How to use the earthpy.plot.draw_legend function in earthpy

To help you get started, we’ve selected a few earthpy examples, based on popular ways it is used in public projects.

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github earthlab / earthpy / examples / plot_calculate_classify_ndvi.py View on Github external
# You can plot the classified NDVI with a categorical legend using the
# ``draw_legend`` function from the ``earthpy.plot`` module.

# Define color map
nbr_colors = ["gray", "y", "yellowgreen", "g", "darkgreen"]
nbr_cmap = ListedColormap(nbr_colors)

fig, ax = plt.subplots(figsize=(12, 12))

im = ax.imshow(ndvi_landsat_class, cmap=nbr_cmap)

# Get list of classes
classes = np.unique(ndvi_landsat_class)
classes = classes.tolist()

ep.draw_legend(im_ax=im, classes=classes, titles=ndvi_cat_names)

ax.set_title(
    "Landsat 8 - Normalized Difference Vegetation Index (NDVI) Classes",
    fontsize=14,
)
ax.set_axis_off()

# Auto adjust subplot to fit figure size
plt.tight_layout()
github earthlab / earthpy / examples / calculate_classify_ndvi.py View on Github external
# You can plot the classified NDVI with a categorical legend using the
# ``draw_legend`` function from the ``earthpy.plot`` module.

# Define color map
nbr_colors = ["gray", "y", "yellowgreen", "g", "darkgreen"]
nbr_cmap = ListedColormap(nbr_colors)

fig, ax = plt.subplots(figsize=(12, 12))

im = ax.imshow(ndvi_landsat_class, cmap=nbr_cmap)

# Get list of classes
classes = np.unique(ndvi_landsat_class)
classes = classes.tolist()

ep.draw_legend(im_ax=im, classes=classes, titles=ndvi_cat_names)

ax.set_title(
    "Landsat 8 - Normalized Difference Vegetation Index (NDVI) Classes",
    fontsize=16,
)
ax.set_axis_off()
plt.show()
github earthlab / earthpy / examples / plot_draw_legend_docs.py View on Github external
# Create a numpy array. Let's pretend this is what you want to plot.
arr = np.random.randint(4, size=(5, 5))

# When plot_bands is updated a cbar will be here as well
ep.plot_bands(arr)
plt.show()

###############################################################################
# Create Custom Discrete Legends with Earthpy
# -------------------------------------------
# If you want to create a custom categorical legend, you can use the ``ep.draw_legend()`` function.

f, ax = plt.subplots(figsize=(8, 5))
im = ax.imshow(arr)
ep.draw_legend(im)
plt.tight_layout()

###############################################################################
# Customize Discrete Legends
# ---------------------------
# By default the draw_legend function creates a legend with default categories.
# You can customize the legend by adding titles.

f, ax = plt.subplots(figsize=(8, 5))
im = ax.imshow(arr)
ep.draw_legend(im, titles=["Small", "Bigger", "Even Bigger", "Ginormous"])
plt.tight_layout()

###############################################################################
# Discrete Legends With Missing Values in the Array
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
github earthlab / earthpy / examples / plot_draw_legend_docs.py View on Github external
)
plt.tight_layout()

###############################################################################
# Custom Colormaps and Ensuring Cmaps Apply to All Valid Classes
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
# You can customize the color map used in your plot too. Notice that in this example,
# 4 category colors are rendered. Yet, the image only contains three values and thus will be
# rendered using three colors. The three colors used to render the image are incorrect by default.
# The colors begin at white and end at black even though the value of 0 which should be black
# is missing from the data.

f, ax = plt.subplots(figsize=(8, 5))
im = ax.imshow(new_arr, cmap="Greys_r")
ep.draw_legend(
    im,
    titles=["Small", "Bigger", "Even Bigger", "Ginormous"],
    classes=[0, 1, 2, 3],
)
plt.tight_layout()

###############################################################################
# Specify vmin and vmax to set the colormap range
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
# In this case, you can use the ``vmin`` and ``vmax`` arguments to set the range of values to use for the colormap.

f, ax = plt.subplots(figsize=(8, 5))
im = ax.imshow(new_arr, cmap="Greys_r", vmin=0, vmax=3)
ep.draw_legend(
    im,
github earthlab / earthpy / examples / plot_draw_legend_docs.py View on Github external
ep.draw_legend(
    im,
    titles=["Small", "Bigger", "Even Bigger", "Ginormous"],
    classes=[0, 1, 2, 3],
)
plt.tight_layout()

###############################################################################
# Specify vmin and vmax to set the colormap range
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
# In this case, you can use the ``vmin`` and ``vmax`` arguments to set the range of values to use for the colormap.

f, ax = plt.subplots(figsize=(8, 5))
im = ax.imshow(new_arr, cmap="Greys_r", vmin=0, vmax=3)
ep.draw_legend(
    im,
    titles=["Small", "Bigger", "Even Bigger", "Ginormous"],
    classes=[0, 1, 2, 3],
)
plt.tight_layout()
github earthlab / earthpy / examples / plot_draw_legend_docs.py View on Github external
# If you want to create a custom categorical legend, you can use the ``ep.draw_legend()`` function.

f, ax = plt.subplots(figsize=(8, 5))
im = ax.imshow(arr)
ep.draw_legend(im)
plt.tight_layout()

###############################################################################
# Customize Discrete Legends
# ---------------------------
# By default the draw_legend function creates a legend with default categories.
# You can customize the legend by adding titles.

f, ax = plt.subplots(figsize=(8, 5))
im = ax.imshow(arr)
ep.draw_legend(im, titles=["Small", "Bigger", "Even Bigger", "Ginormous"])
plt.tight_layout()

###############################################################################
# Discrete Legends With Missing Values in the Array
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
# Now let's pretend that you are creating a series of classified plots. You may have a range of
# values that are expected between 0-4. However not all of your data has all values
# In this case, your legend won't be able to by default create 4 categories because one
# doesn't exist in your data. In this instance, you can specify the values explicitly:

new_arr = arr.copy()
new_arr[new_arr == 0] = 1

f, ax = plt.subplots(figsize=(8, 5))
im = ax.imshow(new_arr)

earthpy

A set of helper functions to make working with spatial data in open source tools easier. This package is maintained by Earth Lab and was originally designed to support the earth analytics education program.

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Latest version published 3 years ago

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