examples from MATLAB Expo 2022 presentation

Author: AlDanial

matlab_expo_2022/bridge_numpy_index.py

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+# bridge_numpy_index.py
+def ind(z, row, col):
+    return z[int(row)-1, int(col)-1]
+def nind(z, *i):
+    int_minus_1 = tuple([int(_) - 1 for _ in i])
+    return z[int_minus_1]

matlab_expo_2022/demo_openpyxl.m

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+% Al Danial, David Garrison
+Im = @py.importlib.import_module;
+OP = Im("openpyxl");
+styles = Im("openpyxl.styles");
+Font = styles.Font;
+Alignment = styles.Alignment;
+PatternFill = styles.PatternFill;
+book = OP.Workbook();
+sheet = book.active;
+sheet.title = "Pets by weight";
+
+% font styles, background color
+ft_title = Font(...
+    pyargs("name","Arial", ...
+    "size",int64(14),"bold",py.True));
+ft_red = Font(color="00FF0000");
+ft_italics = Font(bold=py.True,...
+                  italic=py.True);
+bg_green = PatternFill( ...
+    fgColor="C5FD2F", fill_type="solid");
+
+sheet.merge_cells("B2:D3");
+B2 = sheet.cell(2,2);
+B2.value = "My Pets";
+B2.font = ft_title;
+B2.alignment = Alignment(...
+ horizontal="center", vertical="center");
+
+% column headings
+category={"Name","Animal","weight [kg]"};
+row = int64(4); col = int64(1);
+for i = 1:length(category)
+  nextCell = sheet.cell(row, col+i);
+  nextCell.value = category{i};
+  nextCell.fill = bg_green;
+end
+
+pets = {{"Nutmeg", "Rabbit", 2.5},...
+        {"Annabel", "Dog", 4.3},  ...
+        {"Sunny", "Bird", 0.02},  ...
+        {"Harley", "Dog", 17.1},  ...
+        {"Toby", "Dog", 24.0},    ...
+        {"Mr Socks", "Cat", 3.9}};
+
+for P = pets
+  row = row + 1;
+  for j = 1:length(category)
+    nextCell = cell(sheet,row,col+j);
+    nextCell.value = P{1}{j};
+    if j == 3 && P{1}{j} < 0.1
+      nextCell = cell(sheet,row,col+j);
+      nextCell.font = ft_red;
+    end
+  end
+end
+
+% equation to sum all weights
+eqn = sprintf("=SUM(D4:D%d)", row);
+nextCell = sheet.cell(row+1, 4);
+nextCell.value = eqn;
+
+nextCell = sheet.cell(row+1, 2);
+nextCell.value = "Total weight:";
+nextCell.font = ft_italics;
+
+book.save("pets.xlsx")

matlab_expo_2022/demo_openpyxl.py

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+#!/usr/bin/env python3
+
+import openpyxl as OP
+import openpyxl.styles as styles
+Font = styles.Font
+Alignment = styles.Alignment
+PatternFill = styles.PatternFill
+book = OP.Workbook()
+sheet = book.active
+sheet.title = "Pets by weight"
+
+# font styles, background color
+ft_title = Font(name="Arial",
+                size=14,
+                bold=True)
+ft_red = Font(color="00FF0000")
+ft_italics = Font(bold=True,
+                  italic=True)
+bg_green = PatternFill(
+    fgColor="C5FD2F",fill_type="solid")
+
+sheet.merge_cells("B2:D3")
+B2 = sheet.cell(2,2)
+B2.value = "My Pets"
+B2.font = ft_title
+B2.alignment = Alignment(
+  horizontal="center",vertical="center")
+
+# column headings
+category=["Name","Animal","weight [kg]"]
+row, col = 4, 2
+for i in range(len(category)):
+  nextCell = sheet.cell(row, col+i)
+  nextCell.value = category[i]
+  nextCell.fill = bg_green
+
+
+pets = [["Nutmeg", "Rabbit", 2.5],
+        ["Annabel", "Dog", 4.3],
+        ["Sunny", "Bird", 0.02],
+        ["Harley", "Dog", 17.1],
+        ["Toby", "Dog", 24.0],
+        ["Mr Socks", "Cat", 3.9]]
+
+for P in pets:
+  row += 1
+  for j in range(len(category)):
+    cell = sheet.cell(row,col+j,
+                      P[j])
+    if j == 2 and P[j] < 0.1:
+      nextCell = sheet.cell(row,col+j)
+      nextCell.font = ft_red
+
+
+
+
+# equation to sum all weights
+eqn = f"=SUM(D4:{row+1})"
+nextCell = sheet.cell(row+1, 4)
+nextCell.value = eqn
+
+nextCell = sheet.cell(row+1, 2)
+nextCell.value = "Total weight:"
+nextCell.font = ft_italics;
+
+book.save("pets.xlsx")

matlab_expo_2022/imp.m

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+function [module] = imp(module_name)
+    % Abbreviaiton for py.importlib.import_module(module_name)
+    module = py.importlib.import_module(module_name)
+end

matlab_expo_2022/optim_config.yaml

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+# optim_config.yaml
+max_iter : 1000
+newmark :
+  alpha : 0.25
+  beta : 0.5 
+input_dir : "/xfer/sim_data/2022/05/17"
+tune_coeff : [1.2e-4, -3.25, 58.2]

matlab_expo_2022/pets.xlsx

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+# txy.py
+import numpy as np
+from datetime import datetime
+def F():
+    return { 't' : datetime.now(),
+             'x' : np.arange(12).reshape(2,6),
+             'y' : ['a list', 'with strings']}