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Prepare spind input directly in hdf viewer

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This commit is contained in:
usov_i 2021-06-23 11:25:44 +02:00
parent c10efeb9cc
commit 57e503fc3d
2 changed files with 124 additions and 128 deletions
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126
pyzebra/app/panel_hdf_viewer.py
View File

@ -1,8 +1,10 @@
import base64
import io
import math
import os
import numpy as np
from bokeh.io import curdoc
from bokeh.layouts import column, gridplot, row
from bokeh.models import (
BasicTicker,
@ -40,6 +42,7 @@ from bokeh.models import (
WheelZoomTool,
)
from bokeh.palettes import Cividis256, Greys256, Plasma256 # pylint: disable=E0611
from scipy.optimize import curve_fit
import pyzebra
@ -50,9 +53,9 @@ IMAGE_PLOT_H = int(IMAGE_H * 2) + 27
def create():
doc = curdoc()
det_data = {}
cami_meta = {}
roi_selection = {}
def proposal_textinput_callback(_attr, _old, new):
nonlocal cami_meta
@ -573,29 +576,91 @@ def create():
hkl_button = Button(label="Calculate hkl (slow)", width=210)
hkl_button.on_click(hkl_button_callback)
selection_list = TextAreaInput(rows=7)
def events_list_callback(_attr, _old, new):
doc.events_list_spind.value = new
def selection_button_callback():
nonlocal roi_selection
selection = [
int(np.floor(det_x_range.start)),
int(np.ceil(det_x_range.end)),
int(np.floor(det_y_range.start)),
int(np.ceil(det_y_range.end)),
int(np.floor(frame_range.start)),
int(np.ceil(frame_range.end)),
]
events_list = TextAreaInput(rows=7, width=830)
events_list.on_change("value", events_list_callback)
doc.events_list_hdf_viewer = events_list
filename_id = file_select.value[0][-8:-4]
if filename_id in roi_selection:
roi_selection[f"{filename_id}"].append(selection)
else:
roi_selection[f"{filename_id}"] = [selection]
def add_event_button_callback():
diff_vec = []
p0 = [1.0, 0.0, 1.0]
maxfev = 100000
selection_list.value = str(roi_selection)
wave = det_data["wave"]
ddist = det_data["ddist"]
selection_button = Button(label="Add selection")
selection_button.on_click(selection_button_callback)
gamma = det_data["gamma"][0]
omega = det_data["omega"][0]
nu = det_data["nu"][0]
chi = det_data["chi"][0]
phi = det_data["phi"][0]
scan_motor = det_data["scan_motor"]
var_angle = det_data[scan_motor]
x0 = int(np.floor(det_x_range.start))
xN = int(np.ceil(det_x_range.end))
y0 = int(np.floor(det_y_range.start))
yN = int(np.ceil(det_y_range.end))
fr0 = int(np.floor(frame_range.start))
frN = int(np.ceil(frame_range.end))
data_roi = det_data["data"][fr0:frN, y0:yN, x0:xN]
cnts = np.sum(data_roi, axis=(1, 2))
coeff, _ = curve_fit(gauss, range(len(cnts)), cnts, p0=p0, maxfev=maxfev)
m = cnts.mean()
sd = cnts.std()
snr_cnts = np.where(sd == 0, 0, m / sd)
frC = fr0 + coeff[1]
var_F = var_angle[math.floor(frC)]
var_C = var_angle[math.ceil(frC)]
frStep = frC - math.floor(frC)
var_step = var_C - var_F
var_p = var_F + var_step * frStep
if scan_motor == "gamma":
gamma = var_p
elif scan_motor == "omega":
omega = var_p
elif scan_motor == "nu":
nu = var_p
elif scan_motor == "chi":
chi = var_p
elif scan_motor == "phi":
phi = var_p
intensity = coeff[1] * abs(coeff[2] * var_step) * math.sqrt(2) * math.sqrt(np.pi)
projX = np.sum(data_roi, axis=(0, 1))
coeff, _ = curve_fit(gauss, range(len(projX)), projX, p0=p0, maxfev=maxfev)
x_pos = x0 + coeff[1]
projY = np.sum(data_roi, axis=(0, 2))
coeff, _ = curve_fit(gauss, range(len(projY)), projY, p0=p0, maxfev=maxfev)
y_pos = y0 + coeff[1]
ga, nu = pyzebra.det2pol(ddist, gamma, nu, x_pos, y_pos)
diff_vector = pyzebra.z1frmd(wave, ga, omega, chi, phi, nu)
d_spacing = float(pyzebra.dandth(wave, diff_vector)[0])
diff_vector = diff_vector.flatten() * 1e10
dv1, dv2, dv3 = diff_vector
diff_vec.append(diff_vector)
if events_list.value and not events_list.value.endswith("\n"):
events_list.value = events_list.value + "\n"
events_list.value = (
events_list.value
+ f"{x_pos} {y_pos} {intensity} {snr_cnts} {dv1} {dv2} {dv3} {d_spacing}"
)
add_event_button = Button(label="Add spind event")
add_event_button.on_click(add_event_button_callback)
metadata_table_source = ColumnDataSource(dict(geom=[""], temp=[None], mf=[None]))
num_formatter = NumberFormatter(format="0.00", nan_format="")
@ -623,12 +688,10 @@ def create():
row(proj_display_min_spinner, proj_display_max_spinner),
)
layout_controls = row(
column(selection_button, selection_list),
Spacer(width=20),
column(
row(index_spinner, column(Spacer(height=25), index_slider)), metadata_table, hkl_button
),
layout_controls = column(
row(metadata_table, index_spinner, column(Spacer(height=25), index_slider)),
row(add_event_button, hkl_button),
row(events_list),
)
layout_overview = column(
@ -649,6 +712,17 @@ def create():
return Panel(child=tab_layout, title="hdf viewer")
def gauss(x, *p):
"""Defines Gaussian function
Args:
A - amplitude, mu - position of the center, sigma - width
Returns:
Gaussian function
"""
A, mu, sigma = p
return A * np.exp(-((x - mu) ** 2) / (2.0 * sigma ** 2))
def calculate_hkl(det_data, index):
h = np.empty(shape=(IMAGE_H, IMAGE_W))
k = np.empty(shape=(IMAGE_H, IMAGE_W))

112
pyzebra/app/panel_spind.py
View File

@ -1,5 +1,3 @@
import ast
import math
import os
import subprocess
import tempfile
@ -17,16 +15,18 @@ from bokeh.models import (
TextAreaInput,
TextInput,
)
from scipy.optimize import curve_fit
import pyzebra
def create():
doc = curdoc()
path_prefix_textinput = TextInput(title="Path prefix:", value="")
selection_list = TextAreaInput(title="ROIs:", rows=7)
def events_list_callback(_attr, _old, new):
doc.events_list_hdf_viewer.value = new
events_list = TextAreaInput(title="Spind events:", rows=7, width=1500)
events_list.on_change("value", events_list_callback)
doc.events_list_spind = events_list
lattice_const_textinput = TextInput(
title="Lattice constants:", value="8.3211,8.3211,8.3211,90.00,90.00,90.00"
)
@ -49,7 +49,6 @@ def create():
os.mkdir(temp_peak_list_dir)
temp_event_file = os.path.join(temp_peak_list_dir, "event-0.txt")
temp_hkl_file = os.path.join(temp_dir, "hkl.h5")
roi_dict = ast.literal_eval(selection_list.value)
comp_proc = subprocess.run(
[
@ -72,7 +71,12 @@ def create():
print(" ".join(comp_proc.args))
print(comp_proc.stdout)
diff_vec = prepare_event_file(temp_event_file, roi_dict, path_prefix_textinput.value)
# prepare an event file
diff_vec = []
with open(temp_event_file, "w") as f:
for event in events_list.value.splitlines():
diff_vec.append(np.array(event.split()[4:7], dtype=float))
f.write(event + "\n")
print(f"Content of {temp_event_file}:")
with open(temp_event_file) as f:
@ -179,10 +183,10 @@ def create():
results_table_source.selected.on_change("indices", results_table_select_callback)
tab_layout = row(
tab_layout = column(
events_list,
row(
column(
path_prefix_textinput,
selection_list,
lattice_const_textinput,
row(max_res_spinner, seed_pool_size_spinner),
row(seed_len_tol_spinner, seed_angle_tol_spinner),
@ -190,89 +194,7 @@ def create():
process_button,
),
column(results_table, row(ub_matrix_textareainput, hkl_textareainput)),
),
)
return Panel(child=tab_layout, title="spind")
def gauss(x, *p):
"""Defines Gaussian function
Args:
A - amplitude, mu - position of the center, sigma - width
Returns:
Gaussian function
"""
A, mu, sigma = p
return A * np.exp(-((x - mu) ** 2) / (2.0 * sigma ** 2))
def prepare_event_file(export_filename, roi_dict, path_prefix=""):
diff_vec = []
p0 = [1.0, 0.0, 1.0]
maxfev = 100000
with open(export_filename, "w") as f:
for file, rois in roi_dict.items():
dat = pyzebra.read_detector_data(path_prefix + file + ".hdf")
wave = dat["wave"]
ddist = dat["ddist"]
gamma = dat["gamma"][0]
omega = dat["omega"][0]
nu = dat["nu"][0]
chi = dat["chi"][0]
phi = dat["phi"][0]
scan_motor = dat["scan_motor"]
var_angle = dat[scan_motor]
for roi in rois:
x0, xN, y0, yN, fr0, frN = roi
data_roi = dat["data"][fr0:frN, y0:yN, x0:xN]
cnts = np.sum(data_roi, axis=(1, 2))
coeff, _ = curve_fit(gauss, range(len(cnts)), cnts, p0=p0, maxfev=maxfev)
m = cnts.mean()
sd = cnts.std()
snr_cnts = np.where(sd == 0, 0, m / sd)
frC = fr0 + coeff[1]
var_F = var_angle[math.floor(frC)]
var_C = var_angle[math.ceil(frC)]
frStep = frC - math.floor(frC)
var_step = var_C - var_F
var_p = var_F + var_step * frStep
if scan_motor == "gamma":
gamma = var_p
elif scan_motor == "omega":
omega = var_p
elif scan_motor == "nu":
nu = var_p
elif scan_motor == "chi":
chi = var_p
elif scan_motor == "phi":
phi = var_p
intensity = coeff[1] * abs(coeff[2] * var_step) * math.sqrt(2) * math.sqrt(np.pi)
projX = np.sum(data_roi, axis=(0, 1))
coeff, _ = curve_fit(gauss, range(len(projX)), projX, p0=p0, maxfev=maxfev)
x_pos = x0 + coeff[1]
projY = np.sum(data_roi, axis=(0, 2))
coeff, _ = curve_fit(gauss, range(len(projY)), projY, p0=p0, maxfev=maxfev)
y_pos = y0 + coeff[1]
ga, nu = pyzebra.det2pol(ddist, gamma, nu, x_pos, y_pos)
diff_vector = pyzebra.z1frmd(wave, ga, omega, chi, phi, nu)
d_spacing = float(pyzebra.dandth(wave, diff_vector)[0])
diff_vector = diff_vector.flatten() * 1e10
dv1, dv2, dv3 = diff_vector
diff_vec.append(diff_vector)
f.write(f"{x_pos} {y_pos} {intensity} {snr_cnts} {dv1} {dv2} {dv3} {d_spacing}\n")
return diff_vec