import numpy as np
import pandas as pd
import xarray as xr
from math import sqrt
import plotly.graph_objects as go
import plotly.express as px
import ipywidgets
from sklearn.preprocessing import OrdinalEncoder
[docs]
class DiffractionLabeler:
[docs]
def __init__(self,saxs_data,composition_data,possible_phase_labels):
self.data_view = DiffractionLabelerView()
self.data_model = DiffractionLabelerModel(saxs_data,composition_data,possible_phase_labels)
self.data_index = 0
[docs]
def goto_callback(self,click):
index = self.data_view.current_index.value
self.data_index=index
self.update_plot()
[docs]
def ternary_click_callback(self,figure,location,click):
index = location.point_inds[0]
self.data_index = index
self.data_view.current_index.value = self.data_index
self.update_plot()
[docs]
def update_plot(self):
saxs_data = self.data_model.saxs_data[self.data_index]
composition_data = self.data_model.composition_data[self.data_index]
self.data_view.update_plot(x=saxs_data.q.values,y=saxs_data.values,composition=composition_data)
self.data_view.current_label.value = self.data_model.phase_labels[self.data_index]
[docs]
def draw_peaks(self,peaks):
self.data_view.output.clear_output()
with self.data_view.output:
for i,(vl,(spacing,peak_loc)) in enumerate(zip(self.data_view.fig1.layout.shapes,peaks.items())):
print('{}q* = {}'.format(spacing,peak_loc))
vl.update({
'x0':peak_loc,
'x1':peak_loc,
'visible':True
})
for i,vl, in enumerate(self.data_view.fig1.layout.shapes):
if i>len(peaks)-1:
vl.visible=False
[docs]
def change_qstar_callback(self,figure,location,click):
model = self.data_view.phase_dropdown.value
n_orders = self.data_view.n_orders.value
peaks = self.data_model.get_peaks(model,qstar=location.xs[0],max_order=n_orders)
self.draw_peaks(peaks)
[docs]
def change_model_callback(self,data):
model = self.data_view.phase_dropdown.value
n_orders = self.data_view.n_orders.value
peaks = self.data_model.get_peaks(model,max_order=n_orders)
self.draw_peaks(peaks)
[docs]
def change_norder_callback(self,data):
model = self.data_view.phase_dropdown.value
n_orders = self.data_view.n_orders.value
peaks = self.data_model.get_peaks(model,max_order=n_orders)
self.draw_peaks(peaks)
[docs]
def label(self,label):
self.data_model.phase_labels[self.data_index] = label
self.data_view.update_ternary_colors(self.data_model.ordinal_phase_labels())
self.next_button_callback(None)
[docs]
def run(self):
saxs_data = self.data_model.saxs_data[self.data_index]
composition_data = self.data_model.composition_data[self.data_index]
widget = self.data_view.run(
x = saxs_data.q.values,
y = saxs_data.values,
all_compositions = self.data_model.composition_data,
composition = composition_data,
models = list(self.data_model.models.keys()),
possible_phase_labels=[],
)
self.data_view.intensity.on_click(self.change_qstar_callback)
self.data_view.phase_dropdown.observe(self.change_model_callback)
self.data_view.current_label.value = self.data_model.phase_labels[self.data_index]
self.data_view.current_index.value = str(self.data_index)
self.data_view.bnext.on_click(self.next_button_callback)
self.data_view.bprev.on_click(self.prev_button_callback)
self.data_view.bgoto.on_click(self.goto_callback)
self.data_view.all_ternary.on_click(self.ternary_click_callback)
self.data_view.n_orders.observe(self.change_norder_callback)
self.data_view.b0.on_click(lambda click: self.label('C'))
self.data_view.b1.on_click(lambda click: self.label('L'))
self.data_view.b2.on_click(lambda click: self.label('S'))
self.data_view.b3.on_click(lambda click: self.label('D'))
return widget
##################
### Data Model ###
##################
[docs]
class DiffractionLabelerModel:
[docs]
def __init__(self,saxs_data,composition_data,possible_phase_labels):
self.saxs_data = saxs_data
self.composition_data = composition_data
self.phase_labels = ['Unlabeled']*len(composition_data)
self.possible_phase_labels = possible_phase_labels
self.qstar = 0.02
self.init_models()
[docs]
def ordinal_phase_labels(self):
enc = OrdinalEncoder()
return enc.fit_transform(np.asarray(self.phase_labels)[:,np.newaxis]).flatten()
[docs]
def init_models(self):
self.models = {}
self.models['q*'] = {
'labels':["1"],
'spacings':[1]
}
self.models['LAM'] = {
'labels':["1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20"],
'spacings':[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]
}
self.models['HCP CYL'] = {
'labels': ["1"," sqrt(3)"," 2"," sqrt(7)"," 3"," sqrt(12)"," sqrt(13)"," 4"," sqrt(19)"," sqrt(21)"," 5"," sqrt(27)"," sqrt(28)"," sqrt(31)"," 6"," sqrt(37)"," sqrt(39)"," sqrt(43)"," sqrt(48)","7"],
'spacings': [1, sqrt(3), 2, sqrt(7), 3, sqrt(12), sqrt(13), 4, sqrt(19), sqrt(21), 5, sqrt(27), sqrt(28), sqrt(31), 6, sqrt(37), sqrt(39), sqrt(43), sqrt(48), 7]
}
self.models['SC'] = {
'labels': ["1","sqrt(2)","sqrt(3)","2","sqrt(5)","sqrt(6)","sqrt(8)","3"],
'spacings': [1,sqrt(2),sqrt(3),2,sqrt(5),sqrt(6),sqrt(8),3]
}
self.models['BCC'] = {
'labels':["1","sqrt(2)","sqrt(3)","2","sqrt(5)","sqrt(6)","sqrt(7)","sqrt(8)","3"],
'spacings':[1,sqrt(2),sqrt(3),2,sqrt(5),sqrt(6),sqrt(7),sqrt(8),3],
}
self.models['FCC'] = {
'labels':["sqrt(3)","2","sqrt(8)","sqrt(11)","sqrt(12)","4","sqrt(19)"],
'spacings':[1,2/sqrt(3),sqrt(8)/sqrt(3),sqrt(11)/sqrt(3),sqrt(12)/sqrt(3),4/sqrt(3),sqrt(19)/sqrt(3)],
}
self.models['SPH'] = {
'labels':["1","2/sqrt(3)","2*sqrt(2)/sqrt(3)","2"],
'spacings':[1,2/sqrt(3),2*sqrt(2)/sqrt(3),2],
}
self.models['HCP SPH'] = {
'labels':["sqrt(32)","6","sqrt(41)","sqrt(68)","sqrt(96)","sqrt(113)"],
'spacings':[1,6/sqrt(32),sqrt(41)/sqrt(32),sqrt(68)/sqrt(32),sqrt(96)/sqrt(32),sqrt(113)/sqrt(32)],
}
self.models['DD'] = {
'labels':["sqrt(2)"," sqrt(3)"," 2"," sqrt(6)"," sqrt(8)"," 3"," sqrt(10)"," sqrt(11)"],
'spacings':[1, sqrt(3)/sqrt(2), 2/sqrt(2), sqrt(6)/sqrt(2), sqrt(8)/sqrt(2), 3/sqrt(2), sqrt(10)/sqrt(2), sqrt(11)/sqrt(2)],
}
self.models['GYR'] = {
'labels':["sqrt(6)","sqrt(8)","sqrt(14)","sqrt(16)","sqrt(20)","sqrt(22)","sqrt(24)","sqrt(26)","sqrt(30)","sqrt(32)","sqrt(34)","sqrt(38)","sqrt(40)","sqrt(42)","sqrt(46)","sqrt(48)","sqrt(50)","sqrt(52)","sqrt(56)","sqrt(62)","sqrt(64)","sqrt(66)","sqrt(68)","sqrt(70)","sqrt(72)","sqrt(74)","sqrt(78)","sqrt(80)","sqrt(84)","sqrt(86)","sqrt(88)","sqrt(90)"],
'spacings':[6,8,14,16,20,22,24,26,30,32,34,38,40,42,46,48,50,52,56,62,64,66,68,70,72,74,78,80,84,86,88,90],
}
self.models['GYR']['spacings'] = [sqrt(i)/sqrt(6) for i in self.models['GYR']['spacings']]
[docs]
def get_peaks(self,model,qstar=None,max_order=4):
if qstar is None:
qstar=self.qstar
else:
self.qstar=qstar
peaks = {}
for i,(spacing,label) in enumerate(zip(self.models[model]['spacings'],self.models[model]['labels'])):
if i>=max_order:
break
peaks[label] = spacing*qstar
return peaks
#################
### Data View ###
#################
[docs]
class DiffractionLabelerView:
[docs]
def __init__(self):
self.intensity = None
self.nverts = 8
[docs]
def update_plot(self,x,y,composition):
self.intensity.update({'x':x,'y':y})
self.ternary.update({
'a':(composition[0],),
'b':(composition[1],),
'c':(composition[2],)
})
[docs]
def remove_vertical_lines(self):
self.fig1.layout['shapes'] = []
[docs]
def add_vertical_line(self,x,y0=0,y1=128,row=1,col=1,line_kw=None):
if line_kw is None:
line_kw=dict(color='red',dash='dot',width=0.3)
self.fig1.add_shape(
name='vertical',
xref='x',
yref='paper',
x0=x, x1=x, y0=0, y1=1,
line=line_kw,
)
[docs]
def update_ternary_colors(self,colors):
self.all_ternary.marker['color'] = colors
[docs]
def run(self,x,y,all_compositions,composition,models,possible_phase_labels):
self.fig1 = go.FigureWidget(
go.Scatter(x=x,y=y)
)
self.intensity = self.fig1.data[0]
self.fig1.update_yaxes(type='log')
self.fig1.update_xaxes({'range':(0,0.1)})
self.fig1.update_layout(height=300,width=400,margin=dict(t=10,b=10,l=10,r=0))
for i in range(self.nverts):
self.add_vertical_line(0.02*i)
self.fig1.layout.shapes[i].visible = False
self.fig2 = go.FigureWidget([
go.Scatterternary(
a = all_compositions[:,0],
b = all_compositions[:,1],
c = all_compositions[:,2],
mode = 'markers',
marker={
'color':['black']*len(x),
'colorscale':px.colors.qualitative.Prism,
},
customdata = list(range(len(all_compositions))),
opacity=1.0,
showlegend=False,
),
go.Scatterternary(
a = (composition[0],),
b = (composition[1],),
c = (composition[2],),
mode = 'markers',
showlegend=False,
marker={
'color':'red',
'symbol':'hexagon-open',
'size':10,
},
),
]
)
self.all_ternary = self.fig2.data[0]
self.ternary = self.fig2.data[1]
self.fig2.update_layout(height=300,width=500,margin=dict(t=25,b=35,l=10))
plot_box = ipywidgets.HBox([self.fig1,self.fig2])
self.b0 = ipywidgets.Button(description='Cylinder (yellow)')
self.b1 = ipywidgets.Button(description='Lamellae (purple)')
self.b2 = ipywidgets.Button(description='Sphere (red)')
self.b3 = ipywidgets.Button(description='Disordered (blue)')
self.br = ipywidgets.Button(description='Reset')
self.bprev = ipywidgets.Button(description='Prev')
self.bnext = ipywidgets.Button(description='Next')
self.bgoto = ipywidgets.Button(description='GoTo')
self.current_index = ipywidgets.IntText(description="Data Index:",value=0)
self.n_orders = ipywidgets.BoundedIntText(description='n_orders',min=1,max=8,value=4)
self.phase_dropdown = ipywidgets.Dropdown(
options=models
)
self.current_label_label = ipywidgets.Label('Current Label:')
self.current_label = ipywidgets.Label('')
phase_box = ipywidgets.HBox([
self.phase_dropdown,
self.n_orders,
self.current_label_label,
self.current_label,
])
buttons_hbox1 = ipywidgets.HBox([self.b0,self.b1,self.b2,self.b3,self.br])
buttons_hbox2 = ipywidgets.HBox([
self.current_index,
self.bgoto,
self.bprev,
self.bnext,
])
self.output = ipywidgets.Output()
vbox = ipywidgets.VBox([
buttons_hbox1,
buttons_hbox2,
phase_box,
plot_box,
self.output
])
return vbox
