Witold Wydmański
commited on
Commit
·
7f403fc
1
Parent(s):
68c44ad
fix: fix dataset errors
Browse files- README.md +2 -2
- metagenomic_curated.py +23 -20
README.md
CHANGED
@@ -9,8 +9,8 @@ Please refer to the [study list](https://experimenthub.bioconductor.org/package/
|
|
9 |
|
10 |
## Sample usage
|
11 |
```python
|
12 |
-
ds = datasets.load_dataset("
|
13 |
-
X = np.array(ds['train']['features'])
|
14 |
y = np.array([x['study_condition'] for x in ds['train']['metadata']])
|
15 |
```
|
16 |
|
|
|
9 |
|
10 |
## Sample usage
|
11 |
```python
|
12 |
+
ds = datasets.load_dataset("./metagenomic_curated.py", "EH1726")
|
13 |
+
X = np.array([list(i.values()) for i in ds['train']['features']])
|
14 |
y = np.array([x['study_condition'] for x in ds['train']['metadata']])
|
15 |
```
|
16 |
|
metagenomic_curated.py
CHANGED
@@ -1,4 +1,5 @@
|
|
1 |
#%%
|
|
|
2 |
import pyreadr
|
3 |
import pandas as pd
|
4 |
import numpy as np
|
@@ -8,6 +9,7 @@ import datasets
|
|
8 |
import tempfile
|
9 |
import rdata
|
10 |
import json
|
|
|
11 |
|
12 |
#%%
|
13 |
sqlite_url = "https://experimenthub.bioconductor.org/metadata/experimenthub.sqlite3"
|
@@ -19,22 +21,6 @@ Pasolli E, Schiffer L, Manghi P, Renson A, Obenchain V, Truong D, Beghini F, Mal
|
|
19 |
"""
|
20 |
|
21 |
# %%
|
22 |
-
# def get_metadata():
|
23 |
-
# with tempfile.NamedTemporaryFile(delete=False) as tmpfname:
|
24 |
-
# r = requests.get(sqlite_url, allow_redirects=True)
|
25 |
-
# open(tmpfname.name, 'wb').write(r.content)
|
26 |
-
|
27 |
-
# db = sqlite3.connect(tmpfname.name)
|
28 |
-
# cursor = db.cursor()
|
29 |
-
# cur = cursor.execute("""SELECT * FROM resources""")
|
30 |
-
|
31 |
-
# ehid = []
|
32 |
-
# descriptions = []
|
33 |
-
# for row in cur.fetchall():
|
34 |
-
# if "curatedMetagenomicData" in str(row[-1]):
|
35 |
-
# ehid.append(row[1])
|
36 |
-
# descriptions.append(row[7])
|
37 |
-
# return ehid, descriptions
|
38 |
|
39 |
def get_metadata():
|
40 |
ehids = []
|
@@ -62,12 +48,22 @@ class MetagenomicCurated(datasets.GeneratorBasedBuilder):
|
|
62 |
for ehid, d in zip(ehids, descriptions)
|
63 |
]
|
64 |
|
|
|
|
|
|
|
65 |
def _info(self):
|
|
|
|
|
|
|
|
|
|
|
|
|
66 |
return datasets.DatasetInfo(
|
67 |
description=self.config.description,
|
68 |
citation=CITATION,
|
69 |
homepage="https://waldronlab.io/curatedMetagenomicData/index.html",
|
70 |
license="https://www.r-project.org/Licenses/Artistic-2.0",
|
|
|
71 |
)
|
72 |
|
73 |
def _split_generators(self, dl_manager):
|
@@ -87,22 +83,29 @@ class MetagenomicCurated(datasets.GeneratorBasedBuilder):
|
|
87 |
parsed = rdata.parser.parse_file(filepath)
|
88 |
converted = rdata.conversion.convert(parsed)
|
89 |
expressions = list(converted.values())[0].assayData['exprs']
|
|
|
90 |
data_df = expressions.to_pandas().T
|
|
|
|
|
91 |
study_name = list(converted.keys())[0].split(".")[0]
|
92 |
|
93 |
meta = pyreadr.read_r(rdata_path)['sampleMetadata']
|
94 |
metadata = meta.loc[meta['study_name'] == study_name].set_index('sample_id')
|
95 |
|
96 |
for idx, (i, row) in enumerate(data_df.iterrows()):
|
|
|
|
|
|
|
|
|
97 |
yield idx, {
|
98 |
-
"features": row.
|
99 |
-
"metadata":
|
100 |
}
|
101 |
|
102 |
# %%
|
103 |
if __name__=="__main__":
|
104 |
-
ds = datasets.load_dataset("./metagenomic_curated.py", "
|
105 |
-
X = np.array(ds['train']['features'])
|
106 |
y = np.array([x['study_condition'] for x in ds['train']['metadata']])
|
107 |
|
108 |
# %%
|
|
|
1 |
#%%
|
2 |
+
from typing import Any
|
3 |
import pyreadr
|
4 |
import pandas as pd
|
5 |
import numpy as np
|
|
|
9 |
import tempfile
|
10 |
import rdata
|
11 |
import json
|
12 |
+
from typing import Any
|
13 |
|
14 |
#%%
|
15 |
sqlite_url = "https://experimenthub.bioconductor.org/metadata/experimenthub.sqlite3"
|
|
|
21 |
"""
|
22 |
|
23 |
# %%
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
24 |
|
25 |
def get_metadata():
|
26 |
ehids = []
|
|
|
48 |
for ehid, d in zip(ehids, descriptions)
|
49 |
]
|
50 |
|
51 |
+
def __call__(self, *args: Any, **kwds: Any) -> Any:
|
52 |
+
return super().__call__(*args, **kwds)
|
53 |
+
|
54 |
def _info(self):
|
55 |
+
try:
|
56 |
+
features = {
|
57 |
+
i: datasets.Value("float32") for i in self.features
|
58 |
+
}
|
59 |
+
except:
|
60 |
+
features = {}
|
61 |
return datasets.DatasetInfo(
|
62 |
description=self.config.description,
|
63 |
citation=CITATION,
|
64 |
homepage="https://waldronlab.io/curatedMetagenomicData/index.html",
|
65 |
license="https://www.r-project.org/Licenses/Artistic-2.0",
|
66 |
+
# features=features
|
67 |
)
|
68 |
|
69 |
def _split_generators(self, dl_manager):
|
|
|
83 |
parsed = rdata.parser.parse_file(filepath)
|
84 |
converted = rdata.conversion.convert(parsed)
|
85 |
expressions = list(converted.values())[0].assayData['exprs']
|
86 |
+
|
87 |
data_df = expressions.to_pandas().T
|
88 |
+
self.features = data_df.columns
|
89 |
+
|
90 |
study_name = list(converted.keys())[0].split(".")[0]
|
91 |
|
92 |
meta = pyreadr.read_r(rdata_path)['sampleMetadata']
|
93 |
metadata = meta.loc[meta['study_name'] == study_name].set_index('sample_id')
|
94 |
|
95 |
for idx, (i, row) in enumerate(data_df.iterrows()):
|
96 |
+
try:
|
97 |
+
md = {i: str(j) for i, j in metadata.loc[i].to_dict().items()}
|
98 |
+
except KeyError:
|
99 |
+
md = {}
|
100 |
yield idx, {
|
101 |
+
"features": row.to_dict(),
|
102 |
+
"metadata": md
|
103 |
}
|
104 |
|
105 |
# %%
|
106 |
if __name__=="__main__":
|
107 |
+
ds = datasets.load_dataset("./metagenomic_curated.py", "EH1726")
|
108 |
+
X = np.array([list(i.values()) for i in ds['train']['features']])
|
109 |
y = np.array([x['study_condition'] for x in ds['train']['metadata']])
|
110 |
|
111 |
# %%
|