Merge branch 'main' of https://github.com/PhilippThoelke/goofi-pipe

Author: AntoineBellemare

pyproject.toml

@@ -27,4 +27,4 @@ license = {file = "LICENSE"}
 name = "goofi"
 readme = {file = "README.md", content-type = "text/markdown"}
 requires-python = ">=3.9"
-version = "2.1.16"
+version = "2.1.18"

src/goofi/nodes/analysis/phiid.py

@@ -1,67 +1,60 @@
-import numpy as np
 from copy import deepcopy
-from phyid.calculate import calc_PhiID
+
+import numpy as np
+
 from goofi.data import Data, DataType
 from goofi.node import Node
 from goofi.params import FloatParam, StringParam
 
 information_dynamics_metrics = {
-    "Storage": [
-        "rtr", "xtx", "yty", "sts"
-    ],
-    "Copy": [
-        "xtx", "yty"
-    ],
-    "Transfer": [
-        "xty", "ytx"
-    ],
-    "Erasure": [
-        "rtx", "rty"
-    ],
-    "Downward causation": [
-        "sty", "stx", "str"
-    ],
-    "Upward causation": [
-        "xts", "yts", "rts"
-    ]
+    "Storage": ["rtr", "xtx", "yty", "sts"],
+    "Copy": ["xtx", "yty"],
+    "Transfer": ["xty", "ytx"],
+    "Erasure": ["rtx", "rty"],
+    "Downward causation": ["sty", "stx", "str"],
+    "Upward causation": ["xts", "yts", "rts"],
 }
 
 IIT_metrics = {
-    "Information storage": [
-        "xtx", "yty", "rtr", "sts"
-    ],
-    "Transfer entropy": [
-        "xty", "xtr", "str", "sty"
-    ],
-    "Causal density": [
-        "xtr", "ytr", "sty", "str" ,"str", "xty", "ytx", "stx"
-    ],
-    "Integrated information": [
-        "rts", "xts", "sts", "sty", "str", "yts", "ytx", "stx", "xty"
-    ]
+    "Information storage": ["xtx", "yty", "rtr", "sts"],
+    "Transfer entropy": ["xty", "xtr", "str", "sty"],
+    "Causal density": ["xtr", "ytr", "sty", "str", "str", "xty", "ytx", "stx"],
+    "Integrated information": ["rts", "xts", "sts", "sty", "str", "yts", "ytx", "stx", "xty"],
 }
 
+
 class PhiID(Node):
 
     def config_input_slots():
         return {"matrix": DataType.ARRAY}
 
     def config_output_slots():
-        return {"PhiID": DataType.ARRAY,
-                'inf_dyn': DataType.ARRAY,
-                'IIT': DataType.ARRAY}
+        return {"PhiID": DataType.ARRAY, "inf_dyn": DataType.ARRAY, "IIT": DataType.ARRAY}
 
     def config_params():
         return {
             "PhiID": {
                 "tau": FloatParam(5, 1, 100, doc="Time lag for the PhiID algorithm"),
-                "kind": StringParam("gaussian", options=["gaussian", "discrete"],
-                                     doc="Kind of data (continuous Gaussian or discrete-binarized)"),
-                "redudancy": StringParam("MMI", options=["MMI", "CCS"],
-                                         doc="Redundancy measure to use"),
+                "kind": StringParam(
+                    "gaussian",
+                    options=["gaussian", "discrete"],
+                    doc="Kind of data (continuous Gaussian or discrete-binarized)",
+                ),
+                "redudancy": StringParam("MMI", options=["MMI", "CCS"], doc="Redundancy measure to use"),
             }
         }
 
+    def setup(self):
+        try:
+            from phyid.calculate import calc_PhiID
+        except ImportError:
+            raise ImportError(
+                "The phyid package is not installed. Please install it with the following command:\n"
+                "pip install git+https://github.com/Imperial-MIND-lab/integrated-info-decomp.git"
+            )
+
+        self.calc_PhiID = calc_PhiID
+
     def process(self, matrix: Data):
         # If no input, do nothing
         if matrix is None or matrix.data is None:
@@ -78,10 +71,24 @@ def process(self, matrix: Data):
         redundancy = self.params["PhiID"]["redudancy"].value
 
         # List of atom names in fixed order
-        atom_names = ['rtr', 'rtx', 'rty', 'rts',
-                      'xtr', 'xtx', 'xty', 'xts',
-                      'ytr', 'ytx', 'yty', 'yts',
-                      'str', 'stx', 'sty', 'sts']
+        atom_names = [
+            "rtr",
+            "rtx",
+            "rty",
+            "rts",
+            "xtr",
+            "xtx",
+            "xty",
+            "xts",
+            "ytr",
+            "ytx",
+            "yty",
+            "yts",
+            "str",
+            "stx",
+            "sty",
+            "sts",
+        ]
         n_atoms = len(atom_names)
 
         # Prepare output array: one row per channel, one col per atom
@@ -100,7 +107,7 @@ def process(self, matrix: Data):
                 # TODO
 
             # Run the PhiID calculation
-            atoms_res, _ = calc_PhiID(src, trg, tau, kind=kind, redundancy=redundancy)
+            atoms_res, _ = self.calc_PhiID(src, trg, tau, kind=kind, redundancy=redundancy)
             # add 'str', 'stx', 'sty', 'sts' together
 
             # Each atoms_res[name] is a vector length n_time - tau
@@ -132,22 +139,10 @@ def process(self, matrix: Data):
             channel_labels = matrix.meta["channels"]["dim0"]
         else:
             channel_labels = [f"ch{i}" for i in range(n_channels)]
-        out_meta["channels"] = {
-            "dim0": channel_labels,
-            "dim1": atom_names
-        }
+        out_meta["channels"] = {"dim0": channel_labels, "dim1": atom_names}
         out_phi = {}
-        out_phi['channels'] = {
-            "dim0": channel_labels,
-            "dim1": list(information_dynamics_metrics.keys())
-        }
+        out_phi["channels"] = {"dim0": channel_labels, "dim1": list(information_dynamics_metrics.keys())}
         out_IIT = {}
-        out_IIT['channels'] = {
-            "dim0": channel_labels,
-            "dim1": list(IIT_metrics.keys())
-        }
-
-        return {"PhiID": (PhiID_vals, out_meta),
-                "inf_dyn": (inf_dyn_vals, out_phi),
-                "IIT": (IIT_vals, out_IIT)}
+        out_IIT["channels"] = {"dim0": channel_labels, "dim1": list(IIT_metrics.keys())}
 
+        return {"PhiID": (PhiID_vals, out_meta), "inf_dyn": (inf_dyn_vals, out_phi), "IIT": (IIT_vals, out_IIT)}