зеркало из https://github.com/microsoft/torchgeo.git
Improve customizability of Landsat band plots (#1378)
* Improve customizability of Landsat band plots * Better xlabel * Display default values * More band customization * More band customization * Fix ylim * Fix vertical centering * Fewer sensors * flake8 fix * usetex * Shorter, simpler * Wider thermal bands padding
This commit is contained in:
Adam J. Stewart
GitHub
Родитель
02f2a6cb81
Коммит
9e4f7d12d4
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@ -1,31 +1,50 @@
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Satellite name,Sensor name,Band number,Wavelength start (μm),Wavelength width,Color,Resolution (m)
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Landsat 4-5,tm,6,10.4,2.1,#8c564b,120
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Landsat 7,etm,6,10.4,2.1,#8c564b,60
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Landsat 8-9,tirs,10,10.6,0.59,#8c564b,100
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Landsat 8-9,tirs,11,11.5,1.01,#8c564b,100
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Landsat 1-5,mss,1,0.5,0.1,#2ca02c,60
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Landsat 1-5,mss,2,0.6,0.1,#d62728,60
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Landsat 1-5,mss,3,0.7,0.1,#e377c2,60
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Landsat 1-5,mss,4,0.8,0.3,#ff7f0e,60
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Landsat 4-5,tm,1,0.45,0.07,#1f77b4,30
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Landsat 4-5,tm,2,0.52,0.08,#2ca02c,30
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Landsat 4-5,tm,3,0.63,0.06,#d62728,30
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Landsat 4-5,tm,4,0.76,0.14,#e377c2,30
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Landsat 4-5,tm,5,1.55,0.2,#ff7f0e,30
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Landsat 4-5,tm,7,2.08,0.27,#7f7f7f,30
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Landsat 7,etm,1,0.45,0.07,#1f77b4,30
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Landsat 7,etm,2,0.52,0.08,#2ca02c,30
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Landsat 7,etm,3,0.63,0.06,#d62728,30
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Landsat 7,etm,4,0.77,0.13,#e377c2,30
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Landsat 7,etm,5,1.55,0.2,#ff7f0e,30
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Landsat 7,etm,7,2.09,0.26,#7f7f7f,30
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Landsat 7,etm,8,0.52,0.38,#bcbd22,15
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Landsat 8-9,oli,1,0.43,0.02,#17becf,30
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Landsat 8-9,oli,2,0.45,0.06,#1f77b4,30
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Landsat 8-9,oli,3,0.53,0.06,#2ca02c,30
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Landsat 8-9,oli,4,0.64,0.03,#d62728,30
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Landsat 8-9,oli,5,0.85,0.03,#e377c2,30
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Landsat 8-9,oli,6,1.57,0.08,#ff7f0e,30
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Landsat 8-9,oli,7,2.11,0.18,#7f7f7f,30
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Landsat 8-9,oli,9,1.36,0.02,#9467bd,30
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Landsat 8-9,oli,8,0.5,0.18,#bcbd22,15
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Satellite,Sensor,Band,Wavelength Start (μm),Wavelength Width,Color,Resolution (m)
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Landsat 1--2,RBV,1,0.475,0.1,#1f77b4,80
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Landsat 1--2,RBV,2,0.58,0.1,#2ca02c,80
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Landsat 1--2,RBV,3,0.69,0.14,#d62728,80
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Landsat 3,RBV,1,0.505,0.245,#bcbd22,40
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Landsat 1--5,MSS,1,0.5,0.1,#2ca02c,80
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Landsat 1--5,MSS,2,0.6,0.1,#d62728,80
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Landsat 1--5,MSS,3,0.7,0.1,#e377c2,80
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Landsat 1--5,MSS,4,0.8,0.3,#ff7f0e,80
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Landsat 4--5,TM,1,0.45,0.07,#1f77b4,30
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Landsat 4--5,TM,2,0.52,0.08,#2ca02c,30
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Landsat 4--5,TM,3,0.63,0.06,#d62728,30
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Landsat 4--5,TM,4,0.76,0.14,#e377c2,30
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Landsat 4--5,TM,5,1.55,0.2,#ff7f0e,30
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Landsat 4--5,TM,6,10.4,2.1,#8c564b,120
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Landsat 4--5,TM,7,2.08,0.27,#7f7f7f,30
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Landsat 6,ETM,1,0.45,0.07,#1f77b4,30
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Landsat 6,ETM,2,0.52,0.08,#2ca02c,30
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Landsat 6,ETM,3,0.63,0.06,#d62728,30
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Landsat 6,ETM,4,0.76,0.14,#e377c2,30
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Landsat 6,ETM,5,1.55,0.2,#ff7f0e,30
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Landsat 6,ETM,6,10.4,2.1,#8c564b,120
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Landsat 6,ETM,7,2.08,0.27,#7f7f7f,30
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Landsat 6,ETM,8,0.52,0.38,#bcbd22,15
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Landsat 7,ETM+,1,0.45,0.07,#1f77b4,30
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Landsat 7,ETM+,2,0.52,0.08,#2ca02c,30
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Landsat 7,ETM+,3,0.63,0.06,#d62728,30
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Landsat 7,ETM+,4,0.77,0.13,#e377c2,30
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Landsat 7,ETM+,5,1.55,0.2,#ff7f0e,30
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Landsat 7,ETM+,6,10.4,2.1,#8c564b,60
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Landsat 7,ETM+,7,2.08,0.27,#7f7f7f,30
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Landsat 7,ETM+,8,0.52,0.38,#bcbd22,15
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Landsat 8--9,OLI/TIRS,1,0.43,0.02,#17becf,30
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Landsat 8--9,OLI/TIRS,2,0.45,0.06,#1f77b4,30
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Landsat 8--9,OLI/TIRS,3,0.53,0.06,#2ca02c,30
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Landsat 8--9,OLI/TIRS,4,0.64,0.03,#d62728,30
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Landsat 8--9,OLI/TIRS,5,0.85,0.03,#e377c2,30
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Landsat 8--9,OLI/TIRS,6,1.57,0.08,#ff7f0e,30
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Landsat 8--9,OLI/TIRS,7,2.11,0.18,#7f7f7f,30
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Landsat 8--9,OLI/TIRS,8,0.5,0.18,#bcbd22,15
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Landsat 8--9,OLI/TIRS,9,1.36,0.02,#9467bd,30
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Landsat 8--9,OLI/TIRS,10,10.6,0.59,#8c564b,100
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Landsat 8--9,OLI/TIRS,11,11.5,1.01,#8c564b,100
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@ -3,67 +3,109 @@
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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"""Plot Landsat band wavelengths and resolutions."""
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import argparse
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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# https://www.usgs.gov/faqs/what-are-band-designations-landsat-satellites
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df = pd.read_csv("band_data.csv")
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# Match NeurIPS template
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plt.rcParams.update(
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{
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"font.family": "Times New Roman",
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"font.size": 10,
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"axes.labelsize": 10,
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"text.usetex": True,
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}
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)
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bar_height = 5
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# This dictionary maps a sensor and resolution to a y location on the plot
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bar_to_height_map = {
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("tm", 120): 50,
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("etm", 60): 34,
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("tirs", 100): 12,
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("mss", 60): 60,
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("tm", 30): 44,
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("etm", 30): 28,
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("etm", 15): 22,
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("oli", 30): 6,
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("oli", 15): 0,
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}
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parser = argparse.ArgumentParser(
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formatter_class=argparse.ArgumentDefaultsHelpFormatter, description=__doc__
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)
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parser.add_argument("skip", nargs="*", help="sensors to skip", metavar="SENSOR")
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parser.add_argument(
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"--fig-height", default=5, type=float, help="height of figure in inches"
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)
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parser.add_argument("--bar-start", default=1, type=float, help="height of first bar")
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parser.add_argument("--bar-height", default=3, type=float, help="height of each bar")
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parser.add_argument(
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"--bar-sep", default=3.5, type=float, help="separation between bars"
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)
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parser.add_argument(
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"--bar-jump", default=2.6, type=float, help="additional height for narrow bars"
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)
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parser.add_argument(
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"--sensor-sep", default=2, type=float, help="separation between sensors"
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)
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args = parser.parse_args()
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fig, (ax1, ax2) = plt.subplots(1, 2, gridspec_kw={"width_ratios": [4, 1]})
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fig.subplots_adjust(wspace=0.05)
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# https://www.usgs.gov/landsat-missions/landsat-satellite-missions
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df = pd.read_csv("band_data.csv", skip_blank_lines=True)
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df = df.iloc[::-1]
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for sensor_name, group1 in df.groupby("Sensor name"):
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for resolution, group2 in group1.groupby("Resolution (m)"):
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# Plot one row of data
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y_position = bar_to_height_map[(sensor_name, resolution)]
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fig, ax = plt.subplots(figsize=(5.5, args.fig_height))
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ax1, ax2 = fig.subplots(nrows=1, ncols=2, gridspec_kw={"width_ratios": [3, 1]})
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sensor_names: list[str] = []
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sensor_ylocs: list[float] = []
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res_names: list[int] = []
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res_ylocs: list[float] = []
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bar_min = args.bar_start
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# For each satellite/sensor
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for (satellite, sensor), group1 in df.groupby(["Satellite", "Sensor"], sort=False):
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if sensor in args.skip:
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continue
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sensor_names.append(f"{satellite}\n({sensor})")
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sensor_yloc = 0.0
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res_count = 0
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# For each resolution
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for res, group2 in group1.groupby("Resolution (m)"):
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res_names.append(res)
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res_ylocs.append(bar_min)
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if len(group2) > res_count:
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sensor_yloc = bar_min
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res_count = len(group2)
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# For each band
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for i in range(group2.shape[0]):
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row = group2.iloc[i]
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wavelength_start = row["Wavelength start (μm)"]
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wavelength_width = row["Wavelength width"]
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wavelength_start = row["Wavelength Start (μm)"]
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wavelength_width = row["Wavelength Width"]
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color = row["Color"]
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band_number = row["Band number"]
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band = row["Band"]
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# We've split the plot into two parts as the thermal bands are > 10μm
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# while the other bands are < 3μm
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y = bar_min + args.bar_height / 2
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if wavelength_width < 0.05:
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y += args.bar_jump
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if wavelength_start < 10:
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ax1.broken_barh(
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[[wavelength_start, wavelength_width]],
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[y_position, bar_height],
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[bar_min, args.bar_height],
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edgecolor="k",
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facecolors=color,
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linewidth=0.5,
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alpha=0.8,
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)
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if wavelength_width < 0.05:
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y = y_position + 6.5
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else:
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y = y_position + 2.25
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ax1.text(
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wavelength_start + (wavelength_width / 2),
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y,
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str(band_number),
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band,
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horizontalalignment="center",
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verticalalignment="center",
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verticalalignment="center_baseline",
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)
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else:
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ax2.broken_barh(
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[[wavelength_start, wavelength_width]],
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[y_position, bar_height],
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[bar_min, args.bar_height],
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edgecolor="k",
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facecolors=color,
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linewidth=0.5,
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@ -71,37 +113,36 @@ for sensor_name, group1 in df.groupby("Sensor name"):
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)
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ax2.text(
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wavelength_start + (wavelength_width / 2),
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y_position + 2.25,
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str(band_number),
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y,
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band,
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horizontalalignment="center",
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verticalalignment="center",
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verticalalignment="center_baseline",
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)
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bar_min += args.bar_sep
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bar_min += args.sensor_sep
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sensor_ylocs.append(sensor_yloc)
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# Labels
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fig.supxlabel("Wavelength (μm)")
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ax.set_xlabel(r"Wavelength (\textmu m)")
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ax.set_xticks([0.5], labels=[0.5], alpha=0)
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ax.set_yticks([0], labels=[0], alpha=0)
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ax.spines[["bottom", "left", "top", "right"]].set_visible(False)
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ax1.set_ylabel("Satellite (Sensor)")
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ax1.set_yticks([62.5, 46.5, 30.5, 8.5])
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ax1.set_yticklabels(
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[
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"Landsat 1–5\n(MSS)",
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"Landsat 4–5\n(TM)",
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"Landsat 7\n(ETM+)",
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"Landsat 8–9\n(OLI+TIRS)",
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]
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)
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ax1.set_ylim(-5, 70)
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ax1.spines.right.set_visible(False)
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ax1.spines.top.set_visible(False)
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ax1.set_yticks(np.array(sensor_ylocs) + args.bar_height / 2)
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ax1.set_yticklabels(sensor_names)
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ax1.set_ylim(0, max(res_ylocs) + args.bar_height + args.bar_start)
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ax1.spines[["left", "top", "right"]].set_visible(False)
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ax1.tick_params(axis="both", which="both", left=False)
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ax2.set_xlim(10.1, 12.8)
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ax2.set_ylim(0, max(res_ylocs) + args.bar_height + args.bar_start)
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ax2.yaxis.set_label_position("right")
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ax2.yaxis.tick_right()
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ax2.set_ylabel("Resolution (m)")
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ax2.set_yticks([62.5, 52.5, 46.5, 36.5, 30.5, 24.5, 14.5, 8.5, 2.5])
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ax2.set_yticklabels([60, 120, 30, 60, 30, 15, 100, 30, 15])
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ax2.set_ylim(-5, 70)
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ax2.spines.left.set_visible(False)
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ax2.spines.top.set_visible(False)
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ax2.set_yticks(np.array(res_ylocs) + args.bar_height / 2)
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ax2.set_yticklabels(res_names)
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ax2.spines[["left", "top"]].set_visible(False)
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# Draw axis break symbol
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d = 2
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@ -118,4 +159,5 @@ ax1.plot(1, 0, transform=ax1.transAxes, **kwargs)
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ax2.plot(0, 0, transform=ax2.transAxes, **kwargs)
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plt.tight_layout()
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plt.subplots_adjust(wspace=0.1)
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plt.show()
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