def update_figure(surface_picks, curve, active_well):
"""redraw the plot when the data in tops-storage is updated"""
surface_picks = pd.read_json(surface_picks)
surface_picks = surface_picks[surface_picks['UWI'] == active_well]
w = p.get_well(active_well) ##selects the correct welly.Well object
df = w.df() ##reloads the correct dataframe for the display
# regenerate figure with the new horizontal line
fig = px.line(x=df[curve],
y=df.index,
labels={
'x': curve,
'y': df.index.name
})
fig.layout = {
'uirevision': curve
} # https://community.plotly.com/t/preserving-ui-state-like-zoom-in-dcc-graph-with-uirevision-with-dash/15793
fig.update_yaxes(autorange="reversed")
fig.layout.xaxis.fixedrange = True
fig.layout.template = 'plotly_white'
helper.update_picks_on_plot(fig, surface_picks)
return fig
def update_figure(picks, curve, active_well):
"""redraw the plot when the data in tops-storage is updated"""
w = p.get_well(active_well) ##selects the correct welly.Well object
picks_df = pd.read_json(picks)
picks_selected = picks_df[picks_df['UWI'] == active_well.replace(' ', '-')]
# regenerate figure with the new horizontal line
fig = helper.make_log_plot(w=w, ymin=ymin)
fig.update_layout(uirevision=active_well)
helper.update_picks_on_plot(fig, picks_selected)
return fig
def update_figure(surface_picks, curve, active_well):
"""redraw the plot when the data in tops-storage is updated"""
surface_picks = pd.read_json(surface_picks)
surface_picks = surface_picks[surface_picks['UWI'] == active_well]
w = p.get_well(active_well) ##selects the correct welly.Well object
df = w.df() ##reloads the correct dataframe for the display
# regenerate figure with the new horizontal line
fig = helper.make_log_plot(df)
helper.update_picks_on_plot(fig, surface_picks)
return fig
def update_figure(picks, curve, active_well):
"""redraw the plot when the data in tops-storage is updated"""
w = p.get_well(active_well) ##selects the correct welly.Well object
picks_df = pd.read_json(picks)
for i, row in picks_df.iterrows():
print(row.UWI, row.PICK, row.MD)
print('***Active Well', active_well)
picks_selected = picks_df[picks_df['UWI'] == active_well.replace(' ', '-')]
print('***\n***\n***', picks_selected)
# regenerate figure with the new horizontal line
fig = helper.make_log_plot(df)
helper.update_picks_on_plot(fig, picks_selected)
return fig
def update_figure(surface_picks, curve):
"""redraw the plot when the data in tops-storage is updated"""
surface_picks = json.loads(surface_picks)
# regenerate figure with the new horizontal line
"""this is not updating the figure for the newly selected curve"""
fig = px.line(x=df[curve],
y=df.index,
labels={
'x': curve,
'y': df.index.name
})
fig.update_yaxes(autorange="reversed")
helper.update_picks_on_plot(fig, surface_picks)
return fig ###this does not seem to return to dcc.Graph in the app
def update_figure(picks, curve, active_well):
"""redraw the plot when the data in tops-storage is updated"""
w = p.get_well(active_well) ##selects the correct welly.Well object
picks_df = pd.read_json(picks)
picks_selected = picks_df[picks_df['UWI'] == active_well.replace(' ', '-')]
# regenerate figure with the new horizontal line
fig = px.line(x=w.data[curve], y=w.data[curve].basis, labels = {'x':curve, 'y': 'MD'})
fig.layout = {'uirevision': curve} # https://community.plotly.com/t/preserving-ui-state-like-zoom-in-dcc-graph-with-uirevision-with-dash/15793
fig.update_yaxes(autorange="reversed")
fig.layout.xaxis.fixedrange = True
fig.layout.template = 'plotly_white'
helper.update_picks_on_plot(fig, picks_selected)
return fig
dropdown_options = [{
'label': k,
'value': k
} for k in list(surface_picks.keys())]
##Need to make the selector grab the wanted curve
curve_dropdown_options = [{'label': k, 'value': k} for k in curve_list]
# draw the initial plot
fig_well_1 = px.line(x=df[curve],
y=df.index,
labels={
'x': curve,
'y': df.index.name
})
fig_well_1.update_yaxes(autorange="reversed")
helper.update_picks_on_plot(fig_well_1, surface_picks)
app.layout = html.Div(
children=[
html.Div([
'Mode:',
dcc.RadioItems(id='mode-selector',
options=[{
'label': 'Well Display',
'value': 'display_mode'
}, {
'label': 'Tops',
'value': 'tops_mode'
}],
value='display_mode'), 'Edit tops:',
dcc.Dropdown(id='top-selector',
#well dropdown selector
well_dropdown_options = [{'label': k, 'value': k} for k in well_uwi] ##list of wells to the dropdown
#tops dropdown options
tops_dropdown_options = [{'label': k, 'value': k} for k in list(surface_picks.keys())] ##list of tops to the dropdown
##well log curve dropdown options
curve_dropdown_options = [{'label': k, 'value': k} for k in curve_list] ##list of well log curves to the dropdown
# draw the initial plot
fig_well_1 = px.line(x=df[curve], y=df.index, labels = {'x':curve, 'y': df.index.name}) ##polot data and axis lables
fig_well_1.update_yaxes(autorange="reversed") ## flips the y-axis to increase down assuming depth increases
fig_well_1.layout.xaxis.fixedrange = True ##forces the x axis to a fixed range based on the curve data
fig_well_1.layout.template = 'plotly_white' ##template for the plotly figure
helper.update_picks_on_plot(fig_well_1, surface_picks) ## helper script updates the top picks on the figure
app.title = "SwellCorr"
app.layout = html.Div(
children=[
html.Div([
'Select well:', ##Well selector
dcc.Dropdown(id='well-selector', options=well_dropdown_options, value=well_uwi[0], style={'width': '200px'}),
'Edit tops:', ##existing top to edit selector
dcc.Dropdown(id='top-selector', options=tops_dropdown_options, placeholder="Select a top to edit", style={'width': '200px'}),
html.Hr(),
'Create a new surface pick:', html.Br(), ##dialog to creat a new well top correlation for a well
dcc.Input(id='new-top-name', placeholder='Name for new top', type='text', value=''),
html.Button('Create', id='new-top-button'),