BooleanNode.from_partial_lut with bias and effective connectivity criteria #46

srikanth-iyer · 2024-06-17T22:32:47Z

created a function under BooleanNode to generate a node from partial LUT. a
added fill missing values randomly option
added required bias option
added required effective connectivity option

also, did some code clean up on some old code using ruff linter.

NOTE: Need to add some tests. Will do this in next iteration.

… partial LUT using fill_out_lut() and from_output_list()

…artial_lut()

jcrozum · 2024-06-18T17:53:50Z

cana/boolean_network.py

@@ -174,7 +175,10 @@ def from_file(self, file, type="cnet", keep_constants=True, **kwargs):
    @classmethod
    def from_string_cnet(self, string, keep_constants=True, **kwargs):


add option to retain old behavior in which prime implicant input is assumed

jcrozum · 2024-06-18T18:00:19Z

cana/boolean_node.py

@@ -110,7 +111,12 @@ def __str__(self):

    @classmethod
    def from_output_list(self, outputs=list(), *args, **kwargs):
-        """Instanciate a Boolean Node from a output transition list.


let's revert this for now. We don't have a way to know which inputs are missing yet

jcrozum · 2024-06-18T18:07:02Z

cana/boolean_node.py

@@ -449,6 +580,11 @@ def schemata_look_up_table(
        See also:
            :func:`look_up_table`
        """
+        # Check if the outputs contain '?' and generate an error message if it does. 
+        if '?' in self.outputs:
+            print("Error (schemata_look_up_table): The outputs contain missing values. Please fill the missing values before generating the schemata look-up table.")


raise exception instead or warning

jcrozum · 2024-06-18T18:14:24Z

cana/datasets/bio.py

@@ -22,6 +22,19 @@
 """ Make sure we know what the current directory is """


+def PARTIAL_LUTS_DEMO():


move somewhere else (not bio)

jcrozum · 2024-06-18T18:20:11Z

cana/drawing/schema_vis.py

@@ -11,6 +11,10 @@ def plot_schemata(n, plotTS=True):
    # Init values from BooleanNode
    k = n.k if n.k >= 1 else 1
    outputs = np.array(n.outputs)
+
+    if "?" in outputs: # check if there are any '?' in the output.
+        print("Error (plot_schemata()): The output contains '?'")


raise error

jcrozum · 2024-06-18T18:35:04Z

cana/utils.py

+
+    k = len(partial_lut[0][0])
+
+    all_states = {entry[0]: entry[1] for entry in partial_lut}


just fyi, this works:

all_states = dict(partial_lut)

jcrozum · 2024-06-18T18:46:08Z

cana/boolean_node.py

+            # Calculating max achievable bias
+            max_achievable_output = ['1' if output == '?' else output for output in generated_node.outputs]
+            max_achievable_bias = sum(map(int, max_achievable_output))/2**generated_node.k
+            min_achievable_bias = generated_node.bias(verbose=False)


this relies on the bias function treating unknowns like zeros, which is weird. We might want to change that in the future, so it's probably a good idea to just calculate min_achievable_bias directly, as you've done for its max counterpart

you already have current_ones below, so this would just be

min_achievable_bias = current_ones / 2**generated_node.k

right?

jcrozum · 2024-06-18T19:05:31Z

cana/boolean_node.py

@@ -139,6 +156,120 @@ def from_output_list(self, outputs=list(), *args, **kwargs):
            *args,
            **kwargs
        )
+
+    def from_partial_lut(partial_lut, fill_missing_output_randomly = False, required_node_bias = None, required_effective_connectivity= None,verbose= True, *args, **kwargs):


need more tests to make sure it works

jcrozum · 2024-06-18T19:08:14Z

cana/boolean_node.py

+            required_effective_connectivity (float) : The required effective connectivity to fill the missing output values with. It will generate a node with the closest possible effective connectivity to the required effective connectivity.
+            verbose (bool) : If True, print additional information. Default is True.
+
+        Returns:


make this return a list of all the ones that are "best"

jcrozum · 2024-06-18T19:10:59Z

cana/boolean_node.py

+            for count, permutation in enumerate(permutations):
+                for i, index in enumerate(missing_output_indices):
+                    generated_outputs[index] = permutation[i]
+                generated_node_permutations[count] = BooleanNode.from_output_list(generated_outputs)


refactor generated_node_permutations into its own function. It will be useful all on its own (probably)

…l_lut = false keyword. split Boolean_node.from_partial_lut into three functions added a few tests. need to add more.

Refactor BooleanNode.generate_with_required_bias and effective connectiity for improved readability and performance reorganized partial_lut demo file

srikanth-iyer added 9 commits June 3, 2024 15:39

cleaned imports in tests and some other files

ddbda0b

partial lut and test

36cd7a7

sync relevant changes from schema expansion

dd7ea15

adding temp to branch

03b532a

feat: Added partial_LUT demo tutorial, BooleanNode instantiation with…

7eb27b8

… partial LUT using fill_out_lut() and from_output_list()

added from_partial_lut method in BooleanNode

8fc41d8

added required effective connectivity criterion to BooleanNode.from_p…

e09f217

…artial_lut()

Merge 'cleaning_imports' into two_symbol_partial_lut

a69d3f9

updated from_partial_lut

37f4439

srikanth-iyer requested a review from jcrozum June 17, 2024 22:32

jcrozum requested changes Jun 18, 2024

View reviewed changes

srikanth-iyer added 6 commits June 20, 2024 20:24

retained old behaviour in BooleanNetwork.from_cnet and added a partia…

d894bdb

…l_lut = false keyword. split Boolean_node.from_partial_lut into three functions added a few tests. need to add more.

added warnings, errors

bd7e8dd

Refactor BooleanNode.generate_with_required_bias and effective connectiity for improved readability and performance reorganized partial_lut demo file

converted lists into generator for faster computation

f0e615f

modified description

3a99b8f

added generator to bias function. added tests.

46c6df8

updated generate_with_required_bias : modified sampling randomization

26104c5

srikanth-iyer closed this Jun 27, 2024

srikanth-iyer deleted the from_partial_lut-with-bias-and-effective-connectivity-criteria branch June 27, 2024 17:44

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BooleanNode.from_partial_lut with bias and effective connectivity criteria #46

BooleanNode.from_partial_lut with bias and effective connectivity criteria #46

srikanth-iyer commented Jun 17, 2024

jcrozum Jun 18, 2024

jcrozum Jun 18, 2024

jcrozum Jun 18, 2024

jcrozum Jun 18, 2024

jcrozum Jun 18, 2024

jcrozum Jun 18, 2024

jcrozum Jun 18, 2024

jcrozum Jun 18, 2024

jcrozum Jun 18, 2024

jcrozum Jun 18, 2024

jcrozum Jun 18, 2024

		@@ -174,7 +175,10 @@ def from_file(self, file, type="cnet", keep_constants=True, **kwargs):
		@classmethod
		def from_string_cnet(self, string, keep_constants=True, **kwargs):

		@@ -22,6 +22,19 @@
		""" Make sure we know what the current directory is """


		def PARTIAL_LUTS_DEMO():


		k = len(partial_lut[0][0])

		all_states = {entry[0]: entry[1] for entry in partial_lut}

BooleanNode.from_partial_lut with bias and effective connectivity criteria #46

BooleanNode.from_partial_lut with bias and effective connectivity criteria #46

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srikanth-iyer commented Jun 17, 2024

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