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FIX: transposing ranks for final output. (#99)
* FIX: transposing ranks for final output. Updating documentation in readme accordingly * Adding in transformers for metadata * fixing import * fixing index name for ranks * Add transformer * fixed ordering of rank calculations in q2 * TST: made transposes consistent Found that standalone cli wasn't consistent with q2. Biases weren't factored into standalone ranks. Now fixed. * TST:minor refactor * flake8 * Adding check for soils * TST: adding additional check in cystic fibrosis study. Also adding in cool figure, because, why not * Adding in changelog update * Update CHANGELOG.md
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| Original file line number | Diff line number | Diff line change |
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "!ls" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 2, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "\u001b[34mlatent_dim_3_input_prior_1.00_output_prior_1.00_beta1_0.90_beta2_0.95\u001b[m\u001b[m\r\n", | ||
| "latent_dim_3_input_prior_1.00_output_prior_1.00_beta1_0.90_beta2_0.95_embedding.txt\r\n", | ||
| "latent_dim_3_input_prior_1.00_output_prior_1.00_beta1_0.90_beta2_0.95_ordination.txt\r\n", | ||
| "latent_dim_3_input_prior_1.00_output_prior_1.00_beta1_0.90_beta2_0.95_ranks.txt\r\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "!ls testing" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# Standalone check" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 3, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import pandas as pd\n", | ||
| "import numpy as np\n", | ||
| "fname = 'latent_dim_3_input_prior_1.00_output_prior_1.00_beta1_0.90_beta2_0.95_ranks.txt'\n", | ||
| "ranks = pd.read_csv(f'testing/{fname}', sep='\\t', index_col=0)\n", | ||
| "microbe_metadata = pd.read_csv('microbe-metadata.txt', sep='\\t', index_col=0)\n", | ||
| "metabolite_metadata = pd.read_csv('metabolite-metadata.txt', sep='\\t', index_col=0)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 4, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "microbe_metadata = microbe_metadata.loc[ranks.columns]\n", | ||
| "i = microbe_metadata.Taxon.apply(lambda x: 'Pseudomonas' in x)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 5, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "pseudomonas = microbe_metadata.loc[i].index" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 6, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "metabolite_metadata = metabolite_metadata.dropna(subset=['expert_annotation'])" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 7, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "19" | ||
| ] | ||
| }, | ||
| "execution_count": 7, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "np.sum(ranks.loc[metabolite_metadata.index, pseudomonas[0]] > 0)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# qiime2 check" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 8, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stderr", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "/Users/jmorton/miniconda3/envs/qiime2-2019.7/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", | ||
| " _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n", | ||
| "/Users/jmorton/miniconda3/envs/qiime2-2019.7/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", | ||
| " _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n", | ||
| "/Users/jmorton/miniconda3/envs/qiime2-2019.7/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", | ||
| " _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n", | ||
| "/Users/jmorton/miniconda3/envs/qiime2-2019.7/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", | ||
| " _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n", | ||
| "/Users/jmorton/miniconda3/envs/qiime2-2019.7/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", | ||
| " _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n", | ||
| "/Users/jmorton/miniconda3/envs/qiime2-2019.7/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", | ||
| " np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n", | ||
| "/Users/jmorton/miniconda3/envs/qiime2-2019.7/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", | ||
| " _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n", | ||
| "/Users/jmorton/miniconda3/envs/qiime2-2019.7/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", | ||
| " _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n", | ||
| "/Users/jmorton/miniconda3/envs/qiime2-2019.7/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", | ||
| " _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n", | ||
| "/Users/jmorton/miniconda3/envs/qiime2-2019.7/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", | ||
| " _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n", | ||
| "/Users/jmorton/miniconda3/envs/qiime2-2019.7/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", | ||
| " _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n", | ||
| "/Users/jmorton/miniconda3/envs/qiime2-2019.7/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", | ||
| " np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import qiime2\n", | ||
| "ranks = qiime2.Artifact.load('ranks.qza').view(pd.DataFrame)\n", | ||
| "microbe_metadata = pd.read_csv('microbe-metadata.txt', sep='\\t', index_col=0)\n", | ||
| "metabolite_metadata = pd.read_csv('metabolite-metadata.txt', sep='\\t', index_col=0)\n", | ||
| "microbe_metadata = microbe_metadata.loc[ranks.columns]\n", | ||
| "i = microbe_metadata.Taxon.apply(lambda x: 'Pseudomonas' in x)\n", | ||
| "pseudomonas = microbe_metadata.loc[i].index" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 9, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "metabolite_metadata = metabolite_metadata.dropna(subset=['expert_annotation'])" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 10, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "19" | ||
| ] | ||
| }, | ||
| "execution_count": 10, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "np.sum(ranks.loc[metabolite_metadata.index, pseudomonas[0]] > 0)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.6.7" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } |
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