Update dependencies

acoustic.ipynb

@@ -18,7 +18,7 @@
     "\n",
     "The notebook uses the dlisio library to investigate data from a sonic and an ultrasonic tool in an integrity well log file from the open [Volve Data Village dataset](https://data.equinor.com/dataset/Volve). The file in question is `WL_RAW_PROD_AC-AIMG-CCL-GR_2013-06-05_2.DLIS`, from well F-11 B. While investigating acoustic data from two specific tools is the main topic of this notebook, other types of data can be similarly investigated using dlisio.\n",
     "\n",
-    "This notebook is published under an [MIT license](https://github.com/equinor/dlisio-notebooks/blob/master/LICENSE) and the newest version was developed using `python 3.9.12`. All packages used in this notebook and their versions are listed in `requirements.txt` in the root folder of this repository. Run `pip install -r requirements.txt` if you wish to install all the correct versions. The newest version of this notebook can always be found [on github](https://github.com/equinor/dlisio-notebooks/blob/master/acoustic.ipynb).\n",
+    "This notebook is published under an [MIT license](https://github.com/equinor/dlisio-notebooks/blob/master/LICENSE) and the newest version was developed using `python 3.10.14`. All packages used in this notebook and their versions are listed in `requirements.txt` in the root folder of this repository. Run `pip install -r requirements.txt` if you wish to install all the correct versions. The newest version of this notebook can always be found [on github](https://github.com/equinor/dlisio-notebooks/blob/master/acoustic.ipynb).\n",
     "\n",
     "***Privacy note:*** *This notebook hides well log parameters that contain people's names. This is to avoid their names being tied to the log file by search engines without their explicit consent. Users of the notebook are of course free to uncomment the code lines that hide these names.*"
    ]
@@ -10370,7 +10370,7 @@
     "    return wf_E1s\n",
     "\n",
     "# Determine E1 from the upsampled windowed waveforms\n",
-    "window = signal.tukey(250, 20/250)\n",
+    "window = signal.windows.tukey(250, 20/250)\n",
     "upsampled_wfs, upsampled_wfs_t = signal.resample(window*curves20B['WF2'], 2500, wf_t, axis=1)\n",
     "k_window = 365 + np.arange(-20, 21)\n",
     "wf2_E1 = waveform_E1(upsampled_wfs, k_window)\n",
@@ -10424,7 +10424,7 @@
    "source": [
     "fig, axes = plt.subplots(ncols=2, figsize=(9,4))\n",
     "\n",
-    "cmap = copy.copy(mpl.cm.get_cmap('viridis'))\n",
+    "cmap = copy.copy(mpl.colormaps['viridis'])\n",
     "cmap.set_bad(cmap.colors[0])\n",
     "\n",
     "# Plot a 2D histogram of E_1 values against the values from the CBL channel, and show the scaling\n",
@@ -16469,7 +16469,7 @@
    ],
    "source": [
     "# Get a colormap that ensures that histogram bins with zero occurrences still have a colour\n",
-    "cmap = copy.copy(mpl.cm.get_cmap('viridis'))\n",
+    "cmap = copy.copy(mpl.colormaps['viridis'])\n",
     "cmap.set_bad(cmap.colors[0])\n",
     "\n",
     "# Plot the 2D histogram\n",

requirements.txt

@@ -1,8 +1,14 @@
-dlisio==0.3.6
-pandas==1.4.2
-numpy==1.22.3
-matplotlib==3.5.1
-scipy==1.7.3
-jupyter==1.0.0
-notebook==6.4.11
-azure-storage-blob==12.12.0
+dlisio==1.0.1
+pandas==2.2.2
+numpy==1.26.4
+matplotlib==3.9.0
+scipy==1.13.1
+notebook==7.2.0
+azure-storage-blob==12.20.0
+pyarrow==16.1.0 # suppresses deprecation warning by pandas
+cryptography>=42.0.4 # not directly required, pinned by Snyk to avoid a vulnerability
+fonttools>=4.43.0 # not directly required, pinned by Snyk to avoid a vulnerability
+ipython>=8.10.0 # not directly required, pinned by Snyk to avoid a vulnerability
+pillow>=10.3.0 # not directly required, pinned by Snyk to avoid a vulnerability
+setuptools>=65.5.1 # not directly required, pinned by Snyk to avoid a vulnerability
+tornado>=6.3.3 # not directly required, pinned by Snyk to avoid a vulnerability