Review of Tutorial Notebooks

README.md

@@ -118,5 +118,7 @@ Version 2.2 - Added MobsPy expressions
 
 Version 2.3 - MobsPy standard output is now always concentration.
 
+Version 2.4.4 - Assignments completely added (both notations)
+
 
 

example_models/Tutorial Notebooks/02_Reaction_Inheritance.ipynb

@@ -43,7 +43,7 @@
     {
      "data": {
       "text/plain": [
-       "<mobspy.modules.meta_class.Reactions at 0x7fec96aa6a90>"
+       "<mobspy.modules.meta_class.Reactions at 0x7fc0ef2a1610>"
       ]
      },
      "execution_count": 2,
@@ -130,26 +130,12 @@
    "execution_count": 6,
    "id": "5f0c9765-b7d0-4e26-98ed-8660fcd74f26",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(<mobspy.modules.meta_class.Species at 0x7fec96a7f760>,\n",
-       " <mobspy.modules.meta_class.Species at 0x7fec96aa6370>,\n",
-       " <mobspy.modules.meta_class.Species at 0x7fec96a7ffa0>,\n",
-       " <mobspy.modules.meta_class.Species at 0x7fec96aa66a0>)"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "S = Simulation(Ecoli | Strepto | Glucose | Amino)\n",
-    "\n",
     "# Adding some counts\n",
-    "Ecoli(50), Strepto(25), Glucose(10), Amino(100)"
+    "Ecoli(50), Strepto(25), Glucose(10), Amino(100)\n",
+    "\n",
+    "S = Simulation(Ecoli | Strepto | Glucose | Amino)"
    ]
   },
   {
@@ -180,10 +166,10 @@
      "text": [
       "\n",
       "Species\n",
-      "Amino,0\n",
-      "Ecoli,0\n",
-      "Glucose,0\n",
-      "Strepto,0\n",
+      "Amino,100\n",
+      "Ecoli,50\n",
+      "Glucose,10\n",
+      "Strepto,25\n",
       "\n",
       "Mappings\n",
       "Amino :\n",

example_models/Tutorial Notebooks/03_Characteristics.ipynb

@@ -23,7 +23,7 @@
     {
      "data": {
       "text/plain": [
-       "<mobspy.modules.meta_class.Reactions at 0x7f9367aa3580>"
+       "<mobspy.modules.meta_class.Reactions at 0x7ff51e2a9670>"
       ]
      },
      "execution_count": 1,
@@ -89,7 +89,7 @@
     {
      "data": {
       "text/plain": [
-       "<mobspy.modules.meta_class.Reactions at 0x7f9367a42220>"
+       "<mobspy.modules.meta_class.Reactions at 0x7ff51e280e50>"
       ]
      },
      "execution_count": 3,
@@ -134,7 +134,7 @@
     {
      "data": {
       "text/plain": [
-       "<mobspy.modules.meta_class.Reactions at 0x7f9367aae070>"
+       "<mobspy.modules.meta_class.Reactions at 0x7ff523a39ca0>"
       ]
      },
      "execution_count": 4,

example_models/Tutorial Notebooks/04_Characteristic_restriction.ipynb

@@ -23,7 +23,7 @@
      "text": [
       "\u001b[91mERROR: The same characteristic can only be shared through inheritance. There are two characteristics directly added to two meta-species \n",
       "Repetition in: C, A \n",
-      "Characteristics: {'aaa', 'ccc'}, {'bbb', 'aaa'} \n",
+      "Characteristics: {'aaa', 'ccc'}, {'aaa', 'bbb'} \n",
       "\u001b[0m\n"
      ]
     }

example_models/Tutorial Notebooks/07_Initial_Condition.ipynb

@@ -82,7 +82,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[{'characteristics': 'std$', 'quantity': 100}, {'characteristics': {'big', 'red'}, 'quantity': 150}]\n"
+      "[{'characteristics': 'std$', 'quantity': 100}, {'characteristics': {'red', 'big'}, 'quantity': 150}]\n"
      ]
     }
    ],
@@ -109,7 +109,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[{'characteristics': 'std$', 'quantity': 100}, {'characteristics': {'big', 'red'}, 'quantity': 150}, {'characteristics': {'all$'}, 'quantity': 10}]\n"
+      "[{'characteristics': 'std$', 'quantity': 100}, {'characteristics': {'red', 'big'}, 'quantity': 150}, {'characteristics': {'all$'}, 'quantity': 10}]\n"
      ]
     }
    ],
@@ -138,7 +138,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[{'characteristics': 'std$', 'quantity': 100}, {'characteristics': {'big', 'red'}, 'quantity': 150}, {'characteristics': {'all$'}, 'quantity': 10}, {'characteristics': {'big', 'all$'}, 'quantity': 100}]\n"
+      "[{'characteristics': 'std$', 'quantity': 100}, {'characteristics': {'red', 'big'}, 'quantity': 150}, {'characteristics': {'all$'}, 'quantity': 10}, {'characteristics': {'all$', 'big'}, 'quantity': 100}]\n"
      ]
     }
    ],

example_models/Tutorial Notebooks/08_Units_and_Output.ipynb

@@ -104,7 +104,7 @@
     {
      "data": {
       "text/plain": [
-       "<mobspy.modules.meta_class.Reactions at 0x7fc81629f9a0>"
+       "<mobspy.modules.meta_class.Reactions at 0x7fb17f9de8b0>"
       ]
      },
      "execution_count": 3,

example_models/Tutorial Notebooks/11_Looping_Through_Species.ipynb

@@ -68,7 +68,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'a1', 'a2', 'a3'}\n",
+      "{'a3', 'a1', 'a2'}\n",
       "{'b1', 'b2', 'b3'}\n"
      ]
     },

example_models/Tutorial Notebooks/15_Assignments.ipynb

@@ -77,7 +77,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 2,
    "id": "74f390fe-b828-4d46-95ec-158ec4a414ff",
    "metadata": {},
    "outputs": [
@@ -139,7 +139,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 3,
    "id": "4d52afbc-a46b-4998-bd3b-4611d30156a5",
    "metadata": {},
    "outputs": [
@@ -152,6 +152,13 @@
       "Simulation is Over\n"
      ]
     },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    },
     {
      "data": {
       "image/png": 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\n",
@@ -193,7 +200,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 4,
    "id": "34a015fb-057a-47a7-a617-3bdb29cad5a1",
    "metadata": {},
    "outputs": [

mobspy/plot_scripts/default_plots.py

@@ -37,9 +37,9 @@ def set_plot_units(new_plot_params):
         if new_plot_params['unit_x'] is not None and not ("ignore_unit_label_x" in new_plot_params and
                                                           new_plot_params["ignore_unit_label_x"]):
             if not isinstance(new_plot_params['unit_x'], Quantity):
-                new_plot_params['xlabel'] += f' ({new_plot_params["unit_x"]})'
+                new_plot_params['xlabel'] += f' ({new_plot_params["unit_x"]}s)'
             else:
-                new_plot_params['xlabel'] += f' ({new_plot_params["unit_x"].units})'
+                new_plot_params['xlabel'] += f' ({new_plot_params["unit_x"].units}s)'
 
     if 'ylabel' not in new_plot_params:
         if new_plot_params['output_concentration']: