diff --git a/dungeon-plot/Pipfile b/dungeon-plot/Pipfile
new file mode 100644
index 0000000..9cbfc61
--- /dev/null
+++ b/dungeon-plot/Pipfile
@@ -0,0 +1,15 @@
+[[source]]
+url = "https://pypi.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+perlin-noise = "*"
+opencv-python = "*"
+pillow = "*"
+
+[dev-packages]
+
+[requires]
+python_version = "3.11"
+python_full_version = "3.11.11"
diff --git a/dungeon-plot/Pipfile.lock b/dungeon-plot/Pipfile.lock
new file mode 100644
index 0000000..dfbdc2b
--- /dev/null
+++ b/dungeon-plot/Pipfile.lock
@@ -0,0 +1,183 @@
+{
+    "_meta": {
+        "hash": {
+            "sha256": "2553c9eba8cb970f0e6947604776d0252df7123df82d43616277a066fc0ee1cd"
+        },
+        "pipfile-spec": 6,
+        "requires": {
+            "python_full_version": "3.11.11",
+            "python_version": "3.11"
+        },
+        "sources": [
+            {
+                "name": "pypi",
+                "url": "https://pypi.org/simple",
+                "verify_ssl": true
+            }
+        ]
+    },
+    "default": {
+        "numpy": {
+            "hashes": [
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+                "sha256:f7de08cbe5551911886d1ab60de58448c6df0f67d9feb7d1fb21e9875ef95e91"
+            ],
+            "markers": "python_version >= '3.10'",
+            "version": "==2.2.4"
+        },
+        "opencv-python": {
+            "hashes": [
+                "sha256:03d60ccae62304860d232272e4a4fda93c39d595780cb40b161b310244b736a4",
+                "sha256:085ad9b77c18853ea66283e98affefe2de8cc4c1f43eda4c100cf9b2721142ec",
+                "sha256:1b92ae2c8852208817e6776ba1ea0d6b1e0a1b5431e971a2a0ddd2a8cc398202",
+                "sha256:432f67c223f1dc2824f5e73cdfcd9db0efc8710647d4e813012195dc9122a52a",
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+                "sha256:810549cb2a4aedaa84ad9a1c92fbfdfc14090e2749cedf2c1589ad8359aa169b",
+                "sha256:9d05ef13d23fe97f575153558653e2d6e87103995d54e6a35db3f282fe1f9c66"
+            ],
+            "index": "pypi",
+            "markers": "python_version >= '3.6'",
+            "version": "==4.11.0.86"
+        },
+        "perlin-noise": {
+            "hashes": [
+                "sha256:09f274c8da38f5a2a48b1626032a1b7738990df758a3bc7549ff3464869c6ca4",
+                "sha256:0e0f074743336fbe9cf2cdbdeb74c75d43780a8b3cbc3415859cd396ab4da177"
+            ],
+            "index": "pypi",
+            "version": "==1.13"
+        },
+        "pillow": {
+            "hashes": [
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+                "sha256:e63e4e5081de46517099dc30abe418122f54531a6ae2ebc8680bcd7096860eab",
+                "sha256:f189805c8be5ca5add39e6f899e6ce2ed824e65fb45f3c28cb2841911da19070",
+                "sha256:f7955ecf5609dee9442cbface754f2c6e541d9e6eda87fad7f7a989b0bdb9d71",
+                "sha256:f86d3a7a9af5d826744fabf4afd15b9dfef44fe69a98541f666f66fbb8d3fef9",
+                "sha256:fbd43429d0d7ed6533b25fc993861b8fd512c42d04514a0dd6337fb3ccf22761"
+            ],
+            "index": "pypi",
+            "markers": "python_version >= '3.9'",
+            "version": "==11.1.0"
+        }
+    },
+    "develop": {}
+}
diff --git a/dungeon-plot/dungeon.py b/dungeon-plot/dungeon.py
new file mode 100644
index 0000000..4502b87
--- /dev/null
+++ b/dungeon-plot/dungeon.py
@@ -0,0 +1,102 @@
+import matplotlib.pyplot as plt
+from matplotlib import colors
+import numpy as np
+from perlin_noise import PerlinNoise
+import cv2 as cv
+import os
+from PIL import Image
+import sys
+
+data = np.random.rand(16, 16)
+
+
+def generate_base_map(filename):
+    print("generating base map...")
+
+    cmap = colors.ListedColormap(['white', 'black'])
+    bounds = [0, .5, 1]
+    norm = colors.BoundaryNorm(bounds, cmap.N)
+
+    #dpi=96
+    #size=512
+    #fig, ax = plt.subplots(1, 1, figsize=(size/dpi, size/dpi))
+    fig, ax = plt.subplots()
+    ax.imshow(data, cmap=cmap, norm=norm)
+
+    plt.axis('off')
+
+    plt.savefig(filename, bbox_inches='tight', pad_inches=0)
+    im = Image.open(filename)
+    out = im.resize((512,512))
+    out.save(filename)
+    #plt.savefig('../marshroom/dungeon/dungeon.png', bbox_inches='tight', pad_inches=0, dpi=dpi)
+
+
+def generate_perlin(filename):
+    print("generating perlin noise...")
+
+    noise = PerlinNoise(octaves=10, seed=1)
+    xpix, ypix = 512, 512
+    pic = [[noise([i/xpix, j/ypix]) for j in range(xpix)] for i in range(ypix)]
+
+    plt.imshow(pic, cmap='gray')
+    plt.savefig(filename, bbox_inches='tight', pad_inches=0)
+    im = Image.open(filename)
+    out = im.resize((512,512))
+    out.save(filename)
+
+
+def generate_loot_probability_map(filename, noise_filename, mask_filename):
+    print("generating loot probabilities...")
+
+    #noise = cv.imread(noise_filename)
+    mask = cv.imread(mask_filename, 0)
+    mask = cv.bitwise_not(mask)
+
+    kernel_size = 32
+    kernel = np.ones((kernel_size, kernel_size), np.uint8)
+    eroded = cv.erode(mask, kernel)
+
+    # use quarter-circle kernels to build up shadows in 90 degree corners
+    centres = [
+        (-1, -1),
+        (-1, kernel_size+1),
+        (kernel_size+1, -1),
+        (kernel_size+1, kernel_size+1)]
+
+    joined = mask.copy()
+
+    for centre in centres:
+        circle_kernel = np.zeros((kernel_size, kernel_size), np.uint8)
+        cv.circle(circle_kernel, centre, kernel_size, 255, -1)
+        dilated = cv.dilate(eroded, circle_kernel, iterations=1)
+        joined[dilated == 0] = 0
+
+    # we want white in the corners and black on floors and in wall so we need to invert the colours
+    inverted = cv.bitwise_not(joined)
+
+    # inverting it turns the shadows white, but now the inside of the walls are also white, where we want them to be black.
+    # in the base map the inside of walls is white.
+    # we therefore want to set pixels in the output to zero where the base map is white
+    invmask = cv.bitwise_not(mask)
+    inverted -= invmask
+
+    # we're left with some narrow artifacts which we can erode away
+    erodedinv = cv.erode(inverted, np.ones((3,3),np.uint8))
+
+    # modulate with noise?
+
+    cv.imwrite(filename, erodedinv)
+
+
+noise = 'perlin.png'
+map = 'map.png'
+loot = 'loot.png'
+
+#generate_perlin(noise)
+#generate_base_map(map)
+generate_loot_probability_map(loot, noise, map)
+
+
+
+
diff --git a/dungeon-plot/dungeon.sh b/dungeon-plot/dungeon.sh
new file mode 100755
index 0000000..f2b3415
--- /dev/null
+++ b/dungeon-plot/dungeon.sh
@@ -0,0 +1,13 @@
+infiles="map.png heat.png"
+outdir="../marshroom/dungeon/"
+
+pipenv run python dungeon.py
+
+for f in $infiles
+do
+    #magick $f -resize 512x512 $f
+    echo $f
+done
+
+#cp $infile $outfile
+sxiv *.png