diff --git a/container/dandelion_singularity.ipynb b/container/dandelion_singularity.ipynb
index 1ae9620a5..b5242e050 100644
--- a/container/dandelion_singularity.ipynb
+++ b/container/dandelion_singularity.ipynb
@@ -5,8 +5,6 @@
"colab": {
"name": "dandelion_singularity.ipynb",
"provenance": [],
- "collapsed_sections": [],
- "authorship_tag": "ABX9TyOPc7OMdzKjvVeP1njWF4xt",
"include_colab_link": true
},
"kernelspec": {
@@ -25,7 +23,7 @@
"colab_type": "text"
},
"source": [
- ""
+ ""
]
},
{
@@ -69,7 +67,7 @@
],
"metadata": {
"id": "7jsHAhD9uvwV",
- "outputId": "3c051178-0902-4b4d-e2a0-ab01bc4f652f",
+ "outputId": "ccd8de31-eac2-4105-9f42-b784e32a10d2",
"colab": {
"base_uri": "https://localhost:8080/"
}
@@ -80,12 +78,8 @@
"output_type": "stream",
"name": "stdout",
"text": [
- "⏬ Downloading https://github.com/jaimergp/miniforge/releases/latest/download/Mambaforge-colab-Linux-x86_64.sh...\n",
- "📦 Installing...\n",
- "📌 Adjusting configuration...\n",
- "🩹 Patching environment...\n",
- "⏲ Done in 0:00:23\n",
- "🔁 Restarting kernel...\n"
+ "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+ "\u001b[0m✨🍰✨ Everything looks OK!\n"
]
}
]
@@ -105,290 +99,17 @@
],
"metadata": {
"id": "hg-CU5SJ5W0Y",
- "outputId": "cd3f86ab-243b-4745-86c8-bb71c51ee9ba",
+ "outputId": "09790dd0-c27b-4555-84b7-bd0040ef5be3",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
- "execution_count": 1,
+ "execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
- "\n",
- " __ __ __ __\n",
- " / \\ / \\ / \\ / \\\n",
- " / \\/ \\/ \\/ \\\n",
- "███████████████/ /██/ /██/ /██/ /████████████████████████\n",
- " / / \\ / \\ / \\ / \\ \\____\n",
- " / / \\_/ \\_/ \\_/ \\ o \\__,\n",
- " / _/ \\_____/ `\n",
- " |/\n",
- " ███╗ ███╗ █████╗ ███╗ ███╗██████╗ █████╗\n",
- " ████╗ ████║██╔══██╗████╗ ████║██╔══██╗██╔══██╗\n",
- " ██╔████╔██║███████║██╔████╔██║██████╔╝███████║\n",
- " ██║╚██╔╝██║██╔══██║██║╚██╔╝██║██╔══██╗██╔══██║\n",
- " ██║ ╚═╝ ██║██║ ██║██║ ╚═╝ ██║██████╔╝██║ ██║\n",
- " ╚═╝ ╚═╝╚═╝ ╚═╝╚═╝ ╚═╝╚═════╝ ╚═╝ ╚═╝\n",
- "\n",
- " mamba (0.25.0) supported by @QuantStack\n",
- "\n",
- " GitHub: https://github.com/mamba-org/mamba\n",
- " Twitter: https://twitter.com/QuantStack\n",
- "\n",
- "█████████████████████████████████████████████████████████████\n",
- "\n",
- " Package Version Build Channel Size\n",
- "───────────────────────────────────────────────────────────────────────────────────────────────────────\n",
- " Install:\n",
- "───────────────────────────────────────────────────────────────────────────────────────────────────────\n",
- "\n",
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- "\u001b[32m + r-gtools \u001b[00m 3.9.3 r42h06615bd_1 conda-forge/linux-64 374kB\n",
- "\u001b[32m + r-hms \u001b[00m 1.1.2 r42hc72bb7e_1 conda-forge/noarch 110kB\n",
- "\u001b[32m + r-igraph \u001b[00m 1.3.5 r42hb34fc8a_0 conda-forge/linux-64 4MB\n",
- "\u001b[32m + r-isoband \u001b[00m 0.2.6 r42h7525677_1 conda-forge/linux-64 2MB\n",
- "\u001b[32m + r-iterators \u001b[00m 1.0.14 r42hc72bb7e_1 conda-forge/noarch 359kB\n",
- "\u001b[32m + r-jsonlite \u001b[00m 1.8.3 r42h06615bd_0 conda-forge/linux-64 1MB\n",
- "\u001b[32m + r-kedd \u001b[00m 1.0.3 r42ha770c72_1005 conda-forge/noarch 925kB\n",
- "\u001b[32m + r-kernsmooth \u001b[00m 2.23_20 r42hd009a43_1 conda-forge/linux-64 104kB\n",
- "\u001b[32m + r-labeling \u001b[00m 0.4.2 r42hc72bb7e_2 conda-forge/noarch 70kB\n",
- "\u001b[32m + r-lambda.r \u001b[00m 1.2.4 r42hc72bb7e_2 conda-forge/noarch 124kB\n",
- "\u001b[32m + r-lattice \u001b[00m 0.20_45 r42h06615bd_1 conda-forge/linux-64 1MB\n",
- "\u001b[32m + r-lazyeval \u001b[00m 0.2.2 r42h06615bd_3 conda-forge/linux-64 170kB\n",
- "\u001b[32m + r-lifecycle \u001b[00m 1.0.3 r42hc72bb7e_1 conda-forge/noarch 128kB\n",
- "\u001b[32m + r-magrittr \u001b[00m 2.0.3 r42h06615bd_1 conda-forge/linux-64 221kB\n",
- "\u001b[32m + r-mass \u001b[00m 7.3_58.1 r42h06615bd_1 conda-forge/linux-64 1MB\n",
- "\u001b[32m + r-matrix \u001b[00m 1.5_1 r42h5f7b363_0 conda-forge/linux-64 4MB\n",
- "\u001b[32m + r-matrixstats \u001b[00m 0.62.0 r42h06615bd_1 conda-forge/linux-64 480kB\n",
- "\u001b[32m + r-mgcv \u001b[00m 1.8_41 r42h5f7b363_0 conda-forge/linux-64 3MB\n",
- "\u001b[32m + r-munsell \u001b[00m 0.5.0 r42hc72bb7e_1005 conda-forge/noarch 254kB\n",
- "\u001b[32m + r-nlme \u001b[00m 3.1_160 r42h8da6f51_0 conda-forge/linux-64 2MB\n",
- "\u001b[32m + r-optparse \u001b[00m 1.7.3 r42hc72bb7e_1 conda-forge/noarch 92kB\n",
- "\u001b[32m + r-pillar \u001b[00m 1.8.1 r42hc72bb7e_1 conda-forge/noarch 694kB\n",
- "\u001b[32m + r-pixmap \u001b[00m 0.4_12 r42hc72bb7e_1 conda-forge/noarch 239kB\n",
- "\u001b[32m + r-pkgconfig \u001b[00m 2.0.3 r42hc72bb7e_2 conda-forge/noarch 27kB\n",
- "\u001b[32m + r-pkgload \u001b[00m 1.3.1 r42hc72bb7e_0 conda-forge/noarch 199kB\n",
- "\u001b[32m + r-praise \u001b[00m 1.0.0 r42hc72bb7e_1006 conda-forge/noarch 25kB\n",
- "\u001b[32m + r-prettyunits \u001b[00m 1.1.1 r42hc72bb7e_2 conda-forge/noarch 43kB\n",
- "\u001b[32m + r-processx \u001b[00m 3.8.0 r42h06615bd_0 conda-forge/linux-64 339kB\n",
- "\u001b[32m + r-progress \u001b[00m 1.2.2 r42hc72bb7e_3 conda-forge/noarch 94kB\n",
- "\u001b[32m + r-ps \u001b[00m 1.7.2 r42h06615bd_0 conda-forge/linux-64 331kB\n",
- "\u001b[32m + r-purrr \u001b[00m 0.3.5 r42h06615bd_1 conda-forge/linux-64 424kB\n",
- "\u001b[32m + r-r6 \u001b[00m 2.5.1 r42hc72bb7e_1 conda-forge/noarch 93kB\n",
- "\u001b[32m + r-rcolorbrewer \u001b[00m 1.1_3 r42h785f33e_1 conda-forge/noarch 67kB\n",
- "\u001b[32m + r-rcpp \u001b[00m 1.0.9 r42h7525677_2 conda-forge/linux-64 2MB\n",
- "\u001b[32m + r-rcurl \u001b[00m 1.98_1.9 r42h06615bd_1 conda-forge/linux-64 979kB\n",
- "\u001b[32m + r-readr \u001b[00m 2.1.3 r42h7525677_1 conda-forge/linux-64 893kB\n",
- "\u001b[32m + r-rematch2 \u001b[00m 2.1.2 r42hc72bb7e_2 conda-forge/noarch 55kB\n",
- "\u001b[32m + r-rlang \u001b[00m 1.0.6 r42h7525677_1 conda-forge/linux-64 2MB\n",
- "\u001b[32m + r-rprojroot \u001b[00m 2.0.3 r42hc72bb7e_1 conda-forge/noarch 118kB\n",
- "\u001b[32m + r-scales \u001b[00m 1.2.1 r42hc72bb7e_1 conda-forge/noarch 627kB\n",
- "\u001b[32m + r-segmented \u001b[00m 1.6_1 r42hc72bb7e_0 conda-forge/noarch 779kB\n",
- "\u001b[32m + r-seqinr \u001b[00m 4.2_16 r42h06615bd_1 conda-forge/linux-64 4MB\n",
- "\u001b[32m + r-shazam \u001b[00m 1.1.2 r42h3121a25_1 bioconda/noarch 2MB\n",
- "\u001b[32m + r-snow \u001b[00m 0.4_4 r42hc72bb7e_1 conda-forge/noarch 117kB\n",
- "\u001b[32m + r-sp \u001b[00m 1.5_1 r42h06615bd_0 conda-forge/linux-64 2MB\n",
- "\u001b[32m + r-stringi \u001b[00m 1.7.8 r42h30a9eb7_1 conda-forge/linux-64 953kB\n",
- "\u001b[32m + r-testthat \u001b[00m 3.1.5 r42h7525677_1 conda-forge/linux-64 2MB\n",
- "\u001b[32m + r-tibble \u001b[00m 3.1.8 r42h06615bd_1 conda-forge/linux-64 710kB\n",
- "\u001b[32m + r-tidyr \u001b[00m 1.2.1 r42h7525677_1 conda-forge/linux-64 874kB\n",
- "\u001b[32m + r-tidyselect \u001b[00m 1.2.0 r42hc72bb7e_0 conda-forge/linux-64 223kB\n",
- "\u001b[32m + r-tigger \u001b[00m 1.0.0 r42hc72bb7e_2 conda-forge/linux-64 4MB\n",
- "\u001b[32m + r-tzdb \u001b[00m 0.3.0 r42h7525677_1 conda-forge/linux-64 529kB\n",
- "\u001b[32m + r-utf8 \u001b[00m 1.2.2 r42h06615bd_1 conda-forge/linux-64 167kB\n",
- "\u001b[32m + r-vctrs \u001b[00m 0.5.0 r42h7525677_0 conda-forge/linux-64 1MB\n",
- "\u001b[32m + r-viridislite \u001b[00m 0.4.1 r42hc72bb7e_1 conda-forge/noarch 1MB\n",
- "\u001b[32m + r-vroom \u001b[00m 1.6.0 r42h7525677_1 conda-forge/linux-64 995kB\n",
- "\u001b[32m + r-waldo \u001b[00m 0.4.0 r42hc72bb7e_1 conda-forge/noarch 113kB\n",
- "\u001b[32m + r-withr \u001b[00m 2.5.0 r42hc72bb7e_1 conda-forge/noarch 246kB\n",
- "\u001b[32m + r-yaml \u001b[00m 2.3.6 r42h06615bd_0 conda-forge/linux-64 125kB\n",
- "\u001b[32m + sed \u001b[00m 4.8 he412f7d_0 conda-forge/linux-64 271kB\n",
- "\u001b[32m + sysroot_linux-64 \u001b[00m 2.12 he073ed8_15 conda-forge/noarch 33MB\n",
- "\u001b[32m + tktable \u001b[00m 2.10 hb7b940f_3 conda-forge/linux-64 92kB\n",
- "\u001b[32m + toml \u001b[00m 0.10.2 pyhd8ed1ab_0 conda-forge/noarch 18kB\n",
- "\u001b[32m + typing_extensions \u001b[00m 4.4.0 pyha770c72_0 conda-forge/noarch 30kB\n",
- "\u001b[32m + wget \u001b[00m 1.20.3 ha56f1ee_1 conda-forge/linux-64 824kB\n",
- "\u001b[32m + xmltodict \u001b[00m 0.13.0 pyhd8ed1ab_0 conda-forge/noarch 14kB\n",
- "\u001b[32m + xorg-kbproto \u001b[00m 1.0.7 h7f98852_1002 conda-forge/linux-64 27kB\n",
- "\u001b[32m + xorg-libice \u001b[00m 1.0.10 h7f98852_0 conda-forge/linux-64 59kB\n",
- "\u001b[32m + xorg-libsm \u001b[00m 1.2.3 hd9c2040_1000 conda-forge/linux-64 26kB\n",
- "\u001b[32m + xorg-libx11 \u001b[00m 1.7.2 h7f98852_0 conda-forge/linux-64 963kB\n",
- "\u001b[32m + xorg-libxau \u001b[00m 1.0.9 h7f98852_0 conda-forge/linux-64 13kB\n",
- "\u001b[32m + xorg-libxdmcp \u001b[00m 1.1.3 h7f98852_0 conda-forge/linux-64 19kB\n",
- "\u001b[32m + xorg-libxext \u001b[00m 1.3.4 h7f98852_1 conda-forge/linux-64 55kB\n",
- "\u001b[32m + xorg-libxrender \u001b[00m 0.9.10 h7f98852_1003 conda-forge/linux-64 33kB\n",
- "\u001b[32m + xorg-libxt \u001b[00m 1.2.1 h7f98852_2 conda-forge/linux-64 384kB\n",
- "\u001b[32m + xorg-renderproto \u001b[00m 0.11.1 h7f98852_1002 conda-forge/linux-64 10kB\n",
- "\u001b[32m + xorg-xextproto \u001b[00m 7.3.0 h7f98852_1002 conda-forge/linux-64 28kB\n",
- "\u001b[32m + xorg-xproto \u001b[00m 7.0.31 h7f98852_1007 conda-forge/linux-64 75kB\n",
- "\u001b[32m + yq \u001b[00m 2.13.0 pyhd8ed1ab_0 conda-forge/noarch 21kB\n",
- "\u001b[32m + zipp \u001b[00m 3.10.0 pyhd8ed1ab_0 conda-forge/noarch 14kB\n",
- "\u001b[32m + zlib \u001b[00m 1.2.13 h166bdaf_4 conda-forge/linux-64 94kB\n",
- "\n",
- " Upgrade:\n",
- "───────────────────────────────────────────────────────────────────────────────────────────────────────\n",
- "\n",
- "\u001b[31m - ca-certificates \u001b[00m 2022.6.15 ha878542_0 conda-forge \n",
- "\u001b[32m + ca-certificates \u001b[00m 2022.9.24 ha878542_0 conda-forge/linux-64 154kB\n",
- "\u001b[31m - certifi \u001b[00m 2022.6.15 py37h89c1867_0 conda-forge \n",
- "\u001b[32m + certifi \u001b[00m 2022.9.24 pyhd8ed1ab_0 conda-forge/noarch 159kB\n",
- "\u001b[31m - libcurl \u001b[00m 7.83.1 h7bff187_0 conda-forge \n",
- "\u001b[32m + libcurl \u001b[00m 7.86.0 h7bff187_1 conda-forge/linux-64 357kB\n",
- "\u001b[31m - libzlib \u001b[00m 1.2.12 h166bdaf_2 conda-forge \n",
- "\u001b[32m + libzlib \u001b[00m 1.2.13 h166bdaf_4 conda-forge/linux-64 66kB\n",
- "\u001b[31m - openssl \u001b[00m 1.1.1q h166bdaf_0 conda-forge \n",
- "\u001b[32m + openssl \u001b[00m 1.1.1s h166bdaf_0 conda-forge/linux-64 2MB\n",
- "\n",
- " Summary:\n",
- "\n",
- " Install: 221 packages\n",
- " Upgrade: 5 packages\n",
- "\n",
- " Total download: 465MB\n",
- "\n",
- "───────────────────────────────────────────────────────────────────────────────────────────────────────\n",
- "\n",
"Preparing transaction: ...working... done\n",
"Verifying transaction: ...working... done\n",
"Executing transaction: ...working... done\n"
@@ -400,74 +121,74 @@
"cell_type": "code",
"source": [
"# install dandelion and scanpy\n",
- "!pip install -q sc-dandelion scanpy[leiden]==1.8.2 matplotlib==3.2.2"
+ "!pip install -q sc-dandelion scanpy[leiden] networkx==2.7"
],
"metadata": {
"id": "cz_yEFkJQ6xk",
- "outputId": "b9db756c-55eb-45c7-de18-380fa0f58cd5",
+ "outputId": "210d862e-3fb3-460a-9cd9-616c2696b13d",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
- "execution_count": 2,
+ "execution_count": 3,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
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"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m40.8/40.8 kB\u001b[0m \u001b[31m4.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.5/3.5 MB\u001b[0m \u001b[31m79.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.9/5.9 MB\u001b[0m \u001b[31m100.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m24.8/24.8 MB\u001b[0m \u001b[31m78.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m9.9/9.9 MB\u001b[0m \u001b[31m97.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m233.8/233.8 kB\u001b[0m \u001b[31m21.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.6/3.6 MB\u001b[0m \u001b[31m80.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m103.0/103.0 kB\u001b[0m \u001b[31m9.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m57.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m151.5/151.5 kB\u001b[0m \u001b[31m12.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.9/1.9 MB\u001b[0m \u001b[31m74.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m63.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m17.3/17.3 MB\u001b[0m \u001b[31m40.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m34.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m11.6/11.6 MB\u001b[0m \u001b[31m41.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m43.8/43.8 kB\u001b[0m \u001b[31m2.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m9.6/9.6 MB\u001b[0m \u001b[31m23.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.6/4.6 MB\u001b[0m \u001b[31m26.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m298.0/298.0 kB\u001b[0m \u001b[31m13.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m88.2/88.2 kB\u001b[0m \u001b[31m4.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m98.3/98.3 kB\u001b[0m \u001b[31m8.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m46.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m247.7/247.7 kB\u001b[0m \u001b[31m22.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m180.3/180.3 kB\u001b[0m \u001b[31m16.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m48.9/48.9 kB\u001b[0m \u001b[31m3.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.1/10.1 MB\u001b[0m \u001b[31m63.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m11.6/11.6 MB\u001b[0m \u001b[31m82.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m233.8/233.8 kB\u001b[0m \u001b[31m19.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.7/4.7 MB\u001b[0m \u001b[31m83.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m150.8/150.8 kB\u001b[0m \u001b[31m12.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m42.9/42.9 kB\u001b[0m \u001b[31m3.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.6/2.6 MB\u001b[0m \u001b[31m65.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m108.9/108.9 kB\u001b[0m \u001b[31m10.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ " Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.1/3.1 MB\u001b[0m \u001b[31m72.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m108.9/108.9 kB\u001b[0m \u001b[31m9.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m64.0/64.0 kB\u001b[0m \u001b[31m6.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m64.0/64.0 kB\u001b[0m \u001b[31m6.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.2/3.2 MB\u001b[0m \u001b[31m82.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m34.6/34.6 MB\u001b[0m \u001b[31m15.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m498.1/498.1 kB\u001b[0m \u001b[31m36.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m63.1/63.1 kB\u001b[0m \u001b[31m6.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m64.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.3/3.3 MB\u001b[0m \u001b[31m89.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m70.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.4/3.4 MB\u001b[0m \u001b[31m80.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m98.3/98.3 kB\u001b[0m \u001b[31m9.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m502.3/502.3 kB\u001b[0m \u001b[31m36.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m63.5/63.5 kB\u001b[0m \u001b[31m4.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
- "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m111.8/111.8 kB\u001b[0m \u001b[31m9.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
- "\u001b[?25h Building wheel for adjustText (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for changeo (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for distance (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for umap-learn (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for python-igraph (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
- " Building wheel for sinfo (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+ " Building wheel for session-info (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for airr (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for presto (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for pynndescent (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
@@ -487,18 +208,18 @@
],
"metadata": {
"id": "EGxP8-UOQ63P",
- "outputId": "decc98b3-5539-4b91-c8a9-f34774310487",
+ "outputId": "4ada956d-9698-4d93-8afd-081f23bcd474",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
- "execution_count": 3,
+ "execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
- "dandelion==0.3.0 pandas==1.3.5 numpy==1.21.6 matplotlib==3.2.2 networkx==2.6.3 scipy==1.7.3\n"
+ "dandelion==0.3.1 pandas==1.4.4 numpy==1.22.4 matplotlib==3.7.1 networkx==2.7 scipy==1.10.1\n"
]
}
]
@@ -540,12 +261,12 @@
],
"metadata": {
"id": "58iS20Iw9WgO",
- "outputId": "569013f5-3eb8-4824-919e-f713e3216a72",
+ "outputId": "26f45495-d81e-4d7a-ee7b-4172f0bfea15",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
- "execution_count": 4,
+ "execution_count": 5,
"outputs": [
{
"output_type": "execute_result",
@@ -553,7 +274,7 @@
"text/plain": []
},
"metadata": {},
- "execution_count": 4
+ "execution_count": 5
}
]
},
@@ -569,12 +290,12 @@
],
"metadata": {
"id": "Dmys4I_RJAOa",
- "outputId": "b584de2a-7125-497d-f24e-48bd405e6bdf",
+ "outputId": "3da59d28-ff3a-414b-bade-c3b0f6a260fa",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
- "execution_count": 5,
+ "execution_count": 6,
"outputs": [
{
"output_type": "execute_result",
@@ -582,7 +303,7 @@
"text/plain": []
},
"metadata": {},
- "execution_count": 5
+ "execution_count": 6
}
]
},
@@ -607,7 +328,7 @@
"metadata": {
"id": "BaFeH6e-sceo"
},
- "execution_count": 6,
+ "execution_count": 7,
"outputs": []
},
{
@@ -617,18 +338,18 @@
],
"metadata": {
"id": "hEPKQLhGBzP7",
- "outputId": "fb4dd33b-b115-48b4-e15a-6a71cc3af8a5",
+ "outputId": "5af4e32d-b018-408f-b2d9-4099396ce49a",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
- "execution_count": 7,
+ "execution_count": 8,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
- "Formating fasta(s) : 100%|██████████| 4/4 [00:00<00:00, 21.91it/s]\n"
+ "Formating fasta(s) : 100%|██████████| 4/4 [00:00<00:00, 20.05it/s]\n"
]
}
]
@@ -640,18 +361,18 @@
],
"metadata": {
"id": "5V6dGeYDtaNM",
- "outputId": "233afa9e-9e54-4669-d310-7249fdeb9df0",
+ "outputId": "e8691dc0-f5ce-4c6c-d892-0412d29ed26a",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
- "execution_count": 8,
+ "execution_count": 9,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
- "Assigning genes : 100%|██████████| 4/4 [03:27<00:00, 51.88s/it]\n"
+ "Assigning genes : 100%|██████████| 4/4 [06:22<00:00, 95.59s/it]\n"
]
}
]
@@ -664,19 +385,19 @@
],
"metadata": {
"id": "xs_mO1KPtaWi",
- "outputId": "9fc25f52-5145-4c52-c718-fc4880175519",
+ "outputId": "e6960391-252b-4cba-9118-3fc590906db2",
"colab": {
"base_uri": "https://localhost:8080/",
- "height": 498
+ "height": 502
}
},
- "execution_count": 9,
+ "execution_count": 10,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
- "Processing data file(s) : 100%|██████████| 2/2 [00:01<00:00, 1.38it/s]\n"
+ "Processing data file(s) : 100%|██████████| 2/2 [00:02<00:00, 1.15s/it]\n"
]
},
{
@@ -687,7 +408,7 @@
" Reconstructing heavy chain dmask germline sequences with v_call_genotyped.\n",
" Reassigning alleles\n",
" Reconstructing heavy chain dmask germline sequences with v_call_genotyped.\n",
- " Reconstructing light chain dmaskgermline sequences with v_call.\n"
+ " Reconstructing light chain dmask germline sequences with v_call.\n"
]
},
{
@@ -696,7 +417,7 @@
"text/plain": [
"