Fix notebook example errors

examples/QuickOverview.py

@@ -6,9 +6,9 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.9.1
+#       jupytext_version: 1.14.4
 #   kernelspec:
-#     display_name: Python 3
+#     display_name: Python 3 (ipykernel)
 #     language: python
 #     name: python3
 # ---
@@ -132,7 +132,7 @@
 # To return data to SEG-Y after modification use the `segy_writer` function. `segy_writer` takes as argument a SEISNC dataset which
 # requires certain attributes be set. You can also specify the byte locations to write header information.
 
-# %%
+# %% tags=[]
 from segysak.segy import segy_writer
 
 segy_writer(

examples/example_amplitude_extraction_displays.py

@@ -6,9 +6,9 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.9.1
+#       jupytext_version: 1.14.4
 #   kernelspec:
-#     display_name: Python 3
+#     display_name: Python 3 (ipykernel)
 #     language: python
 #     name: python3
 # ---
@@ -266,7 +266,7 @@
 # To get the horizon window extraction for sum of amplitudes we now need to sum along the time axis. Or
 # we can use the `np.apply_along_axis` function to apply a custom function to our masked cube.
 
-# %%
+# %% tags=[]
 summed_amp = masked_data.sum(dim="twt")
 
 f, ax = plt.subplots(figsize=(12, 4))

examples/example_extract_arbitrary_line.py

@@ -6,9 +6,9 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.11.1
+#       jupytext_version: 1.14.4
 #   kernelspec:
-#     display_name: Python 3
+#     display_name: Python 3 (ipykernel)
 #     language: python
 #     name: python3
 # ---
@@ -239,7 +239,7 @@
     435050.21,
     inplace=True,
 )
-f12_dev_pos.loc_to_tvdss(
+f12_dev_pos.to_tvdss(
     54.9,
     inplace=True,
 )
@@ -288,6 +288,8 @@
 # %% [markdown]
 # To extract the data along the well path we just need to interpolate using the additional `twt` DataArray.
 
-# %%
+# %% tags=[]
 well_seismic = volve_3d.interp(**f12_dev_ilxl, twt=twt)
 well_seismic.data.plot()
+
+# %%

examples/example_extract_data_on_a_horizon.py

@@ -6,9 +6,9 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.9.1
+#       jupytext_version: 1.14.4
 #   kernelspec:
-#     display_name: Python 3
+#     display_name: Python 3 (ipykernel)
 #     language: python
 #     name: python3
 # ---
@@ -107,7 +107,7 @@
     {"iline": top_hugin_ds.iline, "xline": top_hugin_ds.xline, "twt": top_hugin_ds.twt}
 )
 
-# %%
+# %% tags=[]
 #
 fig = plt.figure(figsize=(15, 5))
 top_hugin_amp.plot(cmap="bwr")

examples/example_merge_surveys.py

@@ -6,9 +6,9 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.11.1
+#       jupytext_version: 1.14.4
 #   kernelspec:
-#     display_name: Python 3
+#     display_name: Python 3 (ipykernel)
 #     language: python
 #     name: python3
 # ---

examples/example_reading_and_writing_zgy.py

@@ -6,9 +6,9 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.11.1
+#       jupytext_version: 1.14.4
 #   kernelspec:
-#     display_name: Python 3
+#     display_name: Python 3 (ipykernel)
 #     language: python
 #     name: python3
 # ---
@@ -71,7 +71,7 @@
 # %% [markdown]
 # Check that the global coordinates are the same.
 
-# %%
+# %% tags=[]
 fig, axs = plt.subplots(ncols=2, figsize=(15, 6))
 
 p1 = axs[0].pcolormesh(
@@ -97,3 +97,5 @@
 )
 plt.colorbar(p1, ax=axs[1], label="Seismic Amplitude")
 axs[1].set_title("Loaded from ZGY")
+
+# %%

examples/example_segy_headers.py

@@ -6,9 +6,9 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.9.1
+#       jupytext_version: 1.14.4
 #   kernelspec:
-#     display_name: Python 3
+#     display_name: Python 3 (ipykernel)
 #     language: python
 #     name: python3
 # ---
@@ -87,7 +87,7 @@
 # %% [markdown]
 # We can also just plot up the geometry to check that everything looks ok, here the line numbering and coordinates seem to match up, great!
 
-# %%
+# %% tags=[]
 fig, axs = plt.subplots(nrows=2, figsize=(12, 10), sharex=True, sharey=True)
 
 scrape.plot(

examples/example_segysak_basics.py

@@ -6,13 +6,14 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.9.1
+#       jupytext_version: 1.14.4
 #   kernelspec:
-#     display_name: Python 3
+#     display_name: Python 3 (ipykernel)
 #     language: python
 #     name: python3
 # ---
 
+# %%
 
 # %% [markdown]
 # # SEGY-SAK Basics
@@ -159,5 +160,5 @@
 # %% [markdown]
 # Sometimes we need to modify the dimensions because they were read wrong or to scale them. Modify your dimension from the seisnc and then put it back using `assign_coords`.
 
-# %%
+# %% tags=[]
 new_seisnc.assign_coords(iline=new_seisnc.iline * 10, twt=new_seisnc.twt + 1500)

examples/example_segysak_dask.py

@@ -6,9 +6,9 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.9.1
+#       jupytext_version: 1.14.4
 #   kernelspec:
-#     display_name: Python 3
+#     display_name: Python 3 (ipykernel)
 #     language: python
 #     name: python3
 # ---
@@ -98,7 +98,7 @@
 #
 # The lazy loading of data means we can plot what we want using `xarray` style slicing and `dask` will fetch only the data we need.
 
-# %%
+# %% tags=[]
 fig, axs = plt.subplots(nrows=2, ncols=3, figsize=(20, 10))
 
 iline = seisnc.sel(iline=10100).transpose("twt", "xline").data

examples/example_segysak_segy_vectorisation.py

@@ -6,15 +6,16 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.9.1
+#       jupytext_version: 1.14.4
 #   kernelspec:
-#     display_name: Python 3
+#     display_name: Python 3 (ipykernel)
 #     language: python
 #     name: python3
 # ---
 
+# %%
 
-# %% [markdown] jupyter={"source_hidden": true}
+# %% [markdown]
 # # SEG-Y to Vector DataFrames and Back
 #
 # The connection of segysak to `xarray` greatly simplifies the process of vectorising segy 3D data and returning it to SEGY. To do this, one can use the close relationship between `pandas` and `xarray`.
@@ -80,5 +81,5 @@
 # %% [markdown]
 # Afterwards, use the `segy_writer` utility as normal to return to SEGY.
 
-# %%
+# %% tags=[]
 segy_writer(volve_3d_ds, "test.segy")

examples/example_working_with_3d_gathers.py

@@ -6,9 +6,9 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.11.1
+#       jupytext_version: 1.14.4
 #   kernelspec:
-#     display_name: Python 3
+#     display_name: Python 3 (ipykernel)
 #     language: python
 #     name: python3
 # ---
@@ -157,7 +157,7 @@
 # %% [markdown]
 # Stacking is the process of averaging the gathers for constant time to create a single trace per inline and crossline location.
 
-# %%
+# %% tags=[] jupyter={"outputs_hidden": true}
 fig, axs = plt.subplots(ncols=3, figsize=(20, 10))
 
 plot_kwargs = dict(vmax=5000, interpolation="bicubic", yincrease=False)
@@ -174,3 +174,8 @@
 penobscot_3d_gath_muted.isel(iline=5).data.mean("offset").T.plot.imshow(
     ax=axs[2], **plot_kwargs
 )
+
+# %% tags=[]
+# !pip list
+
+# %%

segysak/segy/_segy_core.py

@@ -4,7 +4,7 @@
 try:
     has_ipywidgets = importlib.util.find_spec("ipywidgets") is not None
     if has_ipywidgets:
-        from tqdm.autonotebook import tqdm
+        from tqdm.auto import tqdm
     else:
         from tqdm import tqdm as tqdm
 except ModuleNotFoundError:

setup.cfg

@@ -26,16 +26,17 @@ packages = find:
 include_package_data = True
 python_requires = >=3.7
 install_requires = 
-    numpy
+    numpy<1.24
     pandas
     matplotlib
     segyio
     xarray
     dask
     distributed
     tqdm
-    scipy
+    scipy!=1.10.0  # version introduced bug with interp
     click
+    pyzgy
     h5netcdf
     addict
     more-itertools>=8.0