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Get things working with numpy 2.4 and pandas 3.0 (#9072)

Browse Source 
* get BertzCT working with numpy 2.4

* test pass with with Pandas 3.0
(on windows at least)

* update testRanker too

* update nb test

* run win32 CI tests with different pandas versions
also updates boost version

* works with pandas 2.0?

* update linux_build_py311 -> linux_build_py312
test both old and new pandas

can't go higher with the python version yet because the older pandas and numpy are not available.

* doctest fix?

---------

Co-authored-by: = <=>
This commit is contained in:
Greg Landrum
2026-02-04 12:06:21 +01:00
committed by greg landrum
parent 56eb0dfa81
commit 3444408692
10 changed files with 92 additions and 52 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
.azure-pipelines/linux_build_py311.yml → .azure-pipelines/linux_build_py312.yml
View File

@@ -7,9 +7,11 @@ steps:
conda update -q conda
conda info -a
conda create --name rdkit_build -c conda-forge --override-channels $(python) cmake \
boost-cpp=$(boost_version) \
boost=$(boost_version) \
numpy=1.24.3 pillow eigen pandas=2.1 matplotlib-base=3.8 \
libboost-python-devel=$(boost_version) \
libboost-python=$(boost_version) \
libboost-devel=$(boost_version) \
libboost=$(boost_version) \
numpy=2.4 pillow eigen pandas=3 matplotlib-base=3.8 \
cairo
conda activate rdkit_build
conda config --env --add channels conda-forge
@@ -66,6 +68,18 @@ steps:
cd build
ctest -j $( $(number_of_cores) ) --output-on-failure -T Test
displayName: Run tests
- bash: |
source ${CONDA}/etc/profile.d/conda.sh
conda activate rdkit_build
conda install -c conda-forge --override-channels numpy=1.24 pandas=2.2
export RDBASE=`pwd`
export PYTHONPATH=${RDBASE}:${PYTHONPATH}
export LD_LIBRARY_PATH=${RDBASE}/lib:${CONDA_PREFIX}/lib:${LD_LIBRARY_PATH}
echo "LD_LIBRARY_PATH: " $LD_LIBRARY_PATH
export QT_QPA_PLATFORM='offscreen'
cd build
ctest -j $( $(number_of_cores) ) --output-on-failure -T Test
displayName: Run tests with older numpy and pandas
- bash: |
source ${CONDA}/etc/profile.d/conda.sh
conda activate rdkit_build

14
.azure-pipelines/vs_build.yml
View File

@@ -7,11 +7,12 @@ steps:
conda install -n base conda-libmamba-solver
conda config --set solver libmamba
conda create --name rdkit_build -c conda-forge --override-channels $(python) ^
boost=$(boost_version) boost-cpp=$(boost_version) ^
libboost-python=(boost_version) ^
libboost-python-devel=(boost_version) ^
libboost=$(boost_version) ^
libboost-devel=$(boost_version) ^
numpy matplotlib cairo pillow eigen pandas=2.1 ^
numpy matplotlib cairo pillow eigen ^
numpy=2.4 pandas=3 ^
sphinx myst-parser ipython jupyter pytest nbval cmake
call activate rdkit_build
conda config --env --add channels conda-forge
@@ -59,6 +60,15 @@ steps:
cd build
ctest -C Release -j $(number_of_cores) --output-on-failure -T Test
displayName: Run tests
- script: |
call activate rdkit_build
conda install -c conda-forge --override-channels numpy=1.26 pandas=2.2
set RDBASE=%cd%
set PYTHONPATH=%RDBASE%;%PYTHONPATH%
set PATH=%RDBASE%\lib;%PATH%
cd build
ctest -C Release -j $(number_of_cores) --output-on-failure -T Test
displayName: Run with older numpy and pandas
- script: |
call activate rdkit_build
conda install -c conda-forge --override-channels sphinx myst-parser

22
Code/ML/InfoTheory/Wrap/testRanker.py
View File

@@ -19,33 +19,33 @@ class TestCase(unittest.TestCase):
pass
def test0GainFuns(self):
arr = numpy.array([9, 5])
arr = numpy.array([9, 5],float)
self.assertTrue(feq(rdit.InfoEntropy(arr), 0.9403))
arr = numpy.array([9, 9])
arr = numpy.array([9, 9],float)
self.assertTrue(feq(rdit.InfoEntropy(arr), 1.0000))
arr = numpy.array([5, 5])
arr = numpy.array([5, 5],float)
self.assertTrue(feq(rdit.InfoEntropy(arr), 1.0000))
arr = numpy.array([5, 0])
arr = numpy.array([5, 0],float)
self.assertTrue(feq(rdit.InfoEntropy(arr), 0.0000))
arr = numpy.array([5, 5, 5])
arr = numpy.array([5, 5, 5],float)
self.assertTrue(feq(rdit.InfoEntropy(arr), 1.5850))
arr = numpy.array([2, 5, 5])
arr = numpy.array([2, 5, 5],float)
self.assertTrue(feq(rdit.InfoEntropy(arr), 1.4834))
mat2 = numpy.array([[6, 2], [3, 3]])
mat2 = numpy.array([[6, 2], [3, 3]],float)
self.assertTrue(feq(rdit.InfoGain(mat2), 0.0481))
self.assertTrue(feq(rdit.ChiSquare(mat2), 0.9333))
mat3 = numpy.array([[1, 1], [2, 1]])
mat3 = numpy.array([[1, 1], [2, 1]],float)
self.assertTrue(feq(rdit.InfoGain(mat3), 0.0200))
mat4 = numpy.array([[2, 0], [1, 2]])
mat4 = numpy.array([[2, 0], [1, 2]],float)
self.assertTrue(feq(rdit.InfoGain(mat4), 0.4200))
mat5 = numpy.array([[0, 0], [0, 0]])
mat5 = numpy.array([[0, 0], [0, 0]],float)
self.assertTrue(feq(rdit.InfoGain(mat5), 0.0000))
mat6 = numpy.array([[1, 0], [1, 0]])
mat6 = numpy.array([[1, 0], [1, 0]],float)
self.assertTrue(feq(rdit.InfoGain(mat6), 0.0000))
def test1ranker(self):

2
Docs/Book/GettingStartedInPython.rst
View File

@@ -3500,7 +3500,7 @@ These are accessible using Python's help command:
>>> m.GetNumAtoms()
7
>>> help(m.GetNumAtoms)
Help on method GetNumAtoms:
Help on method GetNumAtoms...
<BLANKLINE>
GetNumAtoms(...) method of rdkit.Chem.rdchem.Mol instance
GetNumAtoms( (Mol)self [, (int)onlyHeavy=-1 [, (bool)onlyExplicit=True]]) -> int :

10
azure-pipelines.yml
View File

@@ -32,20 +32,20 @@ jobs:
cxx: g++-11
steps:
- template: .azure-pipelines/linux_build.yml
- job: Ubuntu_x64_py311
- job: Ubuntu_x64_py312
timeoutInMinutes: 120
pool:
vmImage: ubuntu-latest
variables:
python: python=3.11
boost_version: 1.82.0
python: python=3.12
boost_version: 1.89.0
compiler: gxx_linux-64
cc: gcc-13
cxx: g++-13
number_of_cores: nproc
python_name: python311
python_name: python312
steps:
- template: .azure-pipelines/linux_build_py311.yml
- template: .azure-pipelines/linux_build_py312.yml
- job: macOS_x64
timeoutInMinutes: 120
pool:

16
rdkit/Chem/GraphDescriptors.py
View File

@@ -229,7 +229,7 @@ def Chi0(mol):
deltas = [x.GetDegree() for x in mol.GetAtoms()]
while 0 in deltas:
deltas.remove(0)
deltas = numpy.array(deltas, 'd')
deltas = numpy.array(deltas, float)
res = sum(numpy.sqrt(1. / deltas))
return res
@@ -244,7 +244,7 @@ def Chi1(mol):
c1s = [x.GetBeginAtom().GetDegree() * x.GetEndAtom().GetDegree() for x in mol.GetBonds()]
while 0 in c1s:
c1s.remove(0)
c1s = numpy.array(c1s, 'd')
c1s = numpy.array(c1s, float)
res = sum(numpy.sqrt(1. / c1s))
return res
@@ -320,7 +320,7 @@ def _pyChiNv_(mol, order=2):
for hkd in _hkDeltas(mol, skipHs=0)])
accum = 0.0
for path in Chem.FindAllPathsOfLengthN(mol, order + 1, useBonds=0):
accum += numpy.prod(deltas[numpy.array(path)])
accum += numpy.prod(deltas[numpy.array(path)],float)
return accum
@@ -358,7 +358,7 @@ def _pyChi0n(mol):
deltas = [_nVal(x) for x in mol.GetAtoms()]
while deltas.count(0):
deltas.remove(0)
deltas = numpy.array(deltas, 'd')
deltas = numpy.array(deltas, float)
res = sum(numpy.sqrt(1. / deltas))
return res
@@ -367,7 +367,7 @@ def _pyChi1n(mol):
""" Similar to Hall Kier Chi1v, but uses nVal instead of valence
"""
delts = numpy.array([_nVal(x) for x in mol.GetAtoms()], 'd')
delts = numpy.array([_nVal(x) for x in mol.GetAtoms()], float)
res = 0.0
for bond in mol.GetBonds():
v = delts[bond.GetBeginAtomIdx()] * delts[bond.GetEndAtomIdx()]
@@ -391,7 +391,7 @@ def _pyChiNn_(mol, order=2):
deltas = numpy.array([(1. / numpy.sqrt(x) if x else 0.0) for x in nval])
accum = 0.0
for path in Chem.FindAllPathsOfLengthN(mol, order + 1, useBonds=0):
accum += numpy.prod(deltas[numpy.array(path)])
accum += numpy.prod(deltas[numpy.array(path)],float)
return accum
@@ -578,10 +578,10 @@ def _CalculateEntropies(connectionDict, atomTypeDict, numAtoms):
"""
connectionList = list(connectionDict.values())
totConnections = sum(connectionList)
connectionIE = totConnections * (entropy.InfoEntropy(numpy.array(connectionList)) +
connectionIE = totConnections * (entropy.InfoEntropy(numpy.array(connectionList, float)) +
math.log(totConnections) / _log2val)
atomTypeList = list(atomTypeDict.values())
atomTypeIE = numAtoms * entropy.InfoEntropy(numpy.array(atomTypeList))
atomTypeIE = numAtoms * entropy.InfoEntropy(numpy.array(atomTypeList, float))
return atomTypeIE + connectionIE

9
rdkit/Chem/PandasPatcher.py
View File

@@ -88,12 +88,13 @@ except ImportError:
log.warning("Failed to import pandas")
raise
dataframe_applymap = pd.DataFrame.applymap
try:
if tuple(map(int, (pd.__version__.split(".")))) >= (2, 1, 0):
if tuple(map(int, (pd.__version__.split(".")))) < (2, 1, 0):
dataframe_applymap = pd.DataFrame.applymap
else:
dataframe_applymap = pd.DataFrame.map
except:
pass
log.warning("Failed to find a suitable map function for data frames")
orig_to_html = getattr(to_html_class, "to_html")
pprint_thing = pandas_formats.printing.pprint_thing
@@ -138,7 +139,7 @@ class MolFormatter:
@classmethod
def get_formatters(cls, df, orig_formatters):
"""Return an instance of MolFormatter for each column that contains Chem.Mol objects"""
df_subset = df.select_dtypes("object")
df_subset = df.select_dtypes(["object", "string"])
return {
col: cls(orig_formatters.get(col, None))
for col in df_subset.columns[dataframe_applymap(df_subset, MolFormatter.is_mol).any()]

2
rdkit/Chem/PandasTools.py
View File

@@ -431,7 +431,7 @@ def WriteSDF(df, out, molColName='ROMol', idName=None, properties=None, allNumer
if allNumeric:
properties.extend([
dt for dt in df.dtypes.keys()
if (np.issubdtype(df.dtypes[dt], np.floating) or np.issubdtype(df.dtypes[dt], np.integer))
if not pd.api.types.is_string_dtype(df.dtypes[dt]) and (np.issubdtype(df.dtypes[dt], np.floating) or np.issubdtype(df.dtypes[dt], np.integer))
])
if molColName in properties:

2
rdkit/Chem/UnitTestPandasTools.py
View File

@@ -212,7 +212,7 @@ class TestPandasTools(unittest.TestCase):
@unittest.skipIf(not hasattr(rdMolDraw2D, 'MolDraw2DCairo'), 'Cairo not available')
def testPandasShouldShowMoleculesWhenTruncating(self):
csv_data = '''"Molecule ChEMBL ID";"Molecule Name";"Molecule Max Phase";"Molecular Weight";"#RO5 Violations";"AlogP";"Compound Key";"Smiles";"Standard Type";"Standard Relation";"Standard Value";"Standard Units";"pChEMBL Value";"Data Validity Comment";"Comment";"Uo Units";"Ligand Efficiency BEI";"Ligand Efficiency LE";"Ligand Efficiency LLE";"Ligand Efficiency SEI";"Potential Duplicate";"Assay ChEMBL ID";"Assay Description";"Assay Type";"BAO Format ID";"BAO Label";"Assay Organism";"Assay Tissue ChEMBL ID";"Assay Tissue Name";"Assay Cell Type";"Assay Subcellular Fraction";"Target ChEMBL ID";"Target Name";"Target Organism";"Target Type";"Document ChEMBL ID";"Source ID";"Source Description";"Document Journal";"Document Year";"Cell ChEMBL ID"
csv_data = r'''"Molecule ChEMBL ID";"Molecule Name";"Molecule Max Phase";"Molecular Weight";"#RO5 Violations";"AlogP";"Compound Key";"Smiles";"Standard Type";"Standard Relation";"Standard Value";"Standard Units";"pChEMBL Value";"Data Validity Comment";"Comment";"Uo Units";"Ligand Efficiency BEI";"Ligand Efficiency LE";"Ligand Efficiency LLE";"Ligand Efficiency SEI";"Potential Duplicate";"Assay ChEMBL ID";"Assay Description";"Assay Type";"BAO Format ID";"BAO Label";"Assay Organism";"Assay Tissue ChEMBL ID";"Assay Tissue Name";"Assay Cell Type";"Assay Subcellular Fraction";"Target ChEMBL ID";"Target Name";"Target Organism";"Target Type";"Document ChEMBL ID";"Source ID";"Source Description";"Document Journal";"Document Year";"Cell ChEMBL ID"
"CHEMBL543779";"";"0";"341.86";"0";"2.60";"1w";"CCN(CC)CCS/C(=N\O)C(=O)c1ccc(C#N)cc1.Cl";"IC50";"'='";"180000.0";"nM";"";"Outside typical range";"";"UO_0000065";"";"";"";"";"False";"CHEMBL644102";"Reversible inhibition of Human AchE";"B";"BAO_0000357";"single protein format";"None";"None";"None";"None";"None";"CHEMBL220";"Acetylcholinesterase";"Homo sapiens";"SINGLE PROTEIN";"CHEMBL1123431";"1";"Scientific Literature";"J. Med. Chem.";"1986";"None"
'''
try:

47
rdkit/Chem/nbtests/github4823.ipynb
View File

@@ -130,7 +130,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 5,
"id": "permanent-liechtenstein",
"metadata": {
"scrolled": true
@@ -139,36 +139,51 @@
{
"data": {
"text/plain": [
"Index(['AMW', 'CLOGP', 'CP', 'CR', 'DAYLIGHT.FPG', 'DAYLIGHT_CLOGP', 'FP',\n",
" 'ISM', 'LIPINSKI_VIOLATIONS', 'NUM_HACCEPTORS', 'NUM_HDONORS',\n",
" 'NUM_HETEROATOMS', 'NUM_LIPINSKIHACCEPTORS', 'NUM_LIPINSKIHDONORS',\n",
" 'NUM_RINGS', 'NUM_ROTATABLEBONDS', 'NUM_ROTATABLEBONDS_O', 'P1',\n",
" 'SMILES', 'ID', 'ROMol'],\n",
" dtype='object')"
"['AMW',\n",
" 'CLOGP',\n",
" 'CP',\n",
" 'CR',\n",
" 'DAYLIGHT.FPG',\n",
" 'DAYLIGHT_CLOGP',\n",
" 'FP',\n",
" 'ISM',\n",
" 'LIPINSKI_VIOLATIONS',\n",
" 'NUM_HACCEPTORS',\n",
" 'NUM_HDONORS',\n",
" 'NUM_HETEROATOMS',\n",
" 'NUM_LIPINSKIHACCEPTORS',\n",
" 'NUM_LIPINSKIHDONORS',\n",
" 'NUM_RINGS',\n",
" 'NUM_ROTATABLEBONDS',\n",
" 'NUM_ROTATABLEBONDS_O',\n",
" 'P1',\n",
" 'SMILES',\n",
" 'ID',\n",
" 'ROMol']"
]
},
"execution_count": 4,
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.columns"
"list(df.columns)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 6,
"id": "careful-netherlands",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<module 'rdkit.Chem.PandasTools' from '/scratch/RDKit_git/rdkit/Chem/PandasTools.py'>"
"<module 'rdkit.Chem.PandasTools' from '/localhome/glandrum/RDKit_git/rdkit/Chem/PandasTools.py'>"
]
},
"execution_count": 5,
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
@@ -181,7 +196,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 7,
"id": "identical-finder",
"metadata": {},
"outputs": [
@@ -261,7 +276,7 @@
"4 223.231 2.43 1.869;-0P;4.71 6.390;-0R;4.71"
]
},
"execution_count": 6,
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
@@ -281,7 +296,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "py312_build",
"language": "python",
"name": "python3"
},
@@ -295,7 +310,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
"version": "3.12.3"
},
"toc": {
"base_numbering": 1,