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nfitternfitter
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Merge pull request OSUrobotics#2 from sabbekosu/winter26-changes
W26 Typo Fixes
2 parents f623058 + face829 commit a5ca6a8

17 files changed

Lines changed: 42 additions & 48 deletions

‎Week_0_python/a_tutorial_strings_format.ipynb‎

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"\n",
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"The curly brackets tell the format function to \"fill in\" the variables that are passed in. Python provides a much nicer way of doing this with **f(\"\")** which we'll show below. It's useful to see the more traditional, C++ or Matlab version first.\n",
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"TODO edits to try/do\n",
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" - add in a 3rd variable to pring\n",
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" - add in a 3rd variable to print\n",
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" - print with 5 decimal places\n",
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" - print out the same variable twice in one line"
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]

‎Week_0_python/f_tutorial_dictionary.ipynb‎

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"outputs": [],
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"source": [
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"# Make up some data\n",
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"my_names = [\"Amazon\", \"Google\", \"Meta\", \"Tiktoc\"]\n",
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"my_names = [\"Amazon\", \"Google\", \"Meta\", \"Tiktok\"]\n",
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"my_sales_figs = [1.1, 2.2, 1.3, 0.1] # made up numbers\n",
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"my_number_employees = [100, 20, 10, 1]"
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]

‎Week_1_data_structures/HW_1_numpy_and_plotting.ipynb‎

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"def rms(in_data):\n",
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" \"\"\" Calculate the root mean square of each row in in_data.\n",
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" @param in_data - A 2-dimensional numpy array\n",
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" @return A 1x number of columns in in_data numpy array containing the RMS of each row in the array.\n",
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" @return A nx1 numpy array containing the RMS of each row in in_data.\n",
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" \"\"\"\n",
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" # TODO: Fill in this function.\n",
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" # Hint: Use numpy functions to operate on the entire array at once rather than\n",

‎Week_1_data_structures/Lab_1_data_analysis.ipynb‎

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"\n",
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"# TODO Fix this to copy the right hand accelerometer data into right_hand_accelerometer_data\n",
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"# On the left-hand side, the columns should start at zero and end at 3 (n_dims_for_right_hand_accelerometer_data)\n",
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"# On the right-hand side, the columns should start at index_wrist_torque_offset and end at index_wrist_torque_offset + 3 (n_dims_for_right_hand_accelerometer_data)\n",
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"# On the right-hand side, the columns should start at index_right_hand_accelerometer_offset and end at index_right_hand_accelerometer_offset + 3 (n_dims_for_right_hand_accelerometer_data)\n",
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"\n",
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"right_hand_accelerometer_data[:, :] = clap_data[:, :]\n",
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"\n",

‎Week_1_data_structures/Lecture_data_structures.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# From Intro_assignment.ipynb, dictionary probelm\n",
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"# From Intro_assignment.ipynb, dictionary problem\n",
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"# Creating one variable for each value you want to store\n",
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"\n",
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"name = \"Me\"\n",

‎Week_1_data_structures/b_practice_numpy.ipynb‎

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"source": [
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"## 2D matrix part 2\n",
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"\n",
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"TODO Now do the same thing again, but add padding by making the first column -1 and the last column 2. I.e, the new numpy array should be 2 x (size of linspace array + 2)\n",
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"\n",
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"my_new_padded_matrix = None\n",
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"\n",
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"print(f\"My matrix shape: {my_new_padded_matrix.shape}, should be (2, size of linspace array + 2)\")\n",
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"print(f\"First column is: {my_new_padded_matrix[:, 0]}, should be [-1. -1.]\")\n",
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"print(f\"Last column is: {my_new_padded_matrix[:, -1]}, should be [2. 2.]\")"
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"TODO Now do the same thing again, but add padding by making the first column -1 and the last column 2. I.e, the new numpy array should be 2 x (size of linspace array + 2)"
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]
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},
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{

‎Week_2_functions/Lab_2_functions.ipynb‎

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"# the last columns of all_data are set to the correct motion ids,\n",
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"# then check that the actual data in all_data is correct\n",
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"# Reminder that you can look in the files (eg, S01F01.csv) to see what the values should be\n",
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"# Reonder 2: If you have print statements in your functions that will also cause the autograder to fail"
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"# Reminder 2: If you have print statements in your functions that will also cause the autograder to fail"
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]
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},
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{
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"outputs": [],
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"source": [
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"# Boolean filters for getting rows for a specific motion type. \n",
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"# Motion type should extract the last columnb in the data\n",
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"# Motion type should extract the last column in the data\n",
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"# uncomment and get the last column\n",
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"# motion_type = all_data[:, ...]\n",
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"\n",

‎Week_2_functions/b_practice_functions.ipynb‎

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"a = 3\n",
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"b = 7\n",
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"my_ret = add_two_numbers(a_number=a, b_number=b)\n",
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"assert my_ret == a * b\n"
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"assert my_ret == a + b\n"
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]
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}
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],

‎Week_4_fitting/HW_2_system_analysis.ipynb‎

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},
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"outputs": [],
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"source": [
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"\n",
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"\n",
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"# TODO: Add importing argrelmax and argrelmin to your imports. They are in scipy.signal\n",
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" \n",
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"# TODO: Write find_peak_or_valley function\n",
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"# This function takes in data and whether or not to search for the peak or the valley. It returns an index or None if no peak/valley\n",
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"# This function takes in data and whether or not to search for the peak or the valley. \n",
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"# It returns an index or empty numpy array if no peak/valley\n",
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"\n",
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"# If b_peak_or_valley is True, return the peak\n",
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"def find_peak_or_valley(data, b_peak_or_valley):\n",
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" pass\n",
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"outputs": [],
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"source": [
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"# TODO write a function that takes in the starting conditions (x and the derivative of x), along with the parameters\n",
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"# you need to calculate the derivative (zeta, k, and m)\n",
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"# you need to calculate the derivative (c, k, and m)\n",
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"# Call integrate.odeint with the function you created above, plus your parameters, \n",
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"# and return the result of that function, along with the t values\n",
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"# You might also want pass in the step for the t and the total amount of time to integrate over as parameters\n",

‎Week_5_systems/Lecture_functions_II.ipynb‎

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"source": [
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"# Functions, part 2, parameter passing (review)\n",
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"\n",
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"- Call using paramter name\n",
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"- Call using parameter name\n",
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"- Default parameters"
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]
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},

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