Redraw plots on orth cut value change
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6b9555c33c
commit
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@ -43,6 +43,7 @@ def create():
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cif_data = {}
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params = {}
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res_files = {}
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_update_slice = None
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app_dlfiles = app.DownloadFiles(n_files=1)
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anglim_div = Div(text="Angular min/max limits:", margin=(5, 5, 0, 5))
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@ -302,10 +303,12 @@ def create():
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preview_lists = TextAreaInput(title="Preview selected list:", width=600, height=150)
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def plot_list_callback():
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nonlocal _update_slice
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fname = created_lists.value
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with io.StringIO(preview_lists.value) as fileobj:
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fdata = pyzebra.parse_hkl(fileobj, fname)
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_plot(fname, [fdata])
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_update_slice = _prepare_plotting(fname, [fdata])
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_update_slice()
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plot_list = Button(label="Plot selected list", button_type="primary", width=200)
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plot_list.on_click(plot_list_callback)
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@ -321,22 +324,13 @@ def create():
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cmap = Dark2[8]
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syms = ["circle", "inverted_triangle", "square", "diamond", "star", "triangle"]
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def _plot(filenames, filedata):
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def _prepare_plotting(filenames, filedata):
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orth_dir = list(map(float, hkl_normal.value.split()))
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cut_tol = hkl_delta.value
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cut_or = hkl_cut.value
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x_dir = list(map(float, hkl_in_plane_x.value.split()))
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k = np.array(k_vectors.value.split()).astype(float).reshape(-1, 3)
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tol_k = tol_k_ni.value
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# different symbols based on file number
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file_flag = 0 in disting_opt_cb.active
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# scale marker size according to intensity
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intensity_flag = 1 in disting_opt_cb.active
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# use color to mark different propagation vectors
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prop_legend_flag = 2 in disting_opt_cb.active
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lattice = list(map(float, cryst_cell.value.strip().split()))
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alpha = lattice[3] * np.pi / 180.0
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beta = lattice[4] * np.pi / 180.0
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@ -429,44 +423,6 @@ def create():
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grid_source.data.update(xs=xs, ys=ys)
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minor_grid_source.data.update(xs=xs_minor, ys=ys_minor)
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scan_x, scan_y = [], []
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scan_m, scan_s, scan_c, scan_l = [], [], [], []
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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 - cut_or) >= cut_tol:
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continue
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if intensity_flag and max(intensity_vec) != 0:
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markersize = max(1, int(intensity_vec[j] / max(intensity_vec) * 20))
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else:
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markersize = 4
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if file_flag:
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plot_symbol = syms[file_flag_vec[j]]
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else:
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plot_symbol = "circle"
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if prop_legend_flag:
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col_value = cmap[k_flag_vec[j]]
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else:
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col_value = "black"
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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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scan_m.append(plot_symbol)
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scan_s.append(markersize)
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# Color and legend label
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scan_c.append(col_value)
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scan_l.append(filenames[file_flag_vec[j]])
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scatter_source.data.update(x=scan_x, y=scan_y, m=scan_m, s=scan_s, c=scan_c, l=scan_l)
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arrow1.visible = True
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arrow1.x_end = x_c[0]
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arrow1.y_end = x_c[1]
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@ -478,23 +434,75 @@ def create():
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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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# Legend items for different file entries (symbol)
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legend_items = []
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if file_flag:
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labels, inds = np.unique(scatter_source.data["l"], return_index=True)
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for label, ind in zip(labels, inds):
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legend_items.append(LegendItem(label=label, renderers=[scatter], index=ind))
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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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# Legend items for propagation vector (color)
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if prop_legend_flag:
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labels, inds = np.unique(scatter_source.data["c"], return_index=True)
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for label, ind in zip(labels, inds):
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label = f"k={k[cmap.index(label)]}"
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legend_items.append(LegendItem(label=label, renderers=[scatter], index=ind))
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# different symbols based on file number
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file_flag = 0 in disting_opt_cb.active
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# scale marker size according to intensity
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intensity_flag = 1 in disting_opt_cb.active
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# use color to mark different propagation vectors
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prop_legend_flag = 2 in disting_opt_cb.active
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plot.legend.items = legend_items
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scan_x, scan_y = [], []
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scan_m, scan_s, scan_c, scan_l = [], [], [], []
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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 - cut_or) >= cut_tol:
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continue
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if intensity_flag and max(intensity_vec) != 0:
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markersize = max(1, int(intensity_vec[j] / max(intensity_vec) * 20))
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else:
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markersize = 4
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if file_flag:
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plot_symbol = syms[file_flag_vec[j]]
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else:
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plot_symbol = "circle"
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if prop_legend_flag:
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col_value = cmap[k_flag_vec[j]]
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else:
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col_value = "black"
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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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scan_m.append(plot_symbol)
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scan_s.append(markersize)
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# Color and legend label
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scan_c.append(col_value)
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scan_l.append(filenames[file_flag_vec[j]])
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scatter_source.data.update(x=scan_x, y=scan_y, m=scan_m, s=scan_s, c=scan_c, l=scan_l)
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# Legend items for different file entries (symbol)
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legend_items = []
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if file_flag:
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labels, inds = np.unique(scatter_source.data["l"], return_index=True)
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for label, ind in zip(labels, inds):
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legend_items.append(LegendItem(label=label, renderers=[scatter], index=ind))
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# Legend items for propagation vector (color)
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if prop_legend_flag:
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labels, inds = np.unique(scatter_source.data["c"], return_index=True)
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for label, ind in zip(labels, inds):
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label = f"k={k[cmap.index(label)]}"
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legend_items.append(LegendItem(label=label, renderers=[scatter], index=ind))
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plot.legend.items = legend_items
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return _update_slice
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def plot_file_callback():
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nonlocal _update_slice
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fnames = []
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fdata = []
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for j, fname in enumerate(upload_data.filename):
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@ -509,7 +517,8 @@ def create():
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fnames.append(fname)
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fdata.append(file_data)
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_plot(fnames, fdata)
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_update_slice = _prepare_plotting(fnames, fdata)
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_update_slice()
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plot_file = Button(label="Plot selected file(s)", button_type="primary", width=200)
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plot_file.on_click(plot_file_callback)
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@ -546,7 +555,14 @@ def create():
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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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def hkl_cut_callback(_attr, _old, _new):
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if _update_slice is not None:
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_update_slice()
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hkl_cut = Spinner(title="cut", value=0, step=0.1, width=70)
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hkl_cut.on_change("value_throttled", hkl_cut_callback)
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hkl_delta = NumericInput(title="delta", value=0.1, mode="float", width=70)
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hkl_in_plane_x = TextInput(title="in-plane X", value="1 0 0", width=70)
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hkl_in_plane_y = TextInput(title="in-plane Y", value="", width=100, disabled=True)
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@ -27,10 +27,11 @@ from pyzebra.app.panel_hdf_viewer import calculate_hkl
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def create():
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_update_slice = None
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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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def plot_file_callback():
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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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@ -43,12 +44,6 @@ def create():
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# where delta is max distance a data point can have from cut in rlu units
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orth_dir = list(map(float, hkl_normal.value.split()))
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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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# Width of cut
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delta = hkl_delta.value
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# Load data files
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md_fnames = measured_data.filename
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md_fdata = measured_data.value
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@ -59,7 +54,7 @@ def create():
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det_data = pyzebra.read_detector_data(io.BytesIO(base64.b64decode(fdata)))
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except:
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print(f"Error loading {fname}")
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return
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return None
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if ind == 0:
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if not flag_ub:
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@ -134,62 +129,76 @@ 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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# Calculate distance of all points to plane
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Q = np.array(o_c) * orth_cut
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N = o_c / np.sqrt(np.sum(o_c**2))
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v = np.empty(np.shape(hkl_c))
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v[:, :, :, :, 0] = hkl_c[:, :, :, :, 0] - Q
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dist = np.abs(np.dot(N, v))
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dist = np.squeeze(dist)
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dist = np.transpose(dist)
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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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# Find points within acceptable distance of plane defined by o_c
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ind = np.where(abs(dist) < delta)
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# Width of cut
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delta = hkl_delta.value
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# Project points onto axes
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x = np.dot(x_c / np.sqrt(np.sum(x_c**2)), hkl_c)
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y = np.dot(y_c / np.sqrt(np.sum(y_c**2)), hkl_c)
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# Calculate distance of all points to plane
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Q = np.array(o_c) * orth_cut
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N = o_c / np.sqrt(np.sum(o_c**2))
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v = np.empty(np.shape(hkl_c))
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v[:, :, :, :, 0] = hkl_c[:, :, :, :, 0] - Q
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dist = np.abs(np.dot(N, v))
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dist = np.squeeze(dist)
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dist = np.transpose(dist)
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# take care of dimensions
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x = np.squeeze(x)
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x = np.transpose(x)
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y = np.squeeze(y)
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y = np.transpose(y)
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# Find points within acceptable distance of plane defined by o_c
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ind = np.where(abs(dist) < delta)
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# Get slices:
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x_slice = x[ind]
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y_slice = y[ind]
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I_slice = I_matrix[ind]
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# Project points onto axes
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x = np.dot(x_c / np.sqrt(np.sum(x_c**2)), hkl_c)
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y = np.dot(y_c / np.sqrt(np.sum(y_c**2)), hkl_c)
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# Meshgrid limits for plotting
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if auto_range_cb.active:
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min_x = np.min(x_slice)
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max_x = np.max(x_slice)
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min_y = np.min(y_slice)
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max_y = np.max(y_slice)
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xrange_min_ni.value = min_x
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xrange_max_ni.value = max_x
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yrange_min_ni.value = min_y
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yrange_max_ni.value = max_y
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else:
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min_x = xrange_min_ni.value
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max_x = xrange_max_ni.value
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min_y = yrange_min_ni.value
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max_y = yrange_max_ni.value
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# take care of dimensions
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x = np.squeeze(x)
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x = np.transpose(x)
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y = np.squeeze(y)
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y = np.transpose(y)
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delta_x = xrange_step_ni.value
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delta_y = yrange_step_ni.value
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# Get slices:
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x_slice = x[ind]
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y_slice = y[ind]
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I_slice = I_matrix[ind]
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# Create interpolated mesh grid for plotting
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grid_x, grid_y = np.mgrid[min_x:max_x:delta_x, min_y:max_y:delta_y]
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I = interpolate.griddata((x_slice, y_slice), I_slice, (grid_x, grid_y))
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# Meshgrid limits for plotting
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if auto_range_cb.active:
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min_x = np.min(x_slice)
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max_x = np.max(x_slice)
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min_y = np.min(y_slice)
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max_y = np.max(y_slice)
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xrange_min_ni.value = min_x
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xrange_max_ni.value = max_x
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yrange_min_ni.value = min_y
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yrange_max_ni.value = max_y
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else:
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min_x = xrange_min_ni.value
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max_x = xrange_max_ni.value
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min_y = yrange_min_ni.value
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max_y = yrange_max_ni.value
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# Update plot
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display_min_ni.value = 0
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display_max_ni.value = np.max(I_slice) * 0.25
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image_source.data.update(
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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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delta_x = xrange_step_ni.value
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delta_y = yrange_step_ni.value
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# Create interpolated mesh grid for plotting
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grid_x, grid_y = np.mgrid[min_x:max_x:delta_x, min_y:max_y:delta_y]
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I = interpolate.griddata((x_slice, y_slice), I_slice, (grid_x, grid_y))
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# Update plot
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display_min_ni.value = 0
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display_max_ni.value = np.max(I_slice) * 0.25
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image_source.data.update(
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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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return _update_slice
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def plot_file_callback():
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nonlocal _update_slice
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_update_slice = _prepare_plotting()
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_update_slice()
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plot_file = Button(label="Plot selected file(s)", button_type="primary", width=200)
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plot_file.on_click(plot_file_callback)
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@ -209,7 +218,14 @@ def create():
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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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def hkl_cut_callback(_attr, _old, _new):
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if _update_slice is not None:
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_update_slice()
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hkl_cut = Spinner(title="cut", value=0, step=0.1, width=70)
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hkl_cut.on_change("value_throttled", hkl_cut_callback)
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hkl_delta = NumericInput(title="delta", value=0.1, mode="float", width=70)
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hkl_in_plane_x = TextInput(title="in-plane X", value="1 0 0", width=70)
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hkl_in_plane_y = TextInput(title="in-plane Y", value="", width=100, disabled=True)
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@ -31,6 +31,7 @@ import pyzebra
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class PlotHKL:
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def __init__(self):
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_update_slice = None
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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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@ -41,23 +42,13 @@ class PlotHKL:
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cmap = Dark2[8]
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syms = ["circle", "inverted_triangle", "square", "diamond", "star", "triangle"]
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def plot_file_callback():
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def _prepare_plotting():
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orth_dir = list(map(float, hkl_normal.value.split()))
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cut_tol = hkl_delta.value
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cut_or = hkl_cut.value
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x_dir = list(map(float, hkl_in_plane_x.value.split()))
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k = np.array(k_vectors.value.split()).astype(float).reshape(-1, 3)
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tol_k = tol_k_ni.value
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# different symbols based on file number
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file_flag = 0 in disting_opt_cb.active
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# scale marker size according to intensity
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intensity_flag = 1 in disting_opt_cb.active
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# use color to mark different propagation vectors
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prop_legend_flag = 2 in disting_opt_cb.active
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# use resolution ellipsis
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res_flag = disting_opt_rb.active
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# multiplier for resolution function (in case of samples with large mosaicity)
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res_mult = res_mult_ni.value
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@ -72,7 +63,7 @@ class PlotHKL:
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file_data = pyzebra.parse_1D(file, ext)
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except:
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print(f"Error loading {md_fnames[0]}")
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return
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return None
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alpha = file_data[0]["alpha_cell"] * np.pi / 180.0
|
||||
beta = file_data[0]["beta_cell"] * np.pi / 180.0
|
||||
@ -124,7 +115,7 @@ class PlotHKL:
|
||||
file_data = pyzebra.parse_1D(file, ext)
|
||||
except:
|
||||
print(f"Error loading {md_fname}")
|
||||
return
|
||||
return None
|
||||
|
||||
pyzebra.normalize_dataset(file_data)
|
||||
|
||||
@ -216,63 +207,6 @@ class PlotHKL:
|
||||
grid_source.data.update(xs=xs, ys=ys)
|
||||
minor_grid_source.data.update(xs=xs_minor, ys=ys_minor)
|
||||
|
||||
el_x, el_y, el_w, el_h, el_c = [], [], [], [], []
|
||||
scan_xs, scan_ys, scan_x, scan_y = [], [], [], []
|
||||
scan_m, scan_s, scan_c, scan_l = [], [], [], []
|
||||
for j in range(len(hkl_coord)):
|
||||
# Get middle hkl from list
|
||||
hklm = M @ hkl_coord[j][2]
|
||||
|
||||
# Decide if point is in the cut
|
||||
proj = np.dot(hklm, o_c)
|
||||
if abs(proj - cut_or) >= cut_tol:
|
||||
continue
|
||||
|
||||
hkl1 = M @ hkl_coord[j][0]
|
||||
hkl2 = M @ hkl_coord[j][1]
|
||||
|
||||
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
|
||||
el_x.extend(np.linspace(hkl1[0], hkl2[0], num=res_N))
|
||||
el_y.extend(np.linspace(hkl1[1], hkl2[1], num=res_N))
|
||||
el_w.extend(np.array(res_vec_x[j]) * 2)
|
||||
el_h.extend(np.array(res_vec_y[j]) * 2)
|
||||
el_c.extend([col_value] * res_N)
|
||||
else:
|
||||
# Plot scan line
|
||||
scan_xs.append([hkl1[0], hkl2[0]])
|
||||
scan_ys.append([hkl1[1], hkl2[1]])
|
||||
|
||||
# Plot middle point of scan
|
||||
scan_x.append(hklm[0])
|
||||
scan_y.append(hklm[1])
|
||||
scan_m.append(plot_symbol)
|
||||
scan_s.append(markersize)
|
||||
|
||||
# Color and legend label
|
||||
scan_c.append(col_value)
|
||||
scan_l.append(md_fnames[file_flag_vec[j]])
|
||||
|
||||
ellipse_source.data.update(x=el_x, y=el_y, width=el_w, height=el_h, c=el_c)
|
||||
scan_source.data.update(
|
||||
xs=scan_xs, ys=scan_ys, x=scan_x, y=scan_y, m=scan_m, s=scan_s, c=scan_c, l=scan_l
|
||||
)
|
||||
|
||||
arrow1.visible = True
|
||||
arrow1.x_end = x_c[0]
|
||||
arrow1.y_end = x_c[1]
|
||||
@ -284,26 +218,110 @@ class PlotHKL:
|
||||
x=[x_c[0] / 2, y_c[0] / 2 - 0.1], y=[x_c[1] - 0.1, y_c[1] / 2], text=["h", "k"]
|
||||
)
|
||||
|
||||
# Legend items for different file entries (symbol)
|
||||
legend_items = []
|
||||
if not res_flag and file_flag:
|
||||
labels, inds = np.unique(scan_source.data["l"], return_index=True)
|
||||
for label, ind in zip(labels, inds):
|
||||
legend_items.append(LegendItem(label=label, renderers=[scatter], index=ind))
|
||||
def _update_slice():
|
||||
cut_tol = hkl_delta.value
|
||||
cut_or = hkl_cut.value
|
||||
|
||||
# Legend items for propagation vector (color)
|
||||
if prop_legend_flag:
|
||||
if res_flag:
|
||||
source, render = ellipse_source, ellipse
|
||||
else:
|
||||
source, render = scan_source, mline
|
||||
# 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
|
||||
|
||||
labels, inds = np.unique(source.data["c"], return_index=True)
|
||||
for label, ind in zip(labels, inds):
|
||||
label = f"k={k[cmap.index(label)]}"
|
||||
legend_items.append(LegendItem(label=label, renderers=[render], index=ind))
|
||||
el_x, el_y, el_w, el_h, el_c = [], [], [], [], []
|
||||
scan_xs, scan_ys, scan_x, scan_y = [], [], [], []
|
||||
scan_m, scan_s, scan_c, scan_l = [], [], [], []
|
||||
for j in range(len(hkl_coord)):
|
||||
# Get middle hkl from list
|
||||
hklm = M @ hkl_coord[j][2]
|
||||
|
||||
plot.legend.items = legend_items
|
||||
# Decide if point is in the cut
|
||||
proj = np.dot(hklm, o_c)
|
||||
if abs(proj - cut_or) >= cut_tol:
|
||||
continue
|
||||
|
||||
hkl1 = M @ hkl_coord[j][0]
|
||||
hkl2 = M @ hkl_coord[j][1]
|
||||
|
||||
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
|
||||
el_x.extend(np.linspace(hkl1[0], hkl2[0], num=res_N))
|
||||
el_y.extend(np.linspace(hkl1[1], hkl2[1], num=res_N))
|
||||
el_w.extend(np.array(res_vec_x[j]) * 2)
|
||||
el_h.extend(np.array(res_vec_y[j]) * 2)
|
||||
el_c.extend([col_value] * res_N)
|
||||
else:
|
||||
# Plot scan line
|
||||
scan_xs.append([hkl1[0], hkl2[0]])
|
||||
scan_ys.append([hkl1[1], hkl2[1]])
|
||||
|
||||
# Plot middle point of scan
|
||||
scan_x.append(hklm[0])
|
||||
scan_y.append(hklm[1])
|
||||
scan_m.append(plot_symbol)
|
||||
scan_s.append(markersize)
|
||||
|
||||
# Color and legend label
|
||||
scan_c.append(col_value)
|
||||
scan_l.append(md_fnames[file_flag_vec[j]])
|
||||
|
||||
ellipse_source.data.update(x=el_x, y=el_y, width=el_w, height=el_h, c=el_c)
|
||||
scan_source.data.update(
|
||||
xs=scan_xs,
|
||||
ys=scan_ys,
|
||||
x=scan_x,
|
||||
y=scan_y,
|
||||
m=scan_m,
|
||||
s=scan_s,
|
||||
c=scan_c,
|
||||
l=scan_l,
|
||||
)
|
||||
|
||||
# Legend items for different file entries (symbol)
|
||||
legend_items = []
|
||||
if not res_flag and file_flag:
|
||||
labels, inds = np.unique(scan_source.data["l"], return_index=True)
|
||||
for label, ind in zip(labels, inds):
|
||||
legend_items.append(LegendItem(label=label, renderers=[scatter], index=ind))
|
||||
|
||||
# Legend items for propagation vector (color)
|
||||
if prop_legend_flag:
|
||||
if res_flag:
|
||||
source, render = ellipse_source, ellipse
|
||||
else:
|
||||
source, render = scan_source, mline
|
||||
|
||||
labels, inds = np.unique(source.data["c"], return_index=True)
|
||||
for label, ind in zip(labels, inds):
|
||||
label = f"k={k[cmap.index(label)]}"
|
||||
legend_items.append(LegendItem(label=label, renderers=[render], index=ind))
|
||||
|
||||
plot.legend.items = legend_items
|
||||
|
||||
return _update_slice
|
||||
|
||||
def plot_file_callback():
|
||||
nonlocal _update_slice
|
||||
_update_slice = _prepare_plotting()
|
||||
_update_slice()
|
||||
|
||||
plot_file = Button(label="Plot selected file(s)", button_type="primary", width=200)
|
||||
plot_file.on_click(plot_file_callback)
|
||||
@ -348,7 +366,14 @@ class PlotHKL:
|
||||
|
||||
hkl_div = Div(text="HKL:", margin=(5, 5, 0, 5))
|
||||
hkl_normal = TextInput(title="normal", value="0 0 1", width=70)
|
||||
|
||||
def hkl_cut_callback(_attr, _old, _new):
|
||||
if _update_slice is not None:
|
||||
_update_slice()
|
||||
|
||||
hkl_cut = Spinner(title="cut", value=0, step=0.1, width=70)
|
||||
hkl_cut.on_change("value_throttled", hkl_cut_callback)
|
||||
|
||||
hkl_delta = NumericInput(title="delta", value=0.1, mode="float", width=70)
|
||||
hkl_in_plane_x = TextInput(title="in-plane X", value="1 0 0", width=70)
|
||||
hkl_in_plane_y = TextInput(title="in-plane Y", value="", width=100, disabled=True)
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user