From f684019447f9ced70a7ca5033e0772d60ebff7ea Mon Sep 17 00:00:00 2001
From: Duncan Holmes <dholmes4@huskers.unl.edu>
Date: Sat, 12 Apr 2025 20:05:06 -0500
Subject: [PATCH] still need to add print statments if you want to know all of
what's going on but i'd rather like... not do that so i'm not going to
---
example_graph_code.py | 166 +++++++++++++++++++++++++++++++++++++++---
1 file changed, 157 insertions(+), 9 deletions(-)
diff --git a/example_graph_code.py b/example_graph_code.py
index c01d003..f086f47 100644
--- a/example_graph_code.py
+++ b/example_graph_code.py
@@ -6,6 +6,7 @@ from kivy.lang import Builder
import matplotlib.pyplot as plt
from matplotlib.backends.backend_agg import FigureCanvasAgg
+import matplotlib.dates as mdates # Import for date formatting
import pandas as pd
from io import BytesIO
@@ -15,50 +16,197 @@ from PIL import Image as PILImage
class GraphScreen(Screen):
def __init__(self, **kwargs):
+ print(f"\t\t i'm in the constructor now")
+ print(f"\t\t i'm gonna call Screen's contructor because that's how it is....")
super().__init__(**kwargs)
+ print(f"\t\t now i'm gonna set graph_texture, which is a variable, to None. Don't worry—it gets set later.")
self.graph_texture = None
+ print(f"\t\t that's the end of the constructor hehe")
+ print('\n\n')
def on_enter(self):
- # Sample CoinGecko-style data
- data = {
- "prices": [
+ print(f"\t\t\t we're in on_enter now . i think this is a 'callback function that gets called when the screen is entered'")
+ print(f"\t\t\t ok well if you say so mr. autocomplete line bot :- / \n")
+
+ # Sample CoinGecko style data
+ data = \
+ {
+ "prices":
+ [
[1711843200000, 69702.31],
[1711929600000, 71246.95],
[1711983682000, 68887.75]
]
}
+ print(f"\t\t\t data: {data}")
+ # Create DataFrame
+ """
+ this is screwy
+ DataFrame object
+ use the parameter collums & the strings... as the labels for said collums
+ use the data dictionary's prices's values as a parameter for inputs into a table
+
+ the visualized version of this is
+ timestamp price
+ 1711843200000 69702.31
+ 1711929600000 71246.95
+ 1711983682000 68887.75
+
+ """
df = pd.DataFrame(data["prices"], columns=["timestamp", "price"])
+ print(f"\t\t\t df: {df}")
+
+ print(f"\t\t\t converting timestamp to datetime...")
+
+ """
+ ok now that we have that weird ahh python table object working
+ let's convert the numerical bull-pucky timestamps to datetime objects
+ from
+ ##### number number blah blah ERRUUGHGHGHH -------> yyyy/mm/dd/hh/mm/ss
+
+ the way it does this is weird but cool
+ 1. call the values inside the timestamp collum like a dicationry does
+ 2. set those values .... by using pd which is like a dictionary? i doubt it.
+ use pd which is a lower level function in this context ... and it's method
+ which converts the values of "timestamp" into datetime objects
+ WHICH IS BADASS
+ 3. the unit="ms" is used becuase the CoinGecko goes down to the milasecond
+ """
+ # convert timestamp to datetime
df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms")
+ print(f"\t\t\t df: {df}")
- # Plot
+ """
+ big boy method useage
+
+ fig .... a figure object 'should be seen as the entire graph'
+ apperntly you can save it as a png or jpeg
+ fig.savefig("my_plot.png")
+ or 'use it in kivy like you're doing right now'
+
+ ax ... axes
+ ax stand for axes
+ ax.plot(x, y) ?????
+ "this is the actual area where you graph is drawn"
+ like the little commie block the graph actually lives in
+
+ ax.plot(x, y) # Plot lines
+ ax.set_title(...) # Add a title
+ ax.set_xlabel(...) # X-axis label
+ ax.set_ylabel(...) # Y-axis label
+ ax.legend(...) # Add a legend
+
+ plt is a static object that allows for static method calling. i guess
+ .subplots() returns a figure and an axis object : - )
+ """
+ # Create Matplotlib Figure and Axis
fig, ax = plt.subplots()
+ print(f'\t\t\t ax: {ax}')
+ print(f'\t\t\t fig: {fig}')
+
+ """
+ ax.plot(x, y) # Plot lines
+ ax.set_title(...) # Add a title
+ ax.set_xlabel(...) # X-axis label
+ ax.set_ylabel(...) # Y-axis label
+ ax.legend(...) # Add a legend
+ """
+ print(f"\t\t\t whole lotta ax methods i'm boutta call")
+ # Plot the data
ax.plot(df["timestamp"], df["price"], label="Price", color="green")
+ print(f"\t\t\tgave ax plot points. like (x,y) but with dates & prices instead of numbers")
+
ax.set_title("Price Over Time")
+ print("\t\t\tgave ax a title")
+
ax.set_xlabel("Date")
+ print("\t\t\tgave ax a label for it's x axis")
+
ax.set_ylabel("Price (USD)")
+ print("\t\t\tgave ax a label for it's y axis")
+
ax.legend()
+ print("\t\t\tgave ax a legend. that means the axis-es are labeled")
+
+ print(f'\t\t\t ax: {ax}')
+
+ # **Key Change:**
+ # Manually set the x-axis tick positions to the exact datetime values in the DataFrame.
+ # it's a method. don't got nothin else to tell ye
+ print(f"\t\t\t i'm gonna make sure only the dates put in the data, show up on the graph ok?")
+ ax.set_xticks(df["timestamp"])
+ print(f"\t\t\t ax.get_xticks = {ax.get_xticks()}")
+
+ # Format the ticks to display in "YYYY-MM-DD" format.
+ print(f"\t\t\t i'm gonna format the numeric gobbelty gook that is the timestamps into a better yyyy_mm_dd format")
+ ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
+ print(f"\t\t\t ax.xaxis.get_major_formatter() = {ax.xaxis.get_major_formatter()}")
- # Convert plot to Kivy texture
+ # Note: Using manual ticks makes auto-formatting less necessary.
+ # fig.autofmt_xdate() # This line is optional now. BECAUSE IT AUTO FORMATS. I'M KEEPING IT IN JUST IN CASE.... world explodes idk
+
+ """
+ 1. makes a FigureCanvasAgg object using fig... a figure object only
+ wow
+ 2. canvas.draw = .... draws the figure onto the canvas
+ uhhh ok thanks autocomplete
+ 3. buf = BytesIO() = ... creates a buffer object
+ ?
+ 4. fig.savefig(buf, format='png') = ... saves the figure to the buffer object
+ 5. buf.seek(0) = ... seeks the buffer object to the beginning
+ """
+ # Convert the plot to a Kivy texture
canvas = FigureCanvasAgg(fig)
canvas.draw()
buf = BytesIO()
fig.savefig(buf, format='png')
buf.seek(0)
+ """
+ 1. pil_image = PILImage.open(buf) = ... opens the buffer object as an image
+ 2. pil_image = pil_image.transpose(PILImage.FLIP_TOP_BOTTOM) = ... flips the image vertically
+ i guess it comes not vertically out the gate? why?
+ if you change FLIP_TOP_BOTTOM to FLIP_LEFT_RIGHT it flips it horizontally
+ and if you change FLIP_TOP_BOTTOM to DEFAULT_STRATEGY it assumely keeps it as it is orginally
+ so that's why the orginal command is there
+ 3. tex = Texture.create(size=pil_image.size, colorfmt='rgba') = ... creates a texture object
+ a texture object is a kivy image widget's property
+ so like
+
+ Image:
+ id: image_id
+ texture: tex
+ """
+ # Flip the image vertically to correct the orientation for Kivy
pil_image = PILImage.open(buf).transpose(PILImage.FLIP_TOP_BOTTOM)
tex = Texture.create(size=pil_image.size, colorfmt='rgba')
tex.blit_buffer(pil_image.convert('RGBA').tobytes(), colorfmt='rgba', bufferfmt='ubyte')
- tex.flip_vertical()
- # Access the image widget via ids correctly
+ #if you had this your graph would be flipped veritcally
+ #the.... uhm. the birdy that told me to how to write this code put this here and it made the graph look funny
+ #i commented it out. and it worked.
+ #i found that very funny.
+ #tex.flip_vertical()
+
+ # Save the generated texture
self.graph_texture = tex
class MyApp(App):
def build(self):
- return Builder.load_file('example_graph_code.kv')
+ print("\t i'm pretty sure this is MyApp's run function")
+ print("\t i'm gonna use Builder's static method load_file() to load your file...")
+ kivy_file_directory = 'example_graph_code.kv'
+ print(f"\t {kivy_file_directory}")
+ return Builder.load_file(kivy_file_directory)
+ print(f"\t i'm done with the build function ;- )")
+
if __name__ == "__main__":
+ print('you pressed the start button :-) ')
+ print("i'm making a MyApp object called app")
app = MyApp()
- app.run()
\ No newline at end of file
+ print("i'm making app do the run function")
+ app.run()
+ print("program's done :-(")
--
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