def update_btn_single():
genotype = genotypes_selection_single_genotype.v_model
if genotype:
vids = get_vid_of_genotype(misc.all_mtg, [genotype])
df = extract_at_module_scale(misc.all_mtg, vids=vids)
geno_frequency = occurence_module_order_along_time(
data=df, frequency_type="cdf")
update_btn_export(link_export_t11, geno_frequency)
if genotype:
vids = get_vid_of_genotype(misc.all_mtg, [genotype])
df = extract_at_module_scale(misc.all_mtg, vids=vids)
res = pd.crosstab(index=df["order"],
columns=df["complete_module"],
normalize="index")
res.columns = ["incomplete", "complete"]
update_btn_export(link_export_t12, res)
if genotype:
vids = get_vid_of_genotype(misc.all_mtg, [genotype])
df = extract_at_module_scale(misc.all_mtg, vids=vids)
res = pd.crosstab(index=df["date"],
columns=df["complete_module"],
normalize="index")
res.columns = ["incomplete", "complete"]
update_btn_export(link_export_t13, res)
def on_change_node_waffle_parameter(widget, event, data):
if not date_selection_waffle.v_model:
pass
else:
with waffle:
waffle.clear_output()
genotype = genotypes_selection_waffle.v_model
vids = get_vid_of_genotype(misc.all_mtg, [genotype])
df = extract_at_node_scale(misc.all_mtg, vids=vids)
tmp = df2waffle(df,
index='rank',
date=date_selection_waffle.v_model,
variable=data,
order=order_selection_waffle.v_model)
# TODO: remove the legend here (which only apply to branching_type)
l_names = {
"1": "Stolon",
"2": "Vegetative bud",
"3": "Initiated bud",
"4": "Aborted bud",
"5": "Floral bud",
"6": "Branch crown"
}
fig = plot_waffle(
tmp,
# layout=layout,
legend_name=l_names,
plot_func=plot_type_waffle.v_model)
display(fig)
def on_change_geno_2d(widget, event, data):
id_selection_2d.items = list(
range(len(get_vid_of_genotype(misc.all_mtg, [data]))))
id_selection_2d.v_model = 1
print_2d_median(misc.all_mtg, data)
print_2d_single_p(misc.all_mtg, data, vid=id_selection_2d.v_model)
def on_change_module_plot_type(widget, event, data):
if date_selection_waffle.v_model and parameter_selection_waffle.v_model:
with waffle:
waffle.clear_output()
genotype = genotypes_selection_waffle.v_model
vids = get_vid_of_genotype(misc.all_mtg, [genotype])
df = extract_at_module_scale(misc.all_mtg, vids=vids)
if aggfunc_selection_waffle.v_model == 'concat_string':
tmp = df2waffle(df,
index='order',
date=date_selection_waffle.v_model,
variable=parameter_selection_waffle.v_model,
aggfunc=lambda x: ' '.join(x),
crosstab=False)
else:
tmp = df2waffle(df,
index='order',
date=date_selection_waffle.v_model,
variable=parameter_selection_waffle.v_model,
aggfunc=aggfunc_selection_waffle.v_model,
crosstab=False)
fig = plot_waffle(
tmp,
# layout=layout,
plot_func=data)
display(fig)
def print_2d_single_p(g, genotype, vid):
with plot2d_single_p:
plot2d_single_p.clear_output()
vids_selected = get_vid_of_genotype(g, genotypes=[genotype])
g.properties()['order'] = orders(g)
scene = visu2d.plot2d(g, [vids_selected[vid]],
dist=[3] * 3,
display=False)
display3d(scene)
def on_change_genotype_p3_t2(widget, event, data):
genotype = genotypes_selection_analyze.v_model
vids = get_vid_of_genotype(misc.all_mtg, [genotype])
df = extract_at_plant_scale(misc.all_mtg, vids=vids)
param = list(df.columns)
param.remove("Genotype")
param.remove('date')
date_selection_analyze.items = list(df.date.unique())
date_selection_analyze.v_model = ""
variable_selection_analyze.items = param
def print_2d_median(g, genotype):
with plot2d_most_central:
plot2d_most_central.clear_output()
vids_selected = get_vid_of_genotype(g, genotypes=[genotype])
g.properties()['order'] = orders(g)
df = extract_at_plant_scale(g, vids=vids_selected)
df_median = median_individuals(df, )
# selection of vid of median individuals
pids = list(df_median.vid)
n = len(pids)
scene = visu2d.plot2d(g, pids, dist=[6] * n, display=False)
display3d(scene)
def on_change_genotype_p3_t1(widget, event, data):
# update table
df = pd.DataFrame()
if misc.all_mtg:
vids = get_vid_of_genotype(misc.all_mtg, genotypes=data)
df = extract_at_plant_scale(misc.all_mtg, vids=vids)
update_grid(df, df_plantscale)
# update descriptors
update_grid(df.describe(), df_description)
update_btn_extract()
def on_change_module_waffle_genotype(widget, event, data):
genotype = genotypes_selection_waffle.v_model
vids = get_vid_of_genotype(misc.all_mtg, [genotype])
df = extract_at_module_scale(misc.all_mtg, vids=vids)
param = list(df.columns)
param.remove("Genotype")
param.remove('date')
param.remove('order')
param.remove('plant')
date_selection_waffle.items = list(df.date.unique())
date_selection_waffle.v_model = ""
parameter_selection_waffle.items = param
def on_change_node_waffle_genotype(widget, event, data):
genotype = genotypes_selection_waffle.v_model
vids = get_vid_of_genotype(misc.all_mtg, [genotype])
df = extract_at_node_scale(misc.all_mtg, vids=vids)
param = list(df.columns)
param.remove("Genotype")
param.remove('date')
date_selection_waffle.items = list(df.date.unique())
date_selection_waffle.v_model = ""
variable_selection_waffle.items = param
order = list(df.order.unique())
order.append({'text': 'All', 'value': None})
order_selection_waffle.items = order
def print_files_description():
with files_description:
files_description.clear_output()
# nb of files selected
nb_files = len(files_selection.v_model)
# experiments names:
exp_names = set(misc.all_mtg.property('Experiment_name').values())
# genotypes:
genotype_names = get_genotypes(misc.all_mtg)
# mtg.properties: + list of possible values
properties = [(p, set(misc.all_mtg.property(p).values()))
for p in misc.all_mtg.property_names() if p not in [
'edge_type', 'index', 'label', 'Experiment_name',
'Genotype', '_line', 'DBI'
]]
print('Number of files selected:', nb_files)
print('Experiment names:', exp_names)
print('List of genotypes:', genotype_names)
for genotype in genotype_names:
print(genotype, ':',
len(get_vid_of_genotype(misc.all_mtg, [genotype])),
' plants')
print('List of properties:', misc.all_mtg.property_names())
print('\n')
print('List of properties values:')
for p in properties:
if p[1]:
if isinstance(next(iter(p[1])), float):
print(
p[0],
' min:',
min(p[1]),
'max:',
max(p[1]),
'mean:',
np.mean(list(p[1])),
'std:',
np.std(list(p[1])),
'Q1:',
np.quantile(list(p[1]), 0.25),
'Q2:',
np.quantile(list(p[1]), 0.50),
'Q3:',
np.quantile(list(p[1]), 0.75),
)
else:
print(p[0], ': ', p[1])
def on_change_genotype(widget, event, data):
# update plant selection
slider_n_plant.disabled = False
box_n_plant.disabled = False
cb_allplants.disabled = False
slider_n_plant.max = len(get_vid_of_genotype(misc.all_mtg, [data]))
slider_n_plant.v_model = 1
# update mtg preview
print_preview(misc.all_mtg,
genotype=data,
p_nb=slider_n_plant.v_model,
width="500px",
height="800px")
def print_3d_growth_developement(g, genotype):
if g:
with plot3d_growth_developement:
plot3d_growth_developement.clear_output()
print('3d growth developement')
vids_selected = get_vid_of_genotype(g, genotypes=[genotype])
g.properties()['order'] = orders(g)
scene = visu3d.plot3d(g,
by=["Sample_date"],
hide_leaves=False,
display=False,
vids=vids_selected)
display3d(scene)
else:
with plot3d_growth_developement:
plot3d_growth_developement.clear_output()
print('Select a Genotype')
def print_3d_floral_intensity(g, genotype):
if g:
with plot3d_floral_intensity:
plot3d_floral_intensity.clear_output()
print('3d floral_intensity ')
vids_selected = get_vid_of_genotype(g, genotypes=[genotype])
g.properties()['order'] = orders(g)
scene = visu3d.plot3d(g,
by=["Sample_date"],
hide_leaves=True,
display=False,
vids=vids_selected)
display3d(scene)
else:
with plot3d_floral_intensity:
plot3d_floral_intensity.clear_output()
print('Select a Genotype')
def on_change_parameter_p3(widget, event, data):
# if date ...
genotype = genotypes_selection_analyze.v_model
vids = get_vid_of_genotype(misc.all_mtg, [genotype])
df = extract_at_plant_scale(misc.all_mtg, vids=vids)
res = df.groupby('date').mean()
p = res.iplot(
kind="line",
mode='lines+markers',
y=data,
xTitle="Dates",
yTitle=data,
# yTitle="Probability",
# title="Relative distribution of complete (True) and incomplete (False) module as function of date for {}".format(genotype),
asFigure=True)
transfert_figure(p, plot_plantscale)
def print_single_genotype_plots():
genotype = genotypes_selection_single_genotype.v_model
vids = get_vid_of_genotype(misc.all_mtg, [genotype])
df = extract_at_module_scale(misc.all_mtg, vids=vids)
if genotype:
# plot occurence module order
fig = plot_module_occurence_module_order_along_time(df, genotype)
transfert_figure(fig, plot_occurence)
# plot occurence module order
fig = plot_module_distribution_complete_incomplete_module_order(
df, genotype)
transfert_figure(fig, plot_distribution_module_order)
# plot occurence module order
fig = plot_module_distribution_complete_incomplete_date(df, genotype)
transfert_figure(fig, plot_distribution_date)
else:
with plot_occurence:
plot_occurence.clear_output()
print('Select a Genotype')
def on_change_date_p3(widget, event, data):
genotype = genotypes_selection_analyze.v_model
vids = get_vid_of_genotype(misc.all_mtg, [genotype])
df = extract_at_module_scale(misc.all_mtg, vids=vids)
tmp = df2waffle(df,
index='order',
date=data,
variable='stage',
crosstab=True)
try:
fig = plot_pie(tmp)
fig.update_layout(
title="Percentage representation of each stage at one date")
transfert_figure_pie(fig, pie_plantscale)
except ValueError:
pass
def update_btn_extract():
genotype = genotypes_selection_extraction.v_model
if genotype:
vids = get_vid_of_genotype(misc.all_mtg, genotype)
df = extract_at_module_scale(misc.all_mtg, vids=vids)
update_btn_export(export_extraction, df)