generated from mwc/lab_scatter
b3603aeeb6
I think this lab was challenging, and I'm not sure if I did it the way we were supposed to, because I had to search how to use multiple lists the way I wanted to, which was using zip. I tried adding the two lists but it didn't seem like that would get my what I wanted, and also it didn't work. I got stuck on getting the points drawn properly for a while; first, I got a single point, then I was able to get a vertical line of points, and then I got identical vertical lines of points at each of the x-values (when I had the y for loop nested inside of the x for loop). I think the top-down vs. bottom-up approaches aren't really separate, but you have to go back and forth between them because the top-down approach helps to identify some of the pieces you need to work bottom- up from. I felt like at the beginning, I thought the program would use some of the stuff we did in the pipes lab, so that informed my top-down plan. Another program I thought about writing during this lab was one that could take a csv file and identify different common elements and group them and display them, but that has more to do with other tasks I was doing than this lab probably, but I still think that some of the things here probably helped me think about breaking that down into smaller pieces.
82 lines
2.4 KiB
Python
82 lines
2.4 KiB
Python
# scatterplot.py
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# ------------
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# By MWC Contributors
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# Uses lots of helper functions in other modules to draw a scatter plot.
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from turtle import *
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from superturtlescat import *
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import constants
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from generate_data import generate_data
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from ticks import get_tick_values
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from plotting import (
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prepare_screen,
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draw_x_axis,
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draw_y_axis,
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draw_x_tick,
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draw_y_tick,
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draw_point,
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)
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from transform import (
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maximum,
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minimum,
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bounds,
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clamp,
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ratio,
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scale,
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get_x_values,
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get_y_values,
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)
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def draw_scatterplot(data, size=5, color="black"):
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"Draws a scatter plot, showing the data"
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prepare_screen()
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draw_axes(data)
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draw_points(data, color, size)
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def draw_axes(data):
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"Draws the scatter plot's axes."
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draw_x_axis()
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x_values = get_x_values(data)
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xmin, xmax = bounds(x_values)
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ticks = get_tick_values(xmin, xmax)
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for tick in ticks:
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screen_x_position = scale(tick, xmin, xmax, 0, constants.PLOT_WIDTH)
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draw_x_tick(screen_x_position, tick)
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draw_y_axis()
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y_values = get_y_values(data)
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ymin, ymax = bounds(y_values)
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ticks = get_tick_values(ymin, ymax)
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for tick in ticks:
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screen_y_position = scale(tick, ymin, ymax, 0, constants.PLOT_WIDTH)
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draw_y_tick(screen_y_position, tick)
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def draw_points(data, color, size):
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"Draws the scatter plot's points."
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#For each point in the data:
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#Get the x and y value from the point.
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#Find the x-bounds and the y-bounds of the data. You'll need these for scaling.
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x_values = get_x_values(data)
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xmin, xmax = bounds(x_values)
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y_values = get_y_values(data)
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ymin, ymax = bounds(y_values)
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#Find the scaled x-position for the point.
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listx = []
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for x_value in x_values:
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scaled_x = scale(x_value, xmin, xmax, 0, constants.PLOT_WIDTH)
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listx.append(scaled_x)
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#Find the scaled y-position for the point.
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listy = []
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for y_value in y_values:
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scaled_y = scale(y_value, ymin, ymax, 0, constants.PLOT_WIDTH)
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listy.append(scaled_y)
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#for something in somethings:
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for scaled_x, scaled_y in zip(listx, listy):
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draw_point(scaled_x, scaled_y, color, size)
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#Use draw_point(scaled_x, scaled_y, color, size) to draw the point.
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with no_delay():
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data = generate_data(50, 10, 500, 5, 400, 1000)
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draw_scatterplot(data, size=5, color="blue")
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hideturtle()
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done() |