), np.float32(p2b), np.float32(p3b)]]])})).blue.values.ravel()[0]))]])
axes5.set_title('Geomedian RGB - All timesteps')
axes5.axis('off')
plt.show(fig5)

# Define 3-D axis to display vectors on
def j(p1r, p1g, p1b, p2r, p2g, p2b, p3r, p3g, p3b):
fig6 = plt.figure()
axes6 = fig6.add_subplot(111, projection='3d')
x = [p1r, p2r, p3r, int(np.median([p1r, p2r, p3r])), int(xr_geomedian(xr.Dataset({"red": (("x", "y", "time"), [[[np.float32(p1r), np.float32(p2r), np.float32(p3r)]]]), "green": (("x", "y", "time"), [[[np.float32(p1g), np.float32(p2g), np.float32(p3g)]]]), "blue": (("x", "y", "time"), [[[np.float32(p1b), np.float32(p2b), np.float32(p3b)]]])})).red.values.ravel()[0])]
y = [p1g, p2g, p3g, int(np.median([p1g, p2g, p3g])), int(xr_geomedian(xr.Dataset({"red": (("x", "y", "time"), [[[np.float32(p1r), np.float32(p2r), np.float32(p3r)]]]), "green": (("x", "y", "time"), [[[np.float32(p1g), np.float32(p2g), np.float32(p3g)]]]), "blue": (("x", "y", "time"), [[[np.float32(p1b), np.float32(p2b), np.float32(p3b)]]])})).green.values.ravel()[0])]
z = [p1b, p2b, p3b, int(np.median([p1b, p2b, p3b])), int(xr_geomedian(xr.Dataset({"red": (("x", "y", "time"), [[[np.float32(p1r), np.float32(p2r), np.float32(p3r)]]]), "green": (("x", "y", "time"), [[[np.float32(p1g), np.float32(p2g), np.float32(p3g)]]]), "blue": (("x", "y", "time"), [[[np.float32(p1b), np.float32(p2b), np.float32(p3b)]]])})).blue.values.ravel()[0])]
labels = [' 1', ' 2', ' 3', ' median', ' geomedian']
axes6.scatter(x, y, z, c=['black','black','black','r', 'blue'], marker='o')
axes6.set_xlabel('Red')
axes6.set_ylabel('Green')
axes6.set_zlabel('Blue')
axes6.set_xlim3d(0, 255)
axes6.set_ylim3d(0, 255)
axes6.set_zlim3d(0, 255)
for ax, ay, az, label in zip(x, y, z, labels):
axes6.text(ax, ay, az, label)
plt.title('Each band represents a dimension.')
plt.show()

# Define outputs
outf = widgets.interactive_output(f, {'p1r': p1r, 'p2r': p2r,'p3r': p3r, 'p1g': p1g, 'p2g': p2g,'p3g': p3g, 'p1b': p1b, 'p2b': p2b,'p3b': p3b})
outg = widgets.interactive_output(g, {'p1r': p1r, 'p2r': p2r,'p3r': p3r, 'p1g': p1g, 'p2g': p2g,'p3g': p3g, 'p1b': p1b, 'p2b': p2b,'p3b': p3b})

outh = widgets.interactive_output(h, {'p1r': p1r, 'p1g': p1g, 'p1b': p1b})
outhh = widgets.interactive_output(hh, {'p2r': p2r, 'p2g': p2g, 'p2b': p2b})
outhhh = widgets.interactive_output(hhh, {'p3r': p3r, 'p3g': p3g, 'p3b': p3b})

outi = widgets.interactive_output(i, {'p1r': p1r, 'p2r': p2r,'p3r': p3r, 'p1g': p1g, 'p2g': p2g,'p3g': p3g, 'p1b': p1b, 'p2b': p2b,'p3b': p3b})
outii = widgets.interactive_output(ii, {'p1r': p1r, 'p2r': p2r,'p3r': p3r, 'p1g': p1g, 'p2g': p2g,'p3g': p3g, 'p1b': p1b, 'p2b': p2b,'p3b': p3b})

outj = widgets.interactive_output(j, {'p1r': p1r, 'p2r': p2r,'p3r': p3r, 'p1g': p1g, 'p2g': p2g,'p3g': p3g, 'p1b': p1b, 'p2b': p2b,'p3b': p3b})

app_output = widgets.HBox([widgets.VBox([widgets.HBox([outh, widgets.VBox([ p1r, p1g, p1b])]), widgets.HBox([outhh, widgets.VBox([p2r, p2g, p2b])]), widgets.HBox([outhhh, widgets.VBox([ p3r, p3g, p3b])])]), widgets.VBox([widgets.HBox([widgets.VBox([outf, outi]), widgets.VBox([outg, outii])]), outj])])

return app_output
2 changes: 1 addition & 1 deletion Tools/dea_tools/app/widgetconstructors.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -274,7 +274,7 @@ def create_dea_wms_layer(product, date, **params):
----------
product : string
The Digital Earth Australia product to load
(e.g. 'ga_ls8c_nbart_gm_cyear_3')
(e.g. 'ga_ls8cls9c_gm_cyear_3')
date : string (yyyy-mm-dd format)
The date to load the product for

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