diff --git a/conda-lock.yml b/conda-lock.yml
index 4415f959..246a31b4 100644
--- a/conda-lock.yml
+++ b/conda-lock.yml
@@ -13,7 +13,7 @@
 version: 1
 metadata:
   content_hash:
-    linux-64: 6cb587378623b3ba8266d069f2ae0be38a13bcc93af340aac311fb4ef322c202
+    linux-64: b7b524b1ba497b9648707a5bfb9c9dd4abb412a6b07af7b0472985be7ba39abe
   channels:
   - url: conda-forge
     used_env_vars: []
@@ -106,6 +106,19 @@ package:
     sha256: 62637ac498bcf47783cbf4f48e9b09e4e2f5a6ad42f43ca8f632c353827b94f4
   category: main
   optional: false
+- name: aom
+  version: 3.7.1
+  manager: conda
+  platform: linux-64
+  dependencies:
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/aom-3.7.1-h59595ed_0.conda
+  hash:
+    md5: 504e70332b8322cda93b7bceb5925fca
+    sha256: 57ad60805ffc7097a690d6d0e07ba432a3dae187158e13001c392177358478f9
+  category: main
+  optional: false
 - name: appdirs
   version: 1.4.4
   manager: conda
@@ -119,15 +132,15 @@ package:
   category: main
   optional: false
 - name: argcomplete
-  version: 3.1.6
+  version: 3.2.1
   manager: conda
   platform: linux-64
   dependencies:
     python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/argcomplete-3.1.6-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/argcomplete-3.2.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 62c3486961e43fb9b495b7854f48fea9b486b2176a9629c6faf80c445543b1aa
+    md5: 0801250abb3d5b86010e20324f0dde94
+    sha256: af221f16a23feea4d91db75b35c5720c9c448814af815fe6d45c5627eb75e897
   category: main
   optional: false
 - name: argon2-cffi
@@ -224,20 +237,20 @@ package:
   category: main
   optional: false
 - name: aws-c-auth
-  version: 0.7.7
+  version: 0.7.8
   manager: conda
   platform: linux-64
   dependencies:
     aws-c-cal: '>=0.6.9,<0.6.10.0a0'
-    aws-c-common: '>=0.9.8,<0.9.9.0a0'
+    aws-c-common: '>=0.9.10,<0.9.11.0a0'
     aws-c-http: '>=0.7.14,<0.7.15.0a0'
     aws-c-io: '>=0.13.36,<0.13.37.0a0'
-    aws-c-sdkutils: '>=0.1.12,<0.1.13.0a0'
+    aws-c-sdkutils: '>=0.1.13,<0.1.14.0a0'
     libgcc-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-auth-0.7.7-h4faf3ed_1.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-auth-0.7.8-h538f98c_2.conda
   hash:
-    md5: e2a9f779fafe385cd516c079e7c9a36b
-    sha256: 2647adb3ef4373e545308791020d6fbbeff4b57a3a1bb9f82dfc89ddf56e458e
+    md5: d42aebb91e28e2fee2a0218cfbff2c90
+    sha256: b06ef95458fc70af4230c9c6690011235cd25288752ff7aa25492fc6d1c0e028
   category: main
   optional: false
 - name: aws-c-cal
@@ -245,25 +258,25 @@ package:
   manager: conda
   platform: linux-64
   dependencies:
-    aws-c-common: '>=0.9.8,<0.9.9.0a0'
+    aws-c-common: '>=0.9.10,<0.9.11.0a0'
     libgcc-ng: '>=12'
-    openssl: '>=3.1.4,<4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-cal-0.6.9-h3b91eb8_1.conda
+    openssl: '>=3.2.0,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-cal-0.6.9-h5d48c4d_2.conda
   hash:
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-    sha256: 8bca41960971a2f6eea0d61a30e6d8b1bf80f520b5959aba92b87d1385d3d0cd
+    md5: 9e51dfd5da37c1817d2a850188861987
+    sha256: ec56734a24eee51e2f89bec3d686dd2c4dbb09d0305248b1d14e4c748065dc23
   category: main
   optional: false
 - name: aws-c-common
-  version: 0.9.8
+  version: 0.9.10
   manager: conda
   platform: linux-64
   dependencies:
     libgcc-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.9.8-hd590300_0.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.9.10-hd590300_0.conda
   hash:
-    md5: 1fd5f2ae093f2dbf28dc4f18fca57309
-    sha256: 09075cb426a0b903b7ca86e4f399eb0be02b6d24e403792a5f378064fcb7a08b
+    md5: 93729f7a54b25cb135ac2b67ea3a7603
+    sha256: dba8a20acedc6bc3574e4068c196969881462ad831aae267d25fbc9409785a6b
   category: main
   optional: false
 - name: aws-c-compression
@@ -271,12 +284,12 @@ package:
   manager: conda
   platform: linux-64
   dependencies:
-    aws-c-common: '>=0.9.8,<0.9.9.0a0'
+    aws-c-common: '>=0.9.10,<0.9.11.0a0'
     libgcc-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-compression-0.2.17-hfd9eb17_6.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-compression-0.2.17-h7f92143_7.conda
   hash:
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-    sha256: d67e50aff37474eee393346d71c9e4bbb6d190f86722ac932b2837acfea33f76
+    md5: c55a1a0c1419fcdfce6d21c41b0f92ab
+    sha256: ce508018c1109d4e5c6b65695639deaa2beea31edc39145bb810efb13ffed2c3
   category: main
   optional: false
 - name: aws-c-event-stream
@@ -284,15 +297,15 @@ package:
   manager: conda
   platform: linux-64
   dependencies:
-    aws-c-common: '>=0.9.8,<0.9.9.0a0'
+    aws-c-common: '>=0.9.10,<0.9.11.0a0'
     aws-c-io: '>=0.13.36,<0.13.37.0a0'
     aws-checksums: '>=0.1.17,<0.1.18.0a0'
     libgcc-ng: '>=12'
     libstdcxx-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-event-stream-0.3.2-h1fff966_7.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-event-stream-0.3.2-h0bcb0bb_8.conda
   hash:
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-    sha256: abade13c6c6b480bc68ba11d2616f81951207ce44115ac10d237c38251641380
+    md5: 21dafb60b5854f82b196f32e5857dec6
+    sha256: d2855cd791a95648ac773aa6561c61f9e77450f123c8aa82eea1d66e90d5bfb1
   category: main
   optional: false
 - name: aws-c-http
@@ -301,14 +314,14 @@ package:
   platform: linux-64
   dependencies:
     aws-c-cal: '>=0.6.9,<0.6.10.0a0'
-    aws-c-common: '>=0.9.8,<0.9.9.0a0'
+    aws-c-common: '>=0.9.10,<0.9.11.0a0'
     aws-c-compression: '>=0.2.17,<0.2.18.0a0'
     aws-c-io: '>=0.13.36,<0.13.37.0a0'
     libgcc-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-http-0.7.14-hc86c171_2.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-http-0.7.14-hd268abd_3.conda
   hash:
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-    sha256: e29a5b81731995634338ced49d241c77f820df37977ab932a637351efc94adba
+    md5: 0b0f7174a0f94d2c9a02fb24f6fc0d00
+    sha256: ff7e6252a299a59b7e6494723ef3043ba31643ec2a750b8593037bc757a2c4fa
   category: main
   optional: false
 - name: aws-c-io
@@ -317,13 +330,13 @@ package:
   platform: linux-64
   dependencies:
     aws-c-cal: '>=0.6.9,<0.6.10.0a0'
-    aws-c-common: '>=0.9.8,<0.9.9.0a0'
+    aws-c-common: '>=0.9.10,<0.9.11.0a0'
     libgcc-ng: '>=12'
-    s2n: '>=1.3.56,<1.3.57.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-io-0.13.36-hc23c90e_0.conda
+    s2n: '>=1.4.0,<1.4.1.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-io-0.13.36-he0cd244_2.conda
   hash:
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-    sha256: b3fe3214b11f3cf3c631bef0be09f88610103c0262225a368914ce149533900d
+    md5: c930336aa72995f1b5459b51df3ba841
+    sha256: 7426f7444cd43cd7a649670c7330c163b40f40aa832e82be873d9de91e49b05e
   category: main
   optional: false
 - name: aws-c-mqtt
@@ -331,46 +344,46 @@ package:
   manager: conda
   platform: linux-64
   dependencies:
-    aws-c-common: '>=0.9.8,<0.9.9.0a0'
+    aws-c-common: '>=0.9.10,<0.9.11.0a0'
     aws-c-http: '>=0.7.14,<0.7.15.0a0'
     aws-c-io: '>=0.13.36,<0.13.37.0a0'
     libgcc-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-mqtt-0.9.10-hba57965_1.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-mqtt-0.9.10-h35285c7_2.conda
   hash:
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-    sha256: 803ddbb520a706f8b43283f37640e1b37b132b399ceef76abb8f4b309933400e
+    md5: 0cca0a3d7dc82f219ac46635478952f6
+    sha256: 246276b22393302b4e9acb934ec40bb78d3be74e7bd2c110272b46c5370a60ee
   category: main
   optional: false
 - name: aws-c-s3
-  version: 0.4.1
+  version: 0.4.4
   manager: conda
   platform: linux-64
   dependencies:
-    aws-c-auth: '>=0.7.7,<0.7.8.0a0'
+    aws-c-auth: '>=0.7.8,<0.7.9.0a0'
     aws-c-cal: '>=0.6.9,<0.6.10.0a0'
-    aws-c-common: '>=0.9.8,<0.9.9.0a0'
+    aws-c-common: '>=0.9.10,<0.9.11.0a0'
     aws-c-http: '>=0.7.14,<0.7.15.0a0'
     aws-c-io: '>=0.13.36,<0.13.37.0a0'
     aws-checksums: '>=0.1.17,<0.1.18.0a0'
     libgcc-ng: '>=12'
-    openssl: '>=3.1.4,<4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-s3-0.4.1-hfadff92_0.conda
+    openssl: '>=3.2.0,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-s3-0.4.4-h0448019_0.conda
   hash:
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-    sha256: 71832dc68eccdb70b06fc195a4f71304893f844131d8d165b308ad34eb79dfe1
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+    sha256: 04142edf1a574e137a9e30a4f4e9b9448e219b6f4216a782ceaed933f27852a6
   category: main
   optional: false
 - name: aws-c-sdkutils
-  version: 0.1.12
+  version: 0.1.13
   manager: conda
   platform: linux-64
   dependencies:
-    aws-c-common: '>=0.9.8,<0.9.9.0a0'
+    aws-c-common: '>=0.9.10,<0.9.11.0a0'
     libgcc-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-sdkutils-0.1.12-hfd9eb17_5.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-sdkutils-0.1.13-h7f92143_0.conda
   hash:
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+    sha256: 8696e7023fde7c4588db8aedd08ffc0b4041c8449bd9edd50f237534cbcfac93
   category: main
   optional: false
 - name: aws-checksums
@@ -378,68 +391,68 @@ package:
   manager: conda
   platform: linux-64
   dependencies:
-    aws-c-common: '>=0.9.8,<0.9.9.0a0'
+    aws-c-common: '>=0.9.10,<0.9.11.0a0'
     libgcc-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-checksums-0.1.17-hfd9eb17_5.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-checksums-0.1.17-h7f92143_6.conda
   hash:
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-    sha256: fa197cea5d34038066ac743ffa3ae688c057152fff55226ec740c5f68a136282
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+    sha256: ac2082211e7d5fd3036f9abd7e398ef67d5327efb3808f17a30fcab59acacbfb
   category: main
   optional: false
 - name: aws-crt-cpp
-  version: 0.24.7
+  version: 0.24.11
   manager: conda
   platform: linux-64
   dependencies:
-    aws-c-auth: '>=0.7.7,<0.7.8.0a0'
+    aws-c-auth: '>=0.7.8,<0.7.9.0a0'
     aws-c-cal: '>=0.6.9,<0.6.10.0a0'
-    aws-c-common: '>=0.9.8,<0.9.9.0a0'
+    aws-c-common: '>=0.9.10,<0.9.11.0a0'
     aws-c-event-stream: '>=0.3.2,<0.3.3.0a0'
     aws-c-http: '>=0.7.14,<0.7.15.0a0'
     aws-c-io: '>=0.13.36,<0.13.37.0a0'
     aws-c-mqtt: '>=0.9.10,<0.9.11.0a0'
-    aws-c-s3: '>=0.4.1,<0.4.2.0a0'
-    aws-c-sdkutils: '>=0.1.12,<0.1.13.0a0'
+    aws-c-s3: '>=0.4.4,<0.4.5.0a0'
+    aws-c-sdkutils: '>=0.1.13,<0.1.14.0a0'
     libgcc-ng: '>=12'
     libstdcxx-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-crt-cpp-0.24.7-h97e63c7_6.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-crt-cpp-0.24.11-h5bdc202_2.conda
   hash:
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+    sha256: 8fbbc276d379eca4de1d30bff8f3103a25b51acbfd1706a2fb3c9473b52e12b3
   category: main
   optional: false
 - name: aws-sdk-cpp
-  version: 1.11.182
+  version: 1.11.210
   manager: conda
   platform: linux-64
   dependencies:
-    aws-c-common: '>=0.9.8,<0.9.9.0a0'
+    aws-c-common: '>=0.9.10,<0.9.11.0a0'
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-    aws-crt-cpp: '>=0.24.7,<0.24.8.0a0'
-    libcurl: '>=8.4.0,<9.0a0'
+    aws-crt-cpp: '>=0.24.11,<0.24.12.0a0'
+    libcurl: '>=8.5.0,<9.0a0'
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     libstdcxx-ng: '>=12'
     libzlib: '>=1.2.13,<1.3.0a0'
-    openssl: '>=3.1.4,<4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/aws-sdk-cpp-1.11.182-h8beafcf_7.conda
+    openssl: '>=3.2.0,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/aws-sdk-cpp-1.11.210-h967ea9e_4.conda
   hash:
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+    sha256: bda4ae2b0207975123a81a24d733dd37894b268d264e5c898b6e716a47538ea1
   category: main
   optional: false
 - name: babel
-  version: 2.13.1
+  version: 2.14.0
   manager: conda
   platform: linux-64
   dependencies:
     python: '>=3.7'
     pytz: ''
     setuptools: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/babel-2.13.1-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/babel-2.14.0-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
 - name: backoff
@@ -516,22 +529,22 @@ package:
   category: main
   optional: false
 - name: boto3
-  version: 1.33.4
+  version: 1.33.13
   manager: conda
   platform: linux-64
   dependencies:
-    botocore: '>=1.33.4,<1.34.0'
+    botocore: '>=1.33.13,<1.34.0'
     jmespath: '>=0.7.1,<2.0.0'
     python: '>=3.7'
     s3transfer: '>=0.8.2,<0.9.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/boto3-1.33.4-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/boto3-1.33.13-pyhd8ed1ab_0.conda
   hash:
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-    sha256: cb63cadfb3c593cb7295b14450e4310af88d32dc1bbf185ec82a325a12e86f28
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   optional: false
 - name: botocore
-  version: 1.33.5
+  version: 1.33.13
   manager: conda
   platform: linux-64
   dependencies:
@@ -539,10 +552,39 @@ package:
     python: '>=3.7'
     python-dateutil: '>=2.1,<3.0.0'
     urllib3: '>=1.25.4,<1.27'
-  url: https://conda.anaconda.org/conda-forge/noarch/botocore-1.33.5-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/botocore-1.33.13-pyhd8ed1ab_0.conda
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+    sha256: 498d08274880ef279e9a6dd68f66b384d71321d92301fa60330712f9edceab0c
+  category: main
+  optional: false
+- name: brotli
+  version: 1.1.0
+  manager: conda
+  platform: linux-64
+  dependencies:
+    brotli-bin: 1.1.0
+    libbrotlidec: 1.1.0
+    libbrotlienc: 1.1.0
+    libgcc-ng: '>=12'
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+  manager: conda
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+    libbrotlienc: 1.1.0
+    libgcc-ng: '>=12'
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   category: main
   optional: false
+- name: brunsli
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+  manager: conda
+  platform: linux-64
+  dependencies:
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+    libgcc-ng: '>=9.3.0'
+    libstdcxx-ng: '>=9.3.0'
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   category: main
   optional: false
+- name: c-blosc2
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+  manager: conda
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+    zlib-ng: '>=2.0.7,<2.1.0a0'
+    zstd: '>=1.5.5,<1.6.0a0'
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   version: 2023.11.17
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+  version: 4.3.1
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+  url: https://conda.anaconda.org/conda-forge/linux-64/cfitsio-4.3.1-hbdc6101_0.conda
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+    libstdcxx-ng: '>=12'
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 - name: cryptography
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+  version: 41.0.7
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     python_abi: 3.11.*
-  url: https://conda.anaconda.org/conda-forge/linux-64/cryptography-41.0.5-py311h63ff55d_0.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/cryptography-41.0.7-py311hcb13ee4_1.conda
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     libstdcxx-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-12.0.107-h59595ed_6.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-12.0.107-hd3aeb46_7.conda
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-  url: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_linux-64-12.0.107-h59595ed_6.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_linux-64-12.0.107-h59595ed_7.conda
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     libstdcxx-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvrtc-12.0.76-h59595ed_1.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvrtc-12.0.76-hd3aeb46_2.conda
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     libstdcxx-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvtx-12.0.76-hcb278e6_0.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvtx-12.0.76-h59595ed_1.conda
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+  version: 2023.12.0
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     toolz: '>=0.10.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/dask-core-2023.11.0-pyhd8ed1ab_0.conda
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   category: main
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 - name: distlib
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+  version: 0.3.8
   manager: conda
   platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/distlib-0.3.7-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/distlib-0.3.8-pyhd8ed1ab_0.conda
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+  manager: conda
+  platform: linux-64
+  dependencies:
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+    six: '>=1.4.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/docker-pycreds-0.4.0-py_0.tar.bz2
   hash:
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 - name: docstring_parser
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 - name: dulwich
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+  version: 0.21.7
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     python_abi: 3.11.*
     urllib3: '>=1.25'
-  url: https://conda.anaconda.org/conda-forge/linux-64/dulwich-0.21.6-py311h459d7ec_2.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/dulwich-0.21.7-py311h459d7ec_0.conda
   hash:
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 - name: fastapi
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+  version: 0.105.0
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     typing-extensions: '>=4.8.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/fastapi-0.104.1-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/fastapi-0.105.0-pyhd8ed1ab_0.conda
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   platform: linux-64
   dependencies:
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-    click: '>=4.0'
+    attrs: '>=19.2.0'
+    click: '>=8.0,<9.dev0'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/fiona-1.9.5-py311hbac4ec9_0.conda
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+  version: 3.8.1
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   category: main
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+    pillow: '>=8.3.2'
+    python: '>=3'
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+  version: 7.0.0
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     zipp: '>=0.5'
-  url: https://conda.anaconda.org/conda-forge/noarch/importlib-metadata-6.8.0-pyha770c72_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/importlib-metadata-7.0.0-pyha770c72_0.conda
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 - name: importlib-resources
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+  version: 7.0.0
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+    importlib-metadata: '>=7.0.0,<7.0.1.0a0'
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     pexpect: '>4.3'
     pickleshare: ''
-    prompt-toolkit: '>=3.0.30,<3.1.0,!=3.0.37'
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+  url: https://conda.anaconda.org/conda-forge/noarch/ipython-8.18.1-pyh707e725_3.conda
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+  version: 2.12.1
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     websocket-client: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.11.1-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.12.1-pyhd8ed1ab_0.conda
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+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server_terminals-0.5.0-pyhd8ed1ab_0.conda
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   category: main
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+  manager: conda
+  platform: linux-64
+  dependencies:
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+  url: https://conda.anaconda.org/conda-forge/linux-64/jxrlib-1.1-h7f98852_2.tar.bz2
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     libstdcxx-ng: '>=12'
   url: https://conda.anaconda.org/conda-forge/linux-64/kealib-1.5.2-hcd42e92_1.conda
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   category: main
   optional: false
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+  manager: conda
+  platform: linux-64
+  dependencies:
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+  url: https://conda.anaconda.org/conda-forge/noarch/lazy_loader-0.3-pyhd8ed1ab_0.conda
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libarrow-14.0.1-h2b6da2a_4_cpu.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libarrow-14.0.1-h0f82fcc_9_cpu.conda
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libarrow-acero-14.0.1-h59595ed_4_cpu.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libarrow-acero-14.0.1-h59595ed_9_cpu.conda
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libarrow-dataset-14.0.1-h59595ed_4_cpu.conda
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libarrow-flight-14.0.1-h120cb0d_4_cpu.conda
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libarrow-flight-sql-14.0.1-h61ff412_4_cpu.conda
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libarrow-substrait-14.0.1-h61ff412_4_cpu.conda
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-    cuda-version: '>=12.0.0,<12.1.0a0'
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     libgcc-ng: '>=12'
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   dependencies:
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-    cuda-version: '>=12.0.0,<12.1.0a0'
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   dependencies:
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-    cuda-version: '>=12.0.0,<12.1.0a0'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libcusparse-12.0.0.76-hcb278e6_1.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libcusparse-12.0.0.76-hd3aeb46_2.conda
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 - name: libdeflate
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   platform: linux-64
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libev-4.33-h516909a_1.tar.bz2
+    libgcc-ng: '>=12'
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   optional: false
 - name: libevent
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 - name: libgdal
-  version: 3.7.3
+  version: 3.8.1
   manager: conda
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@@ -2894,28 +3100,28 @@ package:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libgdal-3.7.3-h73cd2e6_7.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libgdal-3.8.1-hed8bd54_4.conda
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   category: main
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 - name: libgfortran-ng
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 - name: libglib
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     libzlib: '>=1.2.13,<1.3.0a0'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.78.1-h783c2da_1.conda
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 - name: libgoogle-cloud
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   category: main
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-- name: libhwloc
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.17-h166bdaf_0.tar.bz2
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 - name: libjpeg-turbo
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+    zstd: '>=1.5.5,<1.6.0a0'
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 - name: libmagma
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-    openssl: '>=3.1.2,<4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libnetcdf-4.9.2-nompi_h80fb2b6_112.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libnetcdf-4.9.2-nompi_h9612171_113.conda
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.58.0-h47da74e_0.conda
+    openssl: '>=3.2.0,<4.0a0'
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 - name: libnsl
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   dependencies:
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-    cuda-version: '>=12.0.0,<12.1.0a0'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libnvjitlink-12.0.76-hcb278e6_1.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libnvjitlink-12.0.76-hd3aeb46_2.conda
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 - name: libopenblas
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libparquet-14.0.1-h352af49_4_cpu.conda
+    openssl: '>=3.2.0,<4.0a0'
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 - name: libpng
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libpq-16.1-hfc447b1_0.conda
+    openssl: '>=3.2.0,<4.0a0'
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-    proj: '>=9.3.0,<9.3.1.0a0'
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     zlib: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/libspatialite-5.1.0-h7385560_2.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libspatialite-5.1.0-h7bd4643_4.conda
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 - name: libsqlite
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 - name: libxml2
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+  version: 2.12.3
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     websocket-client: ''
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     attrs: '>=22.2.0'
     python: '>=3.8'
     rpds-py: '>=0.7.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/referencing-0.31.1-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/referencing-0.32.0-pyhd8ed1ab_0.conda
   hash:
-    md5: ae08039cf63eb82637b867aea3f04758
-    sha256: efb91b7d2f6e729c01676e52e99071db819628a9f0a3a519c8969f0d2350a371
+    md5: a7b5a535cd614e384594530aee7e6061
+    sha256: dfd40282910a45e58882ed94b502b2a09f475efb04eaaa3bd8b3b5a9b21a19c3
   category: main
   optional: false
 - name: regex
@@ -5259,16 +5530,16 @@ package:
   category: main
   optional: false
 - name: s2n
-  version: 1.3.56
+  version: 1.4.0
   manager: conda
   platform: linux-64
   dependencies:
     libgcc-ng: '>=12'
-    openssl: '>=3.1.4,<4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/s2n-1.3.56-h06160fa_0.conda
+    openssl: '>=3.2.0,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/s2n-1.4.0-h06160fa_0.conda
   hash:
-    md5: 04b4845b9e9b5a0ee6eba013ecdbbddb
-    sha256: 4c00411d49fefc6a53167c3120e386b3f35510544a44d2e647615b510a622f29
+    md5: 3d1b58d2664d96f9fbc0afe5e1d04632
+    sha256: f6cc2bdcb5d809bbaae218e03bdefef4a309d1fc7ccc9444fda59bd4553a83f8
   category: main
   optional: false
 - name: s3transfer
@@ -5315,6 +5586,30 @@ package:
     sha256: 02b16dea74388db9d1a58ad83c758d8dbd1b8c58c148ca247724baa3fad33962
   category: main
   optional: false
+- name: scikit-image
+  version: 0.22.0
+  manager: conda
+  platform: linux-64
+  dependencies:
+    imageio: '>=2.27'
+    lazy_loader: '>=0.2'
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    networkx: '>=2.8'
+    numpy: '>=1.23.5,<2.0a0'
+    packaging: '>=21'
+    pillow: '>=9.0.1'
+    python: '>=3.11,<3.12.0a0'
+    python_abi: 3.11.*
+    pywavelets: '>=1.1.1'
+    scipy: '>=1.8'
+    tifffile: '>=2022.8.12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.22.0-py311h320fe9a_2.conda
+  hash:
+    md5: e94b7f09b52628b89e66cdbd8c3029dd
+    sha256: a7ef0c71a7defbc87b5ece4592624aeeab6424dc199795fa3de61a0d69c5b8ae
+  category: main
+  optional: false
 - name: scipy
   version: 1.11.4
   manager: conda
@@ -5365,6 +5660,34 @@ package:
     sha256: e74d3faf51a6cc429898da0209d95b209270160f3edbf2f6d8b61a99428301cd
   category: main
   optional: false
+- name: sentry-sdk
+  version: 1.39.0
+  manager: conda
+  platform: linux-64
+  dependencies:
+    certifi: ''
+    python: '>=3.7'
+    urllib3: '>=1.25.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/sentry-sdk-1.39.0-pyhd8ed1ab_0.conda
+  hash:
+    md5: c9cf03170f08f8c27a792572c19a6925
+    sha256: c91ab95dab71f76618d9d90cfdc3fdcf8f7189fece57d111f19ddc67f65f9c0e
+  category: main
+  optional: false
+- name: setproctitle
+  version: 1.3.3
+  manager: conda
+  platform: linux-64
+  dependencies:
+    libgcc-ng: '>=12'
+    python: '>=3.11,<3.12.0a0'
+    python_abi: 3.11.*
+  url: https://conda.anaconda.org/conda-forge/linux-64/setproctitle-1.3.3-py311h459d7ec_0.conda
+  hash:
+    md5: 82a78657a66e78c04e614ceb772ee8da
+    sha256: f5c0ffdcaad92565d7041c27084a2263653d8287daf9a41c023a460d776acb72
+  category: main
+  optional: false
 - name: setuptools
   version: 68.2.2
   manager: conda
@@ -5568,6 +5891,19 @@ package:
     sha256: 4a500ac0a9fe56cee7958d6d0f6530272c43ee4c16c52600001decb39fe3cd59
   category: main
   optional: false
+- name: svt-av1
+  version: 1.8.0
+  manager: conda
+  platform: linux-64
+  dependencies:
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/svt-av1-1.8.0-h59595ed_0.conda
+  hash:
+    md5: a9fb862e9d3beb0ebc61c10806056a7d
+    sha256: 6d64facdcdaadc5a3e5e4382ee195b4fde3c84ae3d4156fdd9b78ba7de358ba7
+  category: main
+  optional: false
 - name: sympy
   version: '1.12'
   manager: conda
@@ -5584,17 +5920,16 @@ package:
   category: main
   optional: false
 - name: tbb
-  version: 2021.10.0
+  version: 2021.7.0
   manager: conda
   platform: linux-64
   dependencies:
     libgcc-ng: '>=12'
-    libhwloc: '>=2.9.3,<2.9.4.0a0'
     libstdcxx-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/tbb-2021.10.0-h00ab1b0_2.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/tbb-2021.7.0-h924138e_0.tar.bz2
   hash:
-    md5: eb0d5c122f42714f86a7058d1ce7b2e6
-    sha256: 79a6c48fa1df661af7ab3e4f5fa444dd305d87921be017413a8b97fd6d642328
+    md5: 819421f81b127a5547bf96ad57eccdd9
+    sha256: 452a6def24912d2a118d863095c3f9cb05fe5c997357431a0ca4452eb7f65f08
   category: main
   optional: false
 - name: terminado
@@ -5612,25 +5947,40 @@ package:
     sha256: e90139ef15ea9d75a69cd6b6302c29ed5b01c03ddfa717b71acb32b60af74269
   category: main
   optional: false
+- name: tifffile
+  version: 2023.12.9
+  manager: conda
+  platform: linux-64
+  dependencies:
+    imagecodecs: '>=2023.8.12'
+    numpy: '>=1.19.2'
+    python: '>=3.9'
+  url: https://conda.anaconda.org/conda-forge/noarch/tifffile-2023.12.9-pyhd8ed1ab_0.conda
+  hash:
+    md5: 454bc0aff84f35fa53ba9e0369737a9b
+    sha256: 4786325cea8790d0b19d52ae575afd640fc8a5000fb75470edb7fcf00647dbbd
+  category: main
+  optional: false
 - name: tiledb
-  version: 2.16.3
+  version: 2.18.2
   manager: conda
   platform: linux-64
   dependencies:
     bzip2: '>=1.0.8,<2.0a0'
-    libabseil: '>=20230802.0,<20230803.0a0'
+    libabseil: '>=20230802.1,<20230803.0a0'
+    libcurl: '>=8.5.0,<9.0a0'
     libgcc-ng: '>=12'
     libgoogle-cloud: '>=2.12.0,<2.13.0a0'
     libstdcxx-ng: '>=12'
-    libxml2: '>=2.11.5,<2.12.0a0'
+    libxml2: '>=2.12.2,<2.13.0a0'
     libzlib: '>=1.2.13,<1.3.0a0'
     lz4-c: '>=1.9.3,<1.10.0a0'
-    openssl: '>=3.1.2,<4.0a0'
+    openssl: '>=3.2.0,<4.0a0'
     zstd: '>=1.5.5,<1.6.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/tiledb-2.16.3-h8c794c1_3.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/tiledb-2.18.2-hc1131af_2.conda
   hash:
-    md5: 7de728789b0aba16018f726dc5ddbec2
-    sha256: f021df4b9cfd1a54aac87a6c0bac604edc8ffb36d5b2c4aa20bf2d759ae04a11
+    md5: d86a5ef28245c435828b3f2ef1ee3f28
+    sha256: 58c0d9906ceda465b0d44ef4878e4a2e22512670bf7b12023d7495d3fd988bdc
   category: main
   optional: false
 - name: tinycss2
@@ -5717,7 +6067,7 @@ package:
   manager: conda
   platform: linux-64
   dependencies:
-    aws-sdk-cpp: '>=1.11.182,<1.11.183.0a0'
+    aws-sdk-cpp: '>=1.11.210,<1.11.211.0a0'
     libgcc-ng: '>=12'
     libstdcxx-ng: '>=12'
     python: '>=3.11,<3.12.0a0'
@@ -5725,27 +6075,27 @@ package:
     pytorch: '>=2.1.0,<2.2.0a0'
     requests: ''
     urllib3: '>=1.25'
-  url: https://conda.anaconda.org/conda-forge/linux-64/torchdata-0.7.1-py311ha8bf654_0.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/torchdata-0.7.1-py311h85129bf_1.conda
   hash:
-    md5: fa7532ed041ab78a5eee52d2e6b80b12
-    sha256: 2c64eace1fddfc07d2307d34711b7c1af167a44b73a0b2649e30704035348356
+    md5: b99e8a345639aeaa0c98c0db5851159f
+    sha256: d52efdb064a8aa345c4146f590a0a94ca918b36dae5b26a57ff78dfc60d18bff
   category: main
   optional: false
 - name: torchmetrics
-  version: 1.2.0
+  version: 1.2.1
   manager: conda
   platform: linux-64
   dependencies:
     lightning-utilities: '>=0.8.0'
     numpy: '>1.20.0'
-    packaging: ''
+    packaging: '>17.1'
     python: '>=3.7'
     pytorch: '>=1.8.1'
     setuptools: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/torchmetrics-1.2.0-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/torchmetrics-1.2.1-pyhd8ed1ab_0.conda
   hash:
-    md5: e8ab9fbd0174c2f1392c38d848c53956
-    sha256: 126e5d02c25e82e537b2448af1220878085fda5f081c13eebb4a91a19895ac98
+    md5: f6468e9ea893241ad7b8eae519f7e3a5
+    sha256: 26abe526d9514f096f196628ede28fb10d8e65cc19350b3be19f7bc465a22cec
   category: main
   optional: false
 - name: tornado
@@ -5851,27 +6201,27 @@ package:
   category: main
   optional: false
 - name: typing-extensions
-  version: 4.8.0
+  version: 4.9.0
   manager: conda
   platform: linux-64
   dependencies:
-    typing_extensions: 4.8.0
-  url: https://conda.anaconda.org/conda-forge/noarch/typing-extensions-4.8.0-hd8ed1ab_0.conda
+    typing_extensions: 4.9.0
+  url: https://conda.anaconda.org/conda-forge/noarch/typing-extensions-4.9.0-hd8ed1ab_0.conda
   hash:
-    md5: 384462e63262a527bda564fa2d9126c0
-    sha256: d6e1dddd0c372218ef15912383d351ac8c73465cbf16238017f0269813cafe2d
+    md5: c16524c1b7227dc80b36b4fa6f77cc86
+    sha256: d795c1eb1db4ea147f01ece74e5a504d7c2e8d5ee8c11ec987884967dd938f9c
   category: main
   optional: false
 - name: typing_extensions
-  version: 4.8.0
+  version: 4.9.0
   manager: conda
   platform: linux-64
   dependencies:
     python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.8.0-pyha770c72_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.9.0-pyha770c72_0.conda
   hash:
-    md5: 5b1be40a26d10a06f6d4f1f9e19fa0c7
-    sha256: 38d16b5c53ec1af845d37d22e7bb0e6c934c7f19499123507c5a470f6f8b7dde
+    md5: a92a6440c3fe7052d63244f3aba2a4a7
+    sha256: f3c5be8673bfd905c4665efcb27fa50192f24f84fa8eff2f19cba5d09753d905
   category: main
   optional: false
 - name: typing_utils
@@ -5919,11 +6269,11 @@ package:
     libgcc-ng: '>=12'
     libnuma: '>=2.0.16,<3.0a0'
     libstdcxx-ng: '>=12'
-    rdma-core: '>=48.0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/ucx-1.15.0-h115f88d_1.conda
+    rdma-core: '>=49'
+  url: https://conda.anaconda.org/conda-forge/linux-64/ucx-1.15.0-h6d2d1ec_2.conda
   hash:
-    md5: db13bfa54b060c8c1bc769fa603ed003
-    sha256: bd2b628463fc72a863e10b14f67a161e8f05bf424e3915a6ba3dbbd73ec6d76d
+    md5: 7f74ff71d40e5eba3da56f9e57cf4b25
+    sha256: 9c05d20297a8f761380b5abbd683ea22161b9136f61c05934b732e3eab3a3e4e
   category: main
   optional: false
 - name: uri-template
@@ -5993,7 +6343,7 @@ package:
   category: main
   optional: false
 - name: virtualenv
-  version: 20.24.7
+  version: 20.25.0
   manager: conda
   platform: linux-64
   dependencies:
@@ -6001,10 +6351,35 @@ package:
     filelock: <4,>=3.12.2
     platformdirs: <5,>=3.9.1
     python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.24.7-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.25.0-pyhd8ed1ab_0.conda
+  hash:
+    md5: c119653cba436d8183c27bf6d190e587
+    sha256: 50827c3721a9dbf973b568709d4381add2a6552fa562f26a385c5edc16a534af
+  category: main
+  optional: false
+- name: wandb
+  version: 0.15.12
+  manager: conda
+  platform: linux-64
+  dependencies:
+    appdirs: '>=1.4.3'
+    click: '>=7.1,!=8.0.0'
+    docker-pycreds: '>=0.4.0'
+    gitpython: '>=1.0.0,!=3.1.29'
+    pathtools: ''
+    protobuf: '>=3.19.0,!=4.21.0,<5'
+    psutil: '>=5.0.0'
+    python: '>=3.7'
+    pyyaml: ''
+    requests: '>=2.0.0,<3'
+    sentry-sdk: '>=1.0.0'
+    setproctitle: ''
+    setuptools: ''
+    typing_extensions: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/wandb-0.15.12-pyhd8ed1ab_0.conda
   hash:
-    md5: db990278c2c00b268eed778de44f6057
-    sha256: ad661ae59c64bd73c25dfadb00c601659f4d9cafbf428e36a690075e52bac96a
+    md5: fa93cd3b1f3311ddd07df0a393e18c19
+    sha256: c2f10522299816dc4d39f6aa7346651ae4eeac2140745619dd318451bcd2b91b
   category: main
   optional: false
 - name: wcwidth
@@ -6044,15 +6419,15 @@ package:
   category: main
   optional: false
 - name: websocket-client
-  version: 1.6.4
+  version: 1.7.0
   manager: conda
   platform: linux-64
   dependencies:
     python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/websocket-client-1.6.4-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/websocket-client-1.7.0-pyhd8ed1ab_0.conda
   hash:
-    md5: bdb77b28cf16deac0eef431a068320e8
-    sha256: df45b89862edcd7cd5180ec7b8c0c0ca9fb4d3f7d49ddafccdc76afcf50d8da6
+    md5: 50ad31e07d706aae88b14a4ac9c73f23
+    sha256: d9b537d5b7c5aa7a02a4ce4c6b755e458bd8083b67752a73c92d113ccec6c10f
   category: main
   optional: false
 - name: websockets
@@ -6070,7 +6445,7 @@ package:
   category: main
   optional: false
 - name: xarray
-  version: 2023.11.0
+  version: 2023.12.0
   manager: conda
   platform: linux-64
   dependencies:
@@ -6078,10 +6453,10 @@ package:
     packaging: '>=21.3'
     pandas: '>=1.4'
     python: '>=3.9'
-  url: https://conda.anaconda.org/conda-forge/noarch/xarray-2023.11.0-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/xarray-2023.12.0-pyhd8ed1ab_0.conda
   hash:
-    md5: f445b20bac3db8f604a48592087b2d8f
-    sha256: 71a2000fd5f5065e8c9a184c3f9262b27c4a5eeb5366a6d7e4d267d28e9f07d9
+    md5: e9b31d3ab1b0dd5fd8c24419f6560b90
+    sha256: ab89b70aa3d31a9cacf0e91a7c7a6f8cc45d866d71cdcee1219561cff0e8a9a5
   category: main
   optional: false
 - name: xerces-c
@@ -6324,6 +6699,20 @@ package:
     sha256: 53bf2a18224406e9806adb3b270a2c8a028aca0c89bd40114a85d6446f5c98d1
   category: main
   optional: false
+- name: zfp
+  version: 1.0.0
+  manager: conda
+  platform: linux-64
+  dependencies:
+    _openmp_mutex: '>=4.5'
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/zfp-1.0.0-h59595ed_4.conda
+  hash:
+    md5: 9cfbafab420f42b572f3c032ad59da85
+    sha256: 9ab5aa62493ebe544514783a9a05b933eb3c9f2bc51ace9be8aa91e875a8387c
+  category: main
+  optional: false
 - name: zipp
   version: 3.17.0
   manager: conda
@@ -6349,6 +6738,18 @@ package:
     sha256: 9887a04d7e7cb14bd2b52fa01858f05a6d7f002c890f618d9fcd864adbfecb1b
   category: main
   optional: false
+- name: zlib-ng
+  version: 2.0.7
+  manager: conda
+  platform: linux-64
+  dependencies:
+    libgcc-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/zlib-ng-2.0.7-h0b41bf4_0.conda
+  hash:
+    md5: 49e8329110001f04923fe7e864990b0c
+    sha256: 6b3a22b7cc219e8d83f16c1ceba67aa51e0b7e3bcc4a647b97a0a510559b0477
+  category: main
+  optional: false
 - name: zstd
   version: 1.5.5
   manager: conda
diff --git a/environment.yml b/environment.yml
index 9aa87c6f..67032759 100644
--- a/environment.yml
+++ b/environment.yml
@@ -14,8 +14,10 @@ dependencies:
   - pytorch~=2.1.0=*cuda120*
   - python=3.11
   - rioxarray~=0.15.0
+  - scikit-image~=0.22.0
   - stackstac~=0.5.0
   - torchdata~=0.7.1
   - transformers~=4.35.2
   - typeshed-client~=2.4.0
+  - wandb~=0.15.12
   - zarr~=2.16.1
diff --git a/src/README.md b/src/README.md
index cd719680..c041581b 100644
--- a/src/README.md
+++ b/src/README.md
@@ -1,6 +1,7 @@
 # Clay Foundation Model Modules
 
-This folder contains several LightningDataModule and LightningModule classes.
+This folder contains several LightningDataModule, LightningModule and callback
+classes.
 
 ## DataModules (data pipeline)
 
@@ -10,7 +11,12 @@ This folder contains several LightningDataModule and LightningModule classes.
 
 - model_vit.py - Vision Transformer neural network model architecture
 
+## Callbacks (custom plugins)
+
+- callbacks_wandb.py - Log metrics and predictions to Weights and Biases while training.
+
 ## References
 
 - https://lightning.ai/docs/pytorch/2.1.0/data/datamodule.html
 - https://lightning.ai/docs/pytorch/2.1.0/common/lightning_module.html
+- https://lightning.ai/docs/pytorch/2.1.0/extensions/callbacks.html
diff --git a/src/callbacks_wandb.py b/src/callbacks_wandb.py
new file mode 100644
index 00000000..7998e269
--- /dev/null
+++ b/src/callbacks_wandb.py
@@ -0,0 +1,144 @@
+"""
+Lightning callback functions for logging to Weights & Biases.
+
+Includes a way to visualize RGB images derived from the raw logits of a Masked
+Autoencoder's decoder during the validation loop. I.e. to see if the Vision
+Transformer model is learning how to do image reconstruction.
+
+Usage:
+
+```
+import lightning as L
+
+from src.callbacks_wandb import LogMAEReconstruction
+
+trainer = L.Trainer(
+    ...,
+    callbacks=[LogMAEReconstruction(num_samples=6)]
+)
+```
+
+References:
+- https://lightning.ai/docs/pytorch/2.1.0/common/trainer.html#callbacks
+- https://wandb.ai/wandb/wandb-lightning/reports/Image-Classification-using-PyTorch-Lightning--VmlldzoyODk1NzY
+- https://github.com/ashleve/lightning-hydra-template/blob/wandb-callbacks/src/callbacks/wandb_callbacks.py#L245
+"""
+import lightning as L
+import numpy as np
+import skimage
+import torch
+
+try:
+    import wandb
+except ImportError:
+    wandb = None
+
+
+# %%
+class LogMAEReconstruction(L.Callback):
+    """
+    Logs reconstructed RGB images from a Masked Autoencoder's decoder to WandB.
+    """
+
+    def __init__(self, num_samples: int = 8):
+        """
+        Define how many sample images to log.
+
+        Parameters
+        ----------
+        num_samples : int
+            The number of RGB image samples to upload to WandB. Default is 8.
+        """
+        super().__init__()
+        self.num_samples: int = num_samples
+        self.ready: bool = False
+
+        if wandb is None:
+            raise ModuleNotFoundError(
+                "Package `wandb` is required to be installed to use this callback. "
+                "Please use `pip install wandb` or "
+                "`conda install -c conda-forge wandb` "
+                "to install the package"
+            )
+
+    def on_sanity_check_start(self, trainer, pl_module):
+        """
+        Don't execute callback before validation sanity checks are completed.
+        """
+        self.ready = False
+
+    def on_sanity_check_end(self, trainer, pl_module):
+        """
+        Start executing callback only after all validation sanity checks end.
+        """
+        self.ready = True
+
+    def on_validation_batch_end(
+        self,
+        trainer: L.Trainer,
+        pl_module: L.LightningModule,
+        outputs: dict[str, torch.Tensor],
+        batch: dict[str, torch.Tensor | list[str]],
+        batch_idx: int,
+    ) -> list:
+        """
+        Called in the validation loop at the start of every mini-batch.
+
+        Gather a sample of data from the first mini-batch, get the RGB bands,
+        apply histogram equalization to the image, and log it to WandB.
+        """
+        if self.ready and batch_idx == 0:  # only run on first mini-batch
+            with torch.inference_mode():
+                # Get WandB logger
+                for logger in trainer.loggers:
+                    if isinstance(logger, L.pytorch.loggers.WandbLogger):
+                        break
+
+                # Turn raw logits into reconstructed 512x512 images
+                patchified_pixel_values: torch.Tensor = outputs["logits"]
+                # assert patchified_pixel_values.shape == torch.Size([32, 64, 53248])
+                y_hat: torch.Tensor = pl_module.vit.unpatchify(
+                    patchified_pixel_values=patchified_pixel_values
+                )
+                # assert y_hat.shape == torch.Size([32, 13, 512, 512])
+
+                # Reshape tensors from channel-first to channel-last
+                x: torch.Tensor = torch.einsum(
+                    "bchw->bhwc", batch["image"][: self.num_samples]
+                )
+                y_hat: torch.Tensor = torch.einsum(
+                    "bchw->bhwc", y_hat[: self.num_samples]
+                )
+                # assert y_hat.shape == torch.Size([8, 512, 512, 13])
+                assert x.shape == y_hat.shape
+
+                # Plot original and reconstructed RGB images of Sentinel-2
+                rgb_original: np.ndarray = (
+                    x[:, :, :, [2, 1, 0]].cpu().to(dtype=torch.float32).numpy()
+                )
+                rgb_reconstruction: np.ndarray = (
+                    y_hat[:, :, :, [2, 1, 0]].cpu().to(dtype=torch.float32).numpy()
+                )
+
+                figures: list[wandb.Image] = []
+                for i in range(min(x.shape[0], self.num_samples)):
+                    img_original = wandb.Image(
+                        data_or_path=skimage.exposure.equalize_hist(
+                            image=rgb_original[i]
+                        ),
+                        caption=f"RGB Image {i}",
+                    )
+                    figures.append(img_original)
+
+                    img_reconstruction = wandb.Image(
+                        data_or_path=skimage.exposure.equalize_hist(
+                            image=rgb_reconstruction[i]
+                        ),
+                        caption=f"Reconstructed {i}",
+                    )
+                    figures.append(img_reconstruction)
+
+                # Upload figures to WandB
+                logger.experiment.log(data={"Examples": figures})
+
+            return figures
diff --git a/src/model_vit.py b/src/model_vit.py
index c3255542..a9e96775 100644
--- a/src/model_vit.py
+++ b/src/model_vit.py
@@ -99,7 +99,7 @@ def training_step(
         - https://github.com/huggingface/transformers/blob/v4.35.2/src/transformers/models/vit_mae/modeling_vit_mae.py#L948-L1010
         """
         x: torch.Tensor = batch["image"]
-        # x: torch.Tensor = torch.randn(32, 13, 256, 256)  # BCHW
+        # x: torch.Tensor = torch.randn(32, 13, 512, 512)  # BCHW
 
         # Forward encoder
         outputs_encoder: dict = self(x)
@@ -125,7 +125,7 @@ def training_step(
             on_step=True,
             on_epoch=True,
             prog_bar=True,
-            # logger=True,
+            batch_size=self.B,
         )
 
         return loss
@@ -136,7 +136,37 @@ def validation_step(
         """
         Logic for the neural network's validation loop.
         """
-        pass
+        x: torch.Tensor = batch["image"]
+        # x: torch.Tensor = torch.randn(32, 13, 512, 512)  # BCHW
+
+        # Forward encoder
+        outputs_encoder: dict = self(x)
+        assert outputs_encoder.last_hidden_state.shape == torch.Size([self.B, 17, 768])
+        assert outputs_encoder.ids_restore.shape == torch.Size([self.B, 64])
+        assert outputs_encoder.mask.shape == torch.Size([self.B, 64])
+
+        # Forward decoder
+        outputs_decoder: dict = self.vit.decoder.forward(
+            hidden_states=outputs_encoder.last_hidden_state,
+            ids_restore=outputs_encoder.ids_restore,
+        )
+        # output shape (batch_size, num_patches, patch_size*patch_size*num_channels)
+        assert outputs_decoder.logits.shape == torch.Size([self.B, 64, 53248])
+
+        # Log training loss and metrics
+        loss: torch.Tensor = self.vit.forward_loss(
+            pixel_values=x, pred=outputs_decoder.logits, mask=outputs_encoder.mask
+        )
+        self.log(
+            name="val/loss",
+            value=loss,
+            on_step=True,
+            on_epoch=True,
+            prog_bar=True,
+            batch_size=self.B,
+        )
+
+        return {"loss": loss, "logits": outputs_decoder.logits}
 
     def predict_step(
         self, batch: dict[str, torch.Tensor | list[str]], batch_idx: int
diff --git a/src/tests/test_callbacks.py b/src/tests/test_callbacks.py
new file mode 100644
index 00000000..1af4000a
--- /dev/null
+++ b/src/tests/test_callbacks.py
@@ -0,0 +1,66 @@
+"""
+Tests for custom Callback plugins.
+
+Checks to ensure that the hooks in callbacks can be triggered and produce the
+correct output results.
+"""
+import tempfile
+
+import lightning as L
+import pytest
+import torch
+
+from src.callbacks_wandb import LogMAEReconstruction
+from src.model_vit import ViTLitModule
+
+
+# %%
+def test_callbacks_wandb_log_mae_reconstruction():
+    """
+    Ensure that the LogMAEReconstruction callback can log a set of images to
+    Weights & Biases.
+    """
+    wandb = pytest.importorskip(modname="wandb")
+
+    # Run tests in a temporary folder
+    with tempfile.TemporaryDirectory() as tmpdirname:
+        pl_module: L.LightningModule = ViTLitModule()
+        trainer: L.Trainer = L.Trainer(
+            accelerator="auto",
+            callbacks=[LogMAEReconstruction(num_samples=4)],
+            devices=1,
+            logger=L.pytorch.loggers.WandbLogger(mode="disabled", save_dir=tmpdirname),
+            default_root_dir=tmpdirname,
+        )
+        callback: L.Callback = trainer.callbacks[0]
+
+        assert callback.ready is False  # callback state is not ready at first
+        callback.on_sanity_check_end(trainer=trainer, pl_module=pl_module)
+        assert callback.ready is True  # callback state is ready after sanity_check
+
+        wandb_images: list[wandb.Image] = callback.on_validation_batch_end(
+            trainer=trainer,
+            pl_module=pl_module,
+            outputs={"logits": torch.rand(4, 64, 53248)},
+            batch={"image": torch.rand(4, 13, 512, 512)},
+            batch_idx=0,
+        )
+
+        # Check that wandb saved some log files to the temporary directory
+        # assert os.path.exists(path := f"{tmpdirname}/wandb/latest-run/")
+        # assert set(os.listdir(path=path)) == set(
+        #     [
+        #         f"run-{trainer.logger.version}.wandb",
+        #         "tmp",
+        #         "files",
+        #         "logs",
+        #     ]
+        # )
+
+        # Check that images logged by WandB have the correct caption and format
+        assert len(wandb_images) == 8  # noqa: PLR2004
+        assert all(isinstance(w, wandb.Image) for w in wandb_images)
+        assert wandb_images[0]._caption == "RGB Image 0"
+        assert wandb_images[0].format == "png"
+        assert wandb_images[1]._caption == "Reconstructed 0"
+        assert wandb_images[1].format == "png"
diff --git a/trainer.py b/trainer.py
index db09c476..fa12bba6 100644
--- a/trainer.py
+++ b/trainer.py
@@ -13,6 +13,7 @@
 from lightning.pytorch.cli import ArgsType, LightningCLI
 from lightning.pytorch.plugins.io import AsyncCheckpointIO
 
+from src.callbacks_wandb import LogMAEReconstruction  # noqa: F401
 from src.datamodule import GeoTIFFDataPipeModule
 from src.model_vit import ViTLitModule