extrema_data_x.append(idx)
extrema_data_y.append(bs_df[word_map[tp]][idx])
extrema_data_labels.append(bs_df['str_kpts'][idx])
plt['data'].append(
go.Scatter(
x = initial_extrema_data_x,
y = initial_extrema_data_y,
mode = 'markers',
name = 'initial extrema',
text = initial_extrema_data_labels,
marker = {'size': 15, 'symbol': 'diamond-open', 'color': 'rgb(0, 255, 0)',
'line': {'width': 3}}
)
)
plt['data'].append(
go.Scatter(
x = extrema_data_x,
y = extrema_data_y,
mode = 'markers',
name = 'selected extrema',
text = extrema_data_labels,
marker = {'size': 20, 'symbol': 'circle-open', 'color': 'rgb(255, 0, 0)',
'line': {'width': 4}}
)
)
pf.create_plot(plt)
def plot_modes(api_key, username):
"""
Demonstrate PlotlyFig plotting modes and show the easiest way to make
adjustments.
Offline mode - Set "mode" to "offline"
Create a local html file. Note that offline mode in plotly disables LaTeX
and some fonts on some systems by default. For the full-featured Plotly
experience, please use the Plotly online mode.
Static mode - Set "mode" to "static"
Creates a single image file. Use height and width to specify the size of the
image desired. api_key and username are required for static plotting mode.
Online mode - Set "mode" to "online"
Opens the figure in the Plotly online module.
Notebook mode - Set "mode" to "notebook"
Opens the figure in a Jupyter/IPython notebook. Not shown here, seen
matminer_examples repository.
Return mode - Pass "return_plot=True" into any plotting method
Returns the figure as a 'bare-bones' dictionary. This can then be edited and
passed into 'create_plot' of PlotlyFig or used directly with plotly.
"""
if not api_key or not username:
raise ValueError("Specify your Plotly api_key and username!")
df = load_elastic_tensor()
# First lets set uo our figure generally.
pf = PlotlyFig(df,
title='Elastic data',
mode='offline',
x_scale='log',
y_scale='log')
# Lets plot offline (the default) first. An html file will be created.
pf.xy([('poisson_ratio', 'elastic_anisotropy')], labels='formula')
# Now lets plot again, but changing the filename and without opening.
# We do this with the 'set_arguments' method.
pf.set_arguments(show_offline_plot=False, filename="myplot.html")
pf.xy([('poisson_ratio', 'elastic_anisotropy')], labels='formula')
# Now lets create a static image.
pf.set_arguments(mode='static',
api_key=api_key,
username=username,
filename="my_PlotlyFig_plot.jpeg")
pf.xy([('poisson_ratio', 'elastic_anisotropy')], labels='formula')
# You can change the size of the image with the 'height' and 'width'
# arguments to set_arguments.
# Now we will use the Plotly online interface.
pf.set_arguments(mode='online')
pf.xy([('poisson_ratio', 'elastic_anisotropy')], labels='formula')
# Great! Lets get the JSON representation of the PlotlyFig template as a
# python dictionary. We can do this without changing the plot mode. From
# any plotting method, simply pass 'return_plot=True' to return the plot.
fig = pf.xy([('poisson_ratio', 'elastic_anisotropy')],
labels='formula',
return_plot=True)
print("Here's our returned figure!")
pprint.pprint(fig)
# Edit the figure and plot it with the current plot mode (online):
fig['layout']['hoverlabel']['bgcolor'] = 'pink'
fig['layout']['title'] = 'My Custom Elastic Data Figure'
pf.create_plot(fig)
def plot_modes(api_key, username):
"""
Demonstrate PlotlyFig plotting modes and show the easiest way to make
adjustments.
Offline mode - Set "mode" to "offline"
Create a local html file. Note that offline mode in plotly disables LaTeX
and some fonts on some systems by default. For the full-featured Plotly
experience, please use the Plotly online mode.
Static mode - Set "mode" to "static"
Creates a single image file. Use height and width to specify the size of the
image desired. api_key and username are required for static plotting mode.
Online mode - Set "mode" to "online"
Opens the figure in the Plotly online module.
Notebook mode - Set "mode" to "notebook"
Opens the figure in a Jupyter/IPython notebook. Not shown here, seen
matminer_examples repository.
Return mode - Pass "return_plot=True" into any plotting method
Returns the figure as a 'bare-bones' dictionary. This can then be edited and
passed into 'create_plot' of PlotlyFig or used directly with plotly.
"""
if not api_key or not username:
raise ValueError("Specify your Plotly api_key and username!")
df = load_elastic_tensor()
# First lets set uo our figure generally.
pf = PlotlyFig(df, title='Elastic data', mode='offline', x_scale='log',
y_scale='log')
# Lets plot offline (the default) first. An html file will be created.
pf.xy([('poisson_ratio', 'elastic_anisotropy')], labels='formula')
# Now lets plot again, but changing the filename and without opening.
# We do this with the 'set_arguments' method.
pf.set_arguments(show_offline_plot=False, filename="myplot.html")
pf.xy([('poisson_ratio', 'elastic_anisotropy')], labels='formula')
# Now lets create a static image.
pf.set_arguments(mode='static',
api_key=api_key,
username=username,
filename="my_PlotlyFig_plot.jpeg")
pf.xy([('poisson_ratio', 'elastic_anisotropy')], labels='formula')
# You can change the size of the image with the 'height' and 'width'
# arguments to set_arguments.
# Now we will use the Plotly online interface.
pf.set_arguments(mode='online')
pf.xy([('poisson_ratio', 'elastic_anisotropy')], labels='formula')
# Great! Lets get the JSON representation of the PlotlyFig template as a
# python dictionary. We can do this without changing the plot mode. From
# any plotting method, simply pass 'return_plot=True' to return the plot.
fig = pf.xy([('poisson_ratio', 'elastic_anisotropy')], labels='formula',
return_plot=True)
print("Here's our returned figure!")
pprint.pprint(fig)
# Edit the figure and plot it with the current plot mode (online):
fig['layout']['hoverlabel']['bgcolor'] = 'pink'
fig['layout']['title'] = 'My Custom Elastic Data Figure'
pf.create_plot(fig)
