Address reviewers comments

README.md

@@ -8,7 +8,7 @@ and, when paired with epitope prediction, estimating a population's
 ability to mount an immune response to specific epitopes.
 
 Automated download of allele frequency data download from 
-[allelefrequencies.net](http://www.allelefrequencies.net/).
+[allelefrequencies.net](https://www.allelefrequencies.net/).
 
 Full documentation at [HLAfreq/docs](https://BarinthusBio.github.io/HLAfreq/HLAfreq.html). Source code is available at [BarinthusBio/HLAfreq](https://github.com/BarinthusBio/HLAfreq).
 

examples/paper/reproduce_paper_results2.py

@@ -27,7 +27,7 @@
 iedb_refb = [i for i in iedb_ref if "B" in i]
 
 # Download countries in regions as defined on 
-# http://www.allelefrequencies.net/datasets.asp#tag_4
+# https://www.allelefrequencies.net/datasets.asp#tag_4
 r = requests.get("https://raw.githubusercontent.com/BarinthusBio/HLAfreq/main/data/example/countries.csv")
 with open("data/example/countries.csv", "w") as f:
     f.write(r.text)

examples/paper/reproduce_paper_results3.py

@@ -26,7 +26,7 @@
     pass
 
 # Download countries in regions as defined on 
-# http://www.allelefrequencies.net/datasets.asp#tag_4
+# https://www.allelefrequencies.net/datasets.asp#tag_4
 r = requests.get("https://raw.githubusercontent.com/BarinthusBio/HLAfreq/main/data/example/countries.csv")
 with open("data/example/countries.csv", "w") as f:
     f.write(r.text)

setup.py

@@ -2,7 +2,7 @@
 
 setup(
     name="HLAfreq",
-    version="0.0.5",
+    version="0.0.6",
     url="https://github.com/BarinthusBio/HLAfreq",
     project_urls={
         'Documentaion': "https://barinthusbio.github.io/HLAfreq/HLAfreq.html",

src/HLAfreq/HLAfreq.py

@@ -63,7 +63,7 @@ def makeURL(
 ):
     """Create URL for search of allele frequency net database.
 
-    All arguments are documented [here](http://www.allelefrequencies.net/extaccess.asp)
+    All arguments are documented [here](https://www.allelefrequencies.net/extaccess.asp)
 
     Args:
         country (str, optional): Country name to retrieve records from. Defaults to "".
@@ -78,10 +78,10 @@ def makeURL(
             created using `resolution` and `resolution_pattern`. Defaults to 2.
         region (str, optional): Filter to geographic region. {Asia, Australia,
             Eastern Europe, ...}.
-            All regions listed [here](http://www.allelefrequencies.net/pop6003a.asp).
+            All regions listed [here](https://www.allelefrequencies.net/pop6003a.asp).
             Defaults to "".
         ethnic (str, optional): Filter to ethnicity. {"Amerindian", "Black", "Caucasian", ...}.
-            All ethnicities listed [here](http://www.allelefrequencies.net/pop6003a.asp).
+            All ethnicities listed [here](https://www.allelefrequencies.net/pop6003a.asp).
             Defaults to "".
         study_type (str, optional): Type of study. {"Anthropology", "Blood+Donor",
             "Bone+Marrow+Registry", "Controls+for+Disease+Study", "Disease+Study+Patients",
@@ -104,7 +104,7 @@ def makeURL(
     Returns:
         str: URL to search allelefrequencies.net
     """
-    base = "http://www.allelefrequencies.net/hla6006a.asp?"
+    base = "https://www.allelefrequencies.net/hla6006a.asp?"
     locus_type = "hla_locus_type=Classical&"
     hla_locus = "hla_locus=%s&" % (locus)
     country = "hla_country=%s&" % (country)
@@ -220,15 +220,15 @@ def formatAF(AFtab, ignoreG=True):
         AFtab (pd.DataFrame): Allele frequency data downloaded from allelefrequency.net
             using `getAFdata()`.
         ignoreG (bool, optional): Treat G group alleles as normal.
-            See http://hla.alleles.org/alleles/g_groups.html for details. Defaults to True.
+            See https://hla.alleles.org/alleles/g_groups.html for details. Defaults to True.
 
     Returns:
         pd.DataFrame: The formatted allele frequency data.
     """
     df = AFtab.copy()
-    if df.sample_size.dtype == "O":
+    if pd.api.types.is_string_dtype(df.sample_size.dtype):
         df.sample_size = pd.to_numeric(df.sample_size.str.replace(",", ""))
-    if df.allele_freq.dtype == "O":
+    if pd.api.types.is_string_dtype(df.allele_freq.dtype):
         if ignoreG:
             df.allele_freq = df.allele_freq.str.replace("(*)", "", regex=False)
         df.allele_freq = pd.to_numeric(df.allele_freq)
@@ -245,7 +245,7 @@ def getAFdata(base_url, timeout=20, format=True, ignoreG=True):
         timeout (int): How long to wait to receive a response.
         format (bool): Format the downloaded data using `formatAF()`.
         ignoreG (bool): treat allele G groups as normal.
-            See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
+            See https://hla.alleles.org/alleles/g_groups.html for details. Default = True
 
     Returns:
         pd.DataFrame: allele frequency data parsed into a pandas dataframe
@@ -393,7 +393,8 @@ def collapse_reduced_alleles(AFtab, datasetID="population"):
             row.loci.unique()[0],
             len(row.loci.unique()),
             len(row.sample_size.unique()),
-        ]
+        ],
+        include_groups=False
     )
     collapsed = pd.DataFrame(
         collapsed.tolist(),
@@ -555,7 +556,8 @@ def combineAF(
             np.average(row.allele_freq, weights=row[weights]),
             row.c.sum(),
             row.sample_size.sum(),
-        ]
+        ],
+        include_groups=False
     )
     combined = pd.DataFrame(
         combined.tolist(), columns=["allele", "loci", "wav", "c", "sample_size"]

tests/test_HLAfreq_pymc.py

@@ -34,7 +34,7 @@ def test_correct_c_array(aftab):
     aftab['c'] = 2 * aftab.allele_freq * aftab.sample_size
     c_pivot = aftab.pivot(columns="allele", index="population", values="c")
     c_array = HLAhdi._make_c_array(aftab)
-    pytest.approx(c_array[0]) == c_pivot
+    assert pytest.approx(c_array[0]) == c_pivot
 
 
 def test_correct_c_array_alleles(aftab):
@@ -43,7 +43,7 @@ def test_correct_c_array_alleles(aftab):
     aftab['c'] = 2 * aftab.allele_freq * aftab.sample_size
     c_pivot = aftab.pivot(columns="allele", index="population", values="c")
     c_array = HLAhdi._make_c_array(aftab)
-    c_array[1] == c_pivot.columns
+    assert all(c_array[1] == c_pivot.columns)
 
 
 def test_complete(aftab):