Add a possibility to plot (m)hkl with measured data
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@ -1,5 +1,6 @@
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import base64
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import io
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import os
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import numpy as np
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from bokeh.layouts import column, row
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@ -31,6 +32,9 @@ def create():
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measured_data_div = Div(text="Measured data:")
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measured_data = FileInput(accept=".hdf", multiple=True, width=200)
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upload_hkl_div = Div(text="Open hkl/mhkl data:")
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upload_hkl_fi = FileInput(accept=".hkl,.mhkl", multiple=True, width=200)
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def _prepare_plotting():
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flag_ub = bool(redef_ub_cb.active)
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flag_lattice = bool(redef_lattice_cb.active)
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@ -129,6 +133,24 @@ def create():
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y_c = np.cross(x_c, o_c)
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hkl_in_plane_y.value = " ".join([f"{val:.1f}" for val in y_c])
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# Prepare hkl/mhkl data
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hkl_coord = []
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for j, fname in enumerate(upload_hkl_fi.filename):
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with io.StringIO(base64.b64decode(upload_hkl_fi.value[j]).decode()) as file:
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_, ext = os.path.splitext(fname)
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try:
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fdata = pyzebra.parse_hkl(file, ext)
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except:
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print(f"Error loading {fname}")
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return
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for ind in range(len(fdata["counts"])):
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# Recognize k_flag_vec
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hkl = np.array([fdata["h"][ind], fdata["k"][ind], fdata["k"][ind]])
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# Save data
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hkl_coord.append(hkl)
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def _update_slice():
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# Where should cut be along orthogonal direction (Mutliplication factor onto orth_dir)
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orth_cut = hkl_cut.value
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@ -196,6 +218,22 @@ def create():
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image=[I.T], x=[min_x], dw=[max_x - min_x], y=[min_y], dh=[max_y - min_y]
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)
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scan_x, scan_y = [], []
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for j in range(len(hkl_coord)):
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# Get middle hkl from list
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hklm = M @ hkl_coord[j]
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# Decide if point is in the cut
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proj = np.dot(hklm, o_c)
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if abs(proj - orth_cut) >= delta:
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continue
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# Plot middle point of scan
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scan_x.append(hklm[0])
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scan_y.append(hklm[1])
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scatter_source.data.update(x=scan_x, y=scan_y)
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return _update_slice
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def plot_file_callback():
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@ -219,6 +257,9 @@ def create():
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image_source = ColumnDataSource(dict(image=[np.zeros((1, 1))], x=[0], y=[0], dw=[1], dh=[1]))
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plot.image(source=image_source, color_mapper=color_mapper)
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scatter_source = ColumnDataSource(dict(x=[], y=[]))
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plot.scatter(source=scatter_source, size=4, fill_color="green", line_color="green")
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hkl_div = Div(text="HKL:", margin=(5, 5, 0, 5))
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hkl_normal = TextInput(title="normal", value="0 0 1", width=70)
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@ -312,7 +353,10 @@ def create():
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)
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cm_layout = row(colormap_select, display_min_ni, display_max_ni)
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column1_layout = column(
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row(measured_data_div, measured_data, plot_file),
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row(
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column(row(measured_data_div, measured_data), row(upload_hkl_div, upload_hkl_fi)),
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plot_file,
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),
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plot,
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column(
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hkl_div,
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@ -35,6 +35,9 @@ class PlotHKL:
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measured_data_div = Div(text="Measured data:")
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measured_data = FileInput(accept=".ccl", multiple=True, width=200)
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upload_hkl_div = Div(text="Open hkl/mhkl data:")
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upload_hkl_fi = FileInput(accept=".hkl,.mhkl", multiple=True, width=200)
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min_grid_x = -10
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max_grid_x = 10
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min_grid_y = -5
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@ -218,6 +221,24 @@ class PlotHKL:
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x=[x_c[0] / 2, y_c[0] / 2 - 0.1], y=[x_c[1] - 0.1, y_c[1] / 2], text=["h", "k"]
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)
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# Prepare hkl/mhkl data
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hkl_coord2 = []
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for j, fname in enumerate(upload_hkl_fi.filename):
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with io.StringIO(base64.b64decode(upload_hkl_fi.value[j]).decode()) as file:
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_, ext = os.path.splitext(fname)
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try:
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fdata = pyzebra.parse_hkl(file, ext)
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except:
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print(f"Error loading {fname}")
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return
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for ind in range(len(fdata["counts"])):
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# Recognize k_flag_vec
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hkl = np.array([fdata["h"][ind], fdata["k"][ind], fdata["k"][ind]])
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# Save data
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hkl_coord2.append(hkl)
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def _update_slice():
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cut_tol = hkl_delta.value
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cut_or = hkl_cut.value
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@ -316,6 +337,22 @@ class PlotHKL:
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plot.legend.items = legend_items
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scan_x2, scan_y2 = [], []
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for j in range(len(hkl_coord2)):
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# Get middle hkl from list
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hklm = M @ hkl_coord2[j]
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# Decide if point is in the cut
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proj = np.dot(hklm, o_c)
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if abs(proj - cut_or) >= cut_tol:
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continue
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# Plot middle point of scan
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scan_x2.append(hklm[0])
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scan_y2.append(hklm[1])
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scatter_source2.data.update(x=scan_x2, y=scan_y2)
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return _update_slice
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def plot_file_callback():
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@ -362,6 +399,9 @@ class PlotHKL:
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source=scan_source, marker="m", size="s", fill_color="c", line_color="c"
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)
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scatter_source2 = ColumnDataSource(dict(x=[], y=[]))
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plot.scatter(source=scatter_source2, size=4, fill_color="green", line_color="green")
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plot.add_layout(Legend(items=[], location="top_left", click_policy="hide"))
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hkl_div = Div(text="HKL:", margin=(5, 5, 0, 5))
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@ -401,7 +441,10 @@ class PlotHKL:
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disting_layout = column(disting_opt_div, row(disting_opt_cb, disting_opt_rb))
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layout = column(
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row(measured_data_div, measured_data, plot_file),
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row(
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column(row(measured_data_div, measured_data), row(upload_hkl_div, upload_hkl_fi)),
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plot_file,
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),
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plot,
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row(hkl_layout, k_vectors),
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row(disting_layout, column(tol_k_ni, res_mult_ni)),
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