Merge pull request #78 from sebi06/work_in_progress

added marimo notebooks

demo/notebooks/read_czi_metadata_marimo.py

@@ -0,0 +1,78 @@
+import marimo
+
+__generated_with = "0.10.8"
+app = marimo.App()
+
+
+@app.cell
+def _():
+    import marimo as mo
+    import pandas as pd
+    from czitools.metadata_tools import czi_metadata as czimd
+    from czitools.utils import misc
+    from pathlib import Path
+    import os
+    import glob
+    return Path, czimd, glob, misc, mo, os, pd
+
+
+@app.cell
+def _(mo):
+    file_browser = mo.ui.file_browser(multiple=False)
+
+    # Display the file browser
+    mo.vstack([file_browser])
+    return (file_browser,)
+
+
+@app.cell
+def _(file_browser):
+    filepath = str(file_browser.path(0))
+    print(f"Filepath: {filepath}")
+    return (filepath,)
+
+
+@app.cell
+def _(czimd, filepath):
+    # get only specific metadata
+    czi_dimensions = czimd.CziDimensions(filepath)
+    print(f"SizeS: {czi_dimensions.SizeS}")
+    print(f"SizeT: {czi_dimensions.SizeT}")
+    print(f"SizeZ: {czi_dimensions.SizeZ}")
+    print(f"SizeC: {czi_dimensions.SizeC}")
+    print(f"SizeY: {czi_dimensions.SizeY}")
+    print(f"SizeX: {czi_dimensions.SizeX}")
+    return (czi_dimensions,)
+
+
+@app.cell
+def _(czimd, filepath, misc, mo):
+    # get the complete metadata at once as one big class
+    mdata = czimd.CziMetadata(filepath)
+
+    # get the CZI metadata dictionary directly from filename
+    mdict = czimd.create_md_dict_red(mdata, sort=False, remove_none=True)
+
+    # convert metadata dictionary to a pandas dataframe
+    mdframe = misc.md2dataframe(mdict)
+
+    mo.vstack([mo.ui.table(mdframe)])
+    return mdata, mdframe, mdict
+
+
+@app.cell
+def _(filepath, misc, mo):
+    # get the planetable for the CZI file
+    pt = misc.get_planetable(filepath,
+                             norm_time=True,
+                             pt_complete=True,
+                             t=0,
+                             c=0,
+                             z=0)
+
+    mo.vstack([mo.ui.table(pt)])
+    return (pt,)
+
+
+if __name__ == "__main__":
+    app.run()

demo/notebooks/read_czi_pixeldata_marimo.py

@@ -0,0 +1,168 @@
+import marimo
+
+__generated_with = "0.10.14"
+app = marimo.App(auto_download=["ipynb"])
+
+
+@app.cell
+def _():
+    import marimo as mo
+    import pandas as pd
+    from czitools.metadata_tools import czi_metadata as czimd
+    from czitools.utils import misc
+    from czitools.read_tools import read_tools as czird
+    import dask.array as da
+    from pathlib import Path
+    import os
+    import glob
+    from matplotlib import pyplot as plt
+    import matplotlib.cm as cm
+    from matplotlib.colors import LinearSegmentedColormap
+    return (
+        LinearSegmentedColormap,
+        Path,
+        cm,
+        czimd,
+        czird,
+        da,
+        glob,
+        misc,
+        mo,
+        os,
+        pd,
+        plt,
+    )
+
+
+@app.cell
+def _(mo):
+    file_browser = mo.ui.file_browser(multiple=False)
+
+    # Display the file browser
+    mo.vstack([file_browser])
+    return (file_browser,)
+
+
+@app.cell
+def _(file_browser):
+    filepath = str(file_browser.path(0))
+    print(f"Filepath: {filepath}")
+    return (filepath,)
+
+
+@app.cell
+def _(LinearSegmentedColormap, czird, da, filepath):
+    def hex_to_rgb(hex_color: str) -> tuple[int, int, int]:
+        """
+        Convert a hexadecimal color string to an RGB tuple.
+        Args:
+            hex_color (str): A string representing a color in hexadecimal format (e.g., "#RRGGBB").
+        Returns:
+            tuple[int, int, int]: A tuple containing the RGB values as floats in the range [0, 1].
+        """
+
+        hex_color = hex_color.lstrip("#")
+        rgb = tuple(int(hex_color[i : i + 2], 16) / 255.0 for i in (0, 2, 4))
+
+        return rgb
+
+    # get 6d array with dimension order STCZYX(A)
+    array6d, mdata = czird.read_6darray(filepath, use_dask=False, chunk_zyx=True)
+
+    # show dask array structure
+    if isinstance(array6d, da.Array):
+        print(array6d)
+    else:
+        print("Shape:", array6d.shape, "dtype:", array6d.dtype)
+
+    # get array dimensions
+    dims = array6d.shape[:-2]
+    dims_names = ["S", "T", "C", "Z"]
+
+    cmaps = []
+
+    for ch in range(mdata.image.SizeC):
+        chname = mdata.channelinfo.names[ch]
+        rgb = hex_to_rgb(mdata.channelinfo.colors[ch][3:])
+        cmaps.append(LinearSegmentedColormap.from_list(chname, [(0, 0, 0), rgb]))
+    return (
+        array6d,
+        ch,
+        chname,
+        cmaps,
+        dims,
+        dims_names,
+        hex_to_rgb,
+        mdata,
+        rgb,
+    )
+
+
+@app.cell
+def _(czimd, mdata, misc, mo):
+    # get the CZI metadata dictionary directly from filename
+    mdict = czimd.create_md_dict_red(mdata, sort=False, remove_none=True)
+
+    # convert metadata dictionary to a pandas dataframe
+    mdframe = misc.md2dataframe(mdict)
+
+    mo.vstack([mo.ui.table(mdframe)])
+    return mdframe, mdict
+
+
+@app.cell
+def _(dims, mo):
+    scene = mo.ui.slider(
+        start=0,
+        stop=dims[0] - 1,
+        step=1,
+        label=f"scene [0 - {dims[0]-1}]",
+        show_value=True,
+    )
+
+    time = mo.ui.slider(
+        start=0,
+        stop=dims[1] - 1,
+        step=1,
+        label=f"time [0 - {dims[1]-1}]",
+        show_value=True,
+    )
+
+    channel = mo.ui.slider(
+        start=0,
+        stop=dims[2] - 1,
+        step=1,
+        label=f"channel [0 - {dims[2]-1}]",
+        show_value=True,
+    )
+
+    zplane = mo.ui.slider(
+        start=0,
+        stop=dims[3] - 1,
+        step=1,
+        label=f"zplane [0 - {dims[3]-1}]",
+        show_value=True,
+    )
+
+    mo.vstack([scene, time, channel, zplane])
+    return channel, scene, time, zplane
+
+
+@app.cell
+def _(channel, scene, show_2dplane, time, zplane):
+    show_2dplane(scene.value, time.value, channel.value, zplane.value)
+    return
+
+
+@app.cell
+def _(array6d, cmaps, plt):
+    def show_2dplane(s, t, c, z):
+        plt.figure(figsize=(8, 8))
+        plt.imshow(array6d[s, t, c, z, ...], cmap=cmaps[c], vmin=None, vmax=None)
+        plt.tight_layout()
+        return plt.gca()
+    return (show_2dplane,)
+
+
+if __name__ == "__main__":
+    app.run()

demo/notebooks/read_czi_pixeldata_simple.ipynb

@@ -180,7 +180,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

demo/testing/process.py

@@ -1,4 +1,4 @@
-# -*- coding: utf-8 -*-
+pip# -*- coding: utf-8 -*-
 
 #################################################################
 # File        : process.py

setup.cfg

@@ -1,6 +1,6 @@
 [metadata]
 name = czitools
-version = 0.7.5
+version = 0.7.6
 author = Sebastian Rhode
 author_email = [email protected]
 url = https://github.com/sebi06/czitools

src/czitools/__init__.py

@@ -1,3 +1,3 @@
 # __init__.py
 # version of the czitools package
-__version__ = "0.7.5"
+__version__ = "0.7.6"