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@ivirshup
Created October 12, 2018 08:10
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Scanpy scatter plotting circles
name: scanpy_scatter_ring
channels:
- defaults
- r
- bioconda
- conda-forge
dependencies:
- anndata=0.6.10=py_0
- igraph=0.7.1=hcc8e21d_5
- louvain=0.6.1=py36hfc679d8_1
- python-igraph=0.7.1.post6=py36h470a237_5
- backcall=0.1.0=py36_0
- blas=1.0=mkl
- blosc=1.14.4=hdbcaa40_0
- bzip2=1.0.6=h14c3975_5
- ca-certificates=2018.03.07=0
- cairo=1.14.12=h8948797_3
- certifi=2018.8.24=py36_1
- cycler=0.10.0=py36_0
- dbus=1.13.2=h714fa37_1
- decorator=4.3.0=py36_0
- expat=2.2.6=he6710b0_0
- fontconfig=2.13.0=h9420a91_0
- freetype=2.9.1=h8a8886c_1
- glib=2.56.2=hd408876_0
- gmp=6.1.2=h6c8ec71_1
- gst-plugins-base=1.14.0=hbbd80ab_1
- gstreamer=1.14.0=hb453b48_1
- h5py=2.8.0=py36h989c5e5_3
- hdf5=1.10.2=hba1933b_1
- icu=58.2=h9c2bf20_1
- intel-openmp=2019.0=118
- ipython=7.0.1=py36h39e3cac_0
- ipython_genutils=0.2.0=py36_0
- jedi=0.13.1=py36_0
- jpeg=9b=h024ee3a_2
- kiwisolver=1.0.1=py36hf484d3e_0
- libedit=3.1.20170329=h6b74fdf_2
- libffi=3.2.1=hd88cf55_4
- libgcc-ng=8.2.0=hdf63c60_1
- libgfortran-ng=7.3.0=hdf63c60_0
- libiconv=1.15=h63c8f33_5
- libpng=1.6.34=hb9fc6fc_0
- libstdcxx-ng=8.2.0=hdf63c60_1
- libuuid=1.0.3=h1bed415_2
- libxcb=1.13=h1bed415_1
- libxml2=2.9.8=h26e45fe_1
- llvmlite=0.25.0=py36hd408876_0
- lzo=2.10=h49e0be7_2
- matplotlib=3.0.0=py36h5429711_0
- mkl=2019.0=118
- mkl_fft=1.0.6=py36h7dd41cf_0
- mkl_random=1.0.1=py36h4414c95_1
- natsort=5.4.0=py36_0
- ncurses=6.1=hf484d3e_0
- networkx=2.2=py36_1
- numba=0.40.0=py36h962f231_0
- numexpr=2.6.8=py36hd89afb7_0
- numpy=1.15.2=py36h1d66e8a_1
- numpy-base=1.15.2=py36h81de0dd_1
- openssl=1.0.2p=h14c3975_0
- pandas=0.23.4=py36h04863e7_0
- parso=0.3.1=py36_0
- patsy=0.5.0=py36_0
- pcre=8.42=h439df22_0
- pexpect=4.6.0=py36_0
- pickleshare=0.7.5=py36_0
- pip=10.0.1=py36_0
- pixman=0.34.0=hceecf20_3
- prompt_toolkit=2.0.5=py36_0
- ptyprocess=0.6.0=py36_0
- pycairo=1.17.1=py36h2a1e443_0
- pygments=2.2.0=py36_0
- pyparsing=2.2.2=py36_0
- pyqt=5.9.2=py36h05f1152_2
- pytables=3.4.4=py36ha205bf6_0
- python=3.6.6=h6e4f718_2
- python-dateutil=2.7.3=py36_0
- pytz=2018.5=py36_0
- qt=5.9.6=h8703b6f_2
- readline=7.0=h7b6447c_5
- scikit-learn=0.20.0=py36h4989274_1
- scipy=1.1.0=py36hfa4b5c9_1
- seaborn=0.9.0=py36_0
- setuptools=40.4.3=py36_0
- simplegeneric=0.8.1=py36_2
- sip=4.19.8=py36hf484d3e_0
- six=1.11.0=py36_1
- snappy=1.1.7=hbae5bb6_3
- sqlite=3.25.2=h7b6447c_0
- statsmodels=0.9.0=py36h035aef0_0
- tk=8.6.8=hbc83047_0
- tornado=5.1.1=py36h7b6447c_0
- traitlets=4.3.2=py36_0
- wcwidth=0.1.7=py36_0
- wheel=0.32.1=py36_0
- xz=5.2.4=h14c3975_4
- zlib=1.2.11=ha838bed_2
- pip:
- joblib==0.12.5
- scanpy==1.3.2
- tables==3.4.4
prefix: /scratch-new/isaacv/miniconda3/envs/scanpy_scatter_ring
import scanpy.api as sc
import numpy as np
import pandas as pd
sc.set_figure_params(dpi=300, dpi_save=300) # Makes it more visible
N = 1000
M = 2000
adata = sc.AnnData(
X=np.random.random_sample((N, M)),
obs=pd.DataFrame({"a": np.random.randint(0, 2, N)})
)
adata.obs["a"] = adata.obs["a"].astype(str)
sc.pp.pca(adata)
sc.pl.pca(adata, color="a", size=0.1, save="test.pdf")
name: scanpy_scatter_ring
channels:
- bioconda
- defaults
- conda-forge
- r
dependencies:
- anndata=0.6.10=py_0
- libffi=3.2.1=1
- igraph=0.7.1=hcc8e21d_5
- louvain=0.6.1=py36hfc679d8_1
- python-igraph=0.7.1.post6=py36_4
- appnope=0.1.0=py36hf537a9a_0
- backcall=0.1.0=py36_0
- blas=1.0=mkl
- blosc=1.14.4=hd9629dc_0
- bzip2=1.0.6=h1de35cc_5
- ca-certificates=2018.03.07=0
- cairo=1.14.12=hc4e6be7_4
- certifi=2018.8.24=py36_1
- cycler=0.10.0=py36hfc81398_0
- decorator=4.3.0=py36_0
- fontconfig=2.13.0=h5d5b041_1
- freetype=2.9.1=hb4e5f40_0
- gettext=0.19.8.1=h15daf44_3
- glib=2.56.2=hd9629dc_0
- gmp=6.1.2=hb37e062_1
- h5py=2.8.0=py36h878fce3_3
- hdf5=1.10.2=hfa1e0ec_1
- icu=58.2=h4b95b61_1
- intel-openmp=2019.0=118
- ipython=7.0.1=py36h39e3cac_0
- ipython_genutils=0.2.0=py36h241746c_0
- jedi=0.13.1=py36_0
- kiwisolver=1.0.1=py36h0a44026_0
- libcxx=4.0.1=h579ed51_0
- libcxxabi=4.0.1=hebd6815_0
- libedit=3.1.20170329=hb402a30_2
- libgfortran=3.0.1=h93005f0_2
- libgfortran-ng=3.0.1=h93005f0_2
- libiconv=1.15=hdd342a3_7
- libpng=1.6.34=he12f830_0
- libxml2=2.9.8=hab757c2_1
- llvmlite=0.25.0=py36h8c7ce04_0
- lzo=2.10=h362108e_2
- matplotlib=3.0.0=py36h54f8f79_0
- mkl=2019.0=118
- mkl_fft=1.0.6=py36hb8a8100_0
- mkl_random=1.0.1=py36h5d10147_1
- natsort=5.4.0=py36_0
- ncurses=6.1=h0a44026_0
- networkx=2.2=py36_1
- numba=0.40.0=py36h6440ff4_0
- numexpr=2.6.8=py36h1dc9127_0
- numpy=1.15.2=py36h6a91979_1
- numpy-base=1.15.2=py36h8a80b8c_1
- openssl=1.0.2p=h1de35cc_0
- pandas=0.23.4=py36h6440ff4_0
- parso=0.3.1=py36_0
- patsy=0.5.0=py36_0
- pcre=8.42=h378b8a2_0
- pexpect=4.6.0=py36_0
- pickleshare=0.7.5=py36_0
- pip=10.0.1=py36_0
- pixman=0.34.0=hca0a616_3
- prompt_toolkit=2.0.5=py36_0
- ptyprocess=0.6.0=py36_0
- pycairo=1.17.1=py36ha54c0a8_0
- pygments=2.2.0=py36h240cd3f_0
- pyparsing=2.2.2=py36_0
- pytables=3.4.4=py36h13cba08_0
- python=3.6.6=hc167b69_0
- python-dateutil=2.7.3=py36_0
- pytz=2018.5=py36_0
- readline=7.0=h1de35cc_5
- scikit-learn=0.20.0=py36h4f467ca_1
- scipy=1.1.0=py36h28f7352_1
- seaborn=0.9.0=py36_0
- setuptools=40.4.3=py36_0
- simplegeneric=0.8.1=py36_2
- six=1.11.0=py36_1
- snappy=1.1.7=he62c110_3
- sqlite=3.25.2=ha441bb4_0
- statsmodels=0.9.0=py36h1d22016_0
- tk=8.6.8=ha441bb4_0
- tornado=5.1.1=py36h1de35cc_0
- traitlets=4.3.2=py36h65bd3ce_0
- wcwidth=0.1.7=py36h8c6ec74_0
- wheel=0.32.1=py36_0
- xz=5.2.4=h1de35cc_4
- zlib=1.2.11=hf3cbc9b_2
- pip:
- joblib==0.12.5
- scanpy==1.3.2
- tables==3.4.4
prefix: /Users/isaac/miniconda3/envs/scanpy_scatter_ring
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