zebra/pyzebra
3
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Add ccl_prepare plotting functionality

Browse Source 
* Based on Camilla's notebook
This commit is contained in:
usov_i 2022-05-03 17:18:53 +02:00
parent 42adda235b
commit a192648cc4
2 changed files with 370 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

365
pyzebra/app/panel_ccl_prepare.py
View File

@ -4,25 +4,38 @@ import os
import subprocess
import tempfile
import numpy as np
from bokeh.layouts import column, row
from bokeh.models import (
Arrow,
BoxZoomTool,
Button,
CheckboxGroup,
ColumnDataSource,
CustomJS,
DataRange1d,
Div,
Ellipse,
FileInput,
LinearAxis,
MultiLine,
MultiSelect,
NormalHead,
NumericInput,
Panel,
PanTool,
Plot,
RadioGroup,
Range1d,
ResetTool,
Scatter,
Select,
Spacer,
Text,
TextAreaInput,
TextInput,
WheelZoomTool,
)
from bokeh.palettes import Dark2
import pyzebra
@ -322,15 +335,357 @@ def create():
measured_data_div = Div(text="Measured data:")
measured_data = FileInput(accept=".ccl", multiple=True, width=200)
min_grid_x = -10
max_grid_x = 10
min_grid_y = -5
max_grid_y = 5
cmap = Dark2[8]
syms = ["circle", "inverted_triangle", "square", "diamond", "star", "triangle"]
# Define resolution function
def _res_fun(stt, wave, res_mult):
expr = np.tan(stt / 2 * np.pi / 180)
fwhm = np.sqrt(0.4639 * expr ** 2 - 0.4452 * expr + 0.1506) * res_mult # res in deg
return fwhm
def _bg(x, a, b):
"""Linear background function """
return a * x + b
def plot_file_callback():
pass
orth_dir = list(map(float, hkl_normal.value.split()))
cut_tol = hkl_delta.value
cut_or = 0 # TODO: add slider or numeric input?
x_dir = list(map(float, hkl_in_plane_x.value.split()))
y_dir = list(map(float, hkl_in_plane_y.value.split()))
k = np.array(k_vectors.value.split()).astype(float).reshape(3, 3)
tol_k = 0.1
# Plotting options
grid_flag = 1
grid_minor_flag = 1
grid_div = 2 # Number of minor division lines per unit
# different symbols based on file number
file_flag = 0 in disting_opt_cb.active
# scale marker size according to intensity
intensity_flag = 1 in disting_opt_cb.active
# use color to mark different propagation vectors
prop_legend_flag = 2 in disting_opt_cb.active
# use resolution ellipsis
res_flag = disting_opt_rb.active
# multiplier for resolution function (in case of samples with large mosaicity)
res_mult = res_mult_ni.value
md_fnames = measured_data.filename
md_fdata = measured_data.value
# Load first data cile, read angles and define matrices to perform conversion to cartesian coordinates and back
with io.StringIO(base64.b64decode(md_fdata[0]).decode()) as file:
_, ext = os.path.splitext(md_fnames[0])
try:
file_data = pyzebra.parse_1D(file, ext)
except:
print(f"Error loading {md_fnames[0]}")
return
alpha = file_data[0]["alpha_cell"] * np.pi / 180.0
beta = file_data[0]["beta_cell"] * np.pi / 180.0
gamma = file_data[0]["gamma_cell"] * np.pi / 180.0
# reciprocal angle parameters
alpha_star = np.arccos(
(np.cos(beta) * np.cos(gamma) - np.cos(alpha)) / (np.sin(beta) * np.sin(gamma))
)
beta_star = np.arccos(
(np.cos(alpha) * np.cos(gamma) - np.cos(beta)) / (np.sin(alpha) * np.sin(gamma))
)
gamma_star = np.arccos(
(np.cos(alpha) * np.cos(beta) - np.cos(gamma)) / (np.sin(alpha) * np.sin(beta))
)
# conversion matrix:
M = np.array(
[
[1, 1 * np.cos(gamma_star), 1 * np.cos(beta_star)],
[0, 1 * np.sin(gamma_star), -np.sin(beta_star) * np.cos(alpha)],
[0, 0, 1 * np.sin(beta_star) * np.sin(alpha)],
]
)
M_inv = np.linalg.inv(M)
# Calculate in-plane y-direction
x_c = np.matmul(M, x_dir)
y_c = np.matmul(M, y_dir)
o_c = np.matmul(M, orth_dir)
# Normalize all directions
y_c = y_c / np.linalg.norm(y_c)
x_c = x_c / np.linalg.norm(x_c)
o_c = o_c / np.linalg.norm(o_c)
# Calculations
# Read all data
hkl_coord = []
intensity_vec = []
num_vec = []
k_flag_vec = []
file_flag_vec = []
res_vec_x = []
res_vec_y = []
res_N = 10
for j in range(len(md_fnames)):
with io.StringIO(base64.b64decode(md_fdata[j]).decode()) as file:
_, ext = os.path.splitext(md_fnames[j])
try:
file_data = pyzebra.parse_1D(file, ext)
except:
print(f"Error loading {md_fnames[j]}")
return
# Loop throguh all data
for i in range(len(file_data)):
om = file_data[i]["omega"]
gammad = file_data[i]["twotheta"]
chi = file_data[i]["chi"]
phi = file_data[i]["phi"]
nud = 0 # 1d detector
ub = file_data[i]["ub"]
ddist = float(file_data[i]["detectorDistance"])
counts = file_data[i]["counts"]
mon = file_data[i]["monitor"]
# Determine wavelength from mcvl value (is wavelength stored anywhere???)
mcvl = file_data[i]["mcvl"]
if mcvl == 2.2:
wave = 1.178
elif mcvl == 7.0:
wave = 1.383
else:
wave = 2.3
# Calculate resolution in degrees
res = _res_fun(gammad, wave, res_mult)
# convert to resolution in hkl along scan line
ang2hkl_1d = pyzebra.ang2hkl_1d
res_x = []
res_y = []
scan_om = np.linspace(om[0], om[-1], num=res_N)
for i2 in range(res_N):
expr1 = ang2hkl_1d(
wave, ddist, gammad, scan_om[i2] + res / 2, chi, phi, nud, ub
)
expr2 = ang2hkl_1d(
wave, ddist, gammad, scan_om[i2] - res / 2, chi, phi, nud, ub
)
hkl_temp = np.abs(expr1 - expr2) / 2
hkl_temp = np.matmul(M, hkl_temp)
res_x.append(hkl_temp[0])
res_y.append(hkl_temp[1])
# Get first and final hkl
hkl1 = ang2hkl_1d(wave, ddist, gammad, om[0], chi, phi, nud, ub)
hkl2 = ang2hkl_1d(wave, ddist, gammad, om[-1], chi, phi, nud, ub)
# Get hkl at best intensity
hkl_m = ang2hkl_1d(wave, ddist, gammad, om[np.argmax(counts)], chi, phi, nud, ub)
# Estimate intensity for marker size scaling
y1 = counts[0]
y2 = counts[-1]
x1 = om[0]
x2 = om[-1]
a = (y1 - y2) / (x1 - x2)
b = y1 - a * x1
intensity_exp = np.sum(counts - _bg(om, a, b))
c = int(intensity_exp / mon * 10000)
# Recognize k_flag_vec
found = 0
for j2 in range(len(k)):
# Check if all three components match
test1 = (
np.abs(min(1 - np.mod(hkl_m[0], 1), np.mod(hkl_m[0], 1)) - k[j2][0]) < tol_k
)
test2 = (
np.abs(min(1 - np.mod(hkl_m[1], 1), np.mod(hkl_m[1], 1)) - k[j2][1]) < tol_k
)
test3 = (
np.abs(min(1 - np.mod(hkl_m[2], 1), np.mod(hkl_m[2], 1)) - k[j2][2]) < tol_k
)
if test1 and test2 and test3:
found = 1
k_flag_vec.append(j2)
break
if not found:
k_flag_vec.append(len(k))
# Save data
hkl_list = [
hkl1[0],
hkl1[1],
hkl1[2],
hkl2[0],
hkl2[1],
hkl2[2],
hkl_m[0],
hkl_m[1],
hkl_m[2],
]
hkl_coord.append(hkl_list)
num_vec.append(i)
intensity_vec.append(c)
file_flag_vec.append(j)
res_vec_x.append(res_x)
res_vec_y.append(res_y)
plot.x_range.start = plot.x_range.reset_start = -2
plot.x_range.end = plot.x_range.reset_end = 5
plot.y_range.start = plot.y_range.reset_start = -4
plot.y_range.end = plot.y_range.reset_end = 3.5
xs, ys = [], []
xs_minor, ys_minor = [], []
if grid_flag:
for yy in np.arange(min_grid_y, max_grid_y, 1):
hkl1 = np.matmul(M, [0, yy, 0])
xs.append([-5, 5])
ys.append([hkl1[1], hkl1[1]])
for xx in np.arange(min_grid_x, max_grid_x, 1):
hkl1 = [xx, min_grid_x, 0]
hkl2 = [xx, max_grid_x, 0]
hkl1 = np.matmul(M, hkl1)
hkl2 = np.matmul(M, hkl2)
xs.append([hkl1[0], hkl2[0]])
ys.append([hkl1[1], hkl2[1]])
if grid_minor_flag:
for yy in np.arange(min_grid_y, max_grid_y, 1 / grid_div):
hkl1 = np.matmul(M, [0, yy, 0])
xs_minor.append([min_grid_y, max_grid_y])
ys_minor.append([hkl1[1], hkl1[1]])
for xx in np.arange(min_grid_x, max_grid_x, 1 / grid_div):
hkl1 = [xx, min_grid_x, 0]
hkl2 = [xx, max_grid_x, 0]
hkl1 = np.matmul(M, hkl1)
hkl2 = np.matmul(M, hkl2)
xs_minor.append([hkl1[0], hkl2[0]])
ys_minor.append([hkl1[1], hkl2[1]])
grid_source.data.update(xs=xs, ys=ys)
minor_grid_source.data.update(xs=xs_minor, ys=ys_minor)
scan_x, scan_y, width, height, ellipse_color = [], [], [], [], []
scanl_xs, scanl_ys, scanl_x, scanl_y, scanl_m, scanl_s, scanl_c = [], [], [], [], [], [], []
for j in range(len(num_vec)):
# Get middle hkl from list
hklm = [x for x in hkl_coord[j][6:9]]
hklm = np.matmul(M, hklm)
# Decide if point is in the cut
proj = np.dot(hklm, o_c)
if abs(proj - cut_or) >= cut_tol:
continue
hkl1 = [x for x in hkl_coord[j][0:3]]
hkl2 = [x for x in hkl_coord[j][3:6]]
hkl1 = np.matmul(M, hkl1)
hkl2 = np.matmul(M, hkl2)
if intensity_flag:
markersize = max(1, int(intensity_vec[j] / max(intensity_vec) * 20))
else:
markersize = 4
if file_flag:
plot_symbol = syms[file_flag_vec[j]]
else:
plot_symbol = "circle"
if prop_legend_flag:
col_value = cmap[k_flag_vec[j]]
else:
col_value = "black"
if res_flag:
# Generate series of ellipses along scan line
scan_x.extend(np.linspace(hkl1[0], hkl2[0], num=res_N))
scan_y.extend(np.linspace(hkl1[1], hkl2[1], num=res_N))
width.extend(np.array(res_vec_x[j]) * 2)
height.extend(np.array(res_vec_y[j]) * 2)
ellipse_color.extend([col_value] * res_N)
else:
# Plot scan line
scanl_xs.append([hkl1[0], hkl2[0]])
scanl_ys.append([hkl1[1], hkl2[1]])
scanl_c.append(col_value)
# Plot middle point of scan
scanl_x.append(hklm[0])
scanl_y.append(hklm[1])
scanl_m.append(plot_symbol)
scanl_s.append(markersize)
ellipse_source.data.update(x=scan_x, y=scan_y, w=width, h=height, c=ellipse_color)
scan_source.data.update(
xs=scanl_xs, ys=scanl_ys, x=scanl_x, y=scanl_y, m=scanl_m, s=scanl_s, c=scanl_c
)
arrow1.visible = True
arrow1.x_end = x_c[0]
arrow1.y_end = x_c[1]
arrow2.visible = True
arrow2.x_end = y_c[0]
arrow2.y_end = y_c[1]
kvect_source.data.update(
text_x=[x_c[0] / 2, y_c[0] / 2 - 0.1],
text_y=[x_c[1] - 0.1, y_c[1] / 2],
text=["h", "k"],
)
plot_file = Button(label="Plot selected file(s)", button_type="primary", width=200)
plot_file.on_click(plot_file_callback)
plot = Plot(x_range=DataRange1d(), y_range=DataRange1d(), plot_height=450, plot_width=600)
plot = Plot(x_range=Range1d(), y_range=Range1d(), plot_height=450, plot_width=600)
plot.add_tools(PanTool(), WheelZoomTool(), BoxZoomTool(), ResetTool())
plot.toolbar.logo = None
plot.add_layout(LinearAxis(), place="left")
plot.add_layout(LinearAxis(), place="below")
arrow1 = Arrow(x_start=0, y_start=0, x_end=0, y_end=0, end=NormalHead(size=10), visible=False)
plot.add_layout(arrow1)
arrow2 = Arrow(x_start=0, y_start=0, x_end=0, y_end=0, end=NormalHead(size=10), visible=False)
plot.add_layout(arrow2)
kvect_source = ColumnDataSource(dict(text_x=[], text_y=[], text=[]))
plot.add_glyph(kvect_source, Text(x="text_x", y="text_y", text="text"))
grid_source = ColumnDataSource(dict(xs=[], ys=[]))
minor_grid_source = ColumnDataSource(dict(xs=[], ys=[]))
plot.add_glyph(grid_source, MultiLine(xs="xs", ys="ys", line_color="gray"))
plot.add_glyph(
minor_grid_source, MultiLine(xs="xs", ys="ys", line_color="gray", line_dash="dotted")
)
ellipse_source = ColumnDataSource(dict(x=[], y=[], w=[], h=[], c=[]))
plot.add_glyph(
ellipse_source, Ellipse(x="x", y="y", width="w", height="h", fill_color="c", line_color="c")
)
scan_source = ColumnDataSource(dict(xs=[], ys=[], x=[], y=[], m=[], s=[], c=[]))
plot.add_glyph(scan_source, MultiLine(xs="xs", ys="ys", line_color="c"))
plot.add_glyph(
scan_source, Scatter(x="x", y="y", marker="m", size="s", fill_color="c", line_color="c")
)
hkl_div = Div(text="HKL:", margin=(5, 5, 0, 5))
hkl_normal = TextInput(title="normal", value="0 0 1", width=100)
hkl_delta = NumericInput(title="delta", value=0.1, mode="float", width=70)
@ -350,7 +705,7 @@ def create():
k_vectors = TextAreaInput(
title="k vectors:", value="0.0 0.0 0.0\n0.5 0.0 0.0\n0.5 0.5 0.0", width=150,
)
res_mult = NumericInput(title="Resolution mult:", value=10, mode="int", width=100)
res_mult_ni = NumericInput(title="Resolution mult:", value=10, mode="int", width=100)
fileinput_layout = row(open_cfl_div, open_cfl, open_cif_div, open_cif, open_geom_div, open_geom)
@ -393,7 +748,7 @@ def create():
row(measured_data_div, measured_data, plot_file),
plot,
row(hkl_layout, k_vectors),
row(disting_layout, res_mult),
row(disting_layout, res_mult_ni),
)
tab_layout = row(column1_layout, column2_layout)

10
pyzebra/xtal.py
View File

@ -372,6 +372,16 @@ def ang2hkl(wave, ddist, gammad, om, ch, ph, nud, ub, x, y):
return hkl
def ang2hkl_1d(wave, ddist, ga, om, ch, ph, nu, ub):
"""Calculate hkl-indices of a reflection from its position (angles) at the 1d-detector
"""
z1 = z1frmd(wave, ga, om, ch, ph, nu)
ubinv = np.linalg.inv(ub)
hkl = ubinv @ z1
return hkl
def ang_proc(wave, ddist, gammad, om, ch, ph, nud, x, y):
"""Utility function to calculate ch, ph, ga, om
"""