rename

baseline_data.py

@@ -0,0 +1,94 @@
+import datajoint as dj
+import nixio as nix
+import os
+import numpy as np
+from IPython import embed
+from database import Dataset, Repro
+schema = dj.schema("fish_book", locals())
+
+
+class BaselineData(object):
+
+    def __init__(self, dataset:Dataset):
+        self.__data = []
+        self.__dataset = dataset
+        self._get_data()
+
+
+    def _get_data(self):
+        if not self.__dataset:
+            self.__data = []
+        self.__data = []
+
+        repros = (Repro & self.__dataset & "repro_name like 'BaselineActivity%'")
+        for r in repros:
+            self.__data.append(self.__read_data(r))
+
+    def __read_data(self, r:Repro):
+        if self.__dataset["has_nix"]:
+            return self.__read_data_from_nix(r)
+        else:
+            return self.__read_data_from_directory(r)
+
+    @property
+    def dataset(self):
+        return self.__dataset
+
+    @property
+    def data(self, index:int=0):
+        return self.__data[0] if len(self.__data) >= index else None
+
+    @property
+    def size(self):
+        return len(self.__data)
+
+    def __str__(self):
+        str = "Baseline data of %s " % self.__dataset
+
+    def __read_data_from_nix(self, r)->np.ndarray:
+        data_source = os.path.join(self.__dataset["data_source"], self.__dataset["dataset_id"] + ".nix")
+        if not os.path.exists(data_source):
+            print("Data not found! Trying from folder")
+            return self.__read_data_from_directory(r)
+        f = nix.File.open(data_source, nix.FileMode.ReadOnly)
+        b = f.blocks[0]
+        t = b.tags[r["repro_id"]]
+        if not t:
+            print("Tag not found!")
+        data = t.retrieve_data("Spikes-1")[:]
+        f.close()
+        return data
+
+    def __read_data_from_directory(self, r)->np.ndarray:
+        data = []
+        data_source = os.path.join(self.__dataset["data_source"], "basespikes1.dat")
+        if os.path.exists(data_source):
+            found_run = False
+            with open(data_source, 'r') as f:
+                l = f.readline()
+                while l:
+                    if "index" in l:
+                        index = int(l.strip("#").strip().split(":")[-1])
+                        found_run = index == r["run"]
+                    if l.startswith("#Key") and found_run:
+                        data = self.__do_read(f)
+                        break
+                    l = f.readline()
+        return data
+
+    def __do_read(self, f)->np.ndarray:
+        data = []
+        f.readline()
+        f.readline()
+        l = f.readline()
+        while l and "#" not in l and len(l.strip()) > 0:
+            data.append(float(l.strip()))
+            l = f.readline()
+        return np.asarray(data)
+
+
+if __name__ == "__main__":
+    print("Test")
+    dataset = Dataset & "dataset_id like '2018-11-09-aa-%' "
+    baseline = BaselineData(dataset.fetch1())
+    embed()