class TSTools(object):
def __init__(self):
TSTools.band_index2 = 4
TSTools.pyccd_flag2 = False
TSTools.minv = 0
TSTools.maxv = 6000
TSTools.b1 = 'SWIR1'
TSTools.b2 = 'NIR'
TSTools.b3 = 'RED'
####### Starting Variables #######
pyccd_flag2 = False
current_band = ''
band_index2 = 4
click_col = ''
point_color = ['#43a2ca']
click_df = pd.DataFrame()
click_geojson = ''
PyCCDdf = pd.DataFrame()
results = ''
band_list = ['BLUE', 'GREEN', 'RED', 'NIR', 'SWIR1', 'SWIR2', 'BRIGHTNESS',
'GREENNESS', 'WETNESS', 'NDVI', 'NDFI', 'EVI', 'GV', 'Shade',
'NPV', 'Soil', ]
doy_range = [1, 365]
step = 1 #in years
###### Widgets ######
ylim2 = plots.make_range_slider([0, 4000], -10000, 10000, 500, 'YLim:')
xlim2 = plots.make_range_slider([2000, 2020], 1984, 2020, 1, 'XLim:')
band_selector2 = plots.make_drop('SWIR1', band_list, 'Select band')
image_band_1 = plots.make_drop('SWIR1', band_list, 'Red:')
image_band_2 = plots.make_drop('NIR', band_list, 'Green:')
image_band_3 = plots.make_drop('RED', band_list, 'Blue:')
# Checkbox
color_check = plots.make_checkbox(False, 'Color DOY', False)
stretch_min = plots.make_text_float(0, 0, 'Min:')
stretch_max = plots.make_text_float(6000, 6000, 'Max:')
# Buttons
pyccd_button2 = plots.make_button(False, 'Run PyCCD 2', icon='')
toggle_pyccd_button2 = plots.make_button(False, 'Clear PyCCD', icon='')
clear_layers = plots.make_button(False, 'Clear Map', icon='')
# HTML
hover_label = plots.make_html('Test Value')
###### Plots ######
# Scales
# Dates
lc1_x2 = plots.make_bq_scale('date', datetime.date(xlim2.value[0], 2, 1),
datetime.date(xlim2.value[1], 1, 1))
# DOY
lc1_x3 = plots.make_bq_scale('linear', 0, 365)
# Reflectance
lc2_y2 = plots.make_bq_scale('linear', ylim2.value[0], ylim2.value[1])
# plots
lc3 = plots.make_bq_plot('scatter', [], [], {'x': lc1_x2, 'y': lc2_y2},
[1, 1],
{'click': 'select', 'hover': 'tooltip'},
{'opacity': 1.0, 'fill': 'DarkOrange',
'stroke': 'Red'},
{'opacity': 0.5}, display_legend=True,
labels=['Clicked point'])
lc6 = plots.make_bq_plot('lines', [], [], {'x': lc1_x2, 'y': lc2_y2},
[1, 1], {}, {}, {}, colors=['black'],
stroke_width=3, labels=['PyCCD Model'],
display_legend=False)
lc7 = plots.make_bq_plot('scatter', [], [], {'x': lc1_x2, 'y': lc2_y2},
[1, 1], {}, {}, {}, labels=['Model Endpoint'],
colors=['red'], marker='triangle-up')
lc8 = plots.make_bq_plot('scatter', [], [], {'x': lc1_x3, 'y': lc2_y2},
[1, 1],
{'click': 'select', 'hover': 'tooltip'},
{'opacity': 1.0, 'fill': 'DarkOrange',
'stroke': 'Red'},
{'opacity': 0.5}, display_legend=True,
labels=['Clicked point'])
# Axis
x_ax2 = plots.make_bq_axis('Date', lc1_x2, num_ticks=6, tick_format='%Y',
orientation='horizontal')
x_ax3 = plots.make_bq_axis('DOY', lc1_x3, num_ticks=6,
orientation='horizontal')
y_ay2 = plots.make_bq_axis('SWIR1', lc2_y2, orientation='vertical')
# Figures
fig2 = plots.make_bq_figure([lc3, lc6, lc7], [x_ax2, y_ay2],
{'height': '300px', 'width': '100%'},
'Clicked TS')
fig3 = plots.make_bq_figure([lc8], [x_ax3, y_ay2], {'height': '300px',
'width': '100%'}, 'Clicked DOY')
###### Functions ######
# Change y axis for the clicked point
def change_yaxis2(value):
TSTools.lc2_y2.min = TSTools.ylim2.value[0]
TSTools.lc2_y2.max = TSTools.ylim2.value[1]
# Change x axis for the clicked point
def change_xaxis2(value):
TSTools.lc1_x2.min = datetime.date(TSTools.xlim2.value[0], 2, 1)
TSTools.lc1_x2.max = datetime.date(TSTools.xlim2.value[1], 2, 1)
# Display date of observation when hovering on scatterplot
def hover_event(self, target):
TSTools.hover_label.value = str(target['data']['x'])
# Functions for changing image stretch
def change_image_band1(change):
new_band = change['new']
TSTools.b1 = new_band
def change_image_band2(change):
new_band = change['new']
TSTools.b2 = new_band
def change_image_band3(change):
new_band = change['new']
TSTools.b3 = new_band
# Band selection for clicked point
def on_band_selection2(change):
new_band = change['new']
band_index = change['owner'].index
TSTools.band_index2 = band_index
TSTools.lc3.x = TSTools.click_df['datetime'].values
TSTools.lc3.y = TSTools.click_df[new_band]
TSTools.plot_ts(TSTools.lc3, 'ts')
TSTools.plot_ts(TSTools.lc8, 'doy')
TSTools.y_ay2.label = new_band
if TSTools.pyccd_flag2:
TSTools.do_pyccd2(0)
# Clear everything on map
def clear_map(b):
lft.clear_map(TSTools.m, streets=True)
def add_image2(self, target):
m = TSTools.m
df = TSTools.click_df
current_band = TSTools.band_list[TSTools.band_index2]
sample_col = TSTools.click_col
stretch_min = TSTools.stretch_min.value
stretch_max = TSTools.stretch_max.value
b1 = TSTools.b1
b2 = TSTools.b2
b3 = TSTools.b3
lft.click_event(target, m, current_band, df, sample_col, stretch_min,
stretch_max, b1, b2, b3)
# Plot ts for point
def do_draw(self, action, geo_json):
current_band = TSTools.band_list[TSTools.band_index2]
doy_range = TSTools.doy_range
_col, _df = utils.handle_draw(action, geo_json, current_band,
list(TSTools.xlim2.value), doy_range)
TSTools.click_geojson = geo_json
TSTools.click_df = _df
TSTools.click_col = _col
TSTools.plot_ts(TSTools.lc3, 'ts')
TSTools.plot_ts(TSTools.lc8, 'doy')
# Add time series data to plots
def plot_ts(plot, plottype):
df = TSTools.click_df
if TSTools.color_check.value is True:
color_marks = list(df['color'].values)
else:
color_marks = None
band = TSTools.band_list[TSTools.band_index2]
if plottype == 'ts':
plots.add_plot_ts(df, plot, band=band, color_marks=color_marks)
else:
plots.add_plot_doy(df, plot, band=band, color_marks=color_marks)
if TSTools.pyccd_flag2:
TSTools.do_pyccd2(0)
# Run pyccd for the clicked location
def do_pyccd2(b):
TSTools.pyccd_flag2 = True
display_legend = TSTools.lc7.display_legend
dfPyCCD = TSTools.click_df
band_index = TSTools.band_index2
TSTools.results = ccd_tools.run_pyccd(display_legend, dfPyCCD, band_index)
if band_index > 5:
TSTools.lc6.y = []
TSTools.lc6.x = []
TSTools.lc7.y = []
TSTools.lc7.x = []
TSTools.lc7.display_legend = False
return
else:
ccd_tools.plot_pyccd(dfPyCCD, TSTools.results, band_index, (0, 4000),
TSTools.lc6, TSTools.lc7)
TSTools.lc7.display_legend = True
# Clear pyccd results
def clear_pyccd2(b):
TSTools.lc6.x = []
TSTools.lc7.y = []
####### Widget Interactions #######
dc = ipyleaflet.DrawControl(marker={'shapeOptions': {'color': '#ff0000'}},
polygon={}, circle={}, circlemarker={},
polyline={})
zoom = 5
layout = widgets.Layout(width='50%')
center = (3.3890701010382958, -67.32297252983098)
m = lft.make_map(zoom, layout, center)
# Display controls
ylim2.observe(change_yaxis2)
xlim2.observe(change_xaxis2)
clear_layers.on_click(clear_map)
band_selector2.observe(on_band_selection2, names='value')
image_band_1.observe(change_image_band1, names='value')
image_band_2.observe(change_image_band2, names='value')
image_band_3.observe(change_image_band3, names='value')
# pyccd
pyccd_button2.on_click(do_pyccd2)
toggle_pyccd_button2.on_click(clear_pyccd2)
# Plots
lc3.on_element_click(add_image2)
lc3.tooltip = hover_label
lc3.on_hover(hover_event)
lc8.on_element_click(add_image2)
lc8.tooltip = hover_label
lc8.on_hover(hover_event)
# Mapping
measure = ipyleaflet.MeasureControl(position='bottomleft',
active_color = 'orange',
primary_length_unit = 'kilometers'
)
measure.completed_color = 'red'
dc.on_draw(do_draw)
m.add_control(dc)
m.add_control(measure)
m.add_control(ipyleaflet.LayersControl())
class measures(object):
def __init__(self):
measures.sheet = None
measures.sheet2 = None
measures.band_index1 = 4
measures.band_index2 = 4
measures.pyccd_flag = False
measures.pyccd_flag2 = False
measures.table = None
conn = sqlite3.connect(measures.dbPath)
measures.current_id = measures.current_id
measures.c = conn.cursor()
measures.minv = 0
measures.maxv = 6000
measures.b1 = 'SWIR1'
measures.b2 = 'NIR'
measures.b3 = 'RED'
# Starting variables
pyccd_flag = False
pyccd_flag2 = False
current_band = ''
band_index1 = 4
band_index2 = 4
click_col = ''
point_color = ['#43a2ca']
click_df = pd.DataFrame()
sample_col = ''
sample_df = pd.DataFrame()
PyCCDdf = pd.DataFrame()
table = pd.DataFrame()
band_list = [
'BLUE', 'GREEN', 'RED', 'NIR', 'SWIR1', 'SWIR2', 'BRIGHTNESS',
'GREENNESS', 'WETNESS'
]
year_range = [1986, 2018]
doy_range = [1, 365]
step = 1 #in years
current_id = 0
# Set up database
dbPath = os.getcwd() + '/measures_database'
command = '''CREATE TABLE measures
(id text, lat text, lon text, year1 text, year2 text, direction text, coverType text,
condition text, change text, chaOther text, confCA text,
class text, water text, bare text, albedo text, use text,
height text, transport text, impervious text, density text,
vegType1 text, herbaceous text, shrub text, forestPhenology text,
leafType text, location text, confidence real, notes text,
byear text, brange1 text, brange2 text)'''
conn = sql.make_db(dbPath, command)
# Widgets
# Sliders
years = plots.make_range_slider([1990, 1991], 1990, 2018, 1, 'Years:')
break_years = plots.make_range_slider([1990, 1991], 1990, 2018, 1,
'Years:')
break_year = plots.make_slider(1990, 1991, 2018, 1, 'Years:')
confidence = plots.make_slider(0, 0, 3, 1, 'Confidence:')
ca_confidence = plots.make_slider(0, 0, 3, 1, '')
ylim = plots.make_range_slider([0, 4000], -10000, 10000, 500, 'YLim:')
xlim = plots.make_range_slider([2000, 2018], 1984, 2019, 1, 'XLim:')
ylim2 = plots.make_range_slider([0, 4000], -10000, 10000, 500, 'YLim:')
xlim2 = plots.make_range_slider([2000, 2018], 1984, 2019, 1, 'XLim:')
# Dropdown boxes
drop1 = plots.make_drop('Persistant Ice?',
['Persistant Ice?', 'Yes', 'No'], 'Decision 2')
drop2 = plots.make_drop('Decision 3', ['Decision 3'], 'Decision 3')
drop3 = plots.make_drop('Decision 4', ['Decision 4'], 'Decision 4')
drop4 = plots.make_drop('Decision 5', ['Decision 5'], 'Decision 5')
drop5 = plots.make_drop('Decision 6', ['Decision 6'], 'Decision 6')
drop6 = plots.make_drop('Decision 7', ['Decision 7'], 'Decision 7')
drop7 = plots.make_drop('Decision 8', ['Decision 8'], 'Decision 8')
drop8 = plots.make_drop('Decision 9', ['Decision 9'], 'Decision 9')
drop9 = plots.make_drop('Stable', ['Stable', 'Transitional', 'Break'],
'Label Type:')
drop0 = plots.make_drop(
'Dominant or Secondary?',
['Dominant or Secondary?', 'Dominant', 'Secondary'], 'Decision 1')
band_selector1 = plots.make_drop('SWIR1', band_list, 'Select band')
band_selector2 = plots.make_drop('SWIR1', band_list, 'Select band')
image_band_1 = plots.make_drop('RED', band_list, 'Red:')
image_band_2 = plots.make_drop('GREEN', band_list, 'Green:')
image_band_3 = plots.make_drop('BLUE', band_list, 'Blue:')
# Checkbox
color_check = plots.make_checkbox(False, 'Color DOY', False)
# Select multiple
veg_selector = plots.make_selector(['Veg Type'], [
'Veg Type', 'Cropland', 'Plantation', 'Wetland', 'Riparian/Flood',
'Mangrove'
],
'Veg Type:',
disabled=True)
change_selector = plots.make_selector(['None'], [
'None', 'Deforestation/Logging', 'Fire', 'Insect damage', 'Urban Dev.',
'Flooding', 'Decline/Degradation', 'Regrowth', 'Riparian/Water shift',
'Other (Specify)'
], 'Change Agent:')
direction = plots.make_selector(['None'], [
'None', 'Veg Increase', 'Veg Decrease', 'Water Increase',
'Water Decrease', 'Bare Increase', 'Bare Decrease', 'Urban Increase',
'Urban Decrease', 'Albedo Increase', 'Albedo Decrease'
], 'Directional Change:')
# Text boxes
change_other = plots.make_text('Specify other', 'Specify other', 'Other:')
notes = plots.make_text_large(
'Enter any useful or interesting information about the land cover of this sample',
'',
'Notes',
layout=widgets.Layout()) #,layout=widgets.Layout(width='70%'))
spreadsheet = plots.make_text('Google Spreadsheet Credential JSON',
'Google Spreadsheet Credential JSON',
'Credentials:')
spreadName = plots.make_text('Google Spreadsheet Name',
'Google Spreadsheet Name', 'SS Name:')
sampleWidget = plots.make_text('Path to sample feature collection',
'Path to sample feature collection',
'Path:')
stretch_min = plots.make_text_float(0, 0, 'Min:')
stretch_max = plots.make_text_float(1450, 1450, 'Max:')
zoom_box = plots.make_text_float(12, 12, 'Zoom:')
idBox = plots.make_text('0', '0', 'ID:')
# Buttons
validate = plots.make_button(False, 'Validate', icon='check')
save_button = plots.make_button(False, 'Save', icon='')
load_button = plots.make_button(False, 'Load', icon='')
toggle_pyccd_button = plots.make_button(False, 'Clear Pyccd 1', icon='')
toggle_pyccd_button2 = plots.make_button(False, 'Clear Pyccd 2', icon='')
return_button = plots.make_button(False, 'Return to Sample', icon='')
next_pt = plots.make_button(False, 'Next point', icon='')
previous_pt = plots.make_button(False, 'Previous point', icon='')
pyccd_button = plots.make_button(False, 'Run PyCCD 1', icon='')
pyccd_button2 = plots.make_button(False, 'Run PyCCD 2', icon='')
clear_layers = plots.make_button(False, 'Clear Map', icon='')
delete_rows = plots.make_button(False, 'Delete Last', icon='')
# Validate
valid = plots.make_valid(False, 'Not Saved', '')
valid_load = plots.make_valid(False, 'Not Loaded', '')
# HTML
pt_message = plots.make_html('Current ID: ')
time_label = plots.make_html('')
coord_message = plots.make_html('Lat, Lon: ')
selected_label = plots.make_html('ID of selected point')
hover_label = plots.make_html('Test Value')
text_brush = plots.make_html('Selected year range:')
kml_link = plots.make_html('KML:')
error_label = plots.make_html('Load a point')
# Table
table_widget = qgrid.show_grid(table, show_toolbar=False)
# Plots
# Scales
# Dates
lc1_x = plots.make_bq_scale('date', datetime.date(xlim.value[0], 2, 1),
datetime.date(xlim.value[1], 1, 1))
lc1_x2 = plots.make_bq_scale('date', datetime.date(xlim.value[0], 2, 1),
datetime.date(xlim.value[1], 1, 1))
# DOY
lc1_x3 = plots.make_bq_scale('linear', 0, 365)
# Reflectance
lc2_y = plots.make_bq_scale('linear', ylim.value[0], ylim.value[1])
lc2_y2 = plots.make_bq_scale('linear', ylim.value[0], ylim.value[1])
# plots
lc2 = plots.make_bq_plot('scatter', [], [], {
'x': lc1_x,
'y': lc2_y
}, [1, 1], {
'click': 'select',
'hover': 'tooltip'
}, {
'opacity': 1.0,
'fill': 'DarkOrange',
'stroke': 'Red'
}, {'opacity': 0.5},
display_legend=True,
labels=['Sample point'])
lc3 = plots.make_bq_plot('scatter', [], [], {
'x': lc1_x2,
'y': lc2_y2
}, [1, 1], {
'click': 'select',
'hover': 'tooltip'
}, {
'opacity': 1.0,
'fill': 'DarkOrange',
'stroke': 'Red'
}, {'opacity': 0.5},
display_legend=True,
labels=['Clicked point'])
lc4 = plots.make_bq_plot('lines', [], [], {
'x': lc1_x,
'y': lc2_y
}, [1, 1], {}, {}, {},
colors=['black'],
stroke_width=3)
lc5 = plots.make_bq_plot('scatter', [], [], {
'x': lc1_x,
'y': lc2_y
}, [1, 1], {}, {}, {},
labels=['Model Endpoint'],
colors=['red'],
marker='triangle-up')
lc6 = plots.make_bq_plot('lines', [], [], {
'x': lc1_x2,
'y': lc2_y2
}, [1, 1], {}, {}, {},
colors=['black'],
stroke_width=3)
lc7 = plots.make_bq_plot('scatter', [], [], {
'x': lc1_x2,
'y': lc2_y2
}, [1, 1], {}, {}, {},
labels=['Model Endpoint'],
colors=['red'],
marker='triangle-up')
lc8 = plots.make_bq_plot('scatter', [], [], {
'x': lc1_x3,
'y': lc2_y
}, [1, 1], {
'click': 'select',
'hover': 'tooltip'
}, {
'opacity': 1.0,
'fill': 'DarkOrange',
'stroke': 'Red'
}, {'opacity': 0.5},
display_legend=True,
labels=['Sample point'])
# Axis
x_ax1 = plots.make_bq_axis('Date',
lc1_x,
num_ticks=6,
tick_format='%Y',
orientation='horizontal')
x_ax2 = plots.make_bq_axis('Date',
lc1_x2,
num_ticks=6,
tick_format='%Y',
orientation='horizontal')
x_ax3 = plots.make_bq_axis('DOY',
lc1_x3,
num_ticks=6,
orientation='horizontal')
y_ay1 = plots.make_bq_axis('SWIR1', lc2_y, orientation='vertical')
y_ay2 = plots.make_bq_axis('SWIR1', lc2_y2, orientation='vertical')
# Figures
fig = plots.make_bq_figure([lc2, lc4, lc5], [x_ax1, y_ay1], {
'height': '300px',
'width': '100%'
}, 'Sample TS')
fig2 = plots.make_bq_figure([lc3, lc6, lc7], [x_ax2, y_ay2], {
'height': '300px',
'width': '100%'
}, 'Clicked TS')
fig3 = plots.make_bq_figure([lc8], [x_ax3, y_ay1], {
'height': '300px',
'width': '100%'
}, 'Clicked TS')
# Functions
# Delete data highlighted in rows
def delete_data_rows(a):
measures.c.execute(
"DELETE FROM measures WHERE id = (SELECT MAX(id) FROM measures)")
measures.change_table(0)
condition = measures.drop9.value
if condition == 'Break':
measures.sheet2.delete_row(2)
else:
measures.sheet.delete_row(2)
# Reset dropdowns
def reset_drops():
measures.drop4.set_trait('options', ['Decision 4'])
measures.drop5.set_trait('options', ['Decision 5'])
measures.drop6.set_trait('options', ['Decision 6'])
measures.drop7.set_trait('options', ['Decision 7'])
measures.drop8.set_trait('options', ['Decision 8'])
measures.veg_selector.disabled = True
# Change dropdowns based on drop1 selection
def drop1_clicked(selection):
if selection.new == 'No':
measures.drop2.set_trait('options',
['>30% Vegetated?', 'Yes', 'No'])
elif selection.new == 'Yes':
measures.drop2.set_trait('options', ['Ice/Snow'])
measures.drop3.set_trait('options',
['No other information needed'])
measures.reset_drops()
# Change dropdowns based on drop2 selection
def drop2_clicked(selection):
if '>30% Vegetated?' in measures.drop2.options:
if selection.new == 'Yes':
measures.drop3.set_trait('options', [
'Density', 'Closed (60-70%)', 'Open (30-60%)',
'Sparse (<30%)'
])
measures.veg_selector.disabled = False
measures.drop4.set_trait('options', ['Trees?', 'Yes', 'No'])
elif selection.new == 'No':
measures.drop3.set_trait(
'options',
['Dominant Cover?', 'Water', 'Bare', 'Developed'])
measures.drop4.set_trait('options', ['Decision 4'])
measures.drop5.set_trait('options', ['Decision 5'])
measures.drop6.set_trait('options', ['Decision 6'])
measures.drop7.set_trait('options', ['Decision 7'])
measures.drop8.set_trait('options', ['Decision 8'])
measures.veg_selector.disabled = True
else:
measures.drop3.set_trait('options',
['No Other Information Needed'])
# Change dropdowns based on drop3 selection
def drop3_clicked(selection):
if 'Dominant Cover?' in measures.drop3.options:
measures.veg_selector.disabled = True
if selection.new == 'Water':
measures.drop4.set_trait('options', [
'Water Type', 'Shore/Inter tidal', 'Shallows', 'River',
'Lake/Reservoir', 'Ocean'
])
elif selection.new == 'Bare':
measures.drop4.set_trait('options', [
'Bare Type', 'Soil', 'Rock', 'Quarry (Active)',
'Beach/Sand'
])
elif selection.new == 'Developed':
measures.drop4.set_trait(
'options', ['Surface Albedo', 'High', 'Low', 'Mixed'])
measures.drop5.set_trait(
'options', ['Use', 'Residential', 'Commercial/Industrial'])
measures.drop6.set_trait('options', [
'Building Height', 'No Buildings', '1-2 Stories',
'3-5 Stories', '5+ Stories'
])
measures.drop7.set_trait(
'options', ['Transport', 'Road', 'Not Applicable'])
measures.drop8.set_trait('options', [
'% Impervious', 'High (60-100)', 'Medium (30-60)',
'Low (<30)'
])
# Change dropdowns based on drop4 selection
def drop4_clicked(selection):
if 'Trees?' in measures.drop4.options:
if selection.new == 'Yes':
measures.drop5.set_trait(
'options', ['Height >5m & Canopy >30%', 'Yes', 'No'])
elif selection.new == 'No':
measures.drop5.set_trait('options', [
'Herbaceous Type', 'Grassland', 'Pasture',
'Lawn/Urban Grass', 'Moss/Lichen'
])
# Change dropdowns based on drop5 selection
def drop5_clicked(selection):
if 'Height >5m & Canopy >30%' in measures.drop5.options:
if selection.new == 'Yes':
measures.drop6.set_trait(
'options',
['Forest Type', 'Evergreen', 'Deciduous', 'Mixed'])
measures.drop7.set_trait(
'options', ['Leaf Type', 'Broad', 'Needle', 'Unsure'])
measures.drop8.set_trait('options',
['Location', 'Interior', 'Edge'])
elif selection.new == 'No':
measures.drop6.set_trait(
'options',
['Shrub Type', 'Evergreen', 'Deciduous', 'Mixed'])
# Check validity of current sample
def check_val_status(selection):
selected_secondary_lc = False
wrote_correct_lc = False
if measures.second_class_drop.value != 'Secondary Class Information':
selected_secondary_lc = True
else:
print("Must specify secondary class information!")
if measures.lc.value.capitalize(
) == measures.textClass.value.capitalize():
wrote_correct_lc = True
if selected_secondary_lc and wrote_correct_lc:
measures.valid.value = True
measures.save_button.disabled = False
# load the feature collection, database, and google sheet
def load_everything(sender):
measures.sheet = sheets.load_sheet(measures.spreadName.value, 0,
measures.spreadsheet.value)
measures.sheet2 = sheets.load_sheet(measures.spreadName.value, 1,
measures.spreadsheet.value)
# Load the sample as a feature collection
sample_path = measures.sampleWidget.value
fc_df = utils.fc2dfgeo(sample_path)
measures.fc_df, first_index = utils.check_id(fc_df)
measures.valid_load.value = True
measures.valid_load.description = 'Loaded!'
measures.current_id = first_index - 1
# If the class type is 'break', turn on necessary widgets
def turn_on_break_years(selection):
if selection.new == 'Break':
measures.break_years.disabled = False
measures.break_year.disabled = False
else:
measures.break_years.disabled = True
measures.break_year.disabled = True
# Change yaxis for the sample time series
def change_yaxis(value):
measures.lc2_y.min = measures.ylim.value[0]
measures.lc2_y.max = measures.ylim.value[1]
# Change xaxis for the sample time series
def change_xaxis(value):
measures.lc1_x.min = datetime.date(measures.xlim.value[0], 2, 1)
measures.lc1_x.max = datetime.date(measures.xlim.value[1], 2, 1)
measures.year_range = [measures.xlim.value[0], measures.xlim.value[1]]
# Change y axis for the clicked point
def change_yaxis2(value):
measures.lc2_y2.min = measures.ylim2.value[0]
measures.lc2_y2.max = measures.ylim2.value[1]
# Change x axis for the clicked point
def change_xaxis2(value):
measures.lc1_x2.min = datetime.date(measures.xlim2.value[0], 2, 1)
measures.lc1_x2.max = datetime.date(measures.xlim2.value[1], 2, 1)
# Display date of observation when hovering on scatterplot
def hover_event(self, target):
measures.hover_label.value = str(target['data']['x'])
# Advance to next sample
def advance(b):
measures.lc4.x = []
measures.lc4.y = []
measures.lc5.x = []
measures.lc5.y = []
measures.lc5.display_legend = False
measures.pyccd_flag = False
measures.current_id += 1
measures.pt_message.value = "Point ID: {}".format(measures.current_id)
measures.map_point()
measures.get_ts()
measures.plot_ts(measures.lc2, 'ts')
measures.plot_ts(measures.lc8, 'doy')
measures.change_table(0)
measures.valid.value = False
measures.description = 'Not Saved'
# Go to previous sample
def decrease(b):
measures.lc4.x = []
measures.lc4.y = []
measures.lc5.x = []
measures.lc5.y = []
measures.lc5.display_legend = False
measures.pyccd_flag = False
measures.current_id -= 1
measures.pt_message.value = "Point ID: {}".format(measures.current_id)
measures.map_point()
measures.get_ts()
#measures.plot_ts()
measures.plot_ts(measures.lc2, 'ts')
measures.plot_ts(measures.lc8, 'doy')
measures.change_table(0)
measures.valid.value = False
measures.description = 'Not Saved'
# Go to a specific sample
def go_to_sample(b):
measures.lc4.x = []
measures.lc4.y = []
measures.lc5.x = []
measures.lc5.y = []
measures.lc5.display_legend = False
measures.pyccd_flag = False
measures.current_id = int(b.value)
measures.pt_message.value = "Point ID: {}".format(measures.current_id)
measures.valid.value = False
measures.description = 'Not Saved'
measures.map_point()
measures.get_ts()
#measures.plot_ts()
measures.plot_ts(measures.lc2, 'ts')
measures.plot_ts(measures.lc8, 'doy')
# Return to sample location
def return_to_sample(b):
measures.map_point()
# Update the table based on current ID
def change_table(b):
# Get header
cursor = measures.c.execute('select * from measures')
names = list(map(lambda x: x[0], cursor.description))
previous_inputs = pd.DataFrame()
for i, row in enumerate(
measures.c.execute("SELECT * FROM measures WHERE id = '%s'" %
measures.current_id)):
previous_inputs[i] = row
previous_inputs = previous_inputs.T
if previous_inputs.shape[0] > 0:
previous_inputs.columns = names
measures.table_widget.df = previous_inputs
# Functions for changing image stretch
def change_image_band1(change):
new_band = change['new']
measures.b1 = new_band
def change_image_band2(change):
new_band = change['new']
measures.b2 = new_band
def change_image_band3(change):
new_band = change['new']
measures.b3 = new_band
# Band selection for sample point
def on_band_selection1(change):
band_index = change['owner'].index
measures.band_index1 = band_index
new_band = change['new']
measures.y_ay1.label = new_band
#measures.plot_ts()
measures.plot_ts(measures.lc2, 'ts')
measures.plot_ts(measures.lc8, 'doy')
# Band selection for clicked point
def on_band_selection2(change):
new_band = change['new']
band_index = change['owner'].index
measures.band_index2 = band_index
measures.lc3.x = measures.click_df['datetime']
measures.lc3.y = measures.click_df[new_band]
#measures.plot_ts(measures.lc3, 'ts')
measures.y_ay2.label = new_band
if measures.pyccd_flag2:
measures.do_pyccd2(0)
# Clear everything on map besides current sample
def clear_map(b):
lft.clear_map(measures.m, streets=True)
if hasattr(measures, 'fc_df'):
measures.map_point()
# Add an image to the map when clicked on time series
def add_image(self, target):
m = measures.m
df = measures.sample_df
current_band = measures.band_list[measures.band_index1]
sample_col = measures.sample_col
stretch_min = measures.stretch_min
stretch_max = measures.stretch_max
b1 = measures.b1
b2 = measures.b2
b3 = measures.b3
lft.click_event(target, m, current_band, df, sample_col, stretch_min,
stretch_max, b1, b2, b3)
def add_image2(self, target):
m = measures.m
df = measures.click_df
current_band = measures.band_list[measures.band_index2]
sample_col = measures.click_col
stretch_min = measures.minv
stretch_max = measures.maxv
b1 = measures.b1
b2 = measures.b2
b3 = measures.b3
lft.click_event(target, m, current_band, df, sample_col, stretch_min,
stretch_max, b1, b2, b3)
# Plot ts for point
def do_draw(self, action, geo_json):
current_band = measures.band_list[measures.band_index2]
year_range = measures.year_range
doy_range = measures.doy_range
_col, _df = utils.handle_draw(action, geo_json, current_band,
year_range, doy_range)
measures.click_df = _df
measures.click_col = _col
measures.lc6.x = []
measures.lc6.y = []
measures.lc7.x = []
measures.lc7.y = []
measures.lc3.x = measures.click_df['datetime']
measures.lc3.y = measures.click_df[current_band]
if measures.color_check.value == False:
measures.lc3.colors = list(measures.point_color)
else:
measures.lc3.colors = list(measures.click_df['color'].values)
# Add point location to map
def map_point():
zoom = int(measures.zoom_box.value)
kml = measures.kml_link
name = 'Sample point'
data = measures.fc_df['geometry'][measures.current_id]
coord1 = data['coordinates'][0]
coord2 = data['coordinates'][1]
measures.coord_message.value = "Lat, Lon: {}, {}".format(
coord2, coord1)
lft.add_map_point(data, zoom, measures.m, kml, name)
# Get time series data for location.
def get_ts():
measures.error_label.value = 'Loading'
coords = measures.fc_df['geometry'][measures.current_id]['coordinates']
year_range = measures.year_range
doy_range = measures.doy_range
measures.current_band = measures.band_list[measures.band_index1]
measures.sample_col = utils.get_full_collection(
coords, year_range, doy_range)
measures.sample_df = utils.get_df_full(measures.sample_col,
coords).dropna()
measures.error_label.value = 'Point Loaded!'
# TODO: how is this different from handle_draw?
def plot_ts(plot, plottype):
df = measures.sample_df
if measures.color_check.value == True:
color_marks = list(measures.sample_df['color'].values)
else:
color_marks = None
band = measures.band_list[measures.band_index1]
if plottype == 'ts':
plots.add_plot_ts(df, plot, band=band, color_marks=color_marks)
else:
plots.add_plot_doy(df, plot, band=band, color_marks=color_marks)
if measures.pyccd_flag:
measures.do_pyccd(0)
# Run pyccd for the sample location
def do_pyccd(b):
pyccd_flag = measures.pyccd_flag
display_legend = measures.lc5.display_legend
dfPyCCD = measures.sample_df
band_index = measures.band_index1
results = ccd_tools.run_pyccd(pyccd_flag, display_legend, dfPyCCD,
band_index)
ccd_tools.plot_pyccd(dfPyCCD, results, band_index, (0, 4000),
measures.lc4, measures.lc5)
# Run pyccd for the clicked location
def do_pyccd2(b):
pyccd_flag = measures.pyccd_flag2
display_legend = measures.lc7.display_legend
dfPyCCD = measures.click_df
band_index = measures.band_index1
results = ccd_tools.run_pyccd(pyccd_flag, display_legend, dfPyCCD,
band_index)
ccd_tools.plot_pyccd(dfPyCCD, results, band_index, (0, 4000),
measures.lc6, measures.lc7)
def clear_pyccd(b):
measures.lc4.x = []
measures.lc5.y = []
def clear_pyccd2(b):
measures.lc6.x = []
measures.lc7.y = []
# Save sample
def save_sample():
# Connect to the database
conn = sqlite3.connect(measures.dbPath)
c = conn.cursor()
# Get everything in right format
year1 = measures.years.value[0]
year2 = measures.years.value[1]
waterType = 'N/A'
bareType = 'N/A'
albedo = 'N/A'
use = 'N/A'
height = 'N/A'
transport = 'N/A'
impervious = 'N/A'
density = 'N/A'
vegType1 = 'N/A'
herbaceousType = 'N/A'
shrubType = 'N/A'
forestPhenology = 'N/A'
leafType = 'N/A'
location = 'N/A'
condition = measures.drop9.value
coverType = measures.drop0.value
changeAgent = measures.change_selector.value
changeAgent = [str(i) for i in changeAgent]
changeAgent = ', '.join(changeAgent)
if changeAgent != 'None':
confCA = measures.ca_confidence.value
break_year = measures.break_year.value
break_range1 = measures.break_years.value[0]
break_range2 = measures.break_years.value[1]
else:
confCA = 'N/A'
break_year = 'N/A'
break_range1 = 'N/A'
break_range2 = 'N/A'
ca_other = measures.change_other.value
if ca_other == 'Specify other':
ca_other = 'N/A'
direction = measures.direction.value
direction = [str(i) for i in direction]
direction = ', '.join(direction)
class1 = 'Unfilled'
# Ice/Snow
if measures.drop1.value == 'Yes':
class1 = 'Snow/Ice'
else:
if measures.drop2.value == 'No': #Non-Veg
class1 = measures.drop3.value
if class1 == 'Water':
waterType = measures.drop4.value
elif class1 == 'Bare':
bareType = measures.drop4.value
else:
albedo = measures.drop4.value #HERE
use = measures.drop5.value
height = measures.drop6.value
transport = measures.drop7.value
impervious = measures.drop8.value
elif measures.drop2.value == 'Yes': #Veg
density = measures.drop3.value
vegType1 = measures.veg_selector.value
vegType1 = [str(i) for i in vegType1]
vegType1 = ', '.join(vegType1)
if measures.drop5.value == 'No': #Herbaceous
class1 = 'Herbaceous'
herbaceousType = measures.drop6.value
elif measures.drop5.value == 'Yes':
class1 = 'Forest'
forestPhenology = measures.drop6.value
leafType = measures.drop7.value
location = measures.drop8.value
conf = measures.confidence.value
notes_value = measures.notes.value
idSample = measures.current_id
lat = measures.m.center[0]
lon = measures.m.center[1]
sampleInput = (idSample, lat, lon, year1, year2, direction, coverType,
condition, changeAgent, ca_other, confCA, class1,
waterType, bareType, albedo, use, height, transport,
impervious, density, vegType1, herbaceousType,
shrubType, forestPhenology, leafType, location, conf,
notes_value, break_year, break_range1, break_range2)
# Put sample information into database
c.execute("""insert into measures
values {i}""".format(i=sampleInput))
# Save (commit) the changes
conn.commit()
# Close the cursor
c.close()
# Save to drive
sampleInputList = [
str(idSample),
str(lat),
str(lon),
str(year1),
str(year2), direction, coverType, condition, changeAgent, ca_other,
confCA, class1, waterType, bareType, albedo, use, height,
transport, impervious, density, vegType1, herbaceousType,
shrubType, forestPhenology, leafType, location, conf, notes_value
]
sampleInputListFull = sampleInputList
# Save break information to second sheet
if condition == 'Break':
breakList = [
str(idSample),
str(lat),
str(lon), changeAgent, ca_other, confCA, break_year,
break_range1, break_range2
]
measures.sheet2.insert_row(breakList, 2)
count = len(measures.sheet2.col_values(1))
time.sleep(3)
count_new = len(measures.sheet2.col_values(1))
else:
count = len(measures.sheet.col_values(1))
measures.sheet.insert_row(sampleInputListFull, 2)
time.sleep(3)
count_new = len(measures.sheet.col_values(1))
if count_new > count:
# Change save validity state
measures.valid.value = True
measures.valid.description = 'Saved!'
measures.reset_everything()
else:
time.sleep(10)
if condition == 'Break':
count_new = len(measures.sheet2.col_values(1))
else:
count_new = len(measures.sheet.col_values(1))
if count_new > count:
# Change save validity state
measures.valid.value = True
measures.valid.description = 'Saved!'
measures.reset_everything()
# Reset all widgets
def reset_everything():
measures.drop1.set_trait('value', 'Persistant Ice?')
measures.drop2.set_trait('options', ['Decision 3'])
measures.drop3.set_trait('options', ['Decision 4'])
measures.drop5.set_trait('options', ['Decision 5'])
measures.drop6.set_trait('options', ['Decision 6'])
measures.drop7.set_trait('options', ['Decision 7'])
measures.drop8.set_trait('options', ['Decision 8'])
measures.veg_selector.disabled = True
measures.years.set_trait('value', [1990, 1991])
measures.confidence.set_trait('value', 0)
measures.ca_confidence.set_trait('value', 0)
# Interaction function for saving sample
def do_save_sample(a):
measures.save_sample()
measures.change_table(0)
# Widget interactions
delete_rows.on_click(delete_data_rows)
return_button.on_click(return_to_sample)
save_button.on_click(do_save_sample)
validate.on_click(check_val_status)
drop1.observe(drop1_clicked, 'value')
drop2.observe(drop2_clicked, 'value')
drop3.observe(drop3_clicked, 'value')
drop4.observe(drop4_clicked, 'value')
drop5.observe(drop5_clicked, 'value')
drop9.observe(turn_on_break_years, 'value')
load_button.on_click(load_everything)
dc = ipyleaflet.DrawControl(marker={'shapeOptions': {
'color': '#ff0000'
}},
polygon={},
circle={},
circlemarker={},
polyline={})
zoom = 5
layout = widgets.Layout(width='50%')
center = (3.3890701010382958, -67.32297252983098)
m = lft.make_map(zoom, layout, center)
lft.add_basemap(m, ipyleaflet.basemaps.Esri.WorldImagery)
# Display controls
ylim.observe(change_yaxis)
xlim.observe(change_xaxis)
ylim2.observe(change_yaxis2)
xlim2.observe(change_xaxis2)
clear_layers.on_click(clear_map)
band_selector1.observe(on_band_selection1, names='value')
band_selector2.observe(on_band_selection2, names='value')
image_band_1.observe(change_image_band1, names='value')
image_band_2.observe(change_image_band2, names='value')
image_band_3.observe(change_image_band3, names='value')
# Samples
next_pt.on_click(advance)
previous_pt.on_click(decrease)
# pyccd
pyccd_button.on_click(do_pyccd)
pyccd_button2.on_click(do_pyccd2)
toggle_pyccd_button.on_click(clear_pyccd)
toggle_pyccd_button2.on_click(clear_pyccd2)
# Plots
lc2.on_element_click(add_image)
lc2.tooltip = hover_label
lc2.on_hover(hover_event)
lc3.on_element_click(add_image2)
lc3.tooltip = hover_label
lc3.on_hover(hover_event)
idBox.on_submit(go_to_sample)
# Mapping
dc.on_draw(do_draw)
m.add_control(dc)
m.add_control(ipyleaflet.LayersControl())
class pyccd_explorer(object):
def __init__(self):
measures.band_index1 = 4
measures.band_index2 = 4
measures.pyccd_flag = False
measures.pyccd_flag2 = False
measures.minv = 0
measures.maxv = 6000
measures.b1 = 'SWIR1'
measures.b2 = 'NIR'
measures.b3 = 'RED'
# Starting variables
pyccd_flag = False
pyccd_flag2 = False
current_band = ''
band_index1 = 4
band_index2 = 4
click_col = ''
point_color = ['#43a2ca']
click_df = pd.DataFrame()
sample_col = ''
sample_df = pd.DataFrame()
PyCCDdf = pd.DataFrame()
table = pd.DataFrame()
band_list = ['BLUE', 'GREEN', 'RED', 'NIR', 'SWIR1', 'SWIR2']
year_range = [1986, 2018]
doy_range = [1, 365]
step = 1 #in years
current_id = 0
ylim = plots.make_range_slider([0, 4000], -10000, 10000, 500, 'YLim:')
xlim = plots.make_range_slider([2000, 2018], 1984, 2019, 1, 'XLim:')
ylim2 = plots.make_range_slider([0, 4000], -10000, 10000, 500, 'YLim:')
xlim2 = plots.make_range_slider([2000, 2018], 1984, 2019, 1, 'XLim:')
band_selector1 = plots.make_drop('SWIR1', band_list, 'Select band')
band_selector2 = plots.make_drop('SWIR1', band_list, 'Select band')
image_band_1 = plots.make_drop('RED', band_list, 'Red:')
image_band_2 = plots.make_drop('GREEN', band_list, 'Green:')
image_band_3 = plots.make_drop('BLUE', band_list, 'Blue:')
# Checkbox
color_check = plots.make_checkbox(False, 'Color DOY', False)
stretch_min = plots.make_text_float(0, 0, 'Min:')
stretch_max = plots.make_text_float(1450, 0, 'Max:')
idBox = plots.make_text('0', '0', 'ID:')
load_button = plots.make_button(False, 'Load', icon='')
next_pt = plots.make_button(False, 'Next point', icon='')
previous_pt = plots.make_button(False, 'Previous point', icon='')
pyccd_button = plots.make_button(False, 'Run PyCCD 1', icon='')
pyccd_button2 = plots.make_button(False, 'Run PyCCD 2', icon='')
clear_layers = plots.make_button(False, 'Clear Map', icon='')
# HTML
pt_message = plots.make_html('Current ID: ')
coord_message = plots.make_html('Lat, Lon: ')
time_label = plots.make_html('')
selected_label = plots.make_html('ID of selected point')
hover_label = plots.make_html('Test Value')
text_brush = plots.make_html('Selected year range:')
kml_link = plots.make_html('KML:')
error_label = plots.make_html('Load a point')
# Plots
# Scales
# Dates
lc1_x = plots.make_bq_scale('date', datetime.date(xlim.value[0], 2, 1),
datetime.date(xlim.value[1], 1, 1))
lc1_x2 = plots.make_bq_scale('date', datetime.date(xlim.value[0], 2, 1),
datetime.date(xlim.value[1], 1, 1))
# DOY
lc1_x3 = plots.make_bq_scale('linear', 0, 365)
# Reflectance
lc2_y = plots.make_bq_scale('linear', ylim.value[0], ylim.value[1])
lc2_y2 = plots.make_bq_scale('linear', ylim.value[0], ylim.value[1])
# plots
lc2 = plots.make_bq_plot('scatter', [], [], {
'x': lc1_x,
'y': lc2_y
}, [1, 1], {
'click': 'select',
'hover': 'tooltip'
}, {
'opacity': 1.0,
'fill': 'DarkOrange',
'stroke': 'Red'
}, {'opacity': 0.5},
display_legend=True,
labels=['Sample point'])
lc3 = plots.make_bq_plot('scatter', [], [], {
'x': lc1_x2,
'y': lc2_y2
}, [1, 1], {
'click': 'select',
'hover': 'tooltip'
}, {
'opacity': 1.0,
'fill': 'DarkOrange',
'stroke': 'Red'
}, {'opacity': 0.5},
display_legend=True,
labels=['Clicked point'])
lc4 = plots.make_bq_plot('lines', [], [], {
'x': lc1_x,
'y': lc2_y
}, [1, 1], {}, {}, {},
colors=['black'],
stroke_width=3)
lc5 = plots.make_bq_plot('scatter', [], [], {
'x': lc1_x,
'y': lc2_y
}, [1, 1], {}, {}, {},
labels=['Model Endpoint'],
colors=['red'],
marker='triangle-up')
lc6 = plots.make_bq_plot('lines', [], [], {
'x': lc1_x2,
'y': lc2_y2
}, [1, 1], {}, {}, {},
colors=['black'],
stroke_width=3)
lc7 = plots.make_bq_plot('scatter', [], [], {
'x': lc1_x2,
'y': lc2_y2
}, [1, 1], {}, {}, {},
labels=['Model Endpoint'],
colors=['red'],
marker='triangle-up')
lc8 = plots.make_bq_plot('scatter', [], [], {
'x': lc1_x3,
'y': lc2_y
}, [1, 1], {
'click': 'select',
'hover': 'tooltip'
}, {
'opacity': 1.0,
'fill': 'DarkOrange',
'stroke': 'Red'
}, {'opacity': 0.5},
display_legend=True,
labels=['Sample point'])
x_ax1 = plots.make_bq_axis('Date',
lc1_x,
num_ticks=6,
tick_format='%Y',
orientation='horizontal')
x_ax2 = plots.make_bq_axis('Date',
lc1_x2,
num_ticks=6,
tick_format='%Y',
orientation='horizontal')
x_ax3 = plots.make_bq_axis('DOY',
lc1_x3,
num_ticks=6,
orientation='horizontal')
y_ay1 = plots.make_bq_axis('SWIR1', lc2_y, orientation='vertical')
y_ay2 = plots.make_bq_axis('SWIR1', lc2_y2, orientation='vertical')
# Figures
fig = plots.make_bq_figure([lc2, lc4, lc5], [x_ax1, y_ay1], {
'height': '300px',
'width': '100%'
}, 'Sample TS')
fig2 = plots.make_bq_figure([lc3, lc6, lc7], [x_ax2, y_ay2], {
'height': '300px',
'width': '100%'
}, 'Clicked TS')
fig3 = plots.make_bq_figure([lc8], [x_ax3, y_ay1], {
'height': '300px',
'width': '100%'
}, 'Clicked TS')
# Functions
def load_everything(sender):
# Load the sample as a feature collection
sample_path = measures.sampleWidget.value
fc_df = utils.fc2dfgeo(sample_path)
measures.fc_df, first_index = utils.check_id(fc_df)
measures.current_id = first_index - 1
measures.reset_everything()
def change_yaxis(value):
measures.lc2_y.min = measures.ylim.value[0]
measures.lc2_y.max = measures.ylim.value[1]
def change_xaxis(value):
measures.lc1_x.min = datetime.date(measures.xlim.value[0], 2, 1)
measures.lc1_x.max = datetime.date(measures.xlim.value[1], 2, 1)
measures.year_range = [measures.xlim.value[0], measures.xlim.value[1]]
def change_yaxis2(value):
measures.lc2_y2.min = measures.ylim2.value[0]
measures.lc2_y2.max = measures.ylim2.value[1]
def change_xaxis2(value):
measures.lc1_x2.min = datetime.date(measures.xlim2.value[0], 2, 1)
measures.lc1_x2.max = datetime.date(measures.xlim2.value[1], 2, 1)
def hover_event(self, target):
measures.hover_label.value = str(target['data']['x'])
def advance(b):
# Plot point in map
measures.lc4.x = []
measures.lc4.y = []
measures.lc5.x = []
measures.lc5.y = []
measures.lc5.display_legend = False
measures.pyccd_flag = False
measures.current_id += 1
measures.pt_message.value = "Point ID: {}".format(measures.current_id)
measures.map_point()
measures.get_ts()
measures.plot_ts()
def decrease(b):
# Plot point in map
measures.lc4.x = []
measures.lc4.y = []
measures.lc5.x = []
measures.lc5.y = []
measures.lc5.display_legend = False
measures.pyccd_flag = False
measures.current_id -= 1
measures.pt_message.value = "Point ID: {}".format(measures.current_id)
measures.map_point()
measures.get_ts()
measures.plot_ts()
# Go to a specific sample
def go_to_sample(b):
# Plot point in map
measures.lc4.x = []
measures.lc4.y = []
measures.lc5.x = []
measures.lc5.y = []
measures.lc5.display_legend = False
measures.pyccd_flag = False
measures.current_id = int(b.value)
measures.pt_message.value = "Point ID: {}".format(measures.current_id)
measures.map_point()
measures.get_ts()
measures.plot_ts()
# Functions for changing image stretch
def change_image_band1(change):
new_band = change['new']
measures.b1 = new_band
def change_image_band2(change):
new_band = change['new']
measures.b2 = new_band
def change_image_band3(change):
new_band = change['new']
measures.b3 = new_band
# Band selection for sample point
def on_band_selection1(change):
band_index = change['owner'].index
measures.band_index1 = band_index
measures.plot_ts()
# Band selection for clicked point
def on_band_selection2(change):
new_band = change['new']
band_index = change['owner'].index
measures.band_index2 = band_index
measures.lc3.x = measures.click_df['datetime']
measures.lc3.y = measures.click_df[new_band]
measures.x_ay2.label = new_band
if measures.pyccd_flag2:
measures.do_pyccd2(0)
def clear_map(b):
lft.clear_map(measures.m, streets=True)
measures.map_point()
def add_image(self, target):
m = measures.m
df = measures.sample_df
current_band = measures.band_list[measures.band_index1]
sample_col = measures.sample_col
stretch_min = measures.stretch_min
stretch_max = measures.stretch_max
b1 = measures.b1
b2 = measures.b2
b3 = measures.b3
lft.click_event(target, m, current_band, df, sample_col, stretch_min,
stretch_max, b1, b2, b3)
def add_image2(self, target):
m = measures.m
df = measures.click_df
current_band = measures.band_list[measures.band_index2]
sample_col = measures.click_col
stretch_min = measures.minv
stretch_max = measures.maxv
b1 = measures.b1
b2 = measures.b2
b3 = measures.b3
lft.click_event(target, m, current_band, df, sample_col, stretch_min,
stretch_max, b1, b2, b3)
def do_draw(self, action, geo_json):
current_band = measures.band_list[measures.band_index2]
year_range = measures.year_range
doy_range = measures.doy_range
_col, _df = utils.handle_draw(action, geo_json, current_band,
year_range, doy_range)
measures.click_df = _df
measures.click_col = _col
measures.lc6.x = []
measures.lc6.y = []
measures.lc7.x = []
measures.lc7.y = []
measures.lc3.x = measures.click_df['datetime']
measures.lc3.y = measures.click_df[current_band]
if measures.color_check.value == False:
measures.lc3.colors = list(measures.point_color)
else:
measures.lc3.colors = list(measures.click_df['color'].values)
def map_point():
zoom = 12
kml = measures.kml_link
name = 'Sample point'
data = measures.fc_df['geometry'][measures.current_id]
measures.coord_message.value = "Lat, Lon: {}".format(
data['coordinates'])
lft.add_map_point(data, zoom, measures.m, kml, name)
def get_ts():
measures.error_label.value = 'Loading'
coords = measures.fc_df['geometry'][measures.current_id]['coordinates']
year_range = measures.year_range
doy_range = measures.doy_range
measures.current_band = measures.band_list[measures.band_index1]
measures.sample_col = utils.get_full_collection(
coords, year_range, doy_range)
measures.sample_df = utils.get_df_full(measures.sample_col,
coords).dropna()
measures.error_label.value = 'Point Loaded!'
def plot_ts():
df = measures.sample_df
if measures.color_check.value == True:
color_marks = list(measures.sample_df['color'].values)
else:
color_marks = list(measures.point_color)
band = measures.band_list[measures.band_index1]
plots.add_plot_ts(df, measures.lc2, band, color_marks)
plots.add_plot_doy(df, measures.lc8, band, color_marks)
if measures.pyccd_flag:
measures.do_pyccd(0)
def do_pyccd(b):
pyccd_flag = measures.pyccd_flag
display_legend = measures.lc5.display_legend
dfPyCCD = measures.sample_df
band_index = measures.band_index1
results = ccd_tools.run_pyccd(pyccd_flag, display_legend, dfPyCCD,
band_index)
ccd_tools.plot_pyccd(dfPyCCD, results, band_index, (0, 4000),
measures.lc4, measures.lc5)
def do_pyccd2(b):
pyccd_flag = measures.pyccd_flag2
display_legend = measures.lc7.display_legend
dfPyCCD = measures.click_df
band_index = measures.band_index1
results = ccd_tools.run_pyccd(pyccd_flag, display_legend, dfPyCCD,
band_index)
ccd_tools.plot_pyccd(dfPyCCD, results, band_index, (0, 4000),
measures.lc6, measures.lc7)
# Load database and sample
load_button.on_click(load_everything)
# Map
dc = ipyleaflet.DrawControl(marker={'shapeOptions': {
'color': '#ff0000'
}},
polygon={},
circle={},
circlemarker={},
polyline={})
zoom = 5
layout = widgets.Layout(width='50%')
center = (3.3890701010382958, -67.32297252983098)
m = lft.make_map(zoom, layout, center)
m = lft.add_basemap(m, ipyleaflet.basemaps.Esri.WorldImagery)
# Display controls
ylim.observe(change_yaxis)
xlim.observe(change_xaxis)
ylim2.observe(change_yaxis2)
xlim2.observe(change_xaxis2)
clear_layers.on_click(clear_map)
band_selector1.observe(on_band_selection1, names='value')
band_selector2.observe(on_band_selection2, names='value')
image_band_1.observe(change_image_band1, names='value')
image_band_2.observe(change_image_band2, names='value')
image_band_3.observe(change_image_band3, names='value')
# .samples
next_pt.on_click(advance)
previous_pt.on_click(decrease)
# PyCCD
pyccd_button.on_click(do_pyccd)
pyccd_button2.on_click(do_pyccd2)
# Plots
lc2.on_element_click(add_image)
lc2.tooltip = hover_label
lc2.on_hover(hover_event)
lc3.on_element_click(add_image2)
lc3.tooltip = hover_label
lc3.on_hover(hover_event)
idBox.on_submit(go_to_sample)
# Mapping
dc.on_draw(do_draw)
m.add_control(dc)
m.add_control(ipyleaflet.LayersControl())