From b2022e2a329c4d9c4a3126909533368b06b37a95 Mon Sep 17 00:00:00 2001
From: Oren Ben-Kiki <oren@ben-kiki.org>
Date: Mon, 8 Apr 2024 10:21:01 +0300
Subject: [PATCH] Do not copy __name__.

---
 docs/v0.1.0/.documenter-siteinfo.json | 2 +-
 docs/v0.1.0/anndata_format.html       | 6 +++++-
 docs/v0.1.0/index.html                | 2 +-
 docs/v0.1.0/search_index.js           | 2 +-
 docs/v0.1.0/spheres.html              | 2 +-
 src/anndata_format.jl                 | 6 +++---
 6 files changed, 12 insertions(+), 8 deletions(-)

diff --git a/docs/v0.1.0/.documenter-siteinfo.json b/docs/v0.1.0/.documenter-siteinfo.json
index bffc5b6..26f9fef 100644
--- a/docs/v0.1.0/.documenter-siteinfo.json
+++ b/docs/v0.1.0/.documenter-siteinfo.json
@@ -1 +1 @@
-{"documenter":{"julia_version":"1.10.0","generation_timestamp":"2024-04-07T18:39:26","documenter_version":"1.3.0"}}
\ No newline at end of file
+{"documenter":{"julia_version":"1.10.2","generation_timestamp":"2024-04-08T10:15:27","documenter_version":"1.3.0"}}
\ No newline at end of file
diff --git a/docs/v0.1.0/anndata_format.html b/docs/v0.1.0/anndata_format.html
index ecea991..19029d2 100644
--- a/docs/v0.1.0/anndata_format.html
+++ b/docs/v0.1.0/anndata_format.html
@@ -235,6 +235,10 @@ <h1 id="AnnData-Format">
 </code>.
 </li>
 <li>The 
+<code>__name__
+</code> scalar is not copied.
+</li>
+<li>The 
 <code>excluded_gene
 </code> and 
 <code>excluded_cell
@@ -544,7 +548,7 @@ <h2 id="Index">
 <hr/>
 <p>This document was generated with 
 <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl
-</a> version 1.3.0. Using Julia version 1.10.0.
+</a> version 1.3.0. Using Julia version 1.10.2.
 </p>
 </section>
 <footer class="modal-card-foot">
diff --git a/docs/v0.1.0/index.html b/docs/v0.1.0/index.html
index 659818a..98a45c3 100644
--- a/docs/v0.1.0/index.html
+++ b/docs/v0.1.0/index.html
@@ -238,7 +238,7 @@ <h1 id="Index">
 <hr/>
 <p>This document was generated with 
 <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl
-</a> version 1.3.0. Using Julia version 1.10.0.
+</a> version 1.3.0. Using Julia version 1.10.2.
 </p>
 </section>
 <footer class="modal-card-foot">
diff --git a/docs/v0.1.0/search_index.js b/docs/v0.1.0/search_index.js
index 4ec95ea..d2f294f 100644
--- a/docs/v0.1.0/search_index.js
+++ b/docs/v0.1.0/search_index.js
@@ -1,3 +1,3 @@
 var documenterSearchIndex = {"docs":
-[{"location":"anndata_format.html#AnnData-Format","page":"AnnData Format","title":"AnnData Format","text":"","category":"section"},{"location":"anndata_format.html","page":"AnnData Format","title":"AnnData Format","text":"Metacells.AnnDataFormat\nMetacells.AnnDataFormat.import_h5ads!","category":"page"},{"location":"anndata_format.html#Metacells.AnnDataFormat","page":"AnnData Format","title":"Metacells.AnnDataFormat","text":"Import and export metacells data from/to h5ad files. This allows moving data between the old Python/C++ based AnnData world and the new Julia based Daf world.\n\n\n\n\n\n","category":"module"},{"location":"anndata_format.html#Metacells.AnnDataFormat.import_h5ads!","page":"AnnData Format","title":"Metacells.AnnDataFormat.import_h5ads!","text":"function import_h5ads!(;\n    destination::DafWriter,\n    raw_cells_h5ad::Maybe{AbstractString} = nothing,\n    clean_cells_h5ad::AbstractString,\n    metacells_h5ad::AbstractString,\n    type_property::Maybe{AbstractString} = nothing,\n    rename_type::Maybe{AbstractString} = \"type\",\n    type_colors_csv::Maybe{AbstractString} = nothing,\n    type_properties::Maybe{AbstractStringSet} = nothing,\n    properties_defaults::Maybe{Dict} = nothing,\n)::Nothing\n\nImport an AnnData based metacells dataset into a Daf destination data set. Ideally, the input must include clean_cells_h5ad and the metacells_h5ad computed for them, and optionally also the raw_cells_h5ad including the excluded cells and genes.\n\nIf type annotations were assigned to the metacells, then the name of the type_property should be specified. This can be further enhanced by specifying a type_colors_csv file mapping type names to colors. This should be a comma or tab separated file containing at least two columns, one named \"color\" and one with the same name as the type_property. For consistency, by default the type_property is renamed to the value of rename_type (by default, \"type\"). You can disable this by setting rename_type to nothing. We also call reconstruct_axis! to build the type axis; you can therefore specify an empty_type name, which will be converted to the empty string, to match the Daf convention of \"no value\" for string data, and specify an explicit set of type_properties (by default, any per-metacell property that has the same value for all metacells of each type will be converted to a type property) and properties_defaults.\n\nThis will mostly just read all the specified h5ad files and copy the data into the destination, with the following changes to match the Daf capabilities and conventions:\n\nThe X matrix of the cells is renamed to UMIs, and the X matrix of the metacells is renamed to fraction.\nThe excluded_gene and excluded_cell masks are not copied. Instead, if raw_cells_h5ad is specified, an is_excluded mask is created for both cells and genes, marking these that exist only in the raw_cells_h5ad and not in clean_cells_h5ad and metacells_h5ad.\nThe full_gene_index is not copied.\nThe properly_sampled_gene mask is renamed to the per-gene is_properly_sampled mask.\nThe bursty_lonely_gene mask is renamed to the per-gene is_bursty_lonely mask.\nThe lateral_gene mask is renamed to the per-gene is_lateral mask.\nThe noisy_gene mask is renamed to the per-gene is_noisy mask.\nThe rare_gene mask is renamed to the per-gene is_rare mask.\nThe rare_gene_module has 1 added to it (that is, \"no module\" is 0 in Daf) and is renamed to rare_module.\nThe lateral_genes_module has 1 added to it (that is, \"no module\" is 0 in Daf) and is renamed to lateral_module.\nThe marker_gene mask is renamed to the per-gene is_marker mask.\nThe selected_gene mask is renamed to the per-gene is_selected mask.\nThe ignored_gene mask is renamed to the per-gene is_ignored mask.\nThe ignored_gene_of_<type> masks are converted to an is_ignored mask per-gene-per-type.\nThe projected_noisy_gene mask is renamed to the per-gene is_projected_noisy mask.\nThe atlas_gene, atlas_lateral_gene, atlas_noisy_gene, atlas_marker_gene masks are renamed to the is_atlas, is_atlas_lateral, is_atlas_noisy and is_atlas_marker per-gene masks.\nThe essential_gene_of_<type> masks are converted to an is_essential mask per-gene-per-type.\nThe atlas_essential_gene_of_<type> masks are converted to an is_atlas_essential mask per-gene-per-type.\nThe fitted_gene_of_<type> masks are converted to an is_fitted mask per-gene-per-type.\nThe fitted mask per-gene-per-metacell is renamed to is_fitted.\nThe misfit mask per-gene-per-metacell is renamed to is_misfit.\nThe essential mask per-gene-per-metacell is renamed to is_essential.\nThe full_cell_index is not copied.\nThe properly_sampled_cell mask is renamed to the per-cell is_properly_sampled mask.\nThe rare_cell mask is renamed to the per-cell is_rare mask.\nThe cells_rare_gene_module has 1 added to it (that is, \"no module\" is 0 in Daf) and is renamed to rare_gene_module.\nThe per-cell dissolve mask is renamed to is_dissolved.\nThe per-cell metacell integer annotation is not copied, and the metacell_name string annotation is renamed to metacell.\nThe per-cell most_similar integer annotation is not copied, and the most_similar_name string annotation is renamed to metacell.most_similar.\nThe rare_metacell mask is renamed to the per-metacell is_rare mask.\nThe per-metacell metacells_level is renamed to level.\nThe per-metacell similar mask is renamed to is_similar.\n\nnote: Note\nThere is much duplication of data between the three h5ad files (in particular, per-gene data). Data in raw_cells_h5ad will override data in clean_cells_h5ad, which will override data in metacells_h5ad.\n\nnote: Note\nIt is common to call reconstruct_axis! on the result (e.g., if the cells were collected from a set of batches).\n\n\n\n\n\n","category":"function"},{"location":"anndata_format.html#Index","page":"AnnData Format","title":"Index","text":"","category":"section"},{"location":"anndata_format.html","page":"AnnData Format","title":"AnnData Format","text":"Pages = [\"anndata_format.md\"]","category":"page"},{"location":"spheres.html#Neighborhoods","page":"Neighborhoods","title":"Neighborhoods","text":"","category":"section"},{"location":"spheres.html","page":"Neighborhoods","title":"Neighborhoods","text":"Metacells.Spheres\nMetacells.Spheres.compute_spheres!","category":"page"},{"location":"spheres.html#Metacells.Spheres","page":"Neighborhoods","title":"Metacells.Spheres","text":"Given a set of raw metacells, partition them into spheres such that all metacells in the same sphere are within some (fold factor) radius of each other. The centroids of these spheres can serve as a representation of the cell state manifold which is less sensitive to oversampling of common cell states.\n\n\n\n\n\n","category":"module"},{"location":"spheres.html#Metacells.Spheres.compute_spheres!","page":"Neighborhoods","title":"Metacells.Spheres.compute_spheres!","text":"function compute_spheres(\n    daf::DafWriter;\n    max_sphere_fold_factor::AbstractFloat = 3.0,\n    gene_fraction_regularization::AbstractFloat = 1e-5,\n    min_significant_gene_UMIs:: Unsigned = 40,\n)::Nothing\n\nPartition raw metacells into distinct spheres, using a variant of union-find:\n\nCompute a distance between each two metacells, defined as the maximal fold factor of any of the genes. This fold factor is the absolute value of log base 2 of the fraction of the gene in both metacells, using the gene_fraction_regularization (by default, 1e-5). If the sum of the total UMIs of the gene in both metacells is less than min_significant_gene_UMIs (by default, 40), we ignore this fold factor as insignificant.\nInitially place each metacell in its own sphere.\nPass on all metacell pairs, ordered by increasing distance. If the metacells belong to different spheres, merge both spheres into a single one if the maximal distance between the metacells of the combined sphere is no more than max_sphere_fold_factor (by default, 3.0, or 8x).\nCompute the centroid (geomean) of each gene's fraction of each sphere, using the same gene_fraction_regularization as above.\n\nCONTRACT\n\n\n\n\n\n","category":"function"},{"location":"spheres.html#Index","page":"Neighborhoods","title":"Index","text":"","category":"section"},{"location":"spheres.html","page":"Neighborhoods","title":"Neighborhoods","text":"Pages = [\"spheres.md\"]","category":"page"},{"location":"index.html#Metacells","page":"Metacells","title":"Metacells","text":"","category":"section"},{"location":"index.html","page":"Metacells","title":"Metacells","text":"Metacells.Metacells","category":"page"},{"location":"index.html#Metacells.Metacells","page":"Metacells","title":"Metacells.Metacells","text":"The Metacells.jl package provides computational services for the metacells package, using Daf to hold the data. In the future, we'll ideally migrate all of the metacellspackage computations to this package, converting the Python package to a thin wrapper, and provide a similar thin R wrapper to provide metacell analysis from R as well. For now,Metacells.jlonly provides a subset of the features of the Pythonmetacellspackage, which requires users to convert data fromAnnData(for the old features) toDaf (to the new features).\n\n\n\n\n\n","category":"module"},{"location":"index.html#Index","page":"Metacells","title":"Index","text":"","category":"section"},{"location":"index.html","page":"Metacells","title":"Metacells","text":"","category":"page"}]
+[{"location":"anndata_format.html#AnnData-Format","page":"AnnData Format","title":"AnnData Format","text":"","category":"section"},{"location":"anndata_format.html","page":"AnnData Format","title":"AnnData Format","text":"Metacells.AnnDataFormat\nMetacells.AnnDataFormat.import_h5ads!","category":"page"},{"location":"anndata_format.html#Metacells.AnnDataFormat","page":"AnnData Format","title":"Metacells.AnnDataFormat","text":"Import and export metacells data from/to h5ad files. This allows moving data between the old Python/C++ based AnnData world and the new Julia based Daf world.\n\n\n\n\n\n","category":"module"},{"location":"anndata_format.html#Metacells.AnnDataFormat.import_h5ads!","page":"AnnData Format","title":"Metacells.AnnDataFormat.import_h5ads!","text":"function import_h5ads!(;\n    destination::DafWriter,\n    raw_cells_h5ad::Maybe{AbstractString} = nothing,\n    clean_cells_h5ad::AbstractString,\n    metacells_h5ad::AbstractString,\n    type_property::Maybe{AbstractString} = nothing,\n    rename_type::Maybe{AbstractString} = \"type\",\n    type_colors_csv::Maybe{AbstractString} = nothing,\n    type_properties::Maybe{AbstractStringSet} = nothing,\n    properties_defaults::Maybe{Dict} = nothing,\n)::Nothing\n\nImport an AnnData based metacells dataset into a Daf destination data set. Ideally, the input must include clean_cells_h5ad and the metacells_h5ad computed for them, and optionally also the raw_cells_h5ad including the excluded cells and genes.\n\nIf type annotations were assigned to the metacells, then the name of the type_property should be specified. This can be further enhanced by specifying a type_colors_csv file mapping type names to colors. This should be a comma or tab separated file containing at least two columns, one named \"color\" and one with the same name as the type_property. For consistency, by default the type_property is renamed to the value of rename_type (by default, \"type\"). You can disable this by setting rename_type to nothing. We also call reconstruct_axis! to build the type axis; you can therefore specify an empty_type name, which will be converted to the empty string, to match the Daf convention of \"no value\" for string data, and specify an explicit set of type_properties (by default, any per-metacell property that has the same value for all metacells of each type will be converted to a type property) and properties_defaults.\n\nThis will mostly just read all the specified h5ad files and copy the data into the destination, with the following changes to match the Daf capabilities and conventions:\n\nThe X matrix of the cells is renamed to UMIs, and the X matrix of the metacells is renamed to fraction.\nThe __name__ scalar is not copied.\nThe excluded_gene and excluded_cell masks are not copied. Instead, if raw_cells_h5ad is specified, an is_excluded mask is created for both cells and genes, marking these that exist only in the raw_cells_h5ad and not in clean_cells_h5ad and metacells_h5ad.\nThe full_gene_index is not copied.\nThe properly_sampled_gene mask is renamed to the per-gene is_properly_sampled mask.\nThe bursty_lonely_gene mask is renamed to the per-gene is_bursty_lonely mask.\nThe lateral_gene mask is renamed to the per-gene is_lateral mask.\nThe noisy_gene mask is renamed to the per-gene is_noisy mask.\nThe rare_gene mask is renamed to the per-gene is_rare mask.\nThe rare_gene_module has 1 added to it (that is, \"no module\" is 0 in Daf) and is renamed to rare_module.\nThe lateral_genes_module has 1 added to it (that is, \"no module\" is 0 in Daf) and is renamed to lateral_module.\nThe marker_gene mask is renamed to the per-gene is_marker mask.\nThe selected_gene mask is renamed to the per-gene is_selected mask.\nThe ignored_gene mask is renamed to the per-gene is_ignored mask.\nThe ignored_gene_of_<type> masks are converted to an is_ignored mask per-gene-per-type.\nThe projected_noisy_gene mask is renamed to the per-gene is_projected_noisy mask.\nThe atlas_gene, atlas_lateral_gene, atlas_noisy_gene, atlas_marker_gene masks are renamed to the is_atlas, is_atlas_lateral, is_atlas_noisy and is_atlas_marker per-gene masks.\nThe essential_gene_of_<type> masks are converted to an is_essential mask per-gene-per-type.\nThe atlas_essential_gene_of_<type> masks are converted to an is_atlas_essential mask per-gene-per-type.\nThe fitted_gene_of_<type> masks are converted to an is_fitted mask per-gene-per-type.\nThe fitted mask per-gene-per-metacell is renamed to is_fitted.\nThe misfit mask per-gene-per-metacell is renamed to is_misfit.\nThe essential mask per-gene-per-metacell is renamed to is_essential.\nThe full_cell_index is not copied.\nThe properly_sampled_cell mask is renamed to the per-cell is_properly_sampled mask.\nThe rare_cell mask is renamed to the per-cell is_rare mask.\nThe cells_rare_gene_module has 1 added to it (that is, \"no module\" is 0 in Daf) and is renamed to rare_gene_module.\nThe per-cell dissolve mask is renamed to is_dissolved.\nThe per-cell metacell integer annotation is not copied, and the metacell_name string annotation is renamed to metacell.\nThe per-cell most_similar integer annotation is not copied, and the most_similar_name string annotation is renamed to metacell.most_similar.\nThe rare_metacell mask is renamed to the per-metacell is_rare mask.\nThe per-metacell metacells_level is renamed to level.\nThe per-metacell similar mask is renamed to is_similar.\n\nnote: Note\nThere is much duplication of data between the three h5ad files (in particular, per-gene data). Data in raw_cells_h5ad will override data in clean_cells_h5ad, which will override data in metacells_h5ad.\n\nnote: Note\nIt is common to call reconstruct_axis! on the result (e.g., if the cells were collected from a set of batches).\n\n\n\n\n\n","category":"function"},{"location":"anndata_format.html#Index","page":"AnnData Format","title":"Index","text":"","category":"section"},{"location":"anndata_format.html","page":"AnnData Format","title":"AnnData Format","text":"Pages = [\"anndata_format.md\"]","category":"page"},{"location":"spheres.html#Neighborhoods","page":"Neighborhoods","title":"Neighborhoods","text":"","category":"section"},{"location":"spheres.html","page":"Neighborhoods","title":"Neighborhoods","text":"Metacells.Spheres\nMetacells.Spheres.compute_spheres!","category":"page"},{"location":"spheres.html#Metacells.Spheres","page":"Neighborhoods","title":"Metacells.Spheres","text":"Given a set of raw metacells, partition them into spheres such that all metacells in the same sphere are within some (fold factor) radius of each other. The centroids of these spheres can serve as a representation of the cell state manifold which is less sensitive to oversampling of common cell states.\n\n\n\n\n\n","category":"module"},{"location":"spheres.html#Metacells.Spheres.compute_spheres!","page":"Neighborhoods","title":"Metacells.Spheres.compute_spheres!","text":"function compute_spheres(\n    daf::DafWriter;\n    max_sphere_fold_factor::AbstractFloat = 3.0,\n    gene_fraction_regularization::AbstractFloat = 1e-5,\n    min_significant_gene_UMIs:: Unsigned = 40,\n)::Nothing\n\nPartition raw metacells into distinct spheres, using a variant of union-find:\n\nCompute a distance between each two metacells, defined as the maximal fold factor of any of the genes. This fold factor is the absolute value of log base 2 of the fraction of the gene in both metacells, using the gene_fraction_regularization (by default, 1e-5). If the sum of the total UMIs of the gene in both metacells is less than min_significant_gene_UMIs (by default, 40), we ignore this fold factor as insignificant.\nInitially place each metacell in its own sphere.\nPass on all metacell pairs, ordered by increasing distance. If the metacells belong to different spheres, merge both spheres into a single one if the maximal distance between the metacells of the combined sphere is no more than max_sphere_fold_factor (by default, 3.0, or 8x).\nCompute the centroid (geomean) of each gene's fraction of each sphere, using the same gene_fraction_regularization as above.\n\nCONTRACT\n\n\n\n\n\n","category":"function"},{"location":"spheres.html#Index","page":"Neighborhoods","title":"Index","text":"","category":"section"},{"location":"spheres.html","page":"Neighborhoods","title":"Neighborhoods","text":"Pages = [\"spheres.md\"]","category":"page"},{"location":"index.html#Metacells","page":"Metacells","title":"Metacells","text":"","category":"section"},{"location":"index.html","page":"Metacells","title":"Metacells","text":"Metacells.Metacells","category":"page"},{"location":"index.html#Metacells.Metacells","page":"Metacells","title":"Metacells.Metacells","text":"The Metacells.jl package provides computational services for the metacells package, using Daf to hold the data. In the future, we'll ideally migrate all of the metacellspackage computations to this package, converting the Python package to a thin wrapper, and provide a similar thin R wrapper to provide metacell analysis from R as well. For now,Metacells.jlonly provides a subset of the features of the Pythonmetacellspackage, which requires users to convert data fromAnnData(for the old features) toDaf (to the new features).\n\n\n\n\n\n","category":"module"},{"location":"index.html#Index","page":"Metacells","title":"Index","text":"","category":"section"},{"location":"index.html","page":"Metacells","title":"Metacells","text":"","category":"page"}]
 }
diff --git a/docs/v0.1.0/spheres.html b/docs/v0.1.0/spheres.html
index 469e1fa..de357c2 100644
--- a/docs/v0.1.0/spheres.html
+++ b/docs/v0.1.0/spheres.html
@@ -265,7 +265,7 @@ <h2 id="Index">
 <hr/>
 <p>This document was generated with 
 <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl
-</a> version 1.3.0. Using Julia version 1.10.0.
+</a> version 1.3.0. Using Julia version 1.10.2.
 </p>
 </section>
 <footer class="modal-card-foot">
diff --git a/src/anndata_format.jl b/src/anndata_format.jl
index e55d232..c5e0a78 100644
--- a/src/anndata_format.jl
+++ b/src/anndata_format.jl
@@ -114,6 +114,7 @@ This will mostly just read all the specified `h5ad` files and copy the data into
 changes to match the ``Daf`` capabilities and conventions:
 
   - The `X` matrix of the cells is renamed to `UMIs`, and the `X` matrix of the metacells is renamed to `fraction`.
+  - The `__name__` scalar is not copied.
   - The `excluded_gene` and `excluded_cell` masks are not copied. Instead, if `raw_cells_h5ad` is specified, an
     `is_excluded` mask is created for both cells and genes, marking these that exist only in the `raw_cells_h5ad` and
     not in `clean_cells_h5ad` and `metacells_h5ad`.
@@ -335,9 +336,8 @@ end
 
 function copy_scalars_data(destination::DafWriter, source::DafReader)::Nothing
     for scalar_name in scalar_names(source)
-        rename = scalar_name == "__name__" ? "name" : scalar_name
-        if !has_scalar(destination, rename)
-            copy_scalar!(; destination = destination, source = source, name = scalar_name, rename = rename)
+        if scalar_name != "__name__" && !has_scalar(destination, scalar_name)
+            copy_scalar!(; destination = destination, source = source, name = scalar_name)
         end
     end
     return nothing