started the creation of a model interface and a dataparser for models

CellData.py

@@ -30,6 +30,8 @@ class CellData:
 
     def __init__(self, data_path):
         self.data_path = data_path
+        self.parser = dpf.get_parser(data_path)
+
         self.base_traces = None
         # self.fi_traces = None
         self.fi_intensities = None
@@ -38,7 +40,7 @@ class CellData:
         self.mean_isi_frequencies = None
         self.time_axes = None
         # self.metadata = None
-        self.parser = dpf.get_parser(data_path)
+
 
         self.sampling_interval = self.parser.get_sampling_interval()
         self.recording_times = self.parser.get_recording_times()

DataParserFactory.py

@@ -2,10 +2,12 @@
 from os.path import isdir, exists
 from warnings import warn
 import pyrelacs.DataLoader as Dl
+from models.AbstractModel import AbstractModel
 
 UNKNOWN = -1
 DAT_FORMAT = 0
 NIX_FORMAT = 1
+MODEL = 2
 
 
 class AbstractParser:
@@ -41,7 +43,7 @@ class DatParser(AbstractParser):
         self.sampling_interval = -1
 
     def cell_get_metadata(self):
-        pass
+        raise NotImplementedError("NOT YET OVERRIDDEN FROM ABSTRACT CLASS")
 
     def get_sampling_interval(self):
         if self.sampling_interval == -1:
@@ -206,6 +208,14 @@ class DatParser(AbstractParser):
             raise RuntimeError(self.fi_file + " file doesn't exist!")
 
 
+
+class ModelParser(AbstractParser):
+
+    def __init__(self, model: AbstractModel):
+        self.model = model
+
+
+
 # TODO ####################################
 class NixParser(AbstractParser):
 
@@ -215,18 +225,23 @@ class NixParser(AbstractParser):
 # TODO ####################################
 
 
-def get_parser(data_path: str) -> AbstractParser:
+def get_parser(data_path) -> AbstractParser:
     data_format = __test_for_format__(data_path)
 
     if data_format == DAT_FORMAT:
         return DatParser(data_path)
     elif data_format == NIX_FORMAT:
         return NixParser(data_path)
+    elif MODEL:
+        return ModelParser(data_path)
     elif UNKNOWN:
         raise TypeError("DataParserFactory:get_parser(data_path):\nCannot determine type of data for:" + data_path)
 
 
 def __test_for_format__(data_path):
+    if isinstance(data_path, AbstractModel):
+        return MODEL
+
     if isdir(data_path):
         if exists(data_path + "/fispikes1.dat"):
             return DAT_FORMAT

models/AbstractModel.py

@@ -0,0 +1,9 @@
+
+
+class AbstractModel:
+
+    # TODO what information about the model does the ModelParser need to be able to simulate the right kind of data
+    # for further analysis in cell_data/fi_curve etc.
+
+    def min_stimulus_strength_to_spike(self):
+        raise NotImplementedError("NOT IMPLEMENTED")

models/LIFAC.py

@@ -1,9 +1,10 @@
 
 from stimuli.AbstractStimulus import AbstractStimulus
+from models.AbstractModel import AbstractModel
 import numpy as np
 
 
-class LIFACModel:
+class LIFACModel(AbstractModel):
     # all times in milliseconds
     KEYS = ["mem_res", "mem_tau", "v_base", "v_zero", "threshold", "step_size", "delta_a", "tau_a"]
     VALUES = [100 * 1000000, 0.1 * 200, 0, 0, 10, 0.01, 1, 200]