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# Psi4: an open-source quantum chemistry software package
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"""Module with utility functions for FCHK files."""
import re
import numpy as np
from psi4.driver.p4util.testing import compare_strings, compare_arrays, compare_values, compare_integers
from psi4 import core
from .exceptions import ValidationError
__all__ = ['fchkfile_to_string','compare_fchkfiles', "compare_moldenfiles"]
def _consume_fchk_section(input_list, index):
"""compare a float or integer matrix section"""
n = int(input_list[index].split()[-1])
kind = input_list[index].split()[-3]
if "R" in kind:
dtype = np.float64
format_counter = 5
elif "I" in kind:
dtype = np.float64
format_counter = 6
else:
raise ValidationError('Unknow field type in FCHK reader\n')
extra = 0 if n <= format_counter else n % format_counter
lines = 1 if n <= format_counter else int(n / format_counter)
offset = lines + 1 if extra > 0 else lines
string = ''
for j in range(lines):
string += "".join(str(x) for x in input_list[index + 1 + j])
if extra > 0:
string += "".join(str(x) for x in input_list[index + 1 + lines])
field = np.fromiter(string.split(), dtype=dtype)
return offset + 1, field
[docs]def fchkfile_to_string(fname):
""" Load FCHK file into a string"""
with open(fname, 'r') as handle:
fchk_string = handle.read()
return fchk_string
[docs]def compare_fchkfiles(expected, computed, atol_exponent, label):
"""Comparison function for output data in FCHK (formatted checkpoint) file format.
Compares many fields including number of electrons, highest angular momentum, basis
set exponents, densities, final gradient.
Note only Psi4-style signature (``(expected, computed, atol_exponent, label)``) available.
An older format description can be found here
http://wild.life.nctu.edu.tw/~jsyu/compchem/g09/g09ur/f_formchk.htm
It lists more fields (logical, character) that are not included in this
test function. They should be covered by the string comparison.
This function is only meant to work with PSI4's FCHK files.
Parameters
----------
expected : file
Reference FCHK file against which `computed` is compared.
computed : file
Input FCHK file to compare against `expected`.
atol_exponent : int or float
Absolute tolerance for high accuracy fields -- 1.e-8 or 1.e-9 is suitable.
Values less than one are taken literally; one or greater taken as decimal digits for comparison.
So `1` means `atol=0.1` and `2` means `atol=0.01` but `0.04` means `atol=0.04`
Note that the largest expressable processed atol will be `~0.99`.
label : str
Label for passed and error messages.
"""
fchk_ref = fchkfile_to_string(expected).splitlines()
fchk_calc = fchkfile_to_string(computed).splitlines()
high_accuracy = atol_exponent
low_accuracy = 3
# Those listed below need super high scf convergence (d_conv 1e-12) and might
# show machine dependence. They will be tested with low_accuracy.
sensitive = ['Current cartesian coordinates', 'MO coefficients']
if len(fchk_ref) != len(fchk_calc):
raise ValidationError('The two FCHK files to compare have a different file length! \n')
index = 0
max_length = len(fchk_calc)
tests = []
for start in range(max_length):
if index >= max_length:
break
line = fchk_calc[index]
if "N=" in line:
offset, calc = _consume_fchk_section(fchk_calc, index)
_, ref = _consume_fchk_section(fchk_ref, index)
if any(x in line for x in sensitive):
test = compare_arrays(ref, calc, low_accuracy, f" matrix section: {line}")
else:
test = compare_arrays(ref, calc, high_accuracy, f" matrix section: {line}")
index += offset
elif " R " in line and "N=" not in line:
calc = line.split()[-1]
ref = fchk_ref[index].split()[-1]
test = compare_values(ref, calc, high_accuracy, f" float value: {line}")
index += 1
elif " I " in line and "N=" not in line:
calc = line.split()[-1]
ref = fchk_ref[index].split()[-1]
test = compare_integers(ref, calc, f" int value: {line}")
index += 1
else:
test = compare_strings(line, fchk_ref[index], f"FCK text line {index+1}.")
index += 1
tests.append(test)
return compare_integers(True, all(tests), label)
[docs]def compare_moldenfiles(expected, computed, atol_exponent=7, label="Compare Molden"):
"""Comparison function for output data in Molden file format.
Compares many fields including geometry, basis set, occupations, symmetries, energies.
Note only Psi4-style signature (``(expected, computed, atol_exponent, label)``) available.
A format description is found https://www3.cmbi.umcn.nl/molden/molden_format.html
Parameters
----------
expected : file
Reference Molden file against which `computed` is compared.
computed : file
Input Molden file to compare against `expected`.
atol_exponent : int or float
Absolute tolerance for high accuracy fields -- 1.e-8 or 1.e-9 is suitable.
Values less than one are taken literally; one or greater taken as decimal digits for comparison.
So `1` means `atol=0.1` and `2` means `atol=0.01` but `0.04` means `atol=0.04`
Note that the largest expressable processed atol will be `~0.99`.
label : str
Label for passed and error messages.
"""
def moldenfile_to_string(fname):
with open(fname, 'r') as fn:
molden_string = fn.read()
return molden_string
ref = moldenfile_to_string(expected).splitlines()
calc = moldenfile_to_string(computed).splitlines()
if len(ref) != len(calc):
raise ValidationError(f"These two molden files have different lengths...\n")
high_accuracy = atol_exponent
index = 0
max_len = len(calc)
tests = []
section = 0
geom_re = re.compile(r'^\s*(\w*)\s+(\d+)\s+(\d+)\s+(-?\d+.\d+)\s+(-?\d+.\d+)\s+(-?\d+.\d+)\s*$')
basis_header_re = re.compile(r'^\s*([s,p,d,f,g])\s*(\d*)\s*(\d*.\d*)\s*$')
s1_re = re.compile(r'^\s*(\d+.?\d*)\s+(\d+.?\d*)$')
s2_re = re.compile(r'^\s*(\d+)\s+(-?\d+.\d+[e,E][\+,-]\d+)\s*$')
sym_re = re.compile(r'^\s*Sym\s*=\s*(\w*)\s*$')
energy_re = re.compile(r'^\s*Ene\s*=\s*(-?\d*.?\d*[e,E]?\+?-?\d*)\s*$')
spin_re = re.compile(r'^\s*Spin\s*=\s*(\w*)\s*$')
occ_re = re.compile(r'^\s*Occup\s*=\s*(-?\d*.\d*[e,E]?-?\+?\d*)\s*$')
for i in range(max_len):
line = calc[i]
if geom_re.match(line):
c1, c2, c3, c4, c5, c6 = geom_re.match(line).groups()
r1, r2, r3, r4, r5, r6 = geom_re.match(line).groups()
test = compare_strings(r1, c1) and compare_integers(r2, c2) and compare_integers(r3, c3) and compare_values(r4, c4, high_accuracy) and compare_values(r5, c5, high_accuracy) and compare_values(r6, c6, high_accuracy)
elif basis_header_re.match(line):
c1, c2, c3 = basis_header_re.match(line).groups()
r1, r2, r3 = basis_header_re.match(ref[i]).groups()
test = compare_strings(r1,c1) and compare_integers(r2,c2) and compare_values(r3,c3,3)
elif s1_re.match(line):
c1, c2 = s1_re.match(line).groups()
r1, r2 = s1_re.match(ref[i]).groups()
test = compare_values(r1, c1, high_accuracy) and compare_values(r2, c2, high_accuracy)
elif sym_re.match(line):
c = sym_re.match(line).group(1)
r = sym_re.match(ref[i]).group(1)
test = compare_strings(r, c, f'text line: {line}')
elif energy_re.match(line):
c = energy_re.match(line).group(1)
r = energy_re.match(ref[i]).group(1)
test = compare_values(r, c, high_accuracy, f'float value: {line}')
elif spin_re.match(line):
c = spin_re.match(line).group(1)
r = spin_re.match(ref[i]).group(1)
test = compare_strings(r, c, f'text line: {line}')
elif occ_re.match(line):
c = occ_re.match(line).group(1)
r = occ_re.match(ref[i]).group(1)
test = compare_values(r, c, high_accuracy, f'float value: {line}')
elif s2_re.match(line):
c1, c2 = s2_re.match(line).groups()
r1, r2 = s2_re.match(line).groups()
test = compare_integers(r1, c1, f'int value: {line}') and compare_values(r2, c2, high_accuracy, f'float value: {line}')
else:
test = compare_strings(line, ref[i])
tests.append(test)
return compare_integers(True, all(tests), label)
