circuit-projects/F_toggle_repressed.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6c3937a4-d120-4fe3-8a7c-13f8bdf35019",
   "metadata": {},
   "outputs": [],
   "source": [
    "import dinkum\n",
    "import random\n",
    "import pandas as pd\n",
    "from dinkum.vfg import Gene, Receptor\n",
    "from dinkum.vfn import Tissue\n",
    "\n",
    "from dinkum.display import MultiTissuePanel, tc_record_activity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c38cd1b4-ed55-4007-a1c2-889ccf9c6c48",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initializing: dinkum v0.3.3\n",
      "start=1 stop=10\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=860x380>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dinkum.reset()\n",
    "\n",
    "# create two tissues to demonstrate the toggle-repressed switch                                                              \n",
    "m = Tissue(name='M')\n",
    "n = Tissue(name='N')\n",
    "\n",
    "# The two tissues have their own lineage-identity programs\n",
    "t1 = Gene(name = \"t1\")\n",
    "t2 = Gene(name = \"t2\")\n",
    "t1.is_present(where = m, start = 1)\n",
    "t2.is_present(where = n, start = 1)\n",
    "\n",
    "# Generate the TF co-factor that uses the two pathways\n",
    "# It is present in either tissue\n",
    "coF = Gene(name = \"coF\")\n",
    "coF.activated_or(sources = [t1, t2], delay = 1)\n",
    "\n",
    "# Generate two signaling pathways that are tissue-specific\n",
    "r1 = Gene(name = \"R1\")\n",
    "r2 = Gene(name = \"R2\")\n",
    "r1.activated_by(source = t1, delay = 1)\n",
    "r2.activated_by(source = t2, delay = 1)\n",
    "\n",
    "# The two receptors are activated by their respective ligands and transform into their active state\n",
    "l1 = Gene(name = \"L1\")\n",
    "l2 = Gene(name = \"L2\")\n",
    "ra1 = Gene(name = \"RA1\")\n",
    "ra2 = Gene(name = \"RA2\")\n",
    "ra1.activated_by_and(sources=[r1, l1], delay = 1)\n",
    "ra2.activated_by_and(sources=[r2, l2], delay = 1)\n",
    "\n",
    "# In tissue 1, active receptor 1 cooperates with coF to activate its target(s)\n",
    "up = Gene(name = \"U\")\n",
    "up.activated_by_and(sources = [ra1, coF, t1], delay = 1)\n",
    "\n",
    "# In tissue 2, active receptor 2 cooperates with coF to activate its target(s)\n",
    "down = Gene(name = \"D\")\n",
    "down.and_not(activator = t2, repressor = ra2, delay = 1)\n",
    "\n",
    "# Give the ligands at time step 4 for 3 steps\n",
    "l1.is_present(where=m, start = 3, duration=3)\n",
    "l2.is_present(where=n, start = 3, duration=3)\n",
    "\n",
    "dinkum.run_and_display(stop=10, gene_names=[\"t1\", \"t2\", \"coF\", \"R1\", \"L1\", \"RA1\", \"U\", \"R2\", \"L2\", \"RA2\", \"D\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "dfeba306-0c66-4f01-a87e-153638e426ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on package dinkum:\n",
      "\n",
      "NAME\n",
      "    dinkum\n",
      "\n",
      "PACKAGE CONTENTS\n",
      "    display (package)\n",
      "    observations\n",
      "    vfg\n",
      "    vfn\n",
      "\n",
      "CLASSES\n",
      "    builtins.Exception(builtins.BaseException)\n",
      "        DinkumException\n",
      "            DinkumObservationFailed\n",
      "    builtins.object\n",
      "        GeneActivity\n",
      "        State\n",
      "        Timecourse\n",
      "    collections.UserDict(collections.abc.MutableMapping)\n",
      "        States\n",
      "    \n",
      "    class DinkumException(builtins.Exception)\n",
      "     |  Method resolution order:\n",
      "     |      DinkumException\n",
      "     |      builtins.Exception\n",
      "     |      builtins.BaseException\n",
      "     |      builtins.object\n",
      "     |  \n",
      "     |  Data descriptors defined here:\n",
      "     |  \n",
      "     |  __weakref__\n",
      "     |      list of weak references to the object (if defined)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from builtins.Exception:\n",
      "     |  \n",
      "     |  __init__(self, /, *args, **kwargs)\n",
      "     |      Initialize self.  See help(type(self)) for accurate signature.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Static methods inherited from builtins.Exception:\n",
      "     |  \n",
      "     |  __new__(*args, **kwargs) from builtins.type\n",
      "     |      Create and return a new object.  See help(type) for accurate signature.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from builtins.BaseException:\n",
      "     |  \n",
      "     |  __delattr__(self, name, /)\n",
      "     |      Implement delattr(self, name).\n",
      "     |  \n",
      "     |  __getattribute__(self, name, /)\n",
      "     |      Return getattr(self, name).\n",
      "     |  \n",
      "     |  __reduce__(...)\n",
      "     |      Helper for pickle.\n",
      "     |  \n",
      "     |  __repr__(self, /)\n",
      "     |      Return repr(self).\n",
      "     |  \n",
      "     |  __setattr__(self, name, value, /)\n",
      "     |      Implement setattr(self, name, value).\n",
      "     |  \n",
      "     |  __setstate__(...)\n",
      "     |  \n",
      "     |  __str__(self, /)\n",
      "     |      Return str(self).\n",
      "     |  \n",
      "     |  with_traceback(...)\n",
      "     |      Exception.with_traceback(tb) --\n",
      "     |      set self.__traceback__ to tb and return self.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from builtins.BaseException:\n",
      "     |  \n",
      "     |  __cause__\n",
      "     |      exception cause\n",
      "     |  \n",
      "     |  __context__\n",
      "     |      exception context\n",
      "     |  \n",
      "     |  __dict__\n",
      "     |  \n",
      "     |  __suppress_context__\n",
      "     |  \n",
      "     |  __traceback__\n",
      "     |  \n",
      "     |  args\n",
      "    \n",
      "    class DinkumObservationFailed(DinkumException)\n",
      "     |  Method resolution order:\n",
      "     |      DinkumObservationFailed\n",
      "     |      DinkumException\n",
      "     |      builtins.Exception\n",
      "     |      builtins.BaseException\n",
      "     |      builtins.object\n",
      "     |  \n",
      "     |  Data descriptors inherited from DinkumException:\n",
      "     |  \n",
      "     |  __weakref__\n",
      "     |      list of weak references to the object (if defined)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from builtins.Exception:\n",
      "     |  \n",
      "     |  __init__(self, /, *args, **kwargs)\n",
      "     |      Initialize self.  See help(type(self)) for accurate signature.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Static methods inherited from builtins.Exception:\n",
      "     |  \n",
      "     |  __new__(*args, **kwargs) from builtins.type\n",
      "     |      Create and return a new object.  See help(type) for accurate signature.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from builtins.BaseException:\n",
      "     |  \n",
      "     |  __delattr__(self, name, /)\n",
      "     |      Implement delattr(self, name).\n",
      "     |  \n",
      "     |  __getattribute__(self, name, /)\n",
      "     |      Return getattr(self, name).\n",
      "     |  \n",
      "     |  __reduce__(...)\n",
      "     |      Helper for pickle.\n",
      "     |  \n",
      "     |  __repr__(self, /)\n",
      "     |      Return repr(self).\n",
      "     |  \n",
      "     |  __setattr__(self, name, value, /)\n",
      "     |      Implement setattr(self, name, value).\n",
      "     |  \n",
      "     |  __setstate__(...)\n",
      "     |  \n",
      "     |  __str__(self, /)\n",
      "     |      Return str(self).\n",
      "     |  \n",
      "     |  with_traceback(...)\n",
      "     |      Exception.with_traceback(tb) --\n",
      "     |      set self.__traceback__ to tb and return self.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from builtins.BaseException:\n",
      "     |  \n",
      "     |  __cause__\n",
      "     |      exception cause\n",
      "     |  \n",
      "     |  __context__\n",
      "     |      exception context\n",
      "     |  \n",
      "     |  __dict__\n",
      "     |  \n",
      "     |  __suppress_context__\n",
      "     |  \n",
      "     |  __traceback__\n",
      "     |  \n",
      "     |  args\n",
      "    \n",
      "    class GeneActivity(builtins.object)\n",
      "     |  Methods defined here:\n",
      "     |  \n",
      "     |  __contains__(self, gene)\n",
      "     |  \n",
      "     |  __init__(self)\n",
      "     |      Initialize self.  See help(type(self)) for accurate signature.\n",
      "     |  \n",
      "     |  __repr__(self)\n",
      "     |      Return repr(self).\n",
      "     |  \n",
      "     |  is_active(self, gene_name)\n",
      "     |  \n",
      "     |  report_activity(self)\n",
      "     |  \n",
      "     |  set_activity(self, *, gene=None, active=None)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors defined here:\n",
      "     |  \n",
      "     |  __dict__\n",
      "     |      dictionary for instance variables (if defined)\n",
      "     |  \n",
      "     |  __weakref__\n",
      "     |      list of weak references to the object (if defined)\n",
      "    \n",
      "    class State(builtins.object)\n",
      "     |  State(*, tissues=None, time=None)\n",
      "     |  \n",
      "     |  Hold the gene activity state for multiple tissues.\n",
      "     |  \n",
      "     |  Holds multiple tissue, each with their own GeneActivity object.\n",
      "     |  \n",
      "     |  dict interface supports getting and setting gene activity (value) by\n",
      "     |  tissue (key).\n",
      "     |  \n",
      "     |  `tissues` attribute provides enumeration of available tissues\n",
      "     |  \n",
      "     |  `is_active(gene, tissue)` returns True/False around activity.\n",
      "     |  \n",
      "     |  Methods defined here:\n",
      "     |  \n",
      "     |  __getitem__(self, tissue)\n",
      "     |  \n",
      "     |  __init__(self, *, tissues=None, time=None)\n",
      "     |      Initialize self.  See help(type(self)) for accurate signature.\n",
      "     |  \n",
      "     |  __setitem__(self, tissue, genes)\n",
      "     |  \n",
      "     |  get_by_tissue_name(self, tissue_name)\n",
      "     |  \n",
      "     |  is_active(self, gene, tissue)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Readonly properties defined here:\n",
      "     |  \n",
      "     |  tissues\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors defined here:\n",
      "     |  \n",
      "     |  __dict__\n",
      "     |      dictionary for instance variables (if defined)\n",
      "     |  \n",
      "     |  __weakref__\n",
      "     |      list of weak references to the object (if defined)\n",
      "    \n",
      "    class States(collections.UserDict)\n",
      "     |  Contains (potentially incomplete) set of tissue/gene states for many\n",
      "     |  timepoints.\n",
      "     |  \n",
      "     |  Method resolution order:\n",
      "     |      States\n",
      "     |      collections.UserDict\n",
      "     |      collections.abc.MutableMapping\n",
      "     |      collections.abc.Mapping\n",
      "     |      collections.abc.Collection\n",
      "     |      collections.abc.Sized\n",
      "     |      collections.abc.Iterable\n",
      "     |      collections.abc.Container\n",
      "     |      builtins.object\n",
      "     |  \n",
      "     |  Methods defined here:\n",
      "     |  \n",
      "     |  __init__(self)\n",
      "     |      Initialize self.  See help(type(self)) for accurate signature.\n",
      "     |  \n",
      "     |  is_active(self, current_tp, delay, gene, tissue)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data and other attributes defined here:\n",
      "     |  \n",
      "     |  __abstractmethods__ = frozenset()\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from collections.UserDict:\n",
      "     |  \n",
      "     |  __contains__(self, key)\n",
      "     |      # Modify __contains__ to work correctly when __missing__ is present\n",
      "     |  \n",
      "     |  __copy__(self)\n",
      "     |  \n",
      "     |  __delitem__(self, key)\n",
      "     |  \n",
      "     |  __getitem__(self, key)\n",
      "     |  \n",
      "     |  __ior__(self, other)\n",
      "     |  \n",
      "     |  __iter__(self)\n",
      "     |  \n",
      "     |  __len__(self)\n",
      "     |  \n",
      "     |  __or__(self, other)\n",
      "     |      Return self|value.\n",
      "     |  \n",
      "     |  __repr__(self)\n",
      "     |      Return repr(self).\n",
      "     |  \n",
      "     |  __ror__(self, other)\n",
      "     |      Return value|self.\n",
      "     |  \n",
      "     |  __setitem__(self, key, item)\n",
      "     |  \n",
      "     |  copy(self)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from collections.UserDict:\n",
      "     |  \n",
      "     |  fromkeys(iterable, value=None) from abc.ABCMeta\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from collections.UserDict:\n",
      "     |  \n",
      "     |  __dict__\n",
      "     |      dictionary for instance variables (if defined)\n",
      "     |  \n",
      "     |  __weakref__\n",
      "     |      list of weak references to the object (if defined)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from collections.abc.MutableMapping:\n",
      "     |  \n",
      "     |  clear(self)\n",
      "     |      D.clear() -> None.  Remove all items from D.\n",
      "     |  \n",
      "     |  pop(self, key, default=<object object at 0x74e789988180>)\n",
      "     |      D.pop(k[,d]) -> v, remove specified key and return the corresponding value.\n",
      "     |      If key is not found, d is returned if given, otherwise KeyError is raised.\n",
      "     |  \n",
      "     |  popitem(self)\n",
      "     |      D.popitem() -> (k, v), remove and return some (key, value) pair\n",
      "     |      as a 2-tuple; but raise KeyError if D is empty.\n",
      "     |  \n",
      "     |  setdefault(self, key, default=None)\n",
      "     |      D.setdefault(k[,d]) -> D.get(k,d), also set D[k]=d if k not in D\n",
      "     |  \n",
      "     |  update(self, other=(), /, **kwds)\n",
      "     |      D.update([E, ]**F) -> None.  Update D from mapping/iterable E and F.\n",
      "     |      If E present and has a .keys() method, does:     for k in E: D[k] = E[k]\n",
      "     |      If E present and lacks .keys() method, does:     for (k, v) in E: D[k] = v\n",
      "     |      In either case, this is followed by: for k, v in F.items(): D[k] = v\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from collections.abc.Mapping:\n",
      "     |  \n",
      "     |  __eq__(self, other)\n",
      "     |      Return self==value.\n",
      "     |  \n",
      "     |  get(self, key, default=None)\n",
      "     |      D.get(k[,d]) -> D[k] if k in D, else d.  d defaults to None.\n",
      "     |  \n",
      "     |  items(self)\n",
      "     |      D.items() -> a set-like object providing a view on D's items\n",
      "     |  \n",
      "     |  keys(self)\n",
      "     |      D.keys() -> a set-like object providing a view on D's keys\n",
      "     |  \n",
      "     |  values(self)\n",
      "     |      D.values() -> an object providing a view on D's values\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data and other attributes inherited from collections.abc.Mapping:\n",
      "     |  \n",
      "     |  __hash__ = None\n",
      "     |  \n",
      "     |  __reversed__ = None\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from collections.abc.Collection:\n",
      "     |  \n",
      "     |  __subclasshook__(C) from abc.ABCMeta\n",
      "     |      Abstract classes can override this to customize issubclass().\n",
      "     |      \n",
      "     |      This is invoked early on by abc.ABCMeta.__subclasscheck__().\n",
      "     |      It should return True, False or NotImplemented.  If it returns\n",
      "     |      NotImplemented, the normal algorithm is used.  Otherwise, it\n",
      "     |      overrides the normal algorithm (and the outcome is cached).\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from collections.abc.Iterable:\n",
      "     |  \n",
      "     |  __class_getitem__ = GenericAlias(...) from abc.ABCMeta\n",
      "     |      Represent a PEP 585 generic type\n",
      "     |      \n",
      "     |      E.g. for t = list[int], t.__origin__ is list and t.__args__ is (int,).\n",
      "    \n",
      "    class Timecourse(builtins.object)\n",
      "     |  Timecourse(*, start=None, stop=None)\n",
      "     |  \n",
      "     |  Run a time course for a system b/t two time points, start and stop.\n",
      "     |  \n",
      "     |  Methods defined here:\n",
      "     |  \n",
      "     |  __init__(self, *, start=None, stop=None)\n",
      "     |      Initialize self.  See help(type(self)) for accurate signature.\n",
      "     |  \n",
      "     |  __iter__(self)\n",
      "     |  \n",
      "     |  __len__(self)\n",
      "     |  \n",
      "     |  check(self)\n",
      "     |      Test all of the observations for all of the states.\n",
      "     |  \n",
      "     |  run(self, *, verbose=False)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors defined here:\n",
      "     |  \n",
      "     |  __dict__\n",
      "     |      dictionary for instance variables (if defined)\n",
      "     |  \n",
      "     |  __weakref__\n",
      "     |      list of weak references to the object (if defined)\n",
      "\n",
      "FUNCTIONS\n",
      "    reset(*, verbose=True)\n",
      "    \n",
      "    run(start, stop, *, verbose=False)\n",
      "    \n",
      "    run_and_display(*, start=1, stop=10, gene_names=None, tissue_names=None, verbose=False, save_image=None)\n",
      "        Run and display the circuit model.\n",
      "        \n",
      "        Key parameter:\n",
      "        - start (default: 1)\n",
      "        - stop (default 10)\n",
      "        \n",
      "        Other parameters:\n",
      "        - 'tissue_names' - a list of tissue names to display (default: all).\n",
      "        - 'gene_names' - a list of gene names to display (default: all).\n",
      "        - 'verbose' - display more text output.\n",
      "        - 'save_image' - save image to this file.\n",
      "        - 'canvas_type' - 'ipycanvas' or 'pillow' (default: 'pillow')\n",
      "\n",
      "VERSION\n",
      "    0.3.3\n",
      "\n",
      "FILE\n",
      "    /opt/tljh/user/lib/python3.10/site-packages/dinkum/__init__.py\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(dinkum)"
   ]
  }
 ],
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