plotting updates, poster

archive/scrape.py

@@ -2,7 +2,7 @@ import glob
 import shutil
 from pathlib import Path
 
-from check import make_image
+from check import create_rectangle
 
 
 def get_exps(pattern: str, splitter: str = "_", dry_run: bool = True):
@@ -33,8 +33,8 @@ def get_exps(pattern: str, splitter: str = "_", dry_run: bool = True):
             print(latest_checkpoint)
         if not dry_run:
             shutil.copy(source_path, dir_path)
-            make_image(latest_checkpoint, f"out/version_{i}")
-            # make_image(latest_checkpoint, f"out/version_{i}b", color=False)
+            create_rectangle(latest_checkpoint, f"out/version_{i}")
+            # create_rectangle(latest_checkpoint, f"out/version_{i}b", color=False)
         else:
             print("Would copy", source_path, dir_path)
     return H

callbacks.py

@@ -4,7 +4,7 @@ from pathlib import Path
 
 from lightning import Callback
 
-from check import create_circle
+from check import create_circle_nonblocking as create_circle
 
 
 class SaveImageCallback(Callback):

check.py

@@ -15,21 +15,21 @@ from model import ColorTransformerModel
 # import matplotlib.colors as mcolors
 
 
-def make_image(ckpt: str, fname: str, color=True, **kwargs):
+def create_rectangle(ckpt: str, fname: str, color: bool = True, **kwargs):
     M = ColorTransformerModel.load_from_checkpoint(ckpt)
 
     # preds = M(rgb_tensor)
-    if not color:
+    if color is False:  # black and white ordering...
         N = 949
         linear_space = torch.linspace(0, 1, N)
         rgb_tensor = linear_space.unsqueeze(1).repeat(1, 3)
     else:
         rgb_tensor, names = extract_colors()
 
-    rgb_values = rgb_tensor.detach().numpy()
-    rgb_tensor = preprocess_data(rgb_tensor)
-    preds = M(rgb_tensor)
-    sorted_inds = np.argsort(preds.detach().numpy().ravel())
+    rgb_tensor = preprocess_data(rgb_tensor).to(M.device)
+    preds = M(rgb_tensor).detach().cpu().numpy()
+    rgb_values = rgb_tensor.detach().cpu().numpy()
+    sorted_inds = np.argsort(preds.ravel())
 
     fig, ax = plt.subplots()
     for i in range(len(sorted_inds)):
@@ -44,33 +44,8 @@ def make_image(ckpt: str, fname: str, color=True, **kwargs):
     plt.savefig(f"{fname}.png", **kwargs)
 
 
-# def create_circle(
-#     ckpt: Union[str, ColorTransformerModel], fname: str, skip: bool = True, **kwargs
-# ):
-#     if isinstance(ckpt, str):
+def do_inference(ckpt: Union[str, ColorTransformerModel]):
 
-#         M = ColorTransformerModel.load_from_checkpoint(
-#             ckpt, map_location=lambda storage, loc: storage
-#         )
-#     else:
-#         M = ckpt
-
-#     xkcd_colors, _ = extract_colors()
-#     xkcd_colors = preprocess_data(xkcd_colors).to(M.device)
-#     preds = M(xkcd_colors).detach().cpu().numpy()
-#     rgb_array = xkcd_colors.detach().cpu().numpy()
-#     plot_preds(preds, rgb_array, fname=fname, **kwargs)
-
-
-def plot_preds_serialized(serialized_data, fname, **kwargs):
-    # Deserialize the data
-    preds, rgb_array = pickle.loads(serialized_data)
-    plot_preds(preds, rgb_array, fname=fname, **kwargs)
-
-
-def create_circle(
-    ckpt: Union[str, ColorTransformerModel], fname: str, skip: bool = True, **kwargs
-):
     if isinstance(ckpt, str):
         M = ColorTransformerModel.load_from_checkpoint(
             ckpt, map_location=lambda storage, loc: storage
@@ -82,13 +57,31 @@ def create_circle(
     xkcd_colors = preprocess_data(xkcd_colors).to(M.device)
     preds = M(xkcd_colors).detach().cpu().numpy()
     rgb_array = xkcd_colors.detach().cpu().numpy()
+    return preds, rgb_array
+
+
+def create_circle(ckpt: Union[str, ColorTransformerModel], fname: str, **kwargs):
+    preds, rgb_array = do_inference(ckpt)
+    plot_preds(preds, rgb_array, fname=fname, **kwargs)
+
+
+def _plot_preds_serialized(serialized_data, fname, **kwargs):
+    # Deserialize the data
+    preds, rgb_array = pickle.loads(serialized_data)
+    plot_preds(preds, rgb_array, fname=fname, **kwargs)
+
+
+def create_circle_nonblocking(
+    ckpt: Union[str, ColorTransformerModel], fname: str, **kwargs
+):
+    preds, rgb_array = do_inference(ckpt)
 
     # Serialize the data
     serialized_data = pickle.dumps((preds, rgb_array))
 
-    # Run plot_preds_serialized function in a separate process
+    # Run _plot_preds_serialized function in a separate process
     p = Process(
-        target=plot_preds_serialized, args=(serialized_data, fname), kwargs=kwargs
+        target=_plot_preds_serialized, args=(serialized_data, fname), kwargs=kwargs
     )
     p.start()
     return p
@@ -96,7 +89,7 @@ def create_circle(
 
 def plot_preds(
     preds: np.ndarray,
-    rgb_values,
+    rgb_values: np.ndarray,
     fname: str,
     roll: bool = False,
     radius: float = 1 / 2,
@@ -173,12 +166,10 @@ def plot_preds(
 
 
 if __name__ == "__main__":
-    # name = "color_128_0.3_1.00e-06"
     import argparse
     import glob
 
     parser = argparse.ArgumentParser()
-    # make the following accept a list of arguments
     parser.add_argument("-v", "--version", type=int, nargs="+", default=[0])
     parser.add_argument(
         "--dpi", type=int, default=300, help="Resolution for saved image."
@@ -186,7 +177,7 @@ if __name__ == "__main__":
     parser.add_argument(
         "--studio",
         type=str,
-        default="this_studio",
+        default=["this_studio"],
         nargs="+",
         help="Checkpoint studio name.",
     )
@@ -201,8 +192,8 @@ if __name__ == "__main__":
             # ckpt_path = f"/teamspace/studios/this_studio/colors/lightning_logs/version_{v}/checkpoints/*.ckpt"
             ckpt_path = f"/teamspace/studios/{studio}/colors/lightning_logs/version_{v}/checkpoints/*.ckpt"
             ckpt = glob.glob(ckpt_path)
-            if len(ckpt) > 0:
-                ckpt = ckpt[-1]
+            if len(ckpt) > 0:  # get latest checkpoint
+                ckpt = ckpt[-1]  # TODO: allow specification via CLI
                 print(f"Generating image for checkpoint: {ckpt}")
                 create_circle(
                     ckpt,

datamodule.py

@@ -35,14 +35,18 @@ class ColorDataModule(L.LightningDataModule):
         return [(c, cls.get_hue(c)) for c in train_rgb]
 
     @classmethod
-    def get_xkcd_colors(cls):
+    def get_xkcd_colors(cls, label="hues"):
         rgb_tensor, xkcd_color_names = extract_colors()
         rgb_tensor = preprocess_data(rgb_tensor, skip=True)
-        # return [
-        #     (rgb_tensor[i], xkcd_color_names[i].replace("xkcd:", ""))
-        #     for i in range(len(rgb_tensor))
-        # ]
-        return [(c, cls.get_hue(c)) for c in rgb_tensor]
+        if label == "names":
+            return [
+                (rgb_tensor[i], xkcd_color_names[i].replace("xkcd:", ""))
+                for i in range(len(rgb_tensor))
+            ]
+        if label == "hues":
+            return [(c, cls.get_hue(c)) for c in rgb_tensor]
+        else:
+            raise ValueError("Please specify `label` as one of ['hues', 'names'].")
 
     def setup(self, stage: str):
         # Assign train/val datasets for use in dataloaders

makefile

@@ -72,6 +72,9 @@ sort_lex:
 sort_hsv:
 	python scripts/sortcolor.py -s hsv --dpi 300
 
+poster: sort_lex sort_hsv
+	python scripts/color_poster.py -k hsv lex --rows 119
+
 clean:
 	rm -rf lightning_logs
 	rm -rf .lr_find_*.ckpt

scripts/color_poster.py

@@ -168,14 +168,14 @@ if __name__ == "__main__":
         "--rows", type=int, default=73, help="Number of entries per column"
     )
     parser.add_argument(
-        "--dir", type=str, default="~/color/out", help="Directory to save images"
+        "--dir", type=str, default="~/out_sortcolors", help="Directory to save images"
     )
     parser.add_argument(
         "-k",
         "--kind",
         type=str,
         nargs="+",
-        default=["hsv", "lex", "lab", "umap"],
+        default=["hsv", "lex"],
         help="Kinds of sorting",
     )
     parser.add_argument(
@@ -209,7 +209,7 @@ if __name__ == "__main__":
     # KIND = "hsv"  # choose from umap, hsv
     for KIND in KINDS:
         colors = list(mcolors.XKCD_COLORS.keys())
-        sorted_indices = np.load(f"scripts/{KIND}_sorted_indices.npy")
+        sorted_indices = np.load(f"/teamspace/studios/this_studio/out_sortcolors/{KIND}/sorted_indices.npy")
         sorted_colors = [colors[idx] for idx in sorted_indices]
 
         colors = sorted_colors

scripts/install_ptmono.sh

@@ -0,0 +1,44 @@
+#!/bin/bash
+
+# Source: https://blog.programster.org/ubuntu-install-pt-mono-font
+# Installs PT Mono font onto Ubuntu 12.04 or 14.04 Systems
+
+# Check to make sure the user has the unzip package installed
+export NO_UNZIP=$(apt-cache policy unzip | grep "Installed: (none)" | wc -l)
+
+# Result will be 1 if it is NOT installed
+if [ "$NO_UNZIP" = "0" ]; then
+
+    export TEMP_DIR='temp-technostu-script'
+    cd ~
+    mkdir $TEMP_DIR
+    cd $TEMP_DIR
+
+    # Download PT mono from google fonts
+    export FONT_URL="http://www.google.com/fonts/download"
+    export FONT_URL="$FONT_URL?kit=7qsh9BNBJbZ6khIbS3ZpfKCWcynf_cDxXwCLxiixG1c"
+    wget --content-disposition "$FONT_URL"
+
+    # Create a PT_Mono directory which we will copy across into the fonts directory.
+    mkdir PT_Mono
+    mv PT_Mono.zip PT_Mono/.
+    cd PT_Mono
+    unzip PT_Mono.zip
+    rm PT_Mono.zip
+    cd ..
+    sudo mv PT_Mono /usr/share/fonts/truetype/.
+
+    # Re-cache the fonts
+    echo 'Re-caching fonts...'
+    sudo fc-cache -fv
+
+    # cleanup
+    cd ~
+    sudo rm -rf $TEMP_DIR
+
+    echo 'done!'
+else
+    # User doesnt have unzip installed, tell them how to install it
+    echo 'You need to install unzip for this to work: try '
+    echo '"sudo apt-get install unzip"'
+fi

scripts/sortcolor.py

@@ -82,10 +82,11 @@ def peano_curve(n):
 
 
 if KIND in ("lex", "alpha", "abc"):
+    KIND = "lex"
     preds = np.array(colors)
 
 elif KIND == "umap":
-    PDIR = f"scripts/{KIND}-prod"
+    PDIR = f"/teamspace/studios/this_studio/out_sortcolors/{KIND}"
     Path(PDIR).mkdir(parents=True, exist_ok=True)
     file_path = f"{PDIR}/{SEED:06d}.npy"
     if Path(file_path).exists():
@@ -147,9 +148,9 @@ else:
     raise ValueError(f"Unknown kind: {KIND}")
 
 
-PDIR = f"scripts"
+PDIR = f"/teamspace/studios/this_studio/out_sortcolors/{KIND}"
 Path(PDIR).mkdir(parents=True, exist_ok=True)
-file_path = f"{PDIR}/{KIND}_sorted_indices.npy"
+file_path = f"{PDIR}/sorted_indices.npy"
 # Sort colors by the 1D representation
 sorted_indices = np.argsort(preds)
 sorted_colors = [colors[i] for i in sorted_indices]