Merge pull request #7 from aspuru-guzik-group/feature/neurips-updates

Feature/neurips updates

Dockerfile

@@ -1,6 +1,6 @@
 FROM continuumio/miniconda3:latest
 
-RUN apt-get update && apt-get upgrade
+RUN apt-get update -y && apt-get upgrade -y
 
 SHELL ["/bin/bash", "--login", "-c"]
 
@@ -20,5 +20,8 @@ RUN pip install pytest
 RUN mkdir /data
 COPY . .
 
+RUN chmod 777 tartarus/data/qvina
+RUN chmod 777 tartarus/data/smina
+
 SHELL ["conda", "run", "-n", "tartarus", "/bin/bash", "-c"]
 ENTRYPOINT ["conda", "run", "--no-capture-output", "-n", "tartarus", "python", "/benchmark/benchmark.py"]

README.md

@@ -22,7 +22,7 @@ To run the Tartarus benchmark we recommend using the provided Docker container.
 3. Run the Docker container with the directory of your data mounted, the benchmark mode and the CSV input filename: 
 
 ```bash
-    docker run --rm -it -v ${LOCAL_PATH_TO_DATA}:/data ac/tartarus:latest --mode ${BENCHMARK_MODE} --input_filename ${INPUT_FILENAME}
+    docker run --rm -it -v ${LOCAL_PATH_TO_DATA}:/data johnwilles/tartarus:latest --mode ${BENCHMARK_MODE} --input_filename ${INPUT_FILENAME}
 ```
 
 4. The output file will be written to the same directory by default with the filename `output.csv`. 
@@ -64,8 +64,7 @@ All datasets are found in the [datasets](datasets/) directory. The arrows indica
 
 |Task | Dataset name       | # of smiles |  Columns in file ||||||
 |---|--------------------|------------------|----|----|----|---|----|----|
-| Designing OPV | `hce.csv`          | 24,953         | Dipole moment (&#8593;)  | HOMO-LUMO gap (&#8593;) | LUMO (&#8595;)  |  Combined objective (&#8593;) | PCE<sub>PCBM</sub> -SAS (&#8593;) | PCE<sub>PCDTBT</sub> -SAS (&#8593;) | 
-| Designing OPV | `unbiased_hce.csv` | 1,000          | Dipole moment (&#8593;)  | HOMO-LUMO gap (&#8593;) | LUMO (&#8595;)   | Combined objective (&#8593;) | ||
+| Designing OPV | `hce.csv`          | 24,953         | PCE<sub>PCBM</sub> -SAS (&#8593;) | PCE<sub>PCDTBT</sub> -SAS (&#8593;) | 
 | Designing emitters | `gdb13.csv`        | 403,947          | Singlet-triplet gap (&#8595;) | Oscillator strength (&#8593;) | Multi-objective (&#8593;) |  | ||
 | Designing drugs | `docking.csv`      | 152,296          | 1SYH (&#8595;) | 6Y2F (&#8595;) | 4LDE (&#8595;) |  | | |
 | Designing chemical reaction substrates | `reactivity.csv`      | 60,828          | 	Activation energy &Delta;E<sup>&#8225;</sup> (&#8595;)   |  	Reaction energy &Delta;E<sub>r</sub> (&#8595;)  | &Delta;E<sup>&#8225;</sup> + &Delta;E<sub>r</sub> (&#8595;)  |  - &Delta;E<sup>&#8225;</sup> + &Delta;E<sub>r</sub> (&#8595;)    |     | |
@@ -154,11 +153,3 @@ out in person: (akshat98[AT]stanford[DOT]edu, robert[DOT]pollice[AT]gmail[DOT]co
 
 [Apache License 2.0](https://choosealicense.com/licenses/apache-2.0/)
 
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benchmark.py

@@ -17,10 +17,6 @@ class ResultBase():
 
 @dataclass
 class PCEResult(ResultBase):
-    dipm: float
-    gap: float
-    lumo: float
-    combined: float
     pce_pcbm_sas: float
     pce_pcdtbt_sas: float
 
@@ -72,7 +68,7 @@ def benchmark_smile(smile, mode, verbose):
     elif mode == 'tadf':
         result = TADFResult(smile, *tadf.get_properties(smile, verbose=verbose))
     elif mode == 'docking':
-        result = DockingResult(smile, docking.get_1syh_score(smile, verbose=verbose), docking.get_6y2f_score(smile, verbose=verbose), docking.get_4lde_score(smile, verbose=verbose))
+        result = DockingResult(smile, docking.perform_calc_single(smile, '1syh', docking_program='qvina'), docking.perform_calc_single(smile, '6y2f', docking_program='qvina'), docking.perform_calc_single(smile, '4lde', docking_program='qvina'))
     elif mode == 'reactivity':
         result = ReactivityResult(smile, *reactivity.get_properties(smile, verbose=verbose))
     else: