unimpeded_database

tests/test_unimpeded.py

@@ -0,0 +1,17 @@
+from unimpeded.unimpeded import unimpeded
+
+# These locations will be changed to Zenodo links in the future.
+loc = 'local'
+if loc == 'local':
+    location = '/Users/ongdily/Documents/Cambridge/project2/codes/'
+elif loc == 'hpc':
+    location = '/home/dlo26/rds/rds-dirac-dp192-63QXlf5HuFo/dlo26/'
+
+
+def test_get():
+    database = unimpeded(location=location)
+    samples = database.get(model='klcdm', dataset='bao.sdss_dr16', method='ns')
+    return samples
+
+
+samples = test_get()

unimpeded/database.py

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+import requests
+from anesthetic import read_chains
+import os
+
+class database:
+    def __init__(self, sandbox=True, ACCESS_TOKEN=None, bucket_url=None):
+        self.sandbox = sandbox
+        self.ACCESS_TOKEN = ACCESS_TOKEN
+        self.bucket_url = bucket_url
+
+    def upload(self, method, model, dataset, loc):
+        filename = f"{method}_{model}_{dataset}.csv"
+        if loc == 'hpc':
+            samples = read_chains(f"/home/dlo26/rds/rds-dirac-dp192-63QXlf5HuFo/dlo26/{method}/{model}/{dataset}/{dataset}_polychord_raw/{dataset}") # for hpc
+        elif loc == 'local':
+            samples = read_chains(f"../{method}/{model}/{dataset}/{dataset}_polychord_raw/{dataset}")
+        samples.to_csv(filename) # saving samples as csv, but is it necessary?
+        path = f"./{filename}"
+        print(path)
+        params = {'access_token': self.ACCESS_TOKEN}
+        with open(path, "rb") as fp:
+            print(path)
+            r = requests.put(
+                f"{self.bucket_url}/{filename}",
+                data=fp,
+                params=params
+            )
+    def download(self, ID, method, model, dataset):
+        filename = f"{method}_{model}_{dataset}.csv"
+        url = f'https://sandbox.zenodo.org/record/{ID}/files/{filename}?download=1'
+        response = requests.get(url)
+        with open(filename, 'wb') as file:
+            file.write(response.content)

unimpeded/unimpeded.py

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+"""Loading datasets."""
+from anesthetic import read_chains
+
+
+class unimpeded:
+    """Loading datasets.
+
+    **kwargs
+    ----------
+    location : str
+        The location where the datasets are stored.
+
+    """
+    def __init__(self, **kwargs):
+        self.location = kwargs.pop('location', None)
+
+    def get(self, model, dataset, method):
+        """Get the samples from the dataset.
+
+        Parameters
+        ----------
+        method : str
+            The chosen method, ns or mcmc.
+        model : str
+            The chosen model, e.g. klcdm.
+        dataset : str
+            The chosen dataset, e.g. bao.sdss_dr16.
+        """
+        samples = read_chains(
+            self.location + f"{method}/{model}/{dataset}/"
+            f"{dataset}_polychord_raw/{dataset}")
+        return samples