Exercise Generate a log-log plot of your period T vs. dynamic mass ma. This is the same plot that you drew on the log-log graphing paper from your materials pack. Perform these steps: 1. Define lists or numpy arrays that contain your experimental data. For example, md= [0.10, 0,15, 0.20] defines a list of dynamic masses 0.1, 0.15 and 0.20 kg, and T = [0.75, 0.83, 0.91] defines a list of periods (in seconds). 2. Generate a log-log plot of T vs. ma that shows your data as points (not lines!) using plt.loglog() with the 'o' option. The dynamic mass should be on the horizontal (x) axis. 3. Add grid lines for both the "major" and "minor" ticks, and both axes. Look up the documentation of plt.grid () to see how this is done. Remember that you can get the documentation for any command by running it in a cell of its own and appending a question mark, e.g. plt.grid?. 4. The axis tick labels will likely show up in scientific notation (e.g. 6 x 10-2). For our values (mostly in the 0.1...1 kg range), this is undesirable. Add a line plt.rcParams ['axes. formatter.min_exponent'] = 2 to your code to fix this. This command tells matplotlib to print all numbers between 10-2 and 102 in normal notation. 5. Don't forget to label the x- and y-axes. Look up your code from the "Projectile Motion" lab if you are unsure how to do this. In [] #define your arrays here # # Dynamic masses #md =
Exercise Generate a log-log plot of your period T vs. dynamic mass ma. This is the same plot that you drew on the log-log graphing paper from your materials pack. Perform these steps: 1. Define lists or numpy arrays that contain your experimental data. For example, md= [0.10, 0,15, 0.20] defines a list of dynamic masses 0.1, 0.15 and 0.20 kg, and T = [0.75, 0.83, 0.91] defines a list of periods (in seconds). 2. Generate a log-log plot of T vs. ma that shows your data as points (not lines!) using plt.loglog() with the 'o' option. The dynamic mass should be on the horizontal (x) axis. 3. Add grid lines for both the "major" and "minor" ticks, and both axes. Look up the documentation of plt.grid () to see how this is done. Remember that you can get the documentation for any command by running it in a cell of its own and appending a question mark, e.g. plt.grid?. 4. The axis tick labels will likely show up in scientific notation (e.g. 6 x 10-2). For our values (mostly in the 0.1...1 kg range), this is undesirable. Add a line plt.rcParams ['axes. formatter.min_exponent'] = 2 to your code to fix this. This command tells matplotlib to print all numbers between 10-2 and 102 in normal notation. 5. Don't forget to label the x- and y-axes. Look up your code from the "Projectile Motion" lab if you are unsure how to do this. In [] #define your arrays here # # Dynamic masses #md =
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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![Exercise
Generate a log-log plot of your period T vs. dynamic mass ma. This is the same plot that you drew on the log-log graphing paper from your materials pack.
Perform these steps:
1. Define lists or numpy arrays that contain your experimental data. For example, md = [0.10, 0,15, 0.20] defines a list of dynamic masses 0.1,
0.15 and 0.20 kg, and T = [0.75, 0.83, 0.91] defines a list of periods (in seconds).
2. Generate a log-log plot of T vs. ma that shows your data as points (not lines!) using plt.loglog() with the 'o' option. The dynamic mass
should be on the horizontal (x) axis.
3. Add grid lines for both the "major" and "minor" ticks, and both axes. Look up the documentation of plt.grid() to see how this is done.
Remember that you can get the documentation for any command by running it in a cell of its own and appending a question mark, e.g. plt.grid?.
4. The axis tick labels will likely show up in scientific notation (e.g. 6 × 10−²). For our values (mostly in the 0.1...1 kg range), this is undesirable. Add a line
plt.rcParams ['axes. formatter.min_exponent'] = 2 to your code to fix this. This command tells matplotlib to print all numbers between
10-² and 10² in normal notation.
5. Don't forget to label the x- and y-axes. Look up your code from the "Projectile Motion" lab if you are unsure how to do this.
In [ ]: # define your arrays here
#
# Dynamic masses
#md =
# Periods
# T =
# YOUR CODE HERE
raise NotImplementedError()](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb7f470a0-93f2-43bf-9ed3-2f125d19f075%2Fc948103b-fe73-47de-a27a-8acc8cb1ee14%2Fiunns9_processed.png&w=3840&q=75)
Transcribed Image Text:Exercise
Generate a log-log plot of your period T vs. dynamic mass ma. This is the same plot that you drew on the log-log graphing paper from your materials pack.
Perform these steps:
1. Define lists or numpy arrays that contain your experimental data. For example, md = [0.10, 0,15, 0.20] defines a list of dynamic masses 0.1,
0.15 and 0.20 kg, and T = [0.75, 0.83, 0.91] defines a list of periods (in seconds).
2. Generate a log-log plot of T vs. ma that shows your data as points (not lines!) using plt.loglog() with the 'o' option. The dynamic mass
should be on the horizontal (x) axis.
3. Add grid lines for both the "major" and "minor" ticks, and both axes. Look up the documentation of plt.grid() to see how this is done.
Remember that you can get the documentation for any command by running it in a cell of its own and appending a question mark, e.g. plt.grid?.
4. The axis tick labels will likely show up in scientific notation (e.g. 6 × 10−²). For our values (mostly in the 0.1...1 kg range), this is undesirable. Add a line
plt.rcParams ['axes. formatter.min_exponent'] = 2 to your code to fix this. This command tells matplotlib to print all numbers between
10-² and 10² in normal notation.
5. Don't forget to label the x- and y-axes. Look up your code from the "Projectile Motion" lab if you are unsure how to do this.
In [ ]: # define your arrays here
#
# Dynamic masses
#md =
# Periods
# T =
# YOUR CODE HERE
raise NotImplementedError()
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