معرفی شرکت ها


bmtool-0.3.4


Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

توضیحات

BMTool
ویژگی مقدار
سیستم عامل -
نام فایل bmtool-0.3.4
نام bmtool
نسخه کتابخانه 0.3.4
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Tyler Banks
ایمیل نویسنده tbanks@mail.missouri.edu
آدرس صفحه اصلی https://github.com/tjbanks/bmtool
آدرس اینترنتی https://pypi.org/project/bmtool/
مجوز MIT
# bmtool A collection of scripts to make developing networks in BMTK easier. [![license](https://img.shields.io/github/license/mashape/apistatus.svg?maxAge=2592000)](https://github.com/tjbanks/bmtool/blob/master/LICENSE) ## Getting Started **Installation** ```bash pip install bmtool ``` For developers who will be pulling down additional updates to this repository regularly use the following instead. ```bash git clone https://github.com/tjbanks/bmtool cd bmtool python setup.py develop ``` Then download updates (from this directory) with ``` git pull ``` **Example Use** ```bash > cd your_bmtk_model_directory > bmtool Usage: bmtool [OPTIONS] COMMAND [ARGS]... Options: --verbose Verbose printing --help Show this message and exit. Commands: debug plot util > > bmtool plot Usage: bmtool plot [OPTIONS] COMMAND [ARGS]... Options: --config PATH Configuration file to use, default: "simulation_config.json" --no-display When set there will be no plot displayed, useful for saving plots --help Show this message and exit. Commands: connection Display information related to neuron connections positions Plot cell positions for a given set of populations raster Plot the spike raster for a given population report Plot the specified report using BMTK's default report plotter > > bmtool plot positions ``` ![bmtool](./figures/figure.png "Positions Figure") ## Plotting Configuration BMTool utilizes the default `simulation-config.json` file to know which data files built by BMTK to read. to change this, specify the config after the `plot` command. Eg: ``` bmtool plot --config simulation-config-23.json [FUNCTION] ``` ### From python or Jupyter ``` from bmtool import bmplot bmplot.plot_3d_positions(config="simulation_config.json") ``` ## Ploting Connections All connection tools can be customized by supplying additional arguments. ``` Options: --title TEXT change the plot's title --save-file TEXT save plot to path supplied --sources TEXT comma separated list of source node types [default:all] --targets TEXT comma separated list of target node types [default:all] --sids TEXT comma separated list of source node identifiers [default:node_type_id] --tids TEXT comma separated list of target node identifiers [default:node_type_id] --no-prepend-pop When set don't prepend the population name to the unique ids [default:False] ``` #### `--sources` and `--targets` Are supplied as comma separated lists and corrospond with the population name specified in your model. Eg: ``` #initialize the networks in build_network.py net = NetworkBuilder('hippocampus') exp0net = NetworkBuilder('exp0input') ``` Default behavior is to plot connections between all populations but you can specify only a few to simplify your plots. #### `--sids` and `--tids` Comma separated lists of node identifiers replace the default `cell_id` automatically given to a cell population by BMTK. Any parameter passed to `NetworkBuilder.add_nodes` is stored in network `.h5` files and can be used to identify cells while connecting or producing plots. Eg: ``` # Adding nodes in build_network.py net.add_nodes(N=inpTotal, pop_name='EC', positions=p_EC, model_type='biophysical', model_template='hoc:IzhiCell_EC2', morphology='blank.swc' ) ``` We could then use the pop_name to alter the output of our connection plots. ``` bmtool plot connection --sids pop_name --tids pop_name [FUNCTION] ``` #### `--no-prepend-pop` Default behavior of bmtool is to print the population name before the cell id (or sid/tid) followed by an underscore. Eg: `hippocampus_100`. By supplying `--no-prepend-pop` the cell name becomes `100` unless specified otherwise. #### `All together basic` Using these optional switches we can see the difference in our plot output below. Command line ``` bmtool plot connection total ``` Python or Jupyter Notebook ``` from bmtool import bmplot import matplotlib.pyplot as plt bmplot.connection_matrix(config="simulation_config.json") ``` #### `All together advanced` ``` bmtool plot connection --sources hippocampus --targets hippocampus --sids pop_name --tids pop_name --no-prepend-pop --title 'Hippocampus Total Connections' total ``` Python or Jupyter Notebook ``` from bmtool import bmplot bmplot.connection_matrix(config="simulation_config.json", sources="hippocampus", targets="hippocampus", sids="pop_name", tids="pop_name", no_prepend_pop=True, title="Hippocampus Total Connections") ``` ![bmtool](./figures/connection.png "Connection Figure") ### Plot Total Connections To plot the total number of connections between two populations of cells run Command line ``` bmtool plot connection total ``` Python or Jupyter Notebook ``` from bmtool import bmplot bmplot.connection_matrix(config="simulation_config.json", sources="hippocampus", targets="hippocampus") ``` Remember to customize the output using the instructions above. #### `--synfo` This is an additional flag that can be used in the total connections plot. By default it is set to '0' which plots total connections. If it is specified as '1', it plots the mean and standard deviation number of connections. If it is '2', it plots the .mod files used for that connection type. Finally if it is '3', it plots the parameter file (.json) used for the connection. ![bmtool](./figures/connection_total.png "Connection Total Figure") ### Plot Average Convergence/Divergence To plot the average convergence or divergence of a single cell excute one of the following commands: Command Line ``` bmtool plot connection convergence bmtool plot connection divergence Add --method (std, min, or max) for additional function ``` Python or Jupyter Notebook ``` from bmtool import bmplot bmplot.convergence_connection_matrix(config="simulation_config.json") bmplot.divergence_connection_matrix(config="simulation_config.json") # OR using methods (min,max,std) bmplot.convergence_connection_matrix(config="simulation_config.json", method="min") ``` ![bmtool](./figures/connection_con.png "Connection Convergence Figure") ### Plot Connection Diagram To plot a rough sketch of cell type connectivity and the type of synapse used between cells run: Command Line ``` bmtool plot connection network-graph ``` Python or Jupyter Notebook ``` from bmtool import bmplot bmplot.plot_network_graph(config="simulation_config.json") ``` ![bmtool](./figures/connection_graph.png "Connection Graph Figure") `--edge-property` is an option available to change the synapse name if supplied to `NetworkBuilder.add_edges` when building the network. Default: `model_template` ### Edge Property Histograms To view the distribution of an edge property between cell types run: Command Line ``` bmtool plot connection property-histogram-matrix ``` Python or Jupyter Notebook ``` from bmtool import bmplot bmplot.edge_histogram_matrix(config="simulation_config.json") ``` The following figure was generated using ``` bmtool plot connection --sources hippocampus --targets hippocampus --sids pop_name --tids pop_name --no-prepend-pop --title 'Synaptic Weight Distribution between Cell Types' property-histogram-matrix ``` ``` from bmtool import bmplot bmplot.edge_histogram_matrix(config="simulation_config.json", sources="hippocampus", targets="hippocampus", sids="pop_name", tids="pop_name", no_prepend_pop=True, title="Synaptic Weight Distribution between Cell Types") ``` ![bmtool](./figures/connection_hist.png "Connection Histogram Figure") By default the `property-histogram-matrix` looks at the `syn_weight` value specified in the `NetworkBuilder.add_edges` function when building your network. You can change this by specifying the `--edge-property`. Eg: ``` bmtool plot connection property-histogram-matrix --edge-property [PROPERTY] ``` #### Plotting edge values during/after runtime BMTool is capable of plotting connection properties obtained after runtime from reports. This is useful for synaptic weights that change over time. First, you must explicitly record the connection property in your `simulation_config.json` ``` "reports": { "syn_report": { "cells": "hippocampus", "variable_name": "W_nmda", "module": "netcon_report", "sections": "soma", "syn_type": "pyr2pyr", "file_name": "syns.h5" } } ``` Where `pyr2pyr` is the `POINT_PROCESS` name for the synapse you're attempting to record, and the `variable_name` is a `RANGE` variable listed int the `NEURON` block of the synapse `.mod` file. Once the simulation has been run un the following referencing the report specified above: ``` bmtool plot connection property-histogram-matrix --edge-property pyr2pyr_w --report output/syns.h5 --time 9999 ``` The `--time-compare` option can be be used to show the weight distribution change between the specified times. Eg: ` --time 0 --time-compare 10000` See the [BMTK Commit](https://github.com/AllenInstitute/bmtk/pull/67/files) for more details. ### Plotting Distance Probability Matrix between cell types ![bmtool](./figures/connection_dist.png "Connection Histogram Figure") To show the probability of a cell type being connected to another cell type based on distance run: ``` bmtool plot connection prob ``` Full summary of options: ``` > bmtool plot connection prob --help Usage: bmtool plot connection prob [OPTIONS] Probabilities for a connection between given populations. Distance and type dependent Options: --axis TEXT comma separated list of axis to use for distance measure eg: x,y,z or x,y --bins TEXT number of bins to separate distances into (resolution) - default: 8 --line Create a line plot instead of a binned bar plot --verbose Print plot values for use in another script --help Show this message and exit. ``` A more complete command (used for image above) may look similar to ``` bmtool plot connection --sources hippocampus --targets hippocampus --no-prepend-pop --sids pop_name --tids pop_name prob --bins 10 --line --verbose ``` This will plot cells in the `hippocampus` network, using the `pop_name` as the cell identifier. There will be `10` bins created to group the cell distances. A `line` plot will be generated instead of the default `bar` chart. All values for each plot will be printed to the console due to the `verbose` flag. All `point_process` cell types will be ignored since they do not have physical locations. ### Plotting Current Clamp and Spike Train Info To plot all current clamp info involved in a simulation, use the following command (uses 'simulation_config.json' as default) ``` bmtool plot --config simulation_config_foo.json iclamp ``` To plot all spike trains and their target cells, ``` bmtool plot --config simulation_config_foo.json input ``` ### Printing basic cell information involved in a simulation ``` bmtool plot --config simulation_config_foo.json cells ``` ### Simulation Summary Using previous functions, plots connection probability as a function of distance, total connections, cell information, current clamp information, input spike train information, and a 3D plot of the network if specified. ``` bmtool plot --config simulation_config_foo.json summary ``` ## Cell Tuning ### Python/Jupyter Single Cell Profiler ``` from bmtool.singlecell import Profiler #Example usage profiler = Profiler(template_dir='./components/templates', mechanism_dir='./components/mechanisms/modfiles') profiler.passive_properties('Cell_Cf') profiler.fi_curve('Cell_Cf') profiler.current_injection('Cell_Cf', post_init_function="insert_mechs(123)", inj_amp=300, inj_delay=100) ``` ### Single Cell Tuning From a BMTK Model directory containing a `simulation_config.json` file: ``` bmtool util cell tune --builder ``` For non-BMTK cell tuning: ``` bmtool util cell --template TemplateFile.hoc --mod-folder ./ tune --builder ``` ![bmtool](./figures/figure2.png "Tuning Figure") ### FIR Curve plotting ``` > bmtool util cell fi --help Usage: bmtool util cell fi [OPTIONS] Creates a NEURON GUI window with FI curve and passive properties Options: --title TEXT --min-pa INTEGER Min pA for injection --max-pa INTEGER Max pA for injection --increment FLOAT Increment the injection by [i] pA --tstart INTEGER Injection start time --tdur INTEGER Duration of injection default:1000ms --advanced Interactive dialog to select injection and recording points --help Show this message and exit. > bmtool util cell fi ? Select a cell: (Use arrow keys) » CA3PyramidalCell DGCell IzhiCell IzhiCell_BC IzhiCell_EC IzhiCell_EC2 IzhiCell_EC_BIO IzhiCell_EmoExcitatory IzhiCell_EmoInhibitory IzhiCell_OLM IzhiCell_int ``` ![bmtool](./figures/figure3.png "FIR Figure") ### VHalf Segregation Module Based on the Alturki et al. (2016) paper. Segregate your channel activation for an easier time tuning your cells. ``` > bmtool util cell vhseg --help Usage: bmtool util cell vhseg [OPTIONS] Alturki et al. (2016) V1/2 Automated Segregation Interface, simplify tuning by separating channel activation Options: --title TEXT --tstop INTEGER --outhoc TEXT Specify the file you want the modified cell template written to --outfolder TEXT Specify the directory you want the modified cell template and mod files written to (default: _seg) --outappend Append out instead of overwriting (default: False) --debug Print all debug statements --fminpa INTEGER Starting FI Curve amps (default: 0) --fmaxpa INTEGER Ending FI Curve amps (default: 1000) --fincrement INTEGER Increment the FI Curve amps by supplied pA (default: 100) --infvars TEXT Specify the inf variables to plot, skips the wizard. (Comma separated, eg: inf_mech,minf_mech2,ninf_mech2) --segvars TEXT Specify the segregation variables to globally set, skips the wizard. (Comma separated, eg: mseg_mech,nseg_mech2) --eleak TEXT Specify the eleak var manually --gleak TEXT Specify the gleak var manually --othersec TEXT Specify other sections that a window should be generated for (Comma separated, eg: dend[0],dend[1]) --help Show this message and exit. ``` #### Examples Wizard Mode (Interactive) ``` > bmtool util cell vhseg ? Select a cell: CA3PyramidalCell Using section dend[0] ? Show other sections? (default: No) Yes ? Select other sections (space bar to select): done (2 selections) ? Select inf variables to plot (space bar to select): done (5 selections) ? Select segregation variables [OR VARIABLES YOU WANT TO CHANGE ON ALL SEGMENTS at the same time] (space bar to select): done (2 selections) ``` Command Mode (Non-interactive) ``` bmtool util cell --template CA3PyramidalCell vhseg --othersec dend[0],dend[1] --infvars inf_im --segvars gbar_im --gleak gl_ichan2CA3 --eleak el_ichan2CA3 ``` Example: ![bmtool](./figures/figure4.png "Seg Figure") Simple models can utilize ``` bmtool util cell --hoc cell_template.hoc vhsegbuild --build bmtool util cell --hoc segmented_template.hoc vhsegbuild ``` ex: [https://github.com/tjbanks/two-cell-hco](https://github.com/tjbanks/two-cell-hco)


نیازمندی

مقدار نام
- bmtk
- click
- clint
- h5py
- matplotlib
- networkx
- numpy
- pandas
- questionary
- pynmodlt


نحوه نصب


نصب پکیج whl bmtool-0.3.4:

    pip install bmtool-0.3.4.whl


نصب پکیج tar.gz bmtool-0.3.4:

    pip install bmtool-0.3.4.tar.gz