[Bug]: Error in .to_global() Method for Slice Files with masked=True

[Haukiy]

What happened?

Hi, I encountered an issue when using the .to_global() method for Slice files in fdsreader. When setting masked=True, an error occurs, whereas setting masked=False works as expected. This suggests that the issue is related to handling the masked option.

Since displaying obstructions for better orientation is very useful, I would appreciate it if you could investigate this issue :) I have attached a demo FDS file for reproduction.

TEST_CASE.txt

error:

ValueError Traceback (most recent call last)
Cell In[6], line 9
7 slc=sim.slices
8 slc_soot = slc.get_by_id("SOOT_Z_Decke")
----> 9 data_slc, grid_coords = slc_soot.to_global(masked=True, fill=np.nan, return_coordinates=True)

File ~\AppData\Local\anaconda3\Lib\site-packages\fdsreader\slcf\slice.py:648, in Slice.to_global(self, masked, fill, return_coordinates)
644 if masked:
645 slc_data = np.where(mask, slc_data, fill)
647 grid[:, start_idx['x']: end_idx['x'], start_idx['y']: end_idx['y'],
--> 648 start_idx['z']: end_idx['z']] = slc_data.reshape(
649 (self.n_t, end_idx['x'] - start_idx['x'], end_idx['y'] - start_idx['y'],
650 end_idx['z'] - start_idx['z']))
652 if return_coordinates:
653 coordinates = dict()

ValueError: cannot reshape array of size 0 into shape (76,67,69,1)

Steps to reproduce

import fdsreader as fds
import numpy as np

path=r"-----"

sim=fds.Simulation(path)
slc=sim.slices
slc_soot = slc.get_by_id("SOOT_Z_Decke")
data_slc, grid_coords = slc_soot.to_global(masked=True, fill=np.nan, return_coordinates=True)

FDS version used

FDS-6.9.1-0-g889da6a-release

fdsreader version used

1.11.6

[Haukiy]

Hi everyone,
I "developed" a workaround for handling obstruction masking in slice files, which works well for my specific use cases. This was motivated by the issues I encountered with the default masking method:

• Obstructions appear thicker than expected.
• Not all obstructions are detected accurately.

To address these problems, I opted not to use the built-in masking method and implemented a custom solution instead. Below is an outline of my approach:
data, grid = slice_obj.to_global(masked=False, fill=np.nan, return_coordinates=True)
data = mask_obstructions_in_slice(data, grid, smv_file_path)

The mask_obstructions_in_slice function is attached. I am not a programmer, so it is maybe not the best code structure....

Key Benefits:
-Improved Accuracy: My method resolves the issue of incorrectly sized obstructions and ensures better detection.
-Enhanced Performance: It is significantly faster, especially for large-scale simulations.

Here are some visual comparisons to illustrate the differences:

Default Masking Option (masked=True):

Custom Approach with mask_obstructions_in_slice:

Smokeview Output:

colorbar in the Smokeview image has not been adjusted; it is only included for presentation purposes to highlight obstructions.

Function.txt