<jupyter_start><jupyter_text>Tutorial 6: Post Processing<jupyter_code>#Import required system libraries for file management
import sys,importlib,os

# Provide path to oct-cbort library
module_path=os.path.abspath('/Users/damondepaoli/Documents/GitHub/oct-cbort')
if module_path not in sys.path:
    sys.path.append(module_path)

# Import oct-cbort library
from oct import *

# Choose a directory with all meta/ofd/ofb data within it
d = os.path.join(module_path,'examples/data/4_BL_Benchtop_Phantom_struct_angio_ps')
data = Load(directory = d)<jupyter_output><empty_output><jupyter_text>All the processing steps outlined in the previous tutorials are handled here within the `Post` processer: There are some options we can select from, but most of the settings are loaded from the reconstructsettings.ini/editsettings.ini files<jupyter_code>processer = Post()
processer.processFrameRange(data, startFrame=1, endFrame=1, procState='tomo+angio+struct+ps+stokes', writeState=True,
                          procAll=False, hold=False, holdState='struct', rotCartesian=False)<jupyter_output><empty_output><jupyter_text>We can view the real processed images by using the `showProcessedData(data,processer)` function from the utils<jupyter_code>showProcessedData(data,processer)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08916218293620293, 'fraction_numerical': 0.0030745580322828594, 'mean_word_length': 6.843373493975903, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '663819', 'license': 'MIT', 'n_tokens_mistral': 415, 'n_tokens_neox': 405, 'n_words': 102, 'path': 'tutorials/.ipynb_checkpoints/oct_cb_tutorial_06_post_processing-checkpoint.ipynb', 'repo_name': 'CBORT-NCBIB/oct-cbort', 'size': '1301'}