Merge pull request #26 from naobservatory/simon-remove-mypy

Simon remove mypy

check.sh

@@ -21,15 +21,6 @@ if ! ./test.py; then
     echo "FAIL: tests"
     exit 1
 fi
-
-# if this fails with "mypy: command not found" you need to install mypy
-#   python3 -m pip install mypy
-echo Running mypy to check types...
-if ! mypy --pretty .; then
-    echo "FAIL: types"
-    exit 1
-fi
-
 # if this fails with "black: command not found" you need to install black
 #    python3 -m pip install black
 echo Running black to check formatting...

figures/composite_fig_5.py

@@ -1,8 +1,7 @@
 #!/usr/bin/env python3
 
-from pathlib import Path
 import sys
-
+from pathlib import Path
 
 sys.path.append("..")
 
@@ -149,10 +148,8 @@ def plot_three_virus(
     viruses: dict[str, tuple[float, float]],
     predictor_type: str,
     fig_title: str,
-
     axes: list[plt.Axes],
 ) -> list[plt.Axes]:
-
     final_axes = []
     for i, ((pathogen, xlim), ax) in enumerate(zip(viruses.items(), axes)):
         plot_violin(
@@ -259,9 +256,7 @@ def composite_figure(
     input_data: pd.DataFrame,
 ) -> plt.Figure:
     fig = plt.figure(
-
         figsize=(7, 10),
-
     )
 
     gs = fig.add_gridspec(2, 3, height_ratios=[7, 7], hspace=0.2)

figures/composite_fig_6.py

@@ -4,9 +4,9 @@
 from dataclasses import dataclass
 
 import matplotlib.pyplot as plt  # type: ignore
+import numpy as np
 from matplotlib.lines import Line2D  # type: ignore
 from scipy.stats import gmean
-import numpy as np
 
 PERCENTILES = [5, 25, 50, 75, 95]
 

preprint_stats/cost_required_stat.py

@@ -2,8 +2,9 @@
 
 import csv
 from dataclasses import dataclass
-from scipy.stats import gmean
+
 import numpy as np
+from scipy.stats import gmean
 
 PERCENTILES = [5, 25, 50, 75, 95]
 

preprint_stats/family_percentage_stat.py

@@ -1,17 +1,16 @@
-import os
 import gzip
 import json
+import os
 import subprocess
+
 import matplotlib.pyplot as plt  # type: ignore
-from matplotlib.gridspec import GridSpec
 import matplotlib.ticker as ticker
-
-import pandas as pd
-from scipy.stats import gmean
 import numpy as np
-from PIL import Image
+import pandas as pd
 import seaborn as sns
-
+from matplotlib.gridspec import GridSpec
+from PIL import Image
+from scipy.stats import gmean
 
 dashboard = os.path.expanduser("~/code/mgs-pipeline/dashboard/")
 

preprint_stats/preprint_stats.py

@@ -1,10 +1,10 @@
-import os
 import json
+import os
 import subprocess
+
 import numpy as np
 from scipy.stats import gmean
 
-
 dashboard = os.path.expanduser("~/code/mgs-pipeline/dashboard/")
 
 with open(os.path.join(dashboard, "human_virus_sample_counts.json")) as inf:

preprint_stats/reads_required_stat.py

@@ -2,9 +2,9 @@
 
 import csv
 from dataclasses import dataclass
-from scipy.stats import gmean
 
 import numpy as np
+from scipy.stats import gmean
 
 PERCENTILES = [5, 25, 50, 75, 95]
 

preprint_stats/rothman_inter_site_comparison.py

@@ -1,8 +1,9 @@
 import csv
+from collections import defaultdict
+from math import log
+
 import pandas as pd
 from scipy.stats import gmean
-from math import log
-from collections import defaultdict
 
 PERCENTILES = ["5%", "25%", "50%", "75%", "95%"]
 

preprint_stats/spurbeck_inter_site_comparison.py

@@ -1,8 +1,9 @@
 import csv
+from collections import defaultdict
+from math import log
+
 import pandas as pd
 from scipy.stats import gmean
-from math import log
-from collections import defaultdict
 
 PERCENTILES = ["5%", "25%", "50%", "75%", "95%"]
 

requirements-dev.txt

@@ -1,5 +1,4 @@
 -r requirements.txt
-mypy
 black
 isort
 pandas-stubs