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soma.X.data -> soma.X["data"]
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@johnkerl
johnkerl committed Jun 1, 2022
1 parent b15b94d commit d71970d
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92 changes: 57 additions & 35 deletions apis/python/README-ingestion.md
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Original file line number Diff line number Diff line change
Expand Up @@ -177,40 +177,51 @@ $ python
>>> import tiledbsc
>>> soma = tiledbsc.SOMA('tiledb-data/pbmc-small')
>>> arr = soma.X.data.open_array()
>>> arr.df[:]
obs_id var_id value
0 AAATTCGAATCACG AKR1C3 -0.325888
1 AAATTCGAATCACG CA2 -0.346938
... ... ... ...
1598 TTTAGCTGTACTCT TUBB1 -0.350375
1599 TTTAGCTGTACTCT VDAC3 -0.524551
[1600 rows x 3 columns]
>>> soma.X["data"].df()
value
obs_id var_id
AAATTCGAATCACG AKR1C3 -0.325888
CA2 -0.346938
CD1C -0.253005
GNLY -0.528670
HLA-DPB1 -1.039994
... ...
TTTAGCTGTACTCT S100A9 1.112879
SDPR -0.388176
TREML1 -0.328625
TUBB1 -0.350375
VDAC3 -0.524551
[1600 rows x 1 columns]
-- Note this is a sparse matrix in IJV/COO format
```

```
>>> arr = soma.obs.open_array()
>>> arr.df[:]
>>> soma.obs.df()
orig.ident nCount_RNA nFeature_RNA RNA_snn_res.0.8 letter.idents groups RNA_snn_res.1
obs_id
AAATTCGAATCACG 0 327.0 62 1 1 g2 1
AAGCAAGAGCTTAG 0 126.0 48 0 0 g1 0
AAGCGACTTTGACG 0 443.0 77 1 1 g1 1
AATGCGTGGACGGA 0 389.0 73 1 1 g1 1
AATGTTGACAGTCA 0 100.0 41 0 0 g1 0
... ... ... ... ... ... ... ...
TTACGTACGTTCAG 0 228.0 39 0 0 g1 0
TTGAGGACTACGCA 0 787.0 88 0 0 g1 2
TTGCATTGAGCTAC 0 104.0 40 0 0 g2 2
TTGGTACTGAATCC 0 135.0 45 0 0 g1 2
TTTAGCTGTACTCT 0 462.0 86 1 1 g1 1
[80 rows x 7 columns]
>>> arr = soma.var.open_array()
>>> arr.df[:]
vst.mean vst.variance vst.variance.expected vst.variance.standardized vst.variable
var_id
AKR1C3 0.2625 1.132753 0.553424 2.021191 1
CA2 0.4500 3.263291 1.685451 1.765922 1
CD1C 0.1750 0.576582 0.271217 2.052014 1
GNLY 2.4000 43.762025 24.078566 1.817468 1
...
SDPR 1.1125 15.746677 8.835280 1.680686 1
TREML1 0.3375 1.365665 0.761869 1.792519 1
TUBB1 0.8875 16.202373 6.352400 1.634371 1
VDAC3 1.1250 30.971519 8.986513 2.137607 1
Expand All @@ -219,30 +230,41 @@ VDAC3 1.1250 30.971519 8.986513 2
```
>>> soma.obsm._get_member_names()
['X_tsne', 'X_pca']
>>> arr = soma.obsm['X_pca'].open_array()
>>> arr.df[:]
obs_id X_pca_1 X_pca_2 ... X_pca_18 X_pca_19
0 AAATTCGAATCACG -0.599730 0.970809 ... -0.127195 0.026804
1 AAGCAAGAGCTTAG -0.919219 -2.043828 ... 0.009386 -0.019896
2 AAGCGACTTTGACG -1.380380 1.284101 ... -0.041855 0.027550
.. ... ... ... ... ... ...
78 TTGGTACTGAATCC -1.418764 0.764986 ... -0.064450 0.099118
79 TTTAGCTGTACTCT -1.447483 1.583223 ... -0.014984 0.033992
[80 rows x 20 columns]
>>> soma.obsm['X_pca'].df()
X_pca_1 X_pca_2 ... X_pca_18 X_pca_19
obs_id ...
AAATTCGAATCACG -0.599730 0.970809 ... -0.127195 0.026804
AAGCAAGAGCTTAG -0.919219 -2.043828 ... 0.009386 -0.019896
AAGCGACTTTGACG -1.380380 1.284101 ... -0.041855 0.027550
AATGCGTGGACGGA -1.494413 1.783583 ... -0.045108 0.055206
AATGTTGACAGTCA -0.487798 -1.162107 ... -0.167920 0.026950
... ... ... ... ... ...
TTACGTACGTTCAG 8.858789 -0.195728 ... -0.428616 -0.294552
TTGAGGACTACGCA -0.917909 1.610199 ... -0.113981 -0.110469
TTGCATTGAGCTAC -0.997103 -0.155518 ... 0.056784 -0.027052
TTGGTACTGAATCC -1.418764 0.764986 ... -0.064450 0.099118
TTTAGCTGTACTCT -1.447483 1.583223 ... -0.014984 0.033992
[80 rows x 19 columns]
```

```
>>> arr = soma.raw.X.data.open_array()
>>> arr.df[:]
obs_id var_id value
0 AAATTCGAATCACG ADAR 3.452557
1 AAATTCGAATCACG AIF1 3.452557
... ... ... ...
4454 TTTAGCTGTACTCT XBP1 3.119940
4455 TTTAGCTGTACTCT ZFP36L1 3.119940
[4456 rows x 3 columns]
>>> soma.raw.X["data"].df()
value
obs_id var_id
AAATTCGAATCACG ADAR 3.452557
AIF1 3.452557
ANXA2 3.452557
ARHGDIA 3.452557
ASGR1 3.452557
... ...
TTTAGCTGTACTCT TYMP 4.693411
TYROBP 5.277120
VPS28 3.119940
XBP1 3.119940
ZFP36L1 3.119940
[4456 rows x 1 columns]
```

```
Expand Down
93 changes: 58 additions & 35 deletions apis/python/doc/README-ingestion.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -177,40 +177,52 @@ $ python
>>> import tiledbsc
>>> soma = tiledbsc.SOMA('tiledb-data/pbmc-small')
>>> arr = soma.X.data.open_array()
>>> arr.df[:]
obs_id var_id value
0 AAATTCGAATCACG AKR1C3 -0.325888
1 AAATTCGAATCACG CA2 -0.346938
... ... ... ...
1598 TTTAGCTGTACTCT TUBB1 -0.350375
1599 TTTAGCTGTACTCT VDAC3 -0.524551
[1600 rows x 3 columns]
>>> soma.X["data"].df()
value
obs_id var_id
AAATTCGAATCACG AKR1C3 -0.325888
CA2 -0.346938
CD1C -0.253005
GNLY -0.528670
HLA-DPB1 -1.039994
... ...
TTTAGCTGTACTCT S100A9 1.112879
SDPR -0.388176
TREML1 -0.328625
TUBB1 -0.350375
VDAC3 -0.524551
[1600 rows x 1 columns]
-- Note this is a sparse matrix in IJV/COO format
```

```
>>> arr = soma.obs.open_array()
>>> arr.df[:]
>>> soma.obs.df()
orig.ident nCount_RNA nFeature_RNA RNA_snn_res.0.8 letter.idents groups RNA_snn_res.1
obs_id
AAATTCGAATCACG 0 327.0 62 1 1 g2 1
AAGCAAGAGCTTAG 0 126.0 48 0 0 g1 0
AAGCGACTTTGACG 0 443.0 77 1 1 g1 1
AATGCGTGGACGGA 0 389.0 73 1 1 g1 1
AATGTTGACAGTCA 0 100.0 41 0 0 g1 0
... ... ... ... ... ... ... ...
TTACGTACGTTCAG 0 228.0 39 0 0 g1 0
TTGAGGACTACGCA 0 787.0 88 0 0 g1 2
TTGCATTGAGCTAC 0 104.0 40 0 0 g2 2
TTGGTACTGAATCC 0 135.0 45 0 0 g1 2
TTTAGCTGTACTCT 0 462.0 86 1 1 g1 1
[80 rows x 7 columns]
>>> arr = soma.var.open_array()
>>> arr.df[:]
>>> soma.var.df()
vst.mean vst.variance vst.variance.expected vst.variance.standardized vst.variable
var_id
AKR1C3 0.2625 1.132753 0.553424 2.021191 1
CA2 0.4500 3.263291 1.685451 1.765922 1
CD1C 0.1750 0.576582 0.271217 2.052014 1
GNLY 2.4000 43.762025 24.078566 1.817468 1
...
SDPR 1.1125 15.746677 8.835280 1.680686 1
TREML1 0.3375 1.365665 0.761869 1.792519 1
TUBB1 0.8875 16.202373 6.352400 1.634371 1
VDAC3 1.1250 30.971519 8.986513 2.137607 1
Expand All @@ -219,30 +231,41 @@ VDAC3 1.1250 30.971519 8.986513 2
```
>>> soma.obsm._get_member_names()
['X_tsne', 'X_pca']
>>> arr = soma.obsm['X_pca'].open_array()
>>> arr.df[:]
obs_id X_pca_1 X_pca_2 ... X_pca_18 X_pca_19
0 AAATTCGAATCACG -0.599730 0.970809 ... -0.127195 0.026804
1 AAGCAAGAGCTTAG -0.919219 -2.043828 ... 0.009386 -0.019896
2 AAGCGACTTTGACG -1.380380 1.284101 ... -0.041855 0.027550
.. ... ... ... ... ... ...
78 TTGGTACTGAATCC -1.418764 0.764986 ... -0.064450 0.099118
79 TTTAGCTGTACTCT -1.447483 1.583223 ... -0.014984 0.033992
[80 rows x 20 columns]
>>> soma.obsm['X_pca'].df()
X_pca_1 X_pca_2 ... X_pca_18 X_pca_19
obs_id ...
AAATTCGAATCACG -0.599730 0.970809 ... -0.127195 0.026804
AAGCAAGAGCTTAG -0.919219 -2.043828 ... 0.009386 -0.019896
AAGCGACTTTGACG -1.380380 1.284101 ... -0.041855 0.027550
AATGCGTGGACGGA -1.494413 1.783583 ... -0.045108 0.055206
AATGTTGACAGTCA -0.487798 -1.162107 ... -0.167920 0.026950
... ... ... ... ... ...
TTACGTACGTTCAG 8.858789 -0.195728 ... -0.428616 -0.294552
TTGAGGACTACGCA -0.917909 1.610199 ... -0.113981 -0.110469
TTGCATTGAGCTAC -0.997103 -0.155518 ... 0.056784 -0.027052
TTGGTACTGAATCC -1.418764 0.764986 ... -0.064450 0.099118
TTTAGCTGTACTCT -1.447483 1.583223 ... -0.014984 0.033992
[80 rows x 19 columns]
```

```
>>> arr = soma.raw.X.data.open_array()
>>> arr.df[:]
obs_id var_id value
0 AAATTCGAATCACG ADAR 3.452557
1 AAATTCGAATCACG AIF1 3.452557
... ... ... ...
4454 TTTAGCTGTACTCT XBP1 3.119940
4455 TTTAGCTGTACTCT ZFP36L1 3.119940
[4456 rows x 3 columns]
>>> soma.raw.X["data"].df()
value
obs_id var_id
AAATTCGAATCACG ADAR 3.452557
AIF1 3.452557
ANXA2 3.452557
ARHGDIA 3.452557
ASGR1 3.452557
... ...
TTTAGCTGTACTCT TYMP 4.693411
TYROBP 5.277120
VPS28 3.119940
XBP1 3.119940
ZFP36L1 3.119940
[4456 rows x 1 columns]
```

```
Expand Down
4 changes: 2 additions & 2 deletions apis/python/doc/assay_matrix.md
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Original file line number Diff line number Diff line change
Expand Up @@ -31,8 +31,8 @@ See the TileDBObject constructor.

The `row_dataframe` and `col_dataframe` are nominally:

* `soma.obs` and `soma.var`, for `soma.X.data`
* `soma.obs` and `soma.raw.var`, for `soma.raw.X.data`
* `soma.obs` and `soma.var`, for `soma.X["data"]`
* `soma.obs` and `soma.raw.var`, for `soma.raw.X["data"]`
* `soma.obs` and `soma.obs`, for `soma.obsp` elements
* `soma.var` and `soma.var`, for `soma.obsp` elements

Expand Down
2 changes: 1 addition & 1 deletion apis/python/examples/anndata-and-tiledb.md
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Original file line number Diff line number Diff line change
Expand Up @@ -114,7 +114,7 @@ ZYX 403
[1838 rows x 1 columns]
>>> soma.X.data.df()
>>> soma.X["data"].df()
value
obs_id var_id
AAACATACAACCAC-1 AAGAB -0.186726
Expand Down
4 changes: 2 additions & 2 deletions apis/python/src/tiledbsc/assay_matrix.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,8 +43,8 @@ def __init__(
The `row_dataframe` and `col_dataframe` are nominally:
* `soma.obs` and `soma.var`, for `soma.X.data`
* `soma.obs` and `soma.raw.var`, for `soma.raw.X.data`
* `soma.obs` and `soma.var`, for `soma.X["data"]`
* `soma.obs` and `soma.raw.var`, for `soma.raw.X["data"]`
* `soma.obs` and `soma.obs`, for `soma.obsp` elements
* `soma.var` and `soma.var`, for `soma.obsp` elements
Expand Down
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