diff --git a/synced_files/GA_1_7/Solution/Discharge/Analysis_discharge_solution.ipynb b/synced_files/GA_1_7/Solution/Discharge/Analysis_discharge_solution.ipynb
index bbcf40a28a1f9b9e727535f885cd8ab99eea9d2e..d859c7cde7d4049a504dcf119a30be9a91327486 100644
--- a/synced_files/GA_1_7/Solution/Discharge/Analysis_discharge_solution.ipynb
+++ b/synced_files/GA_1_7/Solution/Discharge/Analysis_discharge_solution.ipynb
@@ -606,7 +606,7 @@
},
{
"cell_type": "markdown",
- "id": "11ddc8c7",
+ "id": "e3ec88c5",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; width:95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
diff --git a/synced_files/GA_1_7/Solution/Emissions/Analysis_emissions_solution.ipynb b/synced_files/GA_1_7/Solution/Emissions/Analysis_emissions_solution.ipynb
index eaee666b66ec1b3f6bd31a1cd3859f055e67928c..33abe5e9e1330b2c5377bd67db0bd5cd3c148979 100644
--- a/synced_files/GA_1_7/Solution/Emissions/Analysis_emissions_solution.ipynb
+++ b/synced_files/GA_1_7/Solution/Emissions/Analysis_emissions_solution.ipynb
@@ -159,7 +159,7 @@
},
{
"cell_type": "markdown",
- "id": "4d6a4ac5",
+ "id": "5f318fac",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; width:95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
@@ -262,7 +262,7 @@
},
{
"cell_type": "markdown",
- "id": "a360a68e",
+ "id": "b88582e2",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; width:95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
@@ -374,7 +374,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "78e8bfb0",
+ "id": "a9249f8a",
"metadata": {},
"outputs": [],
"source": [
@@ -437,7 +437,7 @@
},
{
"cell_type": "markdown",
- "id": "f9e6e4b7",
+ "id": "b8203245",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; width:95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
@@ -538,7 +538,7 @@
},
{
"cell_type": "markdown",
- "id": "b2b33edf",
+ "id": "d20c56cb",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; width:95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
@@ -552,7 +552,7 @@
},
{
"cell_type": "markdown",
- "id": "6dc245f9",
+ "id": "a64c2f48",
"metadata": {},
"source": [
"If you run the code in the cell below, you will obtain a scatter plot of both variables. Explore the relationship between both variables and answer the following questions:\n",
@@ -573,7 +573,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "247c8913",
+ "id": "f11b2a9d",
"metadata": {},
"outputs": [],
"source": [
@@ -589,7 +589,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "36f2bad5",
+ "id": "1bbdd9ef",
"metadata": {},
"outputs": [],
"source": [
@@ -602,7 +602,7 @@
},
{
"cell_type": "markdown",
- "id": "fd15799d",
+ "id": "92f1d815",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; width:95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
diff --git a/synced_files/GA_1_7/Solution/Force/Analysis_force_solution.ipynb b/synced_files/GA_1_7/Solution/Force/Analysis_force_solution.ipynb
index e62246d1696aebaa0547ac0460864c0e0ab5a983..cc56ac7aa29dc1a57dbf47ad0c1a33d17485a3e3 100644
--- a/synced_files/GA_1_7/Solution/Force/Analysis_force_solution.ipynb
+++ b/synced_files/GA_1_7/Solution/Force/Analysis_force_solution.ipynb
@@ -164,7 +164,7 @@
},
{
"cell_type": "markdown",
- "id": "f36e02f9",
+ "id": "dafcccce",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; width:95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
@@ -269,7 +269,7 @@
},
{
"cell_type": "markdown",
- "id": "f1685ef7",
+ "id": "8cadad2e",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; width:95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
@@ -382,7 +382,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "ee4fa46e",
+ "id": "d0876078",
"metadata": {},
"outputs": [],
"source": [
@@ -445,7 +445,7 @@
},
{
"cell_type": "markdown",
- "id": "1954e862",
+ "id": "37c26b83",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; width:95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
@@ -546,7 +546,7 @@
},
{
"cell_type": "markdown",
- "id": "6fbb2622",
+ "id": "f638295c",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; width:95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
@@ -561,7 +561,7 @@
},
{
"cell_type": "markdown",
- "id": "a24abfa0",
+ "id": "79d7654b",
"metadata": {},
"source": [
"If you run the code in the cell below, you will obtain a scatter plot of both variables. Explore the relationship between both variables and answer the following questions:\n",
@@ -582,7 +582,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "fdf07f46",
+ "id": "a08cb231",
"metadata": {},
"outputs": [],
"source": [
@@ -598,7 +598,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "52162335",
+ "id": "2ee565a3",
"metadata": {},
"outputs": [],
"source": [
@@ -611,7 +611,7 @@
},
{
"cell_type": "markdown",
- "id": "135af4ab",
+ "id": "9a9f5228",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; width:95%; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
diff --git a/synced_files/GA_1_7/Student/Discharge/Analysis_discharge.ipynb b/synced_files/GA_1_7/Student/Discharge/Analysis_discharge.ipynb
index 2ded1c6ec8a6745d7aa3690acd885c1f1ae16280..060762e21952ba76e89cf720c59199a1c832a752 100644
--- a/synced_files/GA_1_7/Student/Discharge/Analysis_discharge.ipynb
+++ b/synced_files/GA_1_7/Student/Discharge/Analysis_discharge.ipynb
@@ -384,7 +384,7 @@
},
{
"cell_type": "markdown",
- "id": "6af7f7aa",
+ "id": "7dc6f454",
"metadata": {},
"source": [
"If you run the code in the cell below, you will obtain a scatter plot of both variables. Explore the relationship between both variables and answer the following questions:\n",
@@ -405,7 +405,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "2775d21f",
+ "id": "971ed028",
"metadata": {},
"outputs": [],
"source": [
@@ -421,7 +421,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "dc689f4a",
+ "id": "be96daf6",
"metadata": {},
"outputs": [],
"source": [
diff --git a/synced_files/GA_1_7/Student/Emissions/Analysis_emissions.ipynb b/synced_files/GA_1_7/Student/Emissions/Analysis_emissions.ipynb
index 24200dbe9ea9c30670f5a685fa7f9acbefb5de76..ca883febae59728018b853eaedcc4e418036e717 100644
--- a/synced_files/GA_1_7/Student/Emissions/Analysis_emissions.ipynb
+++ b/synced_files/GA_1_7/Student/Emissions/Analysis_emissions.ipynb
@@ -378,7 +378,7 @@
},
{
"cell_type": "markdown",
- "id": "bb49a9ae",
+ "id": "37696272",
"metadata": {},
"source": [
"If you run the code in the cell below, you will obtain a scatter plot of both variables. Explore the relationship between both variables and answer the following questions:\n",
@@ -399,7 +399,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "06e94020",
+ "id": "26c8bb32",
"metadata": {},
"outputs": [],
"source": [
@@ -415,7 +415,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "20b68004",
+ "id": "3fad295a",
"metadata": {},
"outputs": [],
"source": [
diff --git a/synced_files/GA_1_7/Student/Force/Analysis_force.ipynb b/synced_files/GA_1_7/Student/Force/Analysis_force.ipynb
index 312e63150edaa8686a6d8fc6f45b3bae08860006..69626733241523758c851caea1e290a22de12caa 100644
--- a/synced_files/GA_1_7/Student/Force/Analysis_force.ipynb
+++ b/synced_files/GA_1_7/Student/Force/Analysis_force.ipynb
@@ -384,7 +384,7 @@
},
{
"cell_type": "markdown",
- "id": "4708e1c2",
+ "id": "a55ae969",
"metadata": {},
"source": [
"If you run the code in the cell below, you will obtain a scatter plot of both variables. Explore the relationship between both variables and answer the following questions:\n",
@@ -405,7 +405,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "4687da18",
+ "id": "b81312d7",
"metadata": {},
"outputs": [],
"source": [
@@ -421,7 +421,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "cc6cdabe",
+ "id": "b0439c86",
"metadata": {},
"outputs": [],
"source": [
diff --git a/synced_files/GA_1_7/Unused/Temp/Distribution_Fitting_T.ipynb b/synced_files/GA_1_7/Unused/Temp/Distribution_Fitting_T.ipynb
index 0db7299410def2ee72df2a789355a38ee708fa96..7717142f4c80eaad4b339bbcfb89ce6776068e73 100644
--- a/synced_files/GA_1_7/Unused/Temp/Distribution_Fitting_T.ipynb
+++ b/synced_files/GA_1_7/Unused/Temp/Distribution_Fitting_T.ipynb
@@ -163,7 +163,7 @@
},
{
"cell_type": "markdown",
- "id": "7a98f23d",
+ "id": "0c01eb6e",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
@@ -263,7 +263,7 @@
},
{
"cell_type": "markdown",
- "id": "072da885",
+ "id": "4c5d6753",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
@@ -372,7 +372,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "fce8f81c",
+ "id": "47906ffe",
"metadata": {},
"outputs": [],
"source": [
@@ -434,7 +434,7 @@
},
{
"cell_type": "markdown",
- "id": "b5a9cb50",
+ "id": "4a520071",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
@@ -533,7 +533,7 @@
},
{
"cell_type": "markdown",
- "id": "59dc7afc",
+ "id": "a597d304",
"metadata": {},
"source": [
"<div style=\"background-color:#FAE99E; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px\">\n",
@@ -546,7 +546,7 @@
},
{
"cell_type": "markdown",
- "id": "8542b9a9",
+ "id": "1fa6a986",
"metadata": {},
"source": [
"If you run the code in the cell below, you will obtain a scatter plot of both variables. Explore the relationship between both variables and answer the following questions:\n",
@@ -567,7 +567,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "6061a45e",
+ "id": "82803c17",
"metadata": {},
"outputs": [],
"source": [
diff --git a/synced_files/GA_2_5/Analysis_LP_solution.ipynb b/synced_files/GA_2_5/Analysis_LP_solution.ipynb
index c3afdcca84b744a87396e6eb83a72e8f97940dea..6ebebe92603cfdeb7045f8fe317aeb53db7bebc1 100644
--- a/synced_files/GA_2_5/Analysis_LP_solution.ipynb
+++ b/synced_files/GA_2_5/Analysis_LP_solution.ipynb
@@ -268,7 +268,8 @@
"source": [
"# define parameters\n",
"extension_factor = 1.5 # capacity after extension\n",
- "extension_max_no = 40 # simplified budget limit\n",
+ "extension_max_no = 20 # simplified budget limit\n",
+ "\n",
"timelimit = 300 # seconds\n",
"beta = 2 # explained later\n",
"\n",
@@ -566,7 +567,7 @@
"outputs": [],
"source": [
"# constrain the vehicles to the capacity of the road:\n",
- "c_new = model.addConstrs(link_flow[i, j] <= cap_normal[i,j] + ((cap_extend[i,j]-cap_normal[i,j] ) * link_selected[i,j]) for (i, j) in links)"
+ "# c_new = model.addConstrs(link_flow[i, j] <= cap_normal[i,j] + ((cap_extend[i,j]-cap_normal[i,j] ) * link_selected[i,j]) for (i, j) in links)"
]
},
{
@@ -718,7 +719,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "If you wish to see the velues for the entire network you just need to turn on the labels and run the function again. "
+ "If you wish to see the values for the entire network you just need to turn on the labels and run the function again. "
]
},
{
@@ -761,7 +762,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "mude-week-2-5",
+ "display_name": "Python 3",
"language": "python",
"name": "python3"
},
@@ -775,7 +776,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.12.7"
+ "version": "3.11.5"
}
},
"nbformat": 4,
diff --git a/synced_files/GA_2_5/Analysis_LP_solution.md b/synced_files/GA_2_5/Analysis_LP_solution.md
index f201766b24e2f65fc8e32af9a9e36b0c3a12c080..734fa14e8d6b2538f3f5866eceaab1b0ca3d5569 100644
--- a/synced_files/GA_2_5/Analysis_LP_solution.md
+++ b/synced_files/GA_2_5/Analysis_LP_solution.md
@@ -7,7 +7,7 @@ jupyter:
format_version: '1.3'
jupytext_version: 1.16.4
kernelspec:
- display_name: mude-week-2-5
+ display_name: Python 3
language: python
name: python3
---
@@ -191,7 +191,8 @@ Now that we have the required functions for reading and processing the data, let
```python
# define parameters
extension_factor = 1.5 # capacity after extension
-extension_max_no = 40 # simplified budget limit
+extension_max_no = 20 # simplified budget limit
+
timelimit = 300 # seconds
beta = 2 # explained later
@@ -367,7 +368,7 @@ c_qrt = model.addConstrs(link_flow_sqr[i, j] == link_flow[i, j] * link_flow[i, j
```python
# constrain the vehicles to the capacity of the road:
-c_new = model.addConstrs(link_flow[i, j] <= cap_normal[i,j] + ((cap_extend[i,j]-cap_normal[i,j] ) * link_selected[i,j]) for (i, j) in links)
+# c_new = model.addConstrs(link_flow[i, j] <= cap_normal[i,j] + ((cap_extend[i,j]-cap_normal[i,j] ) * link_selected[i,j]) for (i, j) in links)
```
<!-- #region pycharm={"name": "#%% md\n"} -->
@@ -442,7 +443,7 @@ capacity = {(i, j): cap_normal[i, j] * (1 - links_selected[i, j]) + cap_extend[i
network_visualization_upgraded (G = G, pos=pos, link_flow=link_flows, capacity_new=capacity ,link_select=links_selected, labels='off')
```
-If you wish to see the velues for the entire network you just need to turn on the labels and run the function again.
+If you wish to see the values for the entire network you just need to turn on the labels and run the function again.
```python
# To see flow and capacity for the entire network
diff --git a/synced_files/GA_2_5/Analysis_LP_solution.py b/synced_files/GA_2_5/Analysis_LP_solution.py
index 86cc55862f3a7020da29208966a2cc8a582f0b8b..b8ee1dda06eb89fb6bcfcf8c2595938a0d2dcb61 100644
--- a/synced_files/GA_2_5/Analysis_LP_solution.py
+++ b/synced_files/GA_2_5/Analysis_LP_solution.py
@@ -7,7 +7,7 @@
# format_version: '1.3'
# jupytext_version: 1.16.4
# kernelspec:
-# display_name: mude-week-2-5
+# display_name: Python 3
# language: python
# name: python3
# ---
@@ -184,7 +184,8 @@ plt.show()
# %%
# define parameters
extension_factor = 1.5 # capacity after extension
-extension_max_no = 40 # simplified budget limit
+extension_max_no = 20 # simplified budget limit
+
timelimit = 300 # seconds
beta = 2 # explained later
@@ -347,7 +348,7 @@ c_qrt = model.addConstrs(link_flow_sqr[i, j] == link_flow[i, j] * link_flow[i, j
# %%
# constrain the vehicles to the capacity of the road:
-c_new = model.addConstrs(link_flow[i, j] <= cap_normal[i,j] + ((cap_extend[i,j]-cap_normal[i,j] ) * link_selected[i,j]) for (i, j) in links)
+# c_new = model.addConstrs(link_flow[i, j] <= cap_normal[i,j] + ((cap_extend[i,j]-cap_normal[i,j] ) * link_selected[i,j]) for (i, j) in links)
# %% [markdown] pycharm={"name": "#%% md\n"}
# ## Part 3: Solving the model
@@ -418,7 +419,7 @@ capacity = {(i, j): cap_normal[i, j] * (1 - links_selected[i, j]) + cap_extend[i
network_visualization_upgraded (G = G, pos=pos, link_flow=link_flows, capacity_new=capacity ,link_select=links_selected, labels='off')
# %% [markdown]
-# If you wish to see the velues for the entire network you just need to turn on the labels and run the function again.
+# If you wish to see the values for the entire network you just need to turn on the labels and run the function again.
# %%
# To see flow and capacity for the entire network
diff --git a/synced_files/Week_2_2/old/PA_2_1_solution_sympy.ipynb b/synced_files/Week_2_2/old/PA_2_1_solution_sympy.ipynb
index d62595f5f4e2cdb66f3e2cf0599c8482ffd42de7..6ed5c18e2b239d7bdc7f00d9b57f4ea9ddd699cc 100644
--- a/synced_files/Week_2_2/old/PA_2_1_solution_sympy.ipynb
+++ b/synced_files/Week_2_2/old/PA_2_1_solution_sympy.ipynb
@@ -404,7 +404,7 @@
},
{
"cell_type": "markdown",
- "id": "2d17caa6",
+ "id": "463aeb6b",
"metadata": {},
"source": [
"You could also solve this problem using sympy! What would be the benefit of doing this? Check below how long it will take! You won't need timeit for this one..."
@@ -413,7 +413,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "19e5dbc1",
+ "id": "64714f89",
"metadata": {},
"outputs": [],
"source": [
@@ -423,7 +423,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "71ef0f93",
+ "id": "1179620e",
"metadata": {},
"outputs": [],
"source": [
@@ -433,7 +433,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "1ad5a2ea",
+ "id": "ebaa8811",
"metadata": {},
"outputs": [],
"source": [
@@ -445,7 +445,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "076e8651",
+ "id": "f711decf",
"metadata": {},
"outputs": [],
"source": [
@@ -456,7 +456,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "24a08ec0",
+ "id": "2da1b292",
"metadata": {},
"outputs": [],
"source": [
@@ -465,7 +465,7 @@
},
{
"cell_type": "markdown",
- "id": "70a7e741",
+ "id": "6d323e14",
"metadata": {},
"source": [
"What is the result for the 501th value using float values?"
@@ -474,7 +474,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "9f8c31cb",
+ "id": "ac32792c",
"metadata": {},
"outputs": [],
"source": [
@@ -514,7 +514,7 @@
},
{
"cell_type": "markdown",
- "id": "206167c6",
+ "id": "0d999c47",
"metadata": {},
"source": []
}
diff --git a/synced_files/Week_2_2/old/old_PA10_solution_sympy.ipynb b/synced_files/Week_2_2/old/old_PA10_solution_sympy.ipynb
index 432bc9040f1a8aa05f86cd36f18bc1f6ed495d35..b648134b0835f871d52fb14312d8553ade5478cb 100644
--- a/synced_files/Week_2_2/old/old_PA10_solution_sympy.ipynb
+++ b/synced_files/Week_2_2/old/old_PA10_solution_sympy.ipynb
@@ -404,7 +404,7 @@
},
{
"cell_type": "markdown",
- "id": "cfacddfb",
+ "id": "fda773bf",
"metadata": {},
"source": [
"You could also solve this problem using sympy! What would be the benefit of doing this? Check below how long it will take! You won't need timeit for this one..."
@@ -413,7 +413,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "d77507ca",
+ "id": "a4610868",
"metadata": {},
"outputs": [],
"source": [
@@ -423,7 +423,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "830df2fa",
+ "id": "4d96d48c",
"metadata": {},
"outputs": [],
"source": [
@@ -433,7 +433,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "2a3aa5b0",
+ "id": "b01ca331",
"metadata": {},
"outputs": [],
"source": [
@@ -445,7 +445,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "dbaffbad",
+ "id": "7618eaa8",
"metadata": {},
"outputs": [],
"source": [
@@ -456,7 +456,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "cfcc9078",
+ "id": "3599546a",
"metadata": {},
"outputs": [],
"source": [
@@ -465,7 +465,7 @@
},
{
"cell_type": "markdown",
- "id": "c32e6396",
+ "id": "7d1b5552",
"metadata": {},
"source": [
"What is the result for the 501th value using float values?"
@@ -474,7 +474,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "1ff38cbe",
+ "id": "67c95621",
"metadata": {},
"outputs": [],
"source": [
@@ -514,7 +514,7 @@
},
{
"cell_type": "markdown",
- "id": "acaaf4cd",
+ "id": "60acafbd",
"metadata": {},
"source": []
}