Saravanan666/pypi-org huggingface dataset:
Package: phanim
PHysics ANIMations:
a (quite bad) Physics render libraryThe project is still in the early stages of development, so larger simulation will be slow and features are very limited. Look at the example files to see what cool things you can already do!ExamplesA simple visualisation of the electric field can be found in examples/vectorField.pyA simulation of a triple pendulum with the use of stiff springs can be found in examples/triplePendulum.py. The graphs on the right show the energy that each of the masses has. The yellow graph shows the total energy in the system.Or just a simple double pendulum(looks better imo):RequirementsTo install the requirements run the following command:pip install -r requirements.txtInstallationClone the repository and put your own files in the base folder. Now simply:fromphanimimport*UsageAfter importing you can create a phanim screen as follows:myScreen=phanim.Screen()This will use the device screen resolution. We can also change some of the screen parameters.myScreen=phanim.Screen(fullscreen=False,resolution=(1920,1080))Now we can create something to render on the screen. In this example we will create a simple grid, but the possibilities are endless.grid=phanim.Grid(1,1,10,10)#This creates a grid with each line seperated by 1, and 10 lines to each side of the origin.Now we can add some wait time and animate the grid being added to the screen by:myScreen.wait(60)#This will add an empty animation for 60 frames or 1 seconds.myScreen.play(Create(grid))Now we can run the script and a window with a simple grid should show up.myScreen.run()We can also create different object. For example, a blue arrow, which points to the position of the cursor at all times.
We can create the arrow by defining it like this:arrow=phanim.Arrow(color=color.blue)Now we will create an update function that will be called each frame and move the end of the arrow to the cursor.defsetArrow(screen):arrow.setDirection([0,0],screen.mousePos)Then add this function to the updater list and run the script:myScreen.addUpdater(setArrow)myScreen.play(Create(arrow))myScreen.run()Make sure you only add the .run() command once at the very end of your script. We can also add some dotted lines to track the mouse position like this:lines=DottedLine(),DottedLine()defsetLines(screen):lines[0].setEnds([screen.mousePos[0],0],screen.mousePos)lines[1].setEnds([0,screen.mousePos[1]],screen.mousePos)myScreen.play(Create(lines[0]),Create(lines[1]))myScreen.addUpdater(setLines)After combining the update functions the final script will look like this:fromphanimimport*myScreen=Screen(fullscreen=True)grid=Grid(1,1,10,10)arrow=Arrow(color=color.blue)lines=DottedLine(),DottedLine()defupdate(screen):arrow.setDirection([0,0],screen.mousePos)lines[0].setEnds([screen.mousePos[0],0],screen.mousePos)lines[1].setEnds([0,screen.mousePos[1]],screen.mousePos)myScreen.addUpdater(update)myScreen.wait(60)myScreen.play(Create(grid))myScreen.play(Create(arrow))myScreen.play(Create(lines[0]),Create(lines[1]))myScreen.run()
Package: phanotate
IntroductionPHANOTATE is a tool to annotate phage genomes.  It uses the assumption that non-coding
bases in a phage genome is disadvantageous, and then populates a weighted graph to
find the optimal path through the six frames of the DNA where open reading frames
are beneficial paths, while gaps and overlaps are penalized paths.To installPHANOTATE,pip3 install phanotateorgitclonehttps://github.com/deprekate/PHANOTATE.gitpip3installPHANOTATE/.PHANOTATE ExampleRun on included sample data:phanotate.pytests/NC_001416.1.fastaOutput is the predicted ORFs, and should look like125187+191736+7412636+26332839+28364437+43195737+
...PHANOTATEhas the ability to output different formats: genbank, gff, gff3, fastaOutput a genbank file that contains the genes and genome:$phanotate.pytests/phiX174.fasta-fgenbank|headLOCUSphiX1745386bpFEATURESLocation/QualifiersCDS100..627/note=score:-4.827981E+02CDS687..1622/note=score:-4.857517E+06CDS1686..3227/note=score:-3.785434E+10CDS3224..3484/note=score:-3.779878E+02Output the nucleotide bases of the gene calls in fasta format:$phanotate.pytests/phiX174.fasta-ffna|head-n2
>phiX174_CDS_[100..627][note=score:-4.827981E+02]atgtttcagacttttatttctcgccataattcaaactttttttctgataagctggttctcacttctgttactccagcttcttcggcacctgttttacagacacctaaagctacatcgtcaacgttatattttgatagtttgacggttaatgctggtaatggtggttttcttcattgcattcagatggatacatctgtcaacgccgctaatcaggttgtttctgttggtgctgatattgcttttgatgccgaccctaaattttttgcctgtttggttcgctttgagtcttcttcggttccgactaccctcccgactgcctatgatgtttatcctttgaatggtcgccatgatggtggttattataccgtcaaggactgtgtgactattgacgtccttccccgtacgccgggcaataacgtttatgttggtttcatggtttggtctaactttaccgctactaaatgccgcggattggtttcgctgaatcaggttattaaagagattatttgtctccagccacttaagtgaOutput the amino-acids of the gene calls in fasta format:$phanotate.pytests/phiX174.fasta-ffaa|head-n2
>phiX174_CDS_[100..627][note=score:-4.827981E+02]MFQTFISRHNSNFFSDKLVLTSVTPASSAPVLQTPKATSSTLYFDSLTVNAGNGGFLHCIQMDTSVNAANQVVSVGADIAFDADPKFFACLVRFESSSVPTTLPTAYDVYPLNGRHDGGYYTVKDCVTIDVLPRTPGNNVYVGFMVWSNFTATKCRGLVSLNQVIKEIICLQPLK*
Package: phantasy
PHANTASYPhysicsHigh-levelApplications aNdToolkit forAcceleratorSYstem.Main features ofphantasy:Device configuration management;Device abstraction;Online modeling;Python interactive scripting environment for high-level controls;Virtual accelerator based on EPICS control environment;Web services integration;Physics applications built on top ofphantasyare developed as another
repo:phantasy-apps, whose names in Debian repository are prefixed withpython-, i.e.python-phantasyandpython-phantasy-apps.Changelogs seehere.
Package: phantasy-machines
machinesConfiguration files for both virtual accelerator and physical FRIB accelerator.Run with FLAME model engine:phytool flame-vastart --mach <machine-name> --subm <segment-name> -vmachine-namecould be:FRIB,FRIB_VA,segment-namedefined inphantasy.inifile.Model Machine withphantasy:>>> import phantasy
>>>
>>> # e.g. machine-name: 'FRIB', segment: 'MEBT' (default if skipped)
>>> mp = phantasy.MachinePortal(machine='<machine-name>', segment='<segment-name>')
>>>
>>> # get all device types
>>> mp.get_all_types()
>>>
>>> # get elements by name/type/location
>>> mp.get_elements()
>>>
>>> # get elements regarding to reference elements
>>> mp.next_elements()
>>> lat = mp.work_lattice_conf
>>>
>>> # sync settings from accelerator (VA or REAL)
>>> lat.sync_settings(data_source='control')
>>>
>>> # sync settings from model to accelerator
>>> lat.sync_settings(data_source='model')
>>>
>>> # get the FLAME lattice file
>>> latfile, fm = lat.run()
>>> # ...
Package: phanterpwa
PhanterpwaTools for the phanterpwadeveloper frameworkDependencies installed on setuppsutil
tornado
libsass
transcrypt
pillow
itsdangerous
pydal
passlib
requests-oauthlibRequerimentsPython 3.6+
Python 3.7 RecommendedBrowser CompatibilityThe browser needs compatibility with:HTML5
ES6 (Javascript6)Web TecnologiesjQuery
Font Awesome
Package: phantomas
Python module for easy integration withphantomas- PhantomJS-based modular web performance metrics collectorInstallIn order to use this module you needphantomas“binary” installed in your system.sudo make installThis will runnpm install -g phantomas.Module’s APIimport json
from phantomas import Phantomas

results = Phantomas(
    url="http://example.com",
    exec_path="/my/path/to/phantomas",     # optional
    modules=['headers', 'requestsStats']
).run()

print('Generator: ' + results.get_generator())   # phantomas v1.9.0
print('\nMetrics: ' + json.dumps(results.get_metrics(), indent=True, sort_keys=True))
print('\nDomains: ' + json.dumps(results.get_offenders('domains'), indent=True))

# assertions
assert results.get_metric('notFound') == 0
assert results.get_metric('requests') < 5More docs coming soon! Meanwhile please refer toexample/example.pyscript.
Package: phantominator
Installationpython-mpipinstallphantominatorThe goal is to have easy installation and usage for everyone.  If
something doesn’t work, please open an issue and/or submit a pull
request.  We’ll get it figured out.pygrappais an optional dependency required to run thephantominator.examples.radial_coil_sensexample.AboutPython package for easy generation of numerical phantoms.  I often
need a simple image to try something out on.  In MATLAB, I would use
thephantomcommand to quickly get something to work with.  In
Python, it’s not always quite so easy, so I made this package that’s quick
to install and use so there’s as little friction as possible.  There
are other implementations of Shepp-Logan available from other
projects, but they are usually not as easy to install or include other
things that I don’t want for this project.This package offers both CT and MR versions.Going forward, this module will support Python >= 3.8.UsageAlso see theexamplesmodule and docstrings.  The interface for CT
phantom generation is similar to MATLAB’sphantomfunction.Examples can be run as:# python -m phantominator.examples.[example-name], e.g.:python-mphantominator.examples.shepp_loganBasic usage:# CT phantomfromphantominatorimportshepp_loganph=shepp_logan(128)# MR phantom (returns proton density, T1, and T2 maps)M0,T1,T2=shepp_logan((128,128,20),MR=True)The Shepp-Logan 3D phantom has ellipsoids in [-1, 1] along the z-axis.
The 2D Shepp-Logan exists at z=-0.25, so if we want just a subset
along the z-axis with the first slice being the traditional 2D
phantom, we can use thezlimsoption:fromphantominatorimportshepp_loganM0,T1,T2=shepp_logan((64,64,5),MR=True,zlims=(-.25,.25))We can also generate simple oscillating concentric circles:# Dynamic (concentric circles), 20 time framesfromphantominatorimportdynamicph=dynamic(128,20)If we want to modify ellipse/ellipsoid parameters or we just want to
see what they are.  For example, we can get the MR ellipsoid
parameters like this:fromphantominatorimportmr_ellipsoid_parametersE=mr_ellipsoid_parameters()See docstrings forct_shepp_logan, andmr_shepp_loganfor how
the arrayEis structured.  It follows conventions from MATLAB’s
phantom function.Arbitrary k-space sampling is supported for the single coil 2D
Shepp-Logan phantom:# Given k-space coordinates (kx, ky), where kx and ky are 1D# arrays using the same unit conventions as BART's traj command,# we can find the corresponding k-space measurements:fromphantominatorimportkspace_shepp_logank=kspace_shepp_logan(kx,ky)
Package: phantomjs
PhantomJS wrapper in PythonPre requisitesphantomjs:phantomjscommand line tool.Python 3InstallpipinstallphantomjsUsageUsing with a custom phantomjs script:fromphantomjsimportPhantomphantom=Phantom()conf={'url':'http://example.com/',# Mandatory field}output=phantom.download_page(conf,js_path='/my/phantomjs/script/path')In your phantomjs script, you can take the url as:varsystem=require('system');varjson=JSON.parse(system.args[1]);varurl=json.url;Using the default phantomjs script provided with this package:fromphantomjsimportPhantomphantom=Phantom()conf={'url':'http://example.com/',# Mandatory field'output_type':'html',# json for json'min_wait':1000,# 1 second'max_wait':30000,# 30 seconds'selector':'',# CSS selector if there's any'resource_timeout':3000,# 3 seconds'headers':{"User-Agent":"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.72 Safari/537.36","Accept":"text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3","Sec-Fetch-Mode":"navigate",'Sec-Fetch-Site':'same-origin','Upgrade-Insecure-Requests':'1',},'cookies':[{'name':'_Country','value':'US','domain':'.google.com',},{'name':'_Currency','value':'USD','domain':'.google.com',},],'functions':['function(){window.location.replace("http://icanhazip.com/");}',],}output=phantom.download_page(conf)
Package: phantom_scheduler
==============Phantom Scheduler==============Phantom scheduler used to administer the job submission to clusters."With great power comes great responsibility" -- Uncle BenThis program runs a scheduler and a number of children that keep submitting jobs to a cluster queue.It is particularly useful when one has many short jobs which cannot be submitted all at once. This permits not to lose the priority in the queue.Installation============You can install the ``phantom_scheduler`` using:$ pip install phantom_scheduler
Package: phantomsetup
Phantom setupphantom-setup: generate initial conditions forPhantomsimulationsDocs:https://phantom-setup.readthedocs.io/Repo:https://www.github.com/dmentipl/phantom-setupInstallInstall via conda.conda install phantomsetup --channel dmentiplInstall via pip.pip install phantomsetupUsageTo generate initial conditions for a Phantom simulation via a Python script with phantom-setup:Instantiate aphantomsetup.Setupobject.Add particles, set arrays, units, equation of state, sinks, dust, and other parameters.Write a Phantom HDF5 dump file containing the particle arrays.Write a Phantom in file containing the run time parameters.Compile Phantom with the correct Makefile variables.Then run Phantom.ExamplesTheexamplesfolder contains examples that you can run as a Python script or Jupyter notebook.
Package: phap
PHAPPrograming Helpful Algorithm PackagePowered by Python 3.11English  |简体中文如果你不是在Github上阅读本说明，你可能无法打开非英语版本的说明文档请前往Github网站，确保你能够成功地切换语言LinksGithub|Pypi|Pypi (stralgo)VersionsStable Versionv0.1.0 (stralgo)v1.1.1 (stralgo)v2.1.2v2.2.1Latest Available Versionv3.1.0Latest Version(The data under the master branch is inaccurate. Please refer to the dev branch for details)v3.1.0To UseRead our development document(Click theGithublink to read this document，or you may can not to open the link)Development DocumentBuildPreconditionInstall git and make toolsInstall Python(the version 3.9 or the version 3.11)Clone source code from source repositorygit clone git@github.com:DashBing/phap.gitorgit clone https://github.com/DashBing/phap.gitInitialize packaging environmentmake initorTry to install the package:buildtwineThis is the example command on Windows:python -m pip install build
python -m pip install twineBuild releasemake build
Package: phare
PhareAn asynchronous and ergonomic client library for the Project Lighthouse API.Exampleimportasyncioimportnumpyasnpimportosfromphare.authimportAuthfromphare.lighthouseimportLighthousefromphare.constantsimportLIGHTHOUSE_FRAME_SHAPE,LIGHTHOUSE_URLasyncdefmain():user=os.environ['LIGHTHOUSE_USER']token=os.environ['LIGHTHOUSE_TOKEN']url=os.environ.get('LIGHTHOUSE_URL',LIGHTHOUSE_URL)asyncwithawaitLighthouse.connect(Auth(user,token),url)aslh:frame=np.random.randint(0,255,size=LIGHTHOUSE_FRAME_SHAPE,dtype=np.uint8)awaitlh.put_model(frame)asyncio.run(main())
Package: pharmacy
pharmacyA hospital and retail pharmacy-focused Python package by Danny Limoges, PharmD.This project is in the alpha/planning stage.InstallationAvailable on PyPI as an installable package:https://pypi.org/project/pharmacy/pip install pharmacyWhat is it?This is a collection of modular utilities that aid in processing pharmacy data.  Users must perform their
own data validation to ensure that results generated by pharmacy are accurate
and that the correct data was inputted.What is itnot?pharmacyis not a pharmacy management system and does not replace Epic, Meditech, Pioneer or any other pharmacy software.Syntaxfind_best_matchesGet afuzzy matchbetween two DataFrames and combine them where matched.Output:pandas DataFrame.  All rows from df_orig are kept and their corresponding matches are tacked onto the end if they  meet the match threshold.importpharmacyasrximportpandasaspddf_out=rx.find_best_matches(df_orig# Original pandas DataFrame,df2# DataFrame to match against,match_col# Which column to examine in original DataFrame,match_col_comparator=None# The column name to compare,threshold=80# Only accept matches above this fuzzy match threshold.,scorer=fuzz.token_set_ratio# Which type of fuzzy match?# options: ratio, partial_ratio, token_sort_ratio, token_set_ratio)For more information on fuzzy match types, check out this article:Understanding Fuzzy String Matching: Exploring Fuzz Ratio, Fuzz Partial Ratio, Token Set Ratio, and Token Sort Ratio: Machine Learning Concept 78, by
Chandra Prakash BathulaExample>>>importpandasaspd>>>importpharmacyasrx>>>df=pd.DataFrame(...[('10000-1000-10','Acetaminophen 325mg',),...('20000-2000-30','Lisinopril 10mg','7'),...('30000-3000-30','Tylenol #3','c5'),...],columns=['ndc','description','schedule'])Potential Future GoalsTools to work on data from...Drug dataUse fuzzy and exact-matching to align different drug data files.PricingGeneric EquivalentsUsageShortages and availabilityPatient profilesDemographicsGeolocationPrescription dataFillsClaimsLoss analysisOpportunity analysisModelingIntegrate pharmacy data with TensorFlowGenerate large-scale insightsPredict the outcomes of new clinical services based on current dataIntegrationIncorporate data from ordering sites, etc.
Package: pharma-datamatrix
pharma_datamatrix packageThe package allow users to pass the string produced by the 2D barcode scanners and parse the string into GTIN, PPN, EXPIRY, SERIAL, BATCH and NHRN.Filespharma_datamatrix.py: Primary function that checks the barcode format and inturn calls relevant parsing logic function.gs1_gtin.py: Parse the GS1 GTIN barcode string and validate GTIN & Expiry.ifa_ppn.py: Parse the IFA PPN barcode string (MACRO 06 & MACRO 05) and validate PPN & Expiry.expiry_date_validation.py: This files contains the logic that validates the Expiry date. This file checks if the YYMMDD contains valid digits. Ex: MM to be between 01 & 12. And if the expiry date greater than the date of the scan: i.e. not is valid past date.gs1_gtin_validation.py: This file contains the logic that validates the GS1 - GTIN.ifa_ppn_validation.py: This file contains the logic to validate IFA PPN format.InstallationTo install the package please run the below command:
pip install pharma_datamatrixUsageThe function pharma_datamatrix(barcode: str):
The 'barcode' parameter is of 'string' type and its mandatory. The string should contain the  seperator as per GS1 guidelines.Initial Import:
from pharma_datamatrix import pharma_datamatrixExample 1: Valid GS1 barcode
pharma_datamatrix(']d201085860077038511724123110HB5R21587E4QA11R')
Output: {'SCHEME': 'GS1', 'GTIN': '08586007703851', 'EXPIRY': '241231', 'BATCH': 'HB5R1', 'SERIAL': '21587E4QA11R'}Example 2: Valid PPN barcode
pharma_datamatrix('9N#03752864#1T#12345ABCDE#D#260617#S#12345ABCDEF98765')
Output: {'SCHEME': 'IFA', 'PPN': '03752864', 'EXPIRY': '260617', 'BATCH': '12345ABCDE', 'SERIAL': '12345ABCDEF98765'}Example 3: Invalid barcode (Invalid format)
pharma_datamatrix('085860077038511724113110HB5R21587E4QA11R')
Output: {'ERROR': 'INVALID FORMAT','BARCODE': '085860077038511724113110HB5R21587E4QA11R'}Example 4: Invalid barcode (valid barcode format but Invalid expiry date (31 Nov 24))
pharma_datamatrix('01085860077038511724113110HB5R21587E4QA11R')
Output: {'ERROR': 'INVALID EXPIRY DATE', 'BARCODE': {'SCHEME': 'GS1', 'GTIN': '08586007703851', 'EXPIRY': '241131', 'BATCH': 'HB5R1', 'SERIAL': '21587E4QA11R'}}Example 5: Invalid barcode (valid barcode format but Invalid GTIN)
pharma_datamatrix('01243556547871161724011310TEST3C7E76935A')
Output: {'ERROR': 'INVALID GTIN', 'BARCODE': {'SCHEME': 'GS1', 'GTIN': '24355654787116', 'EXPIRY': '240113', 'BATCH': 'TEST3C7E76935A', 'SERIAL': 'PK133CBABE6C85F2C4A'}}SourceGithub link:https://github.com/PinchofLogic/pharma_datamatrix
Package: pharmastar
药理大师是一个开发中的具有多种功能的中药网络药理学分析工具，可进行经典的网络药理学及反向网络药理学分析。Pharmastar is a multi-functional traditional chinese medicine network pharmacology analysis tool under development for classical network pharmacology and reverse network pharmacology.中文使用EnglishUsage中文使用基本使用pharmastar.analysis中提供了进行网络药理学分析的pipeline函数。reverse函数: 反向网络药理学分析的pipeline函数。使用它仅需使用命令frompharmastarimportanalysisanalysis.reverse(genes,protein_chemical_links_filename,score,chemicals_filename,chunksize,swiss_filename,drug_likeness_num,try_num)它需要一个必需形参genes，这是一个存储编码拟分析靶点的基因的Ensembl ID与其名称的字典，如{'9606.ENSP00000265022': 'DGKG'}。它的可选形参有protein_chemical_links_filename: 字符串类型，从STITCH数据库中下载的protein_chemical.links.transfer的文件名，默认为9606.protein_chemical.links.transfer.v5.0.tsv；score: int类型，仅combined_score大于等于score的记录会被筛选出，默认为900；chemicals_filename: 字符串类型，从STITCH数据库中下载的chemicals数据集的文件名，默认为chemicals.v5.0.tsv.gz；param chunksize: int类型，遍历chemicals数据集时的chunksize，该值过大可能耗尽计算机的内存，默认为1000000；swiss_filename: SwissADME的分析结果（csv文件）的路径，默认为swissadme.csv；drug_likeness_num: int类型，筛选类药性指标时至少有多少个为Yes，默认为3；try_num: int类型，pubchempy重复尝试的次数，默认为3。EnglishPharmastar is a multi-functional traditional chinese medicine network pharmacology analysis tool for classical network pharmacology and reverse network pharmacology.UsageBasic usagepharmastar.analysisprovides pipeline function for network pharmacology analysis.reverse: pipeline function for reverse network pharmacology. To use it, please use commandfrompharmastarimportanalysisanalysis.reverse(genes,protein_chemical_links_filename,score,chemicals_filename,chunksize,swiss_filename,drug_likeness_num,try_num)It needs a required parametergenes, which is a dictionary that stores the Ensembl ID(s) of the gene(s) encoding the target(s) to be analyzed along with their name(s), e.g.{'9606.ENSP00000265022': 'DGKG'}.Its optional parameter includesprotein_chemical_links_filename: dict, filename of the dataset protein_chemical.links.transfer from STITCH database,9606.protein_chemical.links.transfer.v5.0.tsvby default;score: int, only when the combined_score is no less than it will be selected out,900by default;chemicals_filename: str, filename of the dataset chemicals from STITCH database,chemicals.v5.0.tsv.gzby default;param chunksize: int, chunksize of the traversal to the chemicals dataset，the computer's memory may be exhausted if it is too large,1000000by default;swiss_filename: pathway of the SwissADME result,swissadme.csvby default;drug_likeness_num: int, how many 'Yes' at least when processing ADME selection,3by default;try_num: int, the number of times pubchempy tries,3by default.
Package: pharminv
This is a python interface toharminv, a library
for performing harmonic inversion on a signal.Requirements:BLAS & LAPACKlibharminv-devnumpyInstallation:Make sure that you have the requirements above, thenpip install pharminvSeebelowfor help with installing harminv.Usage:harminv.invertcontains the basic functionality of the harminv tool.
This function should remain stable but the API elsewhere is subject to
change.importnumpyasnpimportharminvtime=np.linspace(0,1,1000)signal=np.cos(2*np.pi*time*10)+np.cos(2*np.pi*time*20)inversion=harminv.invert(signal,fmin=1,fmax=100,dt=0.001)inversion.freq# mode frequenciesinversion.decay# decay ratesinversion.Q# Q factorinversion.amplitudes# absolute amplitudesinversion.phase# phase shiftLicense:harminvwas
written by Steven G. Johnson and is licensed under the GNU GPLv2+,
copyright 2005 by the Massachusetts Institute of Technology.This python interface to harminv is licensed under the standard BSD
3-clause license.Installing libharminvOn Debian / Ubuntu this is available withsudoapt-getinstalllibharminv-devOtherwise you’ll need to build it yourself. Download the sources fromhere.You need to install libharminv somewhere that python can find it at
runtime. This should happen by default (installs to/usr/local), but
you may need to change this to/usr:PREFIX=/usrNow install with the following:./configure--with-pic--enable-shared--prefix=$PREFIXmakemakeinstallUser installationIf you don’t have admin rights on your system you’ll need to install to
a directory that you have access to. Here I’ll assume that is$HOME/.local.Here is how I do it (using Anaconda python with the mkl libraries on
CentOS 5):./configure--with-pic--enable-shared--prefix=$HOME/.local--with-blas=$HOME/.local/lib/libopenblas.somakemakeinstallNote that I’ve linked to openblas. I installed this separately. If you
have BLAS/LAPACK installed on your system elsewhere you might not need
to do this. There might be a way to link against Anaconda mkl libraries
but I don’t know what it is.Now you need to setLD_LIBRARY_PATHto include your directory. I
have this in my bashrc:exportLD_LIBRARY_PATH=$HOME/.localFinally, when you install pharminv, you need to tell pip where to look
for your installation of libharminv:CFLAGS="-I$HOME/.local/include -L$HOME/.local/lib"pipinstallpharminv