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nghiadang
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"""
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Wetlands insight tool widget, which can be used to run an interactive
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version of the wetlands insight tool.
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"""
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# Import required packages
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# Force GeoPandas to use Shapely instead of PyGEOS
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# In a future release, GeoPandas will switch to using Shapely by default.
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import os
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os.environ['USE_PYGEOS'] = '0'
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import datacube
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import warnings
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import seaborn as sns
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import matplotlib.pyplot as plt
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from datacube.utils.geometry import CRS
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from ipyleaflet import (
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WMSLayer,
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basemaps,
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basemap_to_tiles,
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Map,
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DrawControl,
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WidgetControl,
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LayerGroup,
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LayersControl,
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)
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from traitlets import Unicode
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from ipywidgets import (
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GridspecLayout,
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Button,
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Layout,
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HBox,
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VBox,
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HTML,
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Output,
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)
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import json
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import geopandas as gpd
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from io import BytesIO
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from dask.diagnostics import ProgressBar
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import deafrica_tools
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from deafrica_tools.dask import create_local_dask_cluster
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from deafrica_tools.wetlands import WIT_drill
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import deafrica_tools.app.widgetconstructors as deawidgets
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def make_box_layout():
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return Layout(
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#border='solid 1px black',
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margin='0px 10px 10px 0px',
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padding='5px 5px 5px 5px',
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width='100%',
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height='100%',
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)
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def create_expanded_button(description, button_style):
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return Button(
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description=description,
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button_style=button_style,
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layout=Layout(width="auto", height="auto"),
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)
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class wit_app(HBox):
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def __init__(self, lang=None):
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super().__init__()
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deafrica_tools.set_lang(lang)
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##########################################################
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# INITIAL ATTRIBUTES #
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self.startdate = "2020-01-01"
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self.enddate = "2020-03-01"
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self.mingooddata = 0.0
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self.resamplingfreq = "1M"
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self.out_csv = "example_WIT.csv"
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self.out_plot = "example_WIT.png"
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self.product_list = [
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(_("None"), "none"),
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(_("ESRI World Imagery"), "esri_world_imagery"),
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(_("Sentinel-2 Geomedian"), "gm_s2_annual"),
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(_("Water Observations from Space"), "wofs_ls_summary_annual"),
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]
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self.product = self.product_list[0][1]
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self.product_year = "2020-01-01"
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self.target = None
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self.action = None
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self.gdf_drawn = None
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##########################################################
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# HEADER FOR APP #
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# Create the Header widget
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header_title_text = _("Wetlands Insight Tool")
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instruction_text = _("Select parameters and AOI")
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self.header = deawidgets.create_html(f"<h3>{header_title_text}</h3><p>{instruction_text}</p>")
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self.header.layout = make_box_layout()
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##########################################################
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# HANDLER FUNCTION FOR DRAW CONTROL #
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# Define the action to take once something is drawn on the map
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def update_geojson(target, action, geo_json):
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self.action = action
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json_data = json.dumps(geo_json)
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binary_data = json_data.encode()
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io = BytesIO(binary_data)
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io.seek(0)
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gdf = gpd.read_file(io)
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gdf.crs = "EPSG:4326"
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self.gdf_drawn = gdf
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gdf_drawn_epsg6933 = gdf.copy().to_crs("EPSG:6933")
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m2_per_km2 = 10 ** 6
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area = gdf_drawn_epsg6933.area.values[0] / m2_per_km2
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polyarea_label = _('Total polygon area')
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polyarea_text = f"<p><b>{polyarea_label}</b>: {area:.2f} km<sup>2</sup></p>"
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if area <= 3000:
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confirmation_text = '<p style="color:#33cc33;">' + _('Area falls within recommended limit') + '</p>'
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self.header.value = header_title_text + polyarea_text + confirmation_text
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else:
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warning_text = '<p style="color:#ff5050;">' + _('Area is too large, please update your polygon') + '</p>'
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self.header.value = header_title_text + polyarea_text + warning_text
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##########################################################
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# WIDGETS FOR APP OUTPUTS #
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self.dask_client = Output(layout=make_box_layout())
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self.progress_bar = Output(layout=make_box_layout())
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self.wit_plot = Output(layout=make_box_layout())
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self.progress_header = deawidgets.create_html("")
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##########################################################
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# MAP WIDGET, DRAWING TOOLS, WMS LAYERS #
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# Create drawing tools
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desired_drawtools = ['rectangle', 'polygon']
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draw_control = deawidgets.create_drawcontrol(desired_drawtools)
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# Begin by displaying an empty layer group, and update the group with desired WMS on interaction.
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self.deafrica_layers = LayerGroup(layers=())
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self.deafrica_layers.name = _('Map Overlays')
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# Create map widget
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self.m = deawidgets.create_map()
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self.m.layout = make_box_layout()
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# Add tools to map widget
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self.m.add_control(draw_control)
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self.m.add_layer(self.deafrica_layers)
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# Store current basemap for future use
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self.basemap = self.m.basemap
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##########################################################
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# WIDGETS FOR APP CONTROLS #
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# Create parameter widgets
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startdate_picker = deawidgets.create_datepicker()
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enddate_picker = deawidgets.create_datepicker()
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min_good_data = deawidgets.create_boundedfloattext(self.mingooddata, 0.0, 1.0, 0.05)
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resampling_freq = deawidgets.create_inputtext(self.resamplingfreq, self.resamplingfreq)
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output_csv = deawidgets.create_inputtext(self.out_csv, self.out_csv)
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output_plot = deawidgets.create_inputtext(self.out_plot, self.out_plot)
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deaoverlay_dropdown = deawidgets.create_dropdown(self.product_list, self.product_list[0][1])
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run_button = create_expanded_button(_("Run"), "info")
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##########################################################
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# COLLECTION OF ALL APP CONTROLS #
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parameter_selection = VBox(
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[
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HTML("<b>" + _("Map Overlay:") + "</b>"),
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deaoverlay_dropdown,
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HTML("<b>" + _("Start Date:") + "</b>"),
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startdate_picker,
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HTML("<b>" + _("End Date:") + "</b>"),
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enddate_picker,
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HTML("<b>" + _("Minimum Good Data:") + "</b>"),
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min_good_data,
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HTML("<b>" + _("Resampling Frequency:") + "</b>"),
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resampling_freq,
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HTML("<b>" + _("Output CSV:") + "</b>"),
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output_csv,
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HTML("<b>" + _("Output Plot:") + "</b>"),
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output_plot,
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]
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)
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parameter_selection.layout = make_box_layout()
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##########################################################
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# SPECIFICATION OF APP LAYOUT #
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# Create the layout #[rowspan, colspan]
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grid = GridspecLayout(11, 10, height="1100px", width="auto")
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# Controls and Status
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grid[0, :] = self.header
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grid[1:6, 0:2] = parameter_selection
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grid[6, 0:2] = run_button
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# Dask and Progress info
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grid[1, 7:] = self.dask_client
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grid[2:7, 7:] = self.progress_bar
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# Map
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grid[1:7, 2:7] = self.m
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# Plot
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grid[7:, :] = self.wit_plot
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# Display using HBox children attribute
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self.children = [grid]
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##########################################################
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# SPECIFICATION UPDATE FUNCTIONS FOR EACH WIDGET #
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# Run update functions whenever various widgets are changed.
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startdate_picker.observe(self.update_startdate, "value")
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enddate_picker.observe(self.update_enddate, "value")
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min_good_data.observe(self.update_mingooddata, "value")
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resampling_freq.observe(self.update_resamplingfreq, "value")
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output_csv.observe(self.update_outputcsv, "value")
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output_plot.observe(self.update_outputplot, "value")
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deaoverlay_dropdown.observe(self.update_deaoverlay, "value")
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run_button.on_click(self.run_app)
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draw_control.on_draw(update_geojson)
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##############################################################
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# DEFINITION OF ALL UPDATE FUNCTIONS #
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# set the start date to the new edited date
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def update_startdate(self, change):
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self.startdate = change.new
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# set the end date to the new edited date
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def update_enddate(self, change):
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self.enddate = change.new
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# set the min good data
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def update_mingooddata(self, change):
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self.mingooddata = change.new
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# set the resampling frequency
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def update_resamplingfreq(self, change):
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self.resamplingfreq = change.new
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# set the output csv
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def update_outputcsv(self, change):
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self.out_csv = change.new
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# set the output plot
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def update_outputplot(self, change):
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self.out_plot = change.new
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# Update product
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def update_deaoverlay(self, change):
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self.product = change.new
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if self.product == "none":
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self.deafrica_layers.clear_layers()
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elif self.product == "esri_world_imagery":
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self.deafrica_layers.clear_layers()
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layer = basemap_to_tiles(basemaps.Esri.WorldImagery)
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self.deafrica_layers.add_layer(layer)
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else:
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self.deafrica_layers.clear_layers()
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layer = deawidgets.create_dea_wms_layer(self.product, self.product_year)
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self.deafrica_layers.add_layer(layer)
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def run_app(self, change):
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# Clear progress bar and output areas before running
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self.dask_client.clear_output()
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self.progress_bar.clear_output()
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self.wit_plot.clear_output()
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# Connect to datacube database
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dc = datacube.Datacube(app="wetland_app")
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# Configure local dask cluster
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with self.dask_client:
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client = create_local_dask_cluster(
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return_client=True, display_client=True
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)
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# Set any defaults
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TCW_threshold = -0.035
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dask_chunks = dict(x=1000, y=1000, time=1)
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#check resampling freq
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if self.resamplingfreq == 'None':
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rsf = None
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else:
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rsf = self.resamplingfreq
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self.progress_header.value = f"<h3>"+_("Progress")+"</h3>"
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# run wetlands polygon drill
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with self.progress_bar:
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# with ProgressBar():
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warnings.filterwarnings("ignore")
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try:
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df = WIT_drill(
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gdf=self.gdf_drawn,
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time=(self.startdate, self.enddate),
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min_gooddata=self.mingooddata,
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resample_frequency=rsf,
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TCW_threshold=TCW_threshold,
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export_csv=self.out_csv,
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dask_chunks=dask_chunks,
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verbose=False,
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verbose_progress=True,
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)
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print(_("WIT complete"))
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except AttributeError:
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print(_("No polygon selected"))
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# close down the dask client
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client.shutdown()
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# save the csv
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if self.out_csv:
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df.to_csv(self.out_csv, index_label="Datetime")
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# ---Plotting------------------------------
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with self.wit_plot:
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fontsize = 17
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plt.rcParams.update({"font.size": fontsize})
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# set up color palette
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pal = [
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sns.xkcd_rgb["cobalt blue"],
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sns.xkcd_rgb["neon blue"],
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sns.xkcd_rgb["grass"],
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sns.xkcd_rgb["beige"],
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sns.xkcd_rgb["brown"],
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]
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# make a stacked area plot
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plt.close("all")
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fig, ax = plt.subplots(constrained_layout=True, figsize=(20, 6))
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ax.stackplot(
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df.index,
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df.wofs_area_percent,
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df.wet_percent,
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df.green_veg_percent,
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df.dry_veg_percent,
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df.bare_soil_percent,
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labels=[
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_("open water"),
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_("wet"),
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_("green veg"),
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_("dry veg"),
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_("bare soil"),
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],
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colors=pal,
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alpha=0.6,
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)
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# set axis limits to the min and max
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ax.set_ylim(0, 100)
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ax.set_xlim(df.index[0], df.index[-1])
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ax.tick_params(axis="x", labelsize=fontsize)
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# add a legend and a tight plot box
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ax.legend(loc="lower left", framealpha=0.6)
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ax.set_title(_("Percentage Fractional Cover, Wetness, and Water"))
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# plt.tight_layout()
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plt.show()
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if self.out_plot:
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# save the figure
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fig.savefig(f"{self.out_plot}")
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