#Pyplot
Stacking rasters into multi-band raster causes value distribution issues
My goal is to stack two seperate single band rasters into a multi-band raster using rasterio. Initially, I seperately check the distribution of each raster. Here are the steps: import numpy as np import rasterio from rasterio.plot import show_hist, show from matplotlib import pyplot # List of input file paths file_list = [raster_1, raster_2] new_names = ['b1', 'b2'] # Define the consistent NODATA_VALUE based on observations from previous cells NODATA_VALUE = -99999.0 with rasterio.open(file_list[0]) as src0: meta = src0.meta # Update band count and set the consistent NODATA_VALUE meta.update(count=len(file_list), nodata=NODATA_VALUE) raster_stack = '/filpath/raster_stack.tif' with rasterio.open(raster_stack, 'w', **meta) as dst: for i, file in enumerate(file_list, start=1): with rasterio.open(file) as src: data = src.read(1) # Convert NaN values to the consistent NODATA_VALUE data = np.nan_to_num(data, nan=NODATA_VALUE) dst.write(data, i) dst.set_band_description(i, new_names[i-1]) # Rename each band But then when I try to plot each and in the new raster stack, I do not get the expected distribution when I do this: fig, (axdsm, axhist_1, axchm, axhist_2) = pyplot.subplots(1,4, figsize=(16,4)) # Open the stacked raster once and pass the dataset object to show with rasterio.open(raster_stack) as src_stack: # Use masked=True to automatically hide NoData values in plots band1 = src_stack.read(1, masked=True) band2 = src_stack.read(2, masked=True) show(band1, ax=axdsm, cmap='viridis', title='DSM channel') show_hist(band1, bins=50, ax=axhist_1, title="DSM Hist (Clean)") show(band2, ax=axchm, cmap='magma', title='CHM channel') show_hist(band2, bins=50, ax=axhist_2, title="CHM Hist (Clean)") pyplot.show() Here is the before and after for one of the rasters then after when I plot the band.
gis.stackexchange.com
September 16, 2026 at 8:59 PM
matplotlib の animation 完全に理解した

import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation

def main() -> None:
rng = np.random.default_rng()
u = rng.random((3, 30, 30))

fig = plt […]

[Original post on misskey.io]
August 31, 2026 at 1:56 PM
here it is, after two hours of pretending i understand how pyplot works: the AFINN Post Vibe Check Experiment Experience. check out that nasty dip between mid-may and late june. what the hell happened there? maybe i swore a lot
July 25, 2026 at 3:09 PM
Count Binface somehow isn’t a pyplot setting
NEW - Greens won’t stand in Clacton.

So it is Nigel Farage versus Count Binface.
July 7, 2026 at 10:14 PM
This illustration of the daily sea-surface temperatures since 1981 most likely exists in a form or another. I am trying to improve it and use a colour scheme that most people will see similarly. Still improvements are needed on the colour variation.
#climatecrisis #python #SST #pyplot
June 30, 2026 at 3:02 PM
pyplot has a seemingly infinite number of options, and all I want is a nice graph
June 28, 2026 at 12:51 PM
#machinelearning #epsilongreedy #qlearning #artificialintelligence #pyplot #numpy #python
Some write-up on emergent decaying epsilon-greedy Q-learning in Python.
Conclusion in thread:
CODE #3: EMERGENT DECAYING EPSILON-GREEDY Q-LEARNING (PYTHON)
Exploring three stages of Q-learning, a classical machine learning concept: epsilon-constant, decaying epsilon-greedy, and emergent…
medium.com
June 22, 2026 at 10:31 AM
This is the first year of a new course I built called Computing and Data Sciences. The tools used this year:

Semester 1:
• Whiteboards
• LaTeX (on overleaf)
• Sheets + Desmos visualization

Semester 2:
• Python in Colab with:
- NumPy
- Pyplot
- Pandas

#ITeachMath #TeamCompSci
April 18, 2026 at 1:08 PM
Creo mas uqes lo que dice Sr Mongolfier. Le pasaron los textos al agente y a correr.
Ademas ver el mismo número repetido en el eje te salta cualquier alarma si has hecho un minimo de gráficos (rollo pyplot o seaborn)
April 10, 2026 at 2:34 PM
Another student sent an update on modeling the atmospheric CO_2 data, and was able to get the model:

a sin(b(x +c)) + d + ex +f x^2

to fit quite nicely.

#ITeachmath #mtbos
April 1, 2026 at 11:18 PM
I FINALLY solved a PyPlot problem that had been driving me up the wall for over a month now! AND I have tomorrow off!!!

Feeling pretty damn good about that right about now!
January 29, 2026 at 11:23 PM
begging the pyplot colourbar to adjust with the rest of the figure
January 28, 2026 at 12:26 PM
was trying to think of other ways to wrangle this and was liek "man, i wish i just had pyplot or something in this flask app"

but then i realized: i can in fact just do that
December 30, 2025 at 10:16 PM
ah, ok, so i think the issue is when you fire off a `df.plot()` (or `gdf.plot()`) it only emits the matplotlib *axes* object, and quarto needs an actual Figure object to recognize a figure. So you need to force the cell to emit a *figure* by doing `pyplot.show()` if no explicit pyplot in the cell
November 23, 2025 at 2:41 AM
The real question is: can PyPlot do this out of the box?
August 8, 2025 at 2:18 AM
having fun on a tuesday

spent the drive to my dad's figuring out how to do this in my head then wrote it this morning while having breakfast after looking up a bunch of pyplot syntax i forgot
August 5, 2025 at 11:41 PM
pensando aqui em cometer o crime que é assinar o copilot só pra não ter que reaprender pandas e pyplot
July 29, 2025 at 6:34 PM
Unfortunately I can't. Perhaps the Melbourne pedestrian data mentioned in the Prophet package documentation might help?

data.melbourne.vic.gov.au/Transport/Pe...

share.google/6DFiuKjPHDXw...
Handling Shocks
```python Python %matplotlib inline from prophet import Prophet import pandas as pd from matplotlib import pyplot as plt import logging logging.getLogger(‘prophet’).setLevel(logging.ERROR) import warn...
share.google
July 20, 2025 at 6:29 AM
Re: Will a Starship go to Mars in the 2026 launch window? Quote from: sdsds on 06/24/2025 09:24 pm I'm using the numpy, scipy, pyplot and pykep packages. A couple of the central functions are a...

#SpaceX #Starship #Program

Origin | Interest | Match
Awakari App
awakari.com
June 25, 2025 at 5:38 AM
Yesterday was very exciting
May 23, 2025 at 1:29 AM
Since I am officially working I cant actually watch the NBA playoffs. Am monitoring this graph instead:
May 23, 2025 at 1:27 AM