diff --git a/__code/__init__.py b/__code/__init__.py
index 9435d1c..2f24ade 100644
--- a/__code/__init__.py
+++ b/__code/__init__.py
@@ -89,3 +89,35 @@ class SvmbirParameters(RecParameters):
weight_type = 'weight type'
verbose = 'verbose'
temp_disk = 'temp disk'
+
+
+class BatchJsonKeys:
+
+ list_raw_files = 'list_raw_files'
+ list_ob_files = 'list_ob_files'
+ list_dc_files = 'list_dc_files'
+ crop_region = 'crop_region'
+ gamma_filtering_flag = 'gamma_filtering_flag'
+ beam_fluctuation_flag = 'beam_fluctuation_flag'
+ beam_fluctuation_region = 'beam_fluctuation_region'
+ tilt_value = 'tilt_value'
+ remove_negative_values_flag = 'remove_negative_values_flag'
+ bm3d_flag = 'bm3d_flag'
+ tomopy_v0_flag = 'tomopy_v0_flag'
+ ketcham_flag = 'ketcham_flag'
+ range_slices_to_reconstruct = 'range_slices_to_reconstruct'
+ laminography_dict = 'laminography_dict'
+
+ angle = 'angle'
+ list_gpus = 'list_gpus'
+ num_iterations = 'num_iterations'
+ mrf_p = 'mrf_p'
+ mrf_sigma = 'mrf_sigma'
+ stop_threshold = 'stop_threshold'
+ verbose = 'verbose'
+ debug = 'debug'
+ log_file_name = 'log_file_name'
+
+ filt_cutoff = 'filt_cutoff'
+ filt_type = 'filt_type'
+
\ No newline at end of file
diff --git a/__code/batch_handler.py b/__code/batch_handler.py
index d195d6d..38dfcf0 100644
--- a/__code/batch_handler.py
+++ b/__code/batch_handler.py
@@ -1,6 +1,10 @@
+import os
+
from __code.parent import Parent
-from __code import DataType
+from __code import DataType, BatchJsonKeys
from __code.laminography_event_handler import LaminographyEventHandler
+from __code.utilities.time import get_current_time_in_special_file_name_format
+from __code.utilities.json import save_json
class BatchHandler(Parent):
@@ -12,19 +16,19 @@ def create_config_file(self):
list_ob_files = self.parent.input_files[DataType.ob]
list_dc_files = self.parent.input_files[DataType.dc]
- # crop region
- crop_left, crop_right, crop_top, crop_bottom = list(self.parent.cropping.result)
+ # crop region (left, right, top, bottom)
+ crop_region = list(self.parent.cropping.result)
## filter #1
# gamma filtering flag
gamma_filtering_flag = self.parent.gamma_filtering_ui.value
- # beam fluctuation correction flag and region
+ # beam fluctuation correction flag and region (left, right, top, bottom)
beam_fluctuation_flag = self.parent.beam_fluctuation_ui.value
- bf_left, bf_right, bf_top, bf_bottom = list(self.parent.beam_fluctuation_roi.value)
+ beam_fluctuation_region = list(self.parent.beam_fluctuation_roi.result)
# tilt value
- tilt_value = self.parent.tilt_options_ui.value
+ tilt_value = self.parent.tilt_option_ui.value
## filter #2
# remove negative values
@@ -36,16 +40,53 @@ def create_config_file(self):
ketcham_flag = self.parent.ring_removal_ui.children[2].value
# range of slices to reconstruct
- top_slice, bottom_slice = list(self.parent.z_range_selection.result)
+ range_slices_to_reconstruct = list(self.parent.z_range_selection.result)
# laminography parameters
- laminography_dict = self.parent.laminography_settings_ui
- angle = laminography_dict['angle'].value
- list_gpu_index = LaminographyEventHandler(laminography_dict['list_gpus'])
- num_iter = laminography_dict['num_iterations'].value
- mrf_p = laminography_dict['mrf_p'].value
- mrf_sigma = laminography_dict['mrf_sigma'].value
- stop_threhsold = laminography_dict['stop_threshold'].value
- verbose = laminography_dict['verbose'].value
-
- json_file_name = pass
\ No newline at end of file
+ ui_laminography_dict = self.parent.laminography_settings_ui
+ angle = ui_laminography_dict[BatchJsonKeys.angle].value
+ list_gpu_index = LaminographyEventHandler.get_gpu_index(laminography_dict[BatchJsonKeys.list_gpus])
+ num_iter = ui_laminography_dict[BatchJsonKeys.num_iterations].value
+ mrf_p = ui_laminography_dict[BatchJsonKeys.mrf_p].value
+ mrf_sigma = ui_laminography_dict[BatchJsonKeys.mrf_sigma].value
+ stop_threhsold = ui_laminography_dict[BatchJsonKeys.stop_threshold].value
+ verbose = ui_laminography_dict[BatchJsonKeys.verbose].value
+ laminograph_dict = {BatchJsonKeys.angle: angle,
+ BatchJsonKeys.list_gpus: list_gpu_index,
+ BatchJsonKeys.num_iterations: num_iter,
+ BatchJsonKeys.mrf_p: mrf_p,
+ BatchJsonKeys.mrf_sigma: mrf_sigma,
+ BatchJsonKeys.stop_threshold: stop_threhsold,
+ BatchJsonKeys.verbose: verbose}
+
+
+ # create json dictionary
+ json_dictionary = {BatchJsonKeys.list_raw_files: list_raw_files,
+ BatchJsonKeys.list_ob_files: list_ob_files,
+ BatchJsonKeys.list_dc_files: list_dc_files,
+ BatchJsonKeys.crop_region: crop_region,
+ BatchJsonKeys.gamma_filtering_flag: gamma_filtering_flag,
+ BatchJsonKeys.beam_fluctuation_flag:beam_fluctuation_flag,
+ BatchJsonKeys.beam_fluctuation_region: beam_fluctuation_region,
+ BatchJsonKeys.tilt_value: tilt_value,
+ BatchJsonKeys.remove_negative_values_flag: remove_negative_values_flag,
+ BatchJsonKeys.bm3d_flag: bm3d_flag,
+ BatchJsonKeys.tomopy_v0_flag: tomopy_v0_flag,
+ BatchJsonKeys.ketcham_flag: ketcham_flag,
+ BatchJsonKeys.range_slices_to_reconstruct: range_slices_to_reconstruct,
+ BatchJsonKeys.laminography_dict: laminography_dict,
+ }
+
+ _current_time = get_current_time_in_special_file_name_format()
+ base_folder_name = self.parent.raw_folder_name
+ json_file_name = os.path.join(os.path.expanduser("~"),
+ f"laminography_{base_folder_name}_{_current_time}.json")
+
+ log_file_name = os.path.join(os.path.expanduser("~"),
+ f"laminography_{base_folder_name}_{_current_time}.cfg")
+
+ # print(f"{json_dictionary =}")
+
+ save_json(json_file_name=json_file_name,
+ json_dictionary=json_dictionary)
+
\ No newline at end of file
diff --git a/__code/laminography_event_handler.py b/__code/laminography_event_handler.py
index 8dac5c0..9a98294 100644
--- a/__code/laminography_event_handler.py
+++ b/__code/laminography_event_handler.py
@@ -12,6 +12,7 @@
from __code.system import System
from __code.utilities.files import save_json
from __code.utilities.time import convert_time_s_in_time_hr_mn_s
+from __code import BatchJsonKeys
class LaminographyEventHandler:
@@ -88,13 +89,13 @@ def set_settings(self):
display(tab)
# saving widgets for batch mode
- self.parent.laminography_settings_ui = {'angle': self.laminography_angle_ui,
- 'list_gpus': self.children_gpus,
- 'num_iterations': self.num_iter_ui,
- 'mrf_p': self.mrf_p_ui,
- 'mrf_sigma': self.mrf_sigma_ui,
- 'stop_threshold': self.stop_threshold_ui,
- 'verbose': self.verbose_ui}
+ self.parent.laminography_settings_ui = {BatchJsonKeys.angle: self.laminography_angle_ui,
+ BatchJsonKeys.list_gpus: self.children_gpus,
+ BatchJsonKeys.num_iterations: self.num_iter_ui,
+ BatchJsonKeys.mrf_p: self.mrf_p_ui,
+ BatchJsonKeys.mrf_sigma: self.mrf_sigma_ui,
+ BatchJsonKeys.stop_threshold: self.stop_threshold_ui,
+ BatchJsonKeys.verbose: self.verbose_ui}
@staticmethod
def get_gpu_index(children_gpus_ui):
@@ -106,19 +107,19 @@ def get_gpu_index(children_gpus_ui):
def get_rec_params(self):
rec_params = {}
- rec_params['num_iter'] = self.num_iter_ui.value
- rec_params['gpu_index'] = LaminographyEventHandler.get_gpu_index(self.children_gpus[1:])
- rec_params['MRF_P'] = self.mrf_p_ui.value
- rec_params['MRF_SIGMA'] = self.mrf_sigma_ui.value
+ rec_params[BatchJsonKeys.num_iterations] = self.num_iter_ui.value
+ rec_params[BatchJsonKeys.list_gpus] = LaminographyEventHandler.get_gpu_index(self.children_gpus[1:])
+ rec_params[BatchJsonKeys.mrf_p] = self.mrf_p_ui.value
+ rec_params[BatchJsonKeys.mrf_sigma] = self.mrf_sigma_ui.value
# rec_params['huber_T'] = self.huber_t
# rec_params['huber_delta'] = self.huber_delta
# rec_params['sigma'] = self.sigma
# rec_params['reject_frac'] = self.reject_frac
- rec_params['verbose'] = self.verbose_ui.value
- rec_params['debug'] = self.debug
- rec_params['stop_thresh'] = self.stop_threshold_ui.value
- rec_params['filt_cutoff'] = 0.5
- rec_params['filt_type'] = 'Ram-Lak'
+ rec_params[BatchJsonKeys.verbose] = self.verbose_ui.value
+ rec_params[BatchJsonKeys.debug] = self.debug
+ rec_params[BatchJsonKeys.stop_threshold] = self.stop_threshold_ui.value
+ rec_params[BatchJsonKeys.filt_cutoff] = 0.5
+ rec_params[BatchJsonKeys.filt_type] = 'Ram-Lak'
return rec_params
diff --git a/__code/laminographyui.py b/__code/laminographyui.py
index 6e0dad2..2d30aba 100644
--- a/__code/laminographyui.py
+++ b/__code/laminographyui.py
@@ -97,6 +97,9 @@ class LaminographyUi:
ob_raw = None
dc_raw = None
+ # name of the raw folder
+ raw_folder_name = None
+
investigate_data_flag = False
o_tilt = None
@@ -116,6 +119,7 @@ def __init__(self, working_dir="./"):
self.working_dir[DataType.raw] = os.path.join(init_path_to_raw, default_input_folder[DataType.raw])
self.working_dir[DataType.ob] = os.path.join(init_path_to_raw, default_input_folder[DataType.ob])
self.working_dir[DataType.dc] = os.path.join(init_path_to_raw, default_input_folder[DataType.dc])
+ print("version 07-30-2024")
# SELECT INPUT DATA ===============================================================================================
def select_raw(self):
diff --git a/__code/laminographyui_batch_mode.py b/__code/laminographyui_batch_mode.py
index 5ca480c..78752eb 100644
--- a/__code/laminographyui_batch_mode.py
+++ b/__code/laminographyui_batch_mode.py
@@ -105,6 +105,9 @@ class LaminographyUi:
ob_raw = None
dc_raw = None
+ # name of the raw folder
+ raw_folder_name = None
+
investigate_data_flag = False
o_tilt = None
@@ -168,6 +171,7 @@ def define_parameters(self):
self.display_section_title(name='Beam fluctuation')
o_beam = BeamFluctuationCorrection(parent=self)
o_beam.beam_fluctuation_correction_option()
+ o_beam.apply_select_beam_fluctuation(batch_mode=True)
self.display_section_title(name='Tilt calculation')
self.tilt_correction_options()
diff --git a/__code/utilities/json.py b/__code/utilities/json.py
new file mode 100644
index 0000000..43d476d
--- /dev/null
+++ b/__code/utilities/json.py
@@ -0,0 +1,17 @@
+import json
+import os
+
+
+def load_json(json_file_name):
+ if not os.path.exists(json_file_name):
+ return None
+
+ with open(json_file_name) as json_file:
+ data = json.load(json_file)
+
+ return data
+
+
+def save_json(json_file_name, json_dictionary=None):
+ with open(json_file_name, 'w') as outfile:
+ json.dump(json_dictionary, outfile)
diff --git a/__code/workflow/load.py b/__code/workflow/load.py
index 18ddcbf..92d5cee 100644
--- a/__code/workflow/load.py
+++ b/__code/workflow/load.py
@@ -76,13 +76,6 @@ def load_percentage_of_data(self, percentage_to_load=5):
max_workers=20) # use 20 workers
)
-
-
-
-
-
-
-
def load_data(self):
self.parent.proj_raw, self.parent.ob_raw, self.parent.dc_raw, self.parent.rot_angles = (
@@ -100,6 +93,12 @@ def load_data(self):
self.parent.dc_raw = np.array([np.zeros_like(self.parent.proj_raw[0])])
+ # debugging - use np.float16 instead of default np.float64
+ print(f"Before conversion: {self.parent.proj_raw.dtype= }")
+ # self.parent.proj_raw = self.parent.proj_raw.astype(np.float16)
+ # self.parent.ob_raw = self.parent.ob_raw.astype(np.float16)
+ # self.parent.dc_raw = self.parent.dc_raw.astype(np.float16)
+ # print(f"After conversion: {self.parent.proj_raw.dtype= }")
self.parent.untouched_sample_data = copy.deepcopy(self.parent.proj_raw)
def select_dc_options(self):
diff --git a/__code/workflow/tilt.py b/__code/workflow/tilt.py
index a00ffc9..24b4f7b 100644
--- a/__code/workflow/tilt.py
+++ b/__code/workflow/tilt.py
@@ -533,7 +533,7 @@ def plot_comparisons(algo_selected, color_range, col, row, zoom_x, zoom_y):
display(self.test_tilt)
def display_batch_options(self):
- self.parent.tilt_options_ui = widgets.VBox([
+ tilt_options_ui = widgets.VBox([
widgets.Label("Tilt value (degrees)",
layout=widgets.Layout(width='200px'),
),
@@ -541,5 +541,7 @@ def display_batch_options(self):
max=90,
value=0)
])
- display(self.parent.tilt_options_ui)
+ display(tilt_options_ui)
+
+ self.parent.tilt_option_ui = tilt_options_ui.children[1]
\ No newline at end of file
diff --git a/imars3d_ui_embedded.ipynb b/imars3d_ui_embedded.ipynb
index fc24477..9db75b4 100644
--- a/imars3d_ui_embedded.ipynb
+++ b/imars3d_ui_embedded.ipynb
@@ -81,7 +81,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "1b9adbc62b054d969ee3d0dc5049bdfc",
+ "model_id": "ffc4a6fd2f644b4dbfe6d76ed8ac88a4",
"version_major": 2,
"version_minor": 0
},
@@ -132,7 +132,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 2,
"id": "bf8e0048",
"metadata": {},
"outputs": [
@@ -173,7 +173,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 3,
"id": "43d257da",
"metadata": {},
"outputs": [
@@ -195,7 +195,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "ob folder selected: ['/HFIR/CG1D/IPTS-32055/raw/ob/2024_06_21_Sample4_before'] with 12 files)\n"
+ "ob folder selected: ['/HFIR/CG1D/IPTS-32055/raw/ob/2024_06_20_Sample1_PreHeat'] with 10 files)\n"
]
}
],
@@ -213,14 +213,14 @@
},
{
"cell_type": "code",
- "execution_count": 5,
- "id": "11a9eab1",
+ "execution_count": 4,
+ "id": "fb81b49a",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "9f9a7fd94f20456d929236f807cb0fcf",
+ "model_id": "529dcc39efbe4ad893b1617bf334ca3e",
"version_major": 2,
"version_minor": 0
},
@@ -238,7 +238,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 5,
"id": "a1abeac0",
"metadata": {},
"outputs": [
@@ -264,14 +264,14 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 6,
"id": "c924c701",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "9e867fad5fa8452dba290c8ff61e1528",
+ "model_id": "0bb1e50801ab4da5b6bd3d9555eeadef",
"version_major": 2,
"version_minor": 0
},
@@ -285,12 +285,12 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "d31b94e3de354dcabadcb82f73eb5af8",
+ "model_id": "61057b986c4c408bb004f6617f674ae3",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
- "ob: 0%| | 0/12 [00:00, ?it/s]"
+ "ob: 0%| | 0/10 [00:00, ?it/s]"
]
},
"metadata": {},
@@ -299,7 +299,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "2730167920cc457cab53618ec0e35d9d",
+ "model_id": "56270305cc1b4f6ea80f8763396b4742",
"version_major": 2,
"version_minor": 0
},
@@ -1289,7 +1289,7 @@
{
"data": {
"text/html": [
- ""
+ ""
],
"text/plain": [
""
@@ -1338,7 +1338,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "ebea4679fa614e6e98ddc2f318a28c3e",
+ "model_id": "b9be5336f5b44980bf27bda3185bdde7",
"version_major": 2,
"version_minor": 0
},
@@ -1398,7 +1398,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "c1a9d30c52b44687a10756d624f1929e",
+ "model_id": "ff7de8cc716f499c80a13ec5b0be4835",
"version_major": 2,
"version_minor": 0
},
@@ -1451,12 +1451,12 @@
"output_type": "stream",
"text": [
"Running normalization ...\n",
- "normalization done in 5.79s\n"
+ "normalization done in 9.75s\n"
]
},
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/plain": [
"