umap | Uniform Manifold Approximation and Projection | Data Visualization library

 by   lmcinnes Python Version: 0.5.3 License: BSD-3-Clause

kandi X-RAY | umap Summary

kandi X-RAY | umap Summary

umap is a Python library typically used in Analytics, Data Visualization applications. umap has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install umap' or download it from GitHub, PyPI.

Uniform Manifold Approximation and Projection
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            kandi-support Support

              umap has a medium active ecosystem.
              It has 6249 star(s) with 728 fork(s). There are 123 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 385 open issues and 319 have been closed. On average issues are closed in 39 days. There are 20 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of umap is 0.5.3

            kandi-Quality Quality

              umap has 0 bugs and 0 code smells.

            kandi-Security Security

              umap has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              umap code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              umap is licensed under the BSD-3-Clause License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              umap releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.

            Top functions reviewed by kandi - BETA

            kandi has reviewed umap and discovered the below as its top functions. This is intended to give you an instant insight into umap implemented functionality, and help decide if they suit your requirements.
            • Visualize a Mapping object
            • Plot matplotlib plot
            • Calculate the extent of a mesh
            • Embed a datashader image
            • Optimizes an eclients
            • Clips a value
            • Compute the rdist between two vectors
            • Create a interactive interactive interactive map
            • Get embedding attribute
            • Calculate the Minkowski gradient
            • Plot the nearest neighbors of the graph
            • Compute the gradient of the Dirichlet distribution
            • Calculate the weighted Minkowski gradient
            • Compute the hellinger
            • Display a plot
            • Calculate discrete parameters for a given metric
            • Calculate bay correlation coefficient
            • Compute the cosine between two vectors
            • Calculate the trustiness vector for a given source
            • Computes the gradient of the Dirichlet distribution
            • Optimizes the layout of an eclidean algorithm
            • Estimate embedding
            • Displays connectivity
            • Optimizes the layout
            • Optimize the layout in a single step
            • Computes the correlation between two matrices
            Get all kandi verified functions for this library.

            umap Key Features

            No Key Features are available at this moment for umap.

            umap Examples and Code Snippets

            Interactivity,UMAP projection
            Rdot img1Lines of Code : 26dot img1License : Non-SPDX (NOASSERTION)
            copy iconCopy
            umap_selected <- umap_embedding(paletteer_palettes())
            
            umap_selected
            
            #> $colorBlindness.Blue2DarkRed12Steps
            #>  [1] "#290AD8" "#264DFF" "#3FA0FF" "#72D9FF" "#AAF7FF" "#E0FFFF" "#FFFFBF"
            #>  [8] "#FFE099" "#FFAD72" "#F76D5E" "#D82632" "#A  
            Install,Usage
            Pythondot img2Lines of Code : 25dot img2License : Permissive (MIT)
            copy iconCopy
            import pandas as pd
            from umap import UMAP
            
            # pip install -U sentence-transformers
            from sentence_transformers import SentenceTransformer
            
            # Load the universal sentence encoder
            model = SentenceTransformer('paraphrase-MiniLM-L6-v2')
            
            # Load original dat  
            Running the Nextflow pipeline on the example dataset
            Pythondot img3Lines of Code : 19dot img3License : Strong Copyleft (GPL-3.0)
            copy iconCopy
            nextflow run aertslab/SCENICprotocol \
                -profile docker,test
            
            mkdir example && cd example/
            # Transcription factors:
            wget https://raw.githubusercontent.com/aertslab/SCENICprotocol/master/example/test_TFs_tiny.txt
            # Motif to TF annotation da  
            umap - galaxy10sdss
            Pythondot img4Lines of Code : 225dot img4License : Non-SPDX (BSD 3-Clause "New" or "Revised" License)
            copy iconCopy
            """
            UMAP on the Galaxy10SDSS dataset
            ---------------------------------------------------------
            
            This is an example of using UMAP on the Galaxy10SDSS
            dataset. The goal of this example is largely to
            demonstrate the use of supervised learning as an
            effe  
            umap - mnist torus sphere example
            Pythondot img5Lines of Code : 84dot img5License : Non-SPDX (BSD 3-Clause "New" or "Revised" License)
            copy iconCopy
            #!/usr/bin/env python
            
            import matplotlib.pyplot as plt
            import numba
            import numpy as np
            from mayavi import mlab
            from sklearn.datasets import load_digits
            from sklearn.model_selection import train_test_split
            
            import umap
            
            digits = load_digits()
            X_train,  
            umap - plot algorithm comparison
            Pythondot img6Lines of Code : 82dot img6License : Non-SPDX (BSD 3-Clause "New" or "Revised" License)
            copy iconCopy
            """
            Comparison of Dimension Reduction Techniques
            --------------------------------------------
            
            A comparison of several different dimension reduction
            techniques on a variety of toy datasets. The datasets
            are all toy datasets, but should provide a repr  
            ReadTheDocs trouble with sklearn/umap
            Pythondot img7Lines of Code : 4dot img7License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            pip>=19.0
            numpy
            llvmlite==0.35.0
            
            How to install umap and umap.plot with Google Colab
            Pythondot img8Lines of Code : 4dot img8License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            !pip install umap-learn[plot]
            !pip install holoviews
            !pip install -U ipykernel
            
            copy iconCopy
            numba.errors.LoweringError: Failed in nopython mode pipeline (step: nopython mode backend)
            Type of #4 arg mismatch: i1 != i32
            
            copy iconCopy
            git clone https://github.com/lmcinnes/umap
            cd umap
            pip install --user -r requirements.txt
            python setup.py install --user
            
            !pip install 'umap-learn==0.3.10'
            

            Community Discussions

            QUESTION

            'what' must be a function or character string in R error message
            Asked 2022-Apr-08 at 14:36

            I am plotting different umaps. I have a part of the code that worked yesterday, however today I get the error message: Error in do.call(c, lapply(2:ncol(nn_idx), function(i) as.vector(rbind(nn_idx[, : 'what' must be a function or character string"

            My code is the following:

            ...

            ANSWER

            Answered 2022-Apr-07 at 17:52

            Maybe you have overwritten the primitive function c ? R lets you do that, I was able to replicate your error bellow, and to fix it you can just remove c and it will revert back to the primitive function, so you can try that, please let me know if it fixes your problem.

            Source https://stackoverflow.com/questions/71786470

            QUESTION

            Ploty problem with callbacks saying x and y cannot be both list of column references or list o columns
            Asked 2022-Apr-01 at 21:17

            Consider the following dash app which is used inside a flask app:

            ...

            ANSWER

            Answered 2022-Apr-01 at 21:17

            I had to filter data before using it in callbacks. Now it looks like below:

            Source https://stackoverflow.com/questions/71711095

            QUESTION

            Normalizing Topic Vectors in Top2vec
            Asked 2022-Feb-16 at 16:13

            I am trying to understand how Top2Vec works. I have some questions about the code that I could not find an answer for in the paper. A summary of what the algorithm does is that it:

            • embeds words and vectors in the same semantic space and normalizes them. This usually has more than 300 dimensions.
            • projects them into 5-dimensional space using UMAP and cosine similarity.
            • creates topics as centroids of clusters using HDBSCAN with Euclidean metric on the projected data.

            what troubles me is that they normalize the topic vectors. However, the output from UMAP is not normalized, and normalizing the topic vectors will probably move them out of their clusters. This is inconsistent with what they described in their paper as the topic vectors are the arithmetic mean of all documents vectors that belong to the same topic.

            This leads to two questions:

            How are they going to calculate the nearest words to find the keywords of each topic given that they altered the topic vector by normalization?

            After creating the topics as clusters, they try to deduplicate the very similar topics. To do so, they use cosine similarity. This makes sense with the normalized topic vectors. In the same time, it is an extension of the inconsistency that normalizing topic vectors introduced. Am I missing something here?

            ...

            ANSWER

            Answered 2022-Feb-16 at 16:13

            I got the answer to my questions from the source code. I was going to delete the question but I will leave the answer any way.

            It is the part I missed and is wrong in my question. Topic vectors are the arithmetic mean of all documents vectors that belong to the same topic. Topic vectors belong to the same semantic space where words and documents vector live.

            That is why it makes sense to normalize them since all words and documents vectors are normalized, and to use the cosine metric when looking for duplicated topics in the higher original semantic space.

            Source https://stackoverflow.com/questions/71143240

            QUESTION

            Why does std::distance doesn't work on iterator of unordered_map?
            Asked 2022-Feb-05 at 07:31

            I have this code:

            ...

            ANSWER

            Answered 2022-Feb-05 at 07:04

            Result of std::next(itr1, 3) is beyond umap.end() and is the source of segfault. More of, umap.end() and umap.begin() would be invalidated by content of unordered_map. This would work but wouldn't allow use of std::distance anyway:

            Source https://stackoverflow.com/questions/70995866

            QUESTION

            How can I identify the anomalous records from the Isolation Forest results?
            Asked 2022-Jan-28 at 09:42

            I am trying to use the Isolation Forest algorithm in the Solitude package to identify anomalous rows in my data.

            I'm using the examples in the documentation to learn about the algorithm, this example uses the Pima Indians Diabetes dataset.

            At the end of the example it provides a dataframe of ids, average_depth and anomaly_score sorted from highest score to lowest.

            How can I tie back the results of the model to the original dataset to see the rows with the highest anomaly score?

            Here's the example from the package documentation

            ...

            ANSWER

            Answered 2022-Jan-22 at 01:29

            Well this was a bit hard.

            Let me know if this code helps you:

            Source https://stackoverflow.com/questions/70808913

            QUESTION

            How Do I delete a remap from .ideavim?
            Asked 2022-Jan-07 at 18:30

            Am using intelij and Ideavim. I remapped Esc to gh by typing inoremap gh in .ideavimrc and its been working fine. Recently, I found out that while typing a word like "Highlight", the gh inbetween will always be read as gh and then vim will move out of insert mode.

            I've tried to revert it by deleting the content in .ideavim but the old gh is still working. I've also tried changing it to gg and then to jj in an attempt to may be erase the old gh, but they seem to be pilling up.

            When I type in :imap, I see this

            And all three of them, gg, gh, and jj are all working as Esc when in insert mode.

            How do I get rid of the rest and leave only jj?

            I've also tried a lot of suggestions, like using iumap or umap but it doesn't seem to be working. Am on windows.

            ...

            ANSWER

            Answered 2022-Jan-07 at 18:30

            The solution was imapclear. This cleared all the previous remaps I made. Note, it will clear only the remaps that are effective in insert mode only. Here is a very usefully resource that helped me https://vim.fandom.com/wiki/Mapping_keys_in_Vim_-_Tutorial_(Part_1)

            Source https://stackoverflow.com/questions/70615244

            QUESTION

            MultiInputOutput Model RandomSearch with Scikit Pipelines
            Asked 2021-Dec-15 at 09:19

            I am trying to compare different regression stategies for a forecasting problem:

            • Using algorithms that support multiple input output regression by default (i.e Linear Regression, Trees etc..).
            • Using algorithms a wrapper to do multiple input output regression (i.e SVR, XGboost)
            • Using the chained regressor to exploit correlations between my targets (as my forecast at t+1 is auto-correlated with the target at t+2).

            The documentation of scikit for the multiple input output wrappers is actually not that good but it is mentioned that:

            https://scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputRegressor.html

            ...

            ANSWER

            Answered 2021-Dec-15 at 09:19

            Dear colleagues it seems that this was due to a problem in XGB.Regressor in any case the right way of creating parameters for the MultiOutput Regressor within a pipeline it would be:

            Source https://stackoverflow.com/questions/70181577

            QUESTION

            Get input of fully connected layer of ResNet model during runtime
            Asked 2021-Dec-06 at 23:26

            Found a Solution, left it as an answer to this question down below :)

            Info about the project: Classification task with 2 classes.

            I am trying to get the output of the fully connected layer of my model for each image I put into the model during runtime. I plan to use them after the model is done training or testing all images to visualize with UMAP.

            The model:

            ...

            ANSWER

            Answered 2021-Dec-06 at 15:00

            x_hat is this vector and is [batch_size, 2048]. So just modify your training step to also return x_hat.

            Source https://stackoverflow.com/questions/70245605

            QUESTION

            Divide legend in two columns ggplot2
            Asked 2021-Nov-29 at 16:19

            I have the following table:

            ...

            ANSWER

            Answered 2021-Nov-29 at 16:13

            You never define fill= as an aesthetic; use guides(color=...) instead.

            Note: with this sample data, I needed to add another color to the scale_color_manual; it shouldn't be necessary with your real data. The only change I'm adding to your code is one argument to guides.

            Source https://stackoverflow.com/questions/70157587

            QUESTION

            Creating unordered map in C++ for counting the pairs
            Asked 2021-Nov-27 at 00:56

            So let's say I have an array, 1 2 1 2 3 4 2 1 and I want to store all the (arr[i], arr[i-1) such that arr[i] != arr[i-1] as a pair in unordered_map for counting these pairs.
            For e.g.

            ...

            ANSWER

            Answered 2021-Nov-26 at 17:29

            You can't just use unordered_map with a pair because there is no default hash implemented. You can however use map which should work fine for your purpose because pair does implement <. See Why can't I compile an unordered_map with a pair as key? when you really want unordered_map.

            You can construct pair with curly braces like this

            Source https://stackoverflow.com/questions/70127777

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install umap

            You can install using 'pip install umap' or download it from GitHub, PyPI.
            You can use umap like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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