diff --git a/pyzebra/app/panel_ccl_prepare.py b/pyzebra/app/panel_ccl_prepare.py
index 0dd273fced6d7086bb646b59c6075666f1926887..1e7c7e496c244939954df569481011488c893d48 100644
--- a/pyzebra/app/panel_ccl_prepare.py
+++ b/pyzebra/app/panel_ccl_prepare.py
@@ -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)
diff --git a/pyzebra/xtal.py b/pyzebra/xtal.py
index 50c3e11bbd51065c3f6e085898996386fcc0ec0f..dfdcb655a114e6aa82156e94a1a820ee00095e15 100644
--- a/pyzebra/xtal.py
+++ b/pyzebra/xtal.py
@@ -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
"""