With the help of stacy we planned the scatterplot

she explained what every function controlled explained
using a language I can understand and we compared
the language she used to mine and using her guidance
I was able to troubleshoot on my own. Because she
had worked previous with Chris she was able to add
his perspective to what I was working with and from
there I was able to understand my input even better.
This commit is contained in:
Aminah 2024-10-22 14:12:16 -04:00
parent 98e723db73
commit 1d4422c951
3 changed files with 180 additions and 18 deletions

21
planning.md Normal file
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Planning the scatter plot
Scatterplot X vs Y
- Draw a scatter plot.
- Draw the axes.
- Draw the x-axis ( min: 14, max: 492)
- ticks at every 100 (100,200,300,400,500)
- Draw the line
- Plot the ploints
-...
- Draw the y-axis ( min: -927, max: 3710)
- ...ticks every 1000 ( -900, 0, 1000, 2000,300)
- Draw the line
- Plot the points.
- ...
use blue dots

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# By MWC Contributors
# Uses lots of helper functions in other modules to draw a scatter plot.
from math import floor, ceil, log
from turtle import *
from superturtle.movement import no_delay
import constants
from generate_data import generate_data
from ticks import get_tick_values
from plotting import (
@ -16,31 +19,124 @@ from plotting import (
draw_y_tick,
draw_point,
)
from superturtle.movement import no_delay
import constants
def flyto(x, y):
penup()
goto(x, y)
pendown()
from generate_data import generate_data
from ticks import get_tick_values
from plotting import (
prepare_screen,
draw_point,
)
from transform import (
maximum,
minimum,
bounds,
clamp,
ratio,
bounds,
scale,
get_x_values,
get_y_values,
get_y_values
)
def draw_x_axis(min_val, max_val):
"Draws the x-axis of the scatter plot from min_val to max_val"
penup
flyto(0,0)
goto(constants.PLOT_WIDTH,0)
pendown()
def get_tick_values(low, high):
"""Returns a list of values to use for ticks (labeled points along an axis).
Includes the lowest value, a bunch of "nice" intermediate values, and the highest value.
"""
tick_interval = get_tick_interval(high - low)
first_tick = ceil(low / tick_interval) * tick_interval
return [low] + list(range(first_tick, high, tick_interval)) + [high]
def get_tick_interval(span):
"""Returns a 'nice' interval for ticks across span.
The interval is a power of ten (e.g. 1000, 100, 0.1)
scaled so that there will be between 0 and 10 internal ticks.
"""
log_span = log(span, 10)
return 10 ** floor(log_span)
def draw_y_axis(min_val, max_val):
"Draws the y-axis of the scatterplot from min_val to max_val"
penup()
flyto(0,0)
goto(0,constants.PLOT_HEIGHT)
pendown
def draw_x_tick(position, label):
"Draws a tick mark on the x-axis at the specified position"
flyto(position, 0)
goto(position, -constants.TICK_LENGTH)
flyto(position, -constants.TICK_LENGTH - 10)
write(label, align='center')
def draw_y_tick(position, label):
"Draws a tick mark on the y-axis at the specified position"
flyto(0, position)
goto(-constants.TICK_LENGTH, position)
write(label, align='right')
def get_tick_values(low, high):
"""Returns a list of values to use for ticks (labeled points along an axis).
Includes the lowest value, a bunch of "nice" intermediate values, and the highest value.
"""
tick_interval = get_tick_interval(high - low)
first_tick = ceil(low / tick_interval) * tick_interval
return [low] + list(range(first_tick, high, tick_interval)) + [high]
def draw_scatterplot(data, size=5, color="black"):
"Draws a scatter plot, showing the data"
prepare_screen()
draw_axes(data)
draw_points(data, color, size)
draw_points(data, size, color)
def draw_axes(data):
"Draws the scatter plot's axes."
x_values = get_x_values(data)
y_values = get_y_values(data)
xmin, xmax = bounds(x_values)
ymin, ymax = bounds(y_values)
draw_x_axis(xmin, xmax)
draw_y_axis(ymin, ymax)
def draw_points(data, color, size):
def draw_points(x,y, color="blue", size=5):
"Draws the scatter plot's points."
x_values = get_x_values(data)
y_values = get_y_values(data)
xmin, xmax = bounds(x_values)
ymin, ymax = bounds(y_values)
for point in data:
x, y = point
screen_x = scale(x, xmin, xmax, 0, constants.PLOT_WIDTH)
screen_y = scale(y, ymin, ymax, 0, constants.PLOT_HEIGHT)
draw_point(screen_x, screen_y, color, size)
with no_delay():
data = generate_data(50, 10, 500, 5, 400, 1000)
draw_scatterplot(data, size=5, color="blue")
hideturtle()
done()

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@ -6,38 +6,83 @@
def maximum(data):
"Returns the largest number in data"
raise NotImplementedError
highest = None
for number in data:
if highest is None:
highest = number
if number > highest:
highest = number
return highest
def minimum(data):
"Returns the smallest number in data"
raise NotImplementedError
lowest = None
for number in data:
if lowest is None:
lowest = number
if number < lowest:
lowest = number
return lowest
def bounds(data):
"Returns a list of the smallest and largest numbers in data"
raise NotImplementedError
return [minimum(data), maximum(data)]
def clamp(value, low, high):
"""Clamps a value to a range from low to high.
Returns value if it is between low and high.
If value is lower than low, returns low. If value is higher than high, returns high.
"""
raise NotImplementedError
if low < value and value < high:
return value
if value <= low:
return low
if value >= high:
return high
def ratio(value, start, end):
"""Returns a number from 0.0 to 1.0, representing how far along value is from start to end.
The return value is clamped to [0, 1], so even if value is lower than start, the return
value will not be lower than 0.0.
"""
raise NotImplementedError
r= (value - start)/ (end-start)
return clamp (r, 0,1)
def scale(value, domain_min, domain_max, range_min, range_max):
"Given a value within a domain, returns the scaled equivalent within range."
raise NotImplementedError
"Given a value within a domain, returns the scaled equivalent within range."
return (range_min + ((ratio(value,domain_min,domain_max)) * (range_max - range_min)))
def get_x_values(points):
"Returns the first value for each point in points."
raise NotImplementedError
x_values = []
for x,y in points:
x_values.append(x)
return x_values
def get_y_values(points):
"Returns the second value for each point in points."
raise NotImplementedError
y_values = []
for x,y in points:
y_values.append(y)
return y_values