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Description
Description:
I’ve noticed a significant difference in how the normalized total energy E_norm is computed between GISTTOOLS and the official GIST Tutorial.
- In GISTTOOLS (
gist.py line 1071):
- The
_recipe_A_normmethod defines:
def _recipe_A_norm(self, index):
"""Create A_norm."""
return (
self.loc[index, "Eww_norm"]
+ self.loc[index, "Esw_norm"]
- self.loc[index, 'dTSsix_norm']
)
It means:
A_norm = Eww_norm + Esw_norm - dTSsix_norm (1)
and:
E_norm = Eww_norm + Esw_norm (2)
- In the GIST Tutorial (Python example for figure 5.):
import gisttools as gt
# Load the GIST data, make sure to set the correct reference energy
gist = gt.gist.load_gist_file('gist.dat',
struct='solute-centered.pdb', eww_ref=-9.5398)
# Calculate the total energy without double counting
gist['E_norm'] = gist['Eww_norm'] * 2 + gist['Esw_norm']
# Set the energy to zero for all voxels with no population
gist.loc[gist['population'] == 0, 'E_norm'] = 0
# Save the new energy to a dx file
gist.save_dx('E_norm', 'gist-E-per-mol-norm.dx')Where, the comment claims double counting is avoided, but the code includes a factor of 2 for Eww_norm,
E_norm = 2 * Eww_norm + Esw_norm (3)
which may imply double counting rather than avoidance. The intention behind this should be clarified.
Eqation 3 effectively doubles the water-water interaction term.
This discrepancy raises concerns about consistency and physical interpretation:
- Multiplying by 2 implies a correction for double counting, but it’s unclear whether this factor is already embedded in the
Eww_normvalues provided by GIST. - If
Eww_normis already computed per interaction (not per molecule), then multiplying by 2 would be incorrect. - Conversely, if
Eww_normis defined per molecule, then doubling would be appropriate for the total.
Question: Could you please clarify the definition of Eww_norm in the GIST output and confirm which version of the E_norm formula is correct for standard GIST analysis?
This is important for ensuring consistency when using GISTTOOLS for visualization, scoring, or comparison with literature results.
Thank you!
— Gaokeng Xiao