├── .gitignore ├── CONTRIBUTORS.md ├── Exercises ├── Exercise1_NeuroMorpho_to_OSB.md ├── Exercise2_HBP_Collaboratory.md ├── Exercise3_AllenCell_on_NSG_via_OSB.md ├── Exercise4_NeoPyNNJupyter.md ├── Exercise5_Hippocampal_model_on_NSG.md ├── Exercise6_FruitFlyBrainObservatory.md ├── Exercise7_OpenWorm.md ├── README.md ├── files │ ├── A1-May29-IR2-3-G.CNG.swc │ └── A1-May29-IR2-3-G.cell.nml └── images │ ├── 3Dview.png │ ├── Cover.pptx │ ├── Logos.png │ ├── neuromorpho.png │ └── osb1.png ├── Part_1_Resources_for_computational_modellers ├── 1_Experimental_datasets │ ├── 1_CellTypesDatabase.pptx │ ├── 2_AllenBrainObservatory.pptx │ ├── 3_crcns_org.pptx │ ├── 5_NeuroMorpho.org.pptx │ └── Template.pptx ├── 2_Structured_data_from_literature │ ├── 1_NeuroElectro.pptx │ ├── 2_Hippocampome.pptx │ ├── 3_CA1.pptx │ ├── 4_ICG.pptx │ └── Template.pptx ├── 3_Analysis_tools │ ├── 1_Neo.pptx │ ├── 2_Elephant.pptx │ ├── 3_NeuronUnit.pptx │ ├── 4_NWB.pptx │ └── Template.pptx ├── 4_Simulation_environments │ ├── 1_NEURON.pptx │ ├── 2_Brian.pptx │ ├── 3_NEST.pptx │ ├── 4_MOOSE.pptx │ ├── 5_Nengo.pptx │ ├── 6_TVB.pptx │ └── Template.pptx ├── 5_Model_sharing │ ├── 1_ModelDB.pptx │ ├── 2_OSB.pptx │ ├── 3_NeuroML.pptx │ ├── 4_PyNN.pptx │ ├── 5_Geppetto.pptx │ ├── 6_GitHub.pptx │ ├── 7_ReScience.pptx │ └── Template.pptx ├── 6_Computing_infrastructure │ ├── 1_Neuroscience_Gateway.pptx │ ├── 2_AWS.pptx │ ├── 4_Binder.pptx │ └── Template.pptx ├── 7_Open_source_initiatives │ ├── 1_NeuralEnsemble.pptx │ ├── 2_OpenWorm.pptx │ ├── 3_BigNeuron.pptx │ ├── 4_FruitFlyBrainObservatory.pptx │ └── Template.pptx ├── 8_Web_portals │ ├── 1_NeuroscienceInformationFramework.pptx │ ├── 3_VirtualFlyBrain.pptx │ ├── 4_HBPCollaboratory.pptx │ ├── 5_NITRC.pptx │ └── Template.pptx ├── Introduction │ └── Introduction.pptx ├── Part1_1_Experimental_datasets.pdf ├── Part1_2_Structured_data_from_literature.pdf ├── Part1_3_Analysis_tools.pdf ├── Part1_4_Simulation_environments.pdf ├── Part1_5_Model_sharing.pdf ├── Part1_6_Computing_infrastructure.pdf ├── Part1_7_Open_source_initiatives.pdf ├── Part1_8_Web_portals.pdf ├── Part1_Introduction.pdf ├── README.md └── compile.py └── README.md /.gitignore: -------------------------------------------------------------------------------- 1 | .DS_Store 2 | /Part_1_Resources_for_computational_modellers/Part1.pptx 3 | /Part_1_Resources_for_computational_modellers/temp 4 | /Part_1_Resources_for_computational_modellers/4_ICG.pdf 5 | /Part_1_Resources_for_computational_modellers/.~lock.4_ICG.pdf# 6 | -------------------------------------------------------------------------------- /CONTRIBUTORS.md: -------------------------------------------------------------------------------- 1 | **We thank the following people for contributing to this tutorial** 2 | 3 | Padraig Gleeson 4 | 5 | Andrew Davison 6 | 7 | Chris Eliasmith 8 | 9 | Diek W. Wheeler 10 | 11 | Adam Tomkins 12 | 13 | Terri Gilbert 14 | 15 | Jeff Teeters 16 | 17 | Fritz Sommer 18 | 19 | Hanchuan Peng 20 | 21 | Rick Gerkin 22 | 23 | Shreejoy Tripathy 24 | 25 | Robert McDougal 26 | 27 | Nicolas P. Rougier 28 | 29 | Konrad Hinsen 30 | 31 | Amitava Majumdar 32 | 33 | Subhashini Sivagnanam 34 | 35 | Hans Ekkehard Plesser 36 | 37 | William Podlaski 38 | 39 | Alex Seeholzer 40 | 41 | Tim Vogels 42 | 43 | Marcel Stimberg 44 | 45 | Dan Goodman 46 | 47 | Romain Brette 48 | 49 | Rob Court 50 | 51 | Stephen D. Larson 52 | 53 | Dilawar Singh 54 | 55 | Upi Bhalla 56 | 57 | Chris Holdgraf 58 | 59 | Matteo Cantarelli 60 | 61 | Giovanni Idili 62 | 63 | Annapaola Iolanda Santarsiero 64 | 65 | Victor Jirsa 66 | 67 | Jeffrey S. Grethe 68 | 69 | Yiyin Zhou 70 | 71 | Chung-Heng Yeh 72 | 73 | Nikul Ukani -------------------------------------------------------------------------------- /Exercises/Exercise1_NeuroMorpho_to_OSB.md: -------------------------------------------------------------------------------- 1 | ## Cell morphology from NeuroMorpho.Org visualised on Open Source Brain 2 | 3 | ### Local software requirements 4 | 5 | None, apart from an up to date web browser. 6 | 7 | ### Instructions 8 | 9 | #### 1. Download morphology from NeuroMorpho.Org in NeuroML 2 format 10 | 11 | Pick a cell, e.g. [this one](http://neuromorpho.org/neuron_info.jsp?neuron_name=A1-May29-IR2-3-G) 12 | 13 | ![NeuroMorpho](images/neuromorpho.png) 14 | 15 | Select **3D Neuron Viewer**. This will show a 3D view of the cell in an external 16 | window (a Java Applet running CVapp, see below if you have issues). Select in **Save as** the option 17 | to download in NeuroML2 format. 18 | 19 | ![3D View](images/3Dview.png) 20 | 21 | If the 3D Neuron Viewer does not open you may have to change your setting to allow 22 | Java Applets to run. See: *"The 3D Neuron Viewer does not launch. What can I do?"* [here](http://neuromorpho.org/myfaq.jsp). 23 | 24 | For Mac you may need to specify where the Java Web Start is located (to run the jnlp file). 25 | When it asks which application to open with, navigate to the root directory (not 26 | Applications), go to "System" -> "Library" -> "CoreServices" and pick "Java Web Start". 27 | 28 | If there is still an issue you can either: 29 | - download the SWC version of the morphology (via **Morphology File (Standardized)**) 30 | - convert the SWC file to NeuroML 2 with a local copy of [CVapp](http://github.com/pgleeson/Cvapp-NeuroMorpho.org), the Java application to visualise SWC files 31 | 32 | or 33 | 34 | - get a copy of the NeuroML 2 file [here](files/A1-May29-IR2-3-G.cell.nml). 35 | 36 | 37 | 38 | #### 2. Set up user account on GitHub 39 | 40 | Get a user account on GitHub: https://github.com/join 41 | 42 | 43 | 44 | #### 3. Add NeuroML file to new repository 45 | 46 | Create a new repository (green button on GitHub homepage after you're logged in), 47 | e.g. named **Test_OSB_NeuroMorpho**. Select **Initialize this repository with a README** 48 | 49 | Add the downloaded file(s) to your repository. Select **Upload files** and choose 50 | the *.nml file (or the *.swc file, or both) and add then to the repository 51 | 52 | 53 | 54 | #### 4. Sign up to Open Source Brain 55 | 56 | Get an account at http://www.opensourcebrain.org/account/register. 57 | 58 | If you have been given an Activation token for joining OSB (which allows you to 59 | skip the step of waiting for OSB admins to approve your account) enter it here. 60 | 61 | Once your account is approved & you log in, you can enter your GitHub usename 62 | (and other details) on your account settings page (click your username on top right & 63 | hit **Edit**) 64 | 65 | #### 5. Create new project on OSB 66 | 67 | Go back to the home page and click **New project** and enter the URL of your repository 68 | on GitHub. This can be found by clicking the green button **Clone or download** on 69 | GitHub, it will be of the form https://github.com/MYUSERNAME/Test_OSB_NeuroMorpho.git. 70 | 71 | Enter a name for your project and select **Create**. 72 | 73 | #### 6. Visualise cell in 3D 74 | 75 | On the homepage of your new project there will be a button to **Explore model** which 76 | should find the first *.nml model in your Github repository. If there are many or 77 | none (i.e. only SWC) you can also click **More** and this will list all the files 78 | in the repo that OSB recognises. 79 | 80 | When the 3D scene loads there will be an option to follow a guided tour of the 81 | OSB interface. You can follow this, or close the dialog and open it later by pressing the 82 | book icon on the left. 83 | 84 | You should see something like the following when the cell is visualised (and **Model 85 | description** pressed): 86 | 87 | ![OSB](images/osb1.png) 88 | 89 | 90 | 91 | -------------------------------------------------------------------------------- /Exercises/Exercise2_HBP_Collaboratory.md: -------------------------------------------------------------------------------- 1 | 2 | ## Run neuronal model on Human Brain Project Collaboratory 3 | 4 | 5 | This will be an interactive demonstration with the following steps 6 | 7 | 8 | - Sign in to HBP Collaboratory 9 | 10 | 11 | 12 | - Create new Jupyter notebook 13 | 14 | 15 | - Run Neuron/Nest models 16 | 17 | -------------------------------------------------------------------------------- /Exercises/Exercise3_AllenCell_on_NSG_via_OSB.md: -------------------------------------------------------------------------------- 1 | ## Run Allen Institute cell model on OSB on NSG and download the results. 2 | 3 | This will be an interactive demonstration with the following steps 4 | 5 | - Compare it to data directly from Allen. 6 | 7 | ... 8 | 9 | - Compare to equivalent cells in NeuroElectro. 10 | 11 | ... 12 | -------------------------------------------------------------------------------- /Exercises/Exercise4_NeoPyNNJupyter.md: -------------------------------------------------------------------------------- 1 | 2 | ## Demonstration of Neo/PyNN using Jupyter notebooks 3 | 4 | This demonstration will illustrate the functionality of the multi simulator 5 | model specification format [PyNN](http://neuralensemble.org/PyNN/) and the data 6 | storage API [Neo](http://neuralensemble.org/Neo/) through the use of browser based 7 | [Jupyter notebooks](http://jupyter.org/), as can be run on [Binder](http://mybinder.org/) 8 | or in the [HBP Collaboratory](https://collab.humanbrainproject.eu/#/collab/3833/nav/30316). -------------------------------------------------------------------------------- /Exercises/Exercise5_Hippocampal_model_on_NSG.md: -------------------------------------------------------------------------------- 1 | 2 | ## CA1 hippocampal model run in parallel on Neuroscience Gateway 3 | 4 | - Apply for account on NSG 5 | 6 | ... 7 | 8 | - Download local copy of CA1 model 9 | 10 | ... 11 | 12 | - Configure network 13 | 14 | ... 15 | 16 | - Send to NSG (web interface) 17 | 18 | ... 19 | 20 | - send to NSG-R (REST API) 21 | 22 | ... 23 | -------------------------------------------------------------------------------- /Exercises/Exercise6_FruitFlyBrainObservatory.md: -------------------------------------------------------------------------------- 1 | # Exploring Brain Circuits with the Fruit Fly Brain Observatory 2 | 3 | This file contains a few quick tutorial on how to get started exploring the fruit fly brain using the [Fruit Fly Brain Observatory](http://fruitflybrain.org/) platform. This tutorial contains the following sections: 4 | - Exploratory Circuit Discovery with NeuroNLP 5 | - [Exercise 1-A: Access NeuroNLP and view the Demos](#exercis-1-a-access-neuronlp-and-view-the-demos) 6 | - [Exercise 1-B: Visualize Neurons in the Ellipsoid body](#exercise-1-b-visualize-neurons-in-the-ellipsoid-body) 7 | - [Exercise 1-C: Explore Fly Medulla Circuit from Janelia EM Data](#exercise-1-c-explore-fly-medulla-circuit-from-janelia-em-data) 8 | - [Exercise 1-D: Create and share a Tag](#exercise-1-d-create-and-share-a-tag) 9 | - [Exercise 1-E: Explore Networks from recent Publications](#exercise-1-e-explore-networks-from-recent-publications) 10 | - Exploring Brain Circuit Function at Multiple Brain Levels 11 | - [Exercise 2-A: Exploring Whole-Brain Level Circuit](#exercise-2-a-exploring-whole-brain-level-circuit) 12 | - [Exercise 2-B: Executing a Lamina Cartridge Circuit](#exercise-2-b-executing-a-lamina-cartridge-circuit) 13 | - Digging Deeper 14 | 15 | ## Exploratory Circuit Discovery with NeuroNLP 16 | 17 | This section contains a few demos on how to get started exploring the fruit fly brain with [NeuroNLP](https://neuronlp.fruitflybrain.org/), which is part of the [Fruit Fly Brain Observatory](http://fruitflybrain.org/) platform. 18 | 19 | ### Local software requirements 20 | 21 | None, apart from an up to date web browser 22 | 23 | ### Instructions 24 | 25 | #### Exercise 1-A: Access NeuroNLP and View the Demos 26 | 27 | 1. Open up [NeuroNLP](https://neuronlp.fruitflybrain.org/). 28 | 2. Create and Account, or sign in as a Guest. 29 | 3. Either follow the Pop-Up to the Demo page, or you can find them yourself by Clicking on NeuroNLP, and finding 'Demos' in the drop down menu. 30 | 4. Find an interesting demo and click launch, the website will then automatically step through a series of queries that demonstrate how to use NeuroNLP. 31 | 32 | 33 | #### Exercise 1-B: Visualize Neurons in the Ellipsoid body 34 | 35 | NeuroNLP contains the morphologies of the [FlyCircuit Database](http://flycircuit.tw). This means we can easily visualize these neurons, and the primary way of starting this is looking at the neuropil level. We are going to start looking at the Ellipsoid Body. 36 | 37 | "Show neurons in the Ellipsoid Body" 38 | 39 | We can Investigate the FlyCircuit data source of a neuron by double clicking its body. By Hovering over the FlyCircuit DB menu in the top left hand corner, you can expand a panel which details the underlying neuron details, with further links to the Virtual Fly Brain where possible. 40 | 41 | From this point, we can start to explore the brain by adding and removing neurons, such as adding neurons that innervate the Ellipsoid body 42 | 43 | "Add neurons that innervate the EB" 44 | 45 | This will start to return a lot of neurons, when this is done, we might might want to reduce the number by only looking at the dopaminergic neurons in this set, using 46 | 47 | "Keep dopaminergic neurons" 48 | 49 | There are lots of ways you can explore the data in NeuroNLP, check out the demos for more ways to slice and combine the data. 50 | 51 | 52 | #### Exercise 1-C: Explore Fly Medulla Circuit from Janelia EM Data 53 | 54 | NeuroNLP contains the detailed connectomic data of the [7 column medulla Electro-Microscopy (EM) data](https://github.com/janelia-flyem/ConnectomeHackathon2015) published by Janelia research campus. We can start out by visualizing all the Lamina neurons that innervate the Medulla in NeuroNLP 55 | 56 | "Show neurons in the Lamina" 57 | 58 | Note that the data only contains the part of the neurons in the medulla. Therefore, currently, we can only visualize their axons in the Medulla. 59 | 60 | We can look at the axons of the Lamina L1 neurons in the Medulla, using: 61 | 62 | "Show L1 neurons in the lamina" 63 | 64 | Nevertheless we can start to see the columnar nature of the Lamina. We can further look at only a single cartridge in the lamina by using: 65 | 66 | "Show neurons in a single cartridge in the lamina" 67 | 68 | We can also start to build up the flow of connectivity in the Lamina, by starting with a single L1 neuron. 69 | 70 | "Show L1 neurons in a single cartridge in the lamina" 71 | 72 | As we are using the connectomic data, we can start to build up the circuit connectomically, by adding the postsynaptic Mi1 and Tm3 neurons: 73 | 74 | "Add postsynaptic neurons" 75 | 76 | We can see a growing circuit of 14 neurons directly connected to the single L1 neuron. We can further run the same command, and build up the neurons 2 synaptic connections away, resulting in 246 neurons. 77 | From here we can pull back to look at the L2 neurons using 78 | 79 | "Keep L2 neurons in a single cartridge" 80 | 81 | And from here we can continue to explore the connectome, such as finding the neurons that synapse onto the L2 neurons: 82 | 83 | "Add presynaptic neurons" 84 | 85 | 86 | #### Exercise 1-D: Create and share a Tag 87 | 88 | After creating an interesting set of queries, you can Tag the results so that they can be easily shared and saved for later. To do this, click Create Tag at the top right, and enter a Tag Name such as "MyDemoTag". When you save this, you can reload the Tag using the Load tag button or share a link directly to the Tag using the link https://neuronlp.fruitflybrain.org/index.html?tag=MyDemoTag. 89 | 90 | Currently, tags cannot be deleted or overwritten by any user. An error will be raised if you are creating a tag that has been previously defined. 91 | 92 | We have used this tagging to create easily accessed links to circuits created from papers. 93 | 94 | #### Exercise 1-E: Explore Networks from recent Publications 95 | 96 | In a recent paper by Sun Yi et. al., Neural signatures of dynamic stimulus selection in Drosophila, they describe a feedforward visual pathway from the medulla to the central complex. We can recreate and explore this network in NeuroNLP, by opening the following [10.1038/nn.4581](https://neuronlp.fruitflybrain.org/index.html?tag=10.1038/nn.4581) Tag. 97 | 98 | 99 | ## Exploring Brain Circuit Function at Multiple Levels 100 | 101 | This section contains a few demos on how to explore executable brain circuits in [NeuroGFX](https://neurogfx.fruitflybrain.org/). 102 | 103 | 104 | ### Local software requirements 105 | 106 | None, apart from an up to date web browser 107 | 108 | ### Instructions 109 | 110 | #### Exercise 2-A: Exploring Whole-Brain Level Circuit 111 | 112 | Open up [NeuroGFX](https://neurogfx.fruitflybrain.org). 113 | 114 | On this page you will see the whole-brain level circuit diagram of the fruit fly. Each block represents an Local Processing Unit (LPU) that is a model of a neuropil. A biological representation of the brain is shown in the small window on the top left. It can be enlarged by hovering the mouse onto the window. To swap the circuit diagram and the fly brain, simply double click on the small window. 115 | 116 | Each LPU block is bound to its corresponding neuropil in the fly brain window. Clicking on an LPU will dim the block and remove the neuropil from the fly brain window. 117 | 118 | You can also play with the "Toggle Neuropil" and "Toggle Track" menu in the top right corner. 119 | 120 | #### Exercise 2-B: Executing a Lamina Cartridge Circuit 121 | 122 | On the main NeuroGFX page, double click on the "LAM" block (for the Lamina Neuropil on the right eye). You will be taken to the Lamina LPU page. When it is loaded, double click on any of the cartridge (red circle). 123 | 124 | Now you will see the circuit diagram of the Lamina cartridge. The morphology of the neurons is visualized in the small window in the top left corner of the screen. Click on the "Load Cartridge" button in the top right corner. This will initiate the communication with a NeuroArch server and load the model data of the cartridge circuit. The pop-up message will notify you when loading is complete. 125 | 126 | You can check the model information by hovering on any of the neuron (orange block). By clicking on the neurons, you can add/remove any neuron in the circuit. Once done, you can simulate the configured circuit by clicking on the "Open NK" button. This will start the simulation of the cartridge circuit with a (currently) predefined visual stimulus. 127 | 128 | Once the simulation is finished, the activity of the neurons will be automatically visualized. 129 | 130 | 131 | ## Digging Deeper 132 | 133 | Details about the software architecture of FFBO and implementation of components are available [here](https://hackpad.com/Introduction-to-the-FFBO-Tutorials-alt48Yg7sUM). 134 | 135 | 136 | 137 | -------------------------------------------------------------------------------- /Exercises/Exercise7_OpenWorm.md: -------------------------------------------------------------------------------- 1 | # Exploring Single Cell Simulated Physiology in Simulated Muscles 2 | 3 | This file contains a set of tutorials hosted on [BadgeList](http://www.badgelist.com/) that were produced by volunteers in the [OpenWorm project](http://openworm.org) to walk you through understanding the math and computer code behind simulating cells with excitable membranes. 4 | - Hodgkin Huxley Tutorial 5 | - Muscle Model Builder 6 | - Muscle Model Explorer 7 | - Muscle Model Hacker 8 | 9 | ## Hodgkin Huxley Tutorial 10 | 11 | This tutorial gives an introduction to the [Hodgkin-Huxley model](https://en.wikipedia.org/wiki/Hodgkin%E2%80%93Huxley_model) by use of executable example implementations in Python and [NeuroML](http://www.neuroml.org). 12 | 13 | ### The aims of this tutorial are: 14 | 15 | 1) Provide a guide to implementing the Hodgkin-Huxley model using both [Python](https://www.python.org/) and a [NeuroML2 implementation](http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00079/abstract) of the same equations. 16 | 2) Give some background information on the electrophysiology underlying the Hodgkin-Huxley model. 17 | 18 | Please [earn the badge for the Hodgkin Huxley tutorial via Badgelist](https://www.badgelist.com/OpenWorm/Hodgkin-Huxley-Tutorial-Graduate) 19 | 20 | ## Muscle Model Builder 21 | 22 | The muscle model project in the OpenWorm project (http://github.com/openworm/muscle_model) is open source code that contains multiple implementations of a published model of c. elegans muscle membrane dynamics. 23 | 24 | [Earning this badge](https://www.badgelist.com/OpenWorm/Muscle-Model-Builder) will show you the basics of how to download the code on your computer, install it, and run it. 25 | 26 | ## Muscle Model Explorer 27 | 28 | [Earning this badge](https://www.badgelist.com/OpenWorm/Muscle-Model-Explorer) will show you how to compare and interpret the output of the muscle model with figures in published papers. 29 | 30 | ## Muscle Model Hacker 31 | 32 | [Earning this badge](https://www.badgelist.com/OpenWorm/Muscle-Model-Hacker) will show you how changes you make to the underlying model code changes the output of the model. 33 | 34 | 35 | -------------------------------------------------------------------------------- /Exercises/README.md: -------------------------------------------------------------------------------- 1 | ## A number of exercises/interactive demonstrations for participants in this Neuroinformatics tutorial 2 | 3 | 4 | ### Hands on demonstrations 5 | 6 | #### Human Brain Project Collaboratory 7 | 8 | [Summary](Exercise2_HBP_Collaboratory.md) 9 | 10 | #### Run Allen Institute cell model on NSG via OSB 11 | 12 | [Summary](Exercise3_AllenCell_on_NSG_via_OSB.md) 13 | 14 | #### Demonstration of Neo/PyNN using Jupyter notebooks 15 | 16 | [Summary](Exercise4_NeoPyNNJupyter.md) 17 | 18 | 19 | ### Participant Exercises 20 | 21 | 22 | #### Cell morphology from NeuroMorpho.Org visualised on Open Source Brain 23 | 24 | [Follow this exercise](Exercise1_NeuroMorpho_to_OSB.md) 25 | 26 | #### Exploring Brain Circuits with the Fruit Fly Brain Observatory 27 | 28 | [Follow this exercise](Exercise6_FruitFlyBrainObservatory.md) 29 | 30 | #### OpenWorm tutorials (introduction to Hodgkin Huxley model etc.) 31 | 32 | [Follow this exercise](Exercise7_OpenWorm.md) 33 | 34 | 35 | 36 | -------------------------------------------------------------------------------- /Exercises/files/A1-May29-IR2-3-G.CNG.swc: -------------------------------------------------------------------------------- 1 | # SWC to SWC conversion from L-Measure. Sridevi Polavaram: spolavar@gmu.edu 2 | # Original fileName:/cng_repository/Soumya/LM_Automated_Testing_Enviornment/Test_Lm3.7.2_10062011_SG_Linux_NMOConv6/TestResults/LoadTest/test_15/A1-May29-IR2-3-G.CNG.swc 3 | # 4 | # Original file A1-May29-IR2-3-G.swc edited by Duncan Donohue using StdSwc version 1.31 on 12/23/09. 5 | # Irregularities and fixes documented in A1-May29-IR2-3-G.swc.std. See StdSwc1.31.doc for more information. 6 | # 7 | # Neurolucida to SWC conversion from L-Measure. R. Scorcioni: rscorcio@gmu.edu 8 | # Original fileName:C:\Documents and Settings\DataProcessing\Desktop\Luebke_Dec_23_Asc\A1-May29-IR2-3-G.ASC 9 | 1 1 172.74 -395.54 -13.53 2.977 -1 10 | 2 1 172.74 -392.56 -13.53 2.977 1 11 | 3 1 172.74 -398.51 -13.53 2.977 1 12 | 4 3 166.8 -400 -16.8 0.565 1 13 | 5 3 159.19 -405.2 -16.39 0.72 4 14 | 6 3 157.19 -406.4 -15.99 0.72 5 15 | 7 3 156 -407.2 -15.58 0.895 6 16 | 8 3 154.69 -407.4 -14.76 0.895 7 17 | 9 3 152.4 -412.4 -14.76 0.72 8 18 | 10 3 151.19 -414.4 -14.76 0.72 9 19 | 11 3 150.4 -416.4 -14.35 0.72 10 20 | 12 3 149.19 -418.4 -13.94 0.72 11 21 | 13 3 148.4 -420.4 -13.94 0.63 12 22 | 14 3 148 -422.4 -13.53 0.63 13 23 | 15 3 147.19 -424.4 -13.12 0.63 14 24 | 16 3 146.4 -426.4 -13.12 0.63 15 25 | 17 3 145.84 -427.34 -13.12 0.63 16 26 | 18 3 144.8 -434 -13.94 0.6 17 27 | 19 3 144.4 -436 -14.35 0.6 18 28 | 20 3 144.4 -438 -14.76 0.6 19 29 | 21 3 144.4 -440 -15.17 0.6 20 30 | 22 3 144.4 -442 -15.17 0.6 21 31 | 23 3 144 -444 -15.58 0.6 22 32 | 24 3 143.6 -446 -15.99 0.6 23 33 | 25 3 143.6 -448 -15.99 0.6 24 34 | 26 3 144 -450 -15.58 0.6 25 35 | 27 3 144.4 -452 -14.76 0.6 26 36 | 28 3 144.8 -453.2 -14.35 0.6 27 37 | 29 3 145.19 -455.2 -13.94 0.6 28 38 | 30 3 145.6 -457.2 -13.53 0.6 29 39 | 31 3 146.4 -459.2 -13.12 0.6 30 40 | 32 3 147.19 -459.6 -12.71 0.6 31 41 | 33 3 147.6 -461.6 -12.3 0.6 32 42 | 34 3 148 -462.8 -12.71 0.6 33 43 | 35 3 148 -464.8 -12.71 0.6 34 44 | 36 3 148 -466.8 -12.71 0.4 35 45 | 37 3 148 -468.8 -12.3 0.4 36 46 | 38 3 148 -470.8 -11.89 0.4 37 47 | 39 3 147.6 -472.8 -11.48 0.63 38 48 | 40 3 147.19 -474.8 -11.07 0.63 39 49 | 41 3 146.4 -476.8 -11.07 0.63 40 50 | 42 3 145.6 -478.8 -10.66 0.63 41 51 | 43 3 144.4 -481.2 -9.84 0.63 42 52 | 44 3 143.6 -483.2 -9.02 0.6 43 53 | 45 3 143.19 -485.2 -8.61 0.6 44 54 | 46 3 142.8 -487.2 -8.19 0.6 45 55 | 47 3 142 -489.2 -8.19 0.4 46 56 | 48 3 141.6 -491.2 -8.19 0.4 47 57 | 49 3 141.19 -493.2 -8.19 0.6 48 58 | 50 3 141.19 -495.2 -8.19 0.6 49 59 | 51 3 140.8 -497.2 -7.79 0.445 50 60 | 52 3 140 -499.2 -7.79 0.445 51 61 | 53 3 139.19 -501.2 -8.19 0.445 52 62 | 54 3 138.4 -503.2 -8.19 0.4 53 63 | 55 3 138 -505.2 -8.19 0.4 54 64 | 56 3 137.19 -507.2 -8.19 0.4 55 65 | 57 3 136.4 -509.2 -7.79 0.4 56 66 | 58 3 136 -511.2 -7.79 0.4 57 67 | 59 3 135.19 -513.2 -7.38 0.4 58 68 | 60 3 134.4 -515.2 -6.97 0.6 59 69 | 61 3 134 -517.2 -6.97 0.6 60 70 | 62 3 133.6 -519.6 -7.38 0.63 61 71 | 63 3 132.4 -521.6 -8.19 0.72 62 72 | 64 3 130.8 -523.2 -8.19 0.72 63 73 | 65 3 145.19 -428.4 -13.12 0.63 17 74 | 66 3 144 -430.4 -13.12 0.72 65 75 | 67 3 142.8 -432.4 -13.53 0.72 66 76 | 68 3 141.6 -434.4 -14.35 0.72 67 77 | 69 3 141.44 -434.66 -15.17 0.72 68 78 | 70 3 140.4 -436.4 -15.17 0.565 69 79 | 71 3 139.6 -438.4 -15.99 0.4 70 80 | 72 3 138.8 -440.4 -16.39 0.4 71 81 | 73 3 138 -442.4 -16.39 0.4 72 82 | 74 3 137.19 -444.4 -16.39 0.4 73 83 | 75 3 136.4 -446.4 -16.8 0.4 74 84 | 76 3 135.6 -448.4 -16.8 0.63 75 85 | 77 3 134 -450.4 -16.8 0.72 76 86 | 78 3 132.8 -452.4 -16.8 0.72 77 87 | 79 3 132 -453.6 -16.8 0.72 78 88 | 80 3 130 -455.6 -16.39 0.72 79 89 | 81 3 129.19 -457.6 -16.39 0.72 80 90 | 82 3 128.4 -459.6 -15.99 0.72 81 91 | 83 3 127.2 -461.6 -15.99 0.565 82 92 | 84 3 125.2 -463.6 -15.99 0.565 83 93 | 85 3 124.4 -465.6 -15.99 0.565 84 94 | 86 3 123.2 -467.6 -15.99 0.63 85 95 | 87 3 122.4 -469.6 -15.99 0.63 86 96 | 88 3 121.2 -471.6 -15.58 0.63 87 97 | 89 3 119.2 -473.6 -15.58 0.63 88 98 | 90 3 118 -475.6 -15.58 0.63 89 99 | 91 3 116 -477.6 -15.58 0.63 90 100 | 92 3 114 -478.8 -15.58 0.63 91 101 | 93 3 112 -480.8 -15.58 0.63 92 102 | 94 3 110.8 -482.8 -15.99 0.565 93 103 | 95 3 108.8 -484.8 -15.99 0.565 94 104 | 96 3 106.8 -486.8 -15.99 0.565 95 105 | 97 3 104.8 -488 -15.99 0.565 96 106 | 98 3 102.8 -489.2 -15.99 0.565 97 107 | 99 3 100.8 -491.2 -15.99 0.72 98 108 | 100 3 98.8 -492.4 -15.58 0.72 99 109 | 101 3 96.8 -493.6 -15.17 0.72 100 110 | 102 3 94.8 -495.6 -14.35 0.72 101 111 | 103 3 92.8 -496.8 -13.94 0.565 102 112 | 104 3 90.8 -498.8 -13.53 0.565 103 113 | 105 3 88.8 -500.8 -13.94 0.565 104 114 | 106 3 87.6 -502.8 -13.94 0.565 105 115 | 107 3 154 -408 -14.76 0.895 8 116 | 108 3 152 -408.4 -13.53 0.63 107 117 | 109 3 150 -408.8 -13.12 0.6 108 118 | 110 3 149.08 -408.98 -12.71 0.6 109 119 | 111 3 148 -410.4 -11.07 0.72 110 120 | 112 3 146.8 -412 -9.02 0.72 111 121 | 113 3 146 -413.2 -6.97 0.72 112 122 | 114 3 145.6 -413.6 -4.92 0.72 113 123 | 115 3 144.8 -414 -2.87 0.72 114 124 | 116 3 144 -414.4 -0.82 0.72 115 125 | 117 3 143.6 -414.8 1.23 0.72 116 126 | 118 3 143.6 -415.6 3.28 0.72 117 127 | 119 3 142.8 -416.8 5.33 0.72 118 128 | 120 3 142 -418 7.38 0.72 119 129 | 121 3 141.6 -418.4 9.43 0.72 120 130 | 122 3 141.19 -418.8 11.48 0.72 121 131 | 123 3 138.6 -421 13.53 0.72 122 132 | 124 3 135.6 -426.6 15.58 0.72 123 133 | 125 3 132.8 -427.4 16.8 0.72 124 134 | 126 3 129.8 -431.2 18.86 0.72 125 135 | 127 3 132.19 -434.4 20.91 0.72 126 136 | 128 3 127.2 -441 22.96 0.72 127 137 | 129 3 118.2 -448 25.01 0.72 128 138 | 130 3 148 -409.2 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0.63 154 164 | 156 3 98 -432.8 -23.78 0.63 155 165 | 157 3 95.25 -430.92 -29.52 0.63 156 166 | 158 3 94.4 -431.2 -29.52 0.63 157 167 | 159 3 92.4 -432.4 -30.34 0.63 158 168 | 160 3 90.4 -433.2 -31.16 0.63 159 169 | 161 3 88.4 -433.6 -31.98 0.6 160 170 | 162 3 87.2 -432.8 -32.79 0.4 161 171 | 163 3 85.2 -432.4 -33.21 0.4 162 172 | 164 3 83.2 -432.4 -34.03 0.4 163 173 | 165 3 81.2 -432.4 -34.44 0.4 164 174 | 166 3 79.2 -432.4 -35.26 0.4 165 175 | 167 3 77.2 -432.8 -36.49 0.4 166 176 | 168 3 75.2 -433.2 -37.31 0.4 167 177 | 169 3 73.2 -433.2 -38.13 0.6 168 178 | 170 3 71.2 -433.2 -38.13 0.6 169 179 | 171 3 69.2 -433.6 -38.54 0.6 170 180 | 172 3 67.2 -434 -38.95 0.4 171 181 | 173 3 65.2 -434.4 -39.36 0.4 172 182 | 174 3 63.2 -435.2 -39.36 0.565 173 183 | 175 3 61.2 -436.4 -39.36 0.72 174 184 | 176 3 59.2 -437.6 -39.36 0.72 175 185 | 177 3 57.2 -438.4 -39.77 0.72 176 186 | 178 3 55.2 -439.6 -39.77 0.72 177 187 | 179 3 53.6 -442 -40.18 0.72 178 188 | 180 3 132 -409.2 -12.3 0.6 138 189 | 181 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0.6 207 217 | 209 3 76 -401.2 -7.79 0.6 208 218 | 210 3 74 -400.8 -7.38 0.6 209 219 | 211 3 72 -400.8 -6.97 0.6 210 220 | 212 3 70 -401.2 -6.56 0.6 211 221 | 213 3 68 -401.2 -6.15 0.6 212 222 | 214 3 66 -400.8 -5.74 0.6 213 223 | 215 3 64 -400.4 -5.33 0.6 214 224 | 216 3 62 -400.4 -4.92 0.6 215 225 | 217 3 60 -400.8 -4.51 0.6 216 226 | 218 3 58 -401.2 -3.69 0.4 217 227 | 219 3 56 -401.2 -2.87 0.4 218 228 | 220 3 54 -401.6 -2.46 0.6 219 229 | 221 3 49.8 -402 -1.64 0.6 220 230 | 222 3 46.6 -405.6 -0.82 0.6 221 231 | 223 3 39.79 -409 0.41 0.6 222 232 | 224 3 125.6 -406.8 -10.66 0.565 183 233 | 225 3 123.6 -405.6 -10.25 0.565 224 234 | 226 3 121.6 -403.6 -10.25 0.565 225 235 | 227 3 119.6 -402.4 -9.84 0.565 226 236 | 228 3 117.6 -401.2 -9.02 0.63 227 237 | 229 3 115.6 -400 -7.79 0.63 228 238 | 230 3 113.6 -399.2 -6.97 0.565 229 239 | 231 3 111.6 -398 -6.97 0.565 230 240 | 232 3 110 -395.6 -6.56 0.72 231 241 | 233 3 108.8 -393.6 -6.97 0.72 232 242 | 234 3 107.6 -391.6 -7.38 0.72 233 243 | 235 3 106.4 -389.6 -7.79 0.72 234 244 | 236 3 105.2 -387.6 -8.19 0.72 235 245 | 237 3 104 -385.6 -9.02 0.72 236 246 | 238 3 102.8 -383.6 -9.43 0.565 237 247 | 239 3 100.8 -381.6 -10.66 0.565 238 248 | 240 3 98.8 -379.6 -11.07 0.72 239 249 | 241 3 97.2 -378.4 -10.66 0.72 240 250 | 242 3 95.6 -376 -9.84 0.72 241 251 | 243 3 95.6 -374 -9.43 0.445 242 252 | 244 3 95.2 -372 -9.43 0.445 243 253 | 245 3 94.4 -370 -9.02 0.445 244 254 | 246 3 92.8 -368 -8.61 0.565 245 255 | 247 3 91.6 -366 -8.19 0.565 246 256 | 248 3 90.4 -364 -7.38 0.565 247 257 | 249 3 89.2 -362 -6.15 0.72 248 258 | 250 3 87.6 -360.4 -4.09 0.72 249 259 | 251 3 86.4 -358.4 -2.46 0.72 250 260 | 252 3 85.6 -356.4 -1.23 0.63 251 261 | 253 3 85.2 -354.4 0 0.6 252 262 | 254 3 84.8 -352.4 1.23 0.6 253 263 | 255 3 84.8 -351.6 2.46 0.6 254 264 | 256 3 177.2 -402 -20.09 0.85 1 265 | 257 3 179.6 -403.2 -19.68 0.85 256 266 | 258 3 182.45 -406 -20.09 0.85 257 267 | 259 3 182.02 -405.6 -20.09 0.85 258 268 | 260 3 186.73 -408.06 -20.09 0.1 259 269 | 261 3 186.4 -406.4 -20.09 0.6 260 270 | 262 3 190.4 -408.8 -22.55 0.6 261 271 | 263 3 190.4 -410.22 -22.55 0.6 262 272 | 264 3 190.4 -410.4 -24.6 0.6 263 273 | 265 3 190 -412 -26.24 0.6 264 274 | 266 3 189.6 -414 -27.47 0.6 265 275 | 267 3 189.2 -416 -28.7 0.6 266 276 | 268 3 188.4 -418 -30.34 0.6 267 277 | 269 3 187.6 -420 -31.16 0.6 268 278 | 270 3 186.8 -422 -31.57 0.4 269 279 | 271 3 186 -424 -31.98 0.4 270 280 | 272 3 185.6 -426 -32.39 0.4 271 281 | 273 3 185.2 -428 -32.79 0.4 272 282 | 274 3 185.2 -430 -33.61 0.6 273 283 | 275 3 185.2 -432 -34.85 0.6 274 284 | 276 3 185.6 -434 -36.49 0.6 275 285 | 277 3 186 -435.2 -38.54 0.4 276 286 | 278 3 186.8 -437.2 -40.59 0.4 277 287 | 279 3 187.2 -438.4 -41.82 0.565 278 288 | 280 3 188 -439.6 -43.87 0.565 279 289 | 281 3 189.2 -440.8 -45.92 0.565 280 290 | 282 3 189.2 -441.2 -47.97 0.565 281 291 | 283 3 190 -442.8 -47.97 0.6 282 292 | 284 3 190.8 -444.8 -48.79 0.6 283 293 | 285 3 191.2 -446.8 -49.2 0.6 284 294 | 286 3 191.2 -448.8 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0.72 361 371 | 363 3 200.8 -411.6 -13.12 0.72 362 372 | 364 3 202 -412.4 -11.07 0.72 363 373 | 365 3 203.2 -412.8 -9.43 0.445 364 374 | 366 3 204.8 -413.2 -7.38 0.445 365 375 | 367 3 206.4 -414.4 -5.33 0.63 366 376 | 368 3 208 -415.6 -3.28 0.63 367 377 | 369 3 210 -416.4 -1.64 0.4 368 378 | 370 3 212 -417.2 0.41 0.4 369 379 | 371 3 214 -418 2.46 0.565 370 380 | 372 3 215.2 -418.8 4.51 0.6 371 381 | 373 3 217.2 -419.6 6.56 0.6 372 382 | 374 3 219.2 -420.4 7.79 0.565 373 383 | 375 3 221.2 -421.2 9.43 0.565 374 384 | 376 3 223.2 -422.4 10.25 0.565 375 385 | 377 3 225.2 -423.6 11.89 0.72 376 386 | 378 3 226.8 -424.8 13.94 0.72 377 387 | 379 3 228.4 -426 15.99 0.72 378 388 | 380 3 229.6 -426.4 18.04 0.8 379 389 | 381 3 232.4 -427.2 20.09 0.8 380 390 | 382 3 231.4 -434.4 22.14 0.8 381 391 | 383 3 236.4 -438.8 24.19 0.8 382 392 | 384 3 240.2 -437.8 26.24 0.8 383 393 | 385 3 244.2 -439.2 28.29 0.8 384 394 | 386 3 197.2 -407.6 -19.27 0.4 358 395 | 387 3 199.2 -407.2 -19.27 0.4 386 396 | 388 3 201.2 -406 -19.68 0.4 387 397 | 389 3 203.2 -405.2 -20.09 0.63 388 398 | 390 3 204.8 -404 -20.5 0.63 389 399 | 391 3 206.8 -403.2 -20.91 0.63 390 400 | 392 3 208.8 -402.8 -21.73 0.6 391 401 | 393 3 210.8 -402.4 -22.55 0.6 392 402 | 394 3 212.8 -401.6 -22.55 0.6 393 403 | 395 3 214.8 -400.8 -22.55 0.6 394 404 | 396 3 216.8 -400 -22.55 0.4 395 405 | 397 3 218.8 -399.2 -22.14 0.4 396 406 | 398 3 220.8 -398.4 -22.14 0.4 397 407 | 399 3 222.8 -397.6 -21.73 0.63 398 408 | 400 3 224.8 -396.4 -21.73 0.63 399 409 | 401 3 226.8 -395.6 -21.32 0.6 400 410 | 402 3 228.8 -395.2 -20.91 0.6 401 411 | 403 3 230.8 -395.2 -20.91 0.6 402 412 | 404 3 232.8 -395.6 -20.91 0.4 403 413 | 405 3 234.8 -395.6 -20.91 0.4 404 414 | 406 3 236 -395.6 -21.32 0.4 405 415 | 407 3 238 -395.6 -21.73 0.4 406 416 | 408 3 240 -396 -21.73 0.4 407 417 | 409 3 242 -396 -21.73 0.4 408 418 | 410 3 244 -396 -21.73 0.4 409 419 | 411 3 246 -396.4 -22.14 0.4 410 420 | 412 3 248 -396.4 -22.14 0.4 411 421 | 413 3 250 -396.4 -22.14 0.4 412 422 | 414 3 252 -396 -22.55 0.4 413 423 | 415 3 254 -396 -22.14 0.4 414 424 | 416 3 256 -396.4 -22.14 0.4 415 425 | 417 3 258 -397.2 -22.14 0.4 416 426 | 418 3 260 -398 -21.73 0.4 417 427 | 419 3 262 -398.8 -21.32 0.4 418 428 | 420 3 264 -399.6 -20.91 0.6 419 429 | 421 3 266 -400 -20.5 0.6 420 430 | 422 3 268 -400.4 -20.09 0.6 421 431 | 423 3 270 -400.4 -20.5 0.6 422 432 | 424 3 272 -400 -20.91 0.6 423 433 | 425 3 274 -399.6 -20.5 0.6 424 434 | 426 3 183.3 -406.8 -20.09 0.85 258 435 | 427 3 182.8 -407.6 -20.09 0.6 426 436 | 428 3 184 -409.6 -18.45 0.6 427 437 | 429 3 184.4 -410.8 -16.39 0.6 428 438 | 430 3 184.4 -412 -14.35 0.6 429 439 | 431 3 184.34 -412.3 -14.35 0.6 430 440 | 432 3 184 -414 -12.3 0.6 431 441 | 433 3 184 -414.8 -11.48 0.6 432 442 | 434 3 184.4 -416.8 -10.25 0.6 433 443 | 435 3 184.4 -418.8 -9.02 0.6 434 444 | 436 3 184.8 -420.8 -8.19 0.6 435 445 | 437 3 184.8 -422.8 -7.38 0.6 436 446 | 438 3 184.8 -424.8 -6.15 0.6 437 447 | 439 3 184.8 -426.8 -5.33 0.6 438 448 | 440 3 184.4 -428.8 -4.51 0.6 439 449 | 441 3 184.4 -430.8 -3.28 0.6 440 450 | 442 3 184.8 -432.8 -1.23 0.6 441 451 | 443 3 184.8 -434.8 0 0.6 442 452 | 444 3 184 -436.8 0.82 0.6 443 453 | 445 3 183.89 -437.33 0.82 0.6 444 454 | 446 3 183.6 -438.8 1.23 0.6 445 455 | 447 3 183.6 -440.8 1.64 0.6 446 456 | 448 3 183.6 -442.8 2.04 0.6 447 457 | 449 3 183.2 -444.8 2.87 0.6 448 458 | 450 3 182 -446.4 4.09 0.72 449 459 | 451 3 180.8 -448.4 4.51 0.72 450 460 | 452 3 180 -450.8 4.51 0.445 451 461 | 453 3 179.2 -452.8 5.33 0.445 452 462 | 454 3 178.8 -454.8 6.15 0.445 453 463 | 455 3 178 -456.8 6.97 0.445 454 464 | 456 3 177.2 -458.8 7.38 0.63 455 465 | 457 3 176.4 -460.8 7.38 0.63 456 466 | 458 3 175.6 -462.8 7.79 0.6 457 467 | 459 3 175.2 -464.8 8.61 0.4 458 468 | 460 3 175.2 -467.2 9.02 0.4 459 469 | 461 3 175.6 -469.2 10.25 0.6 460 470 | 462 3 176 -471.2 11.48 0.6 461 471 | 463 3 176 -473.2 12.3 0.6 462 472 | 464 3 176 -475.2 13.12 0.6 463 473 | 465 3 175.6 -477.2 13.94 0.6 464 474 | 466 3 175.2 -479.2 14.76 0.6 465 475 | 467 3 174.8 -481.2 15.99 0.6 466 476 | 468 3 174.4 -483.2 16.8 0.4 467 477 | 469 3 174.4 -485.2 17.63 0.4 468 478 | 470 3 174.4 -487.2 18.04 0.4 469 479 | 471 3 174.4 -489.2 18.45 0.4 470 480 | 472 3 174.4 -491.2 18.86 0.4 471 481 | 473 3 173.6 -493.2 19.27 0.6 472 482 | 474 3 173.6 -495.2 19.27 0.6 473 483 | 475 3 174 -497.2 18.86 0.6 474 484 | 476 3 190 -444.8 7.79 0.63 445 485 | 477 3 191.2 -446.4 8.19 0.63 476 486 | 478 3 192.4 -448.4 8.61 0.63 477 487 | 479 3 193.2 -450.4 9.02 0.63 478 488 | 480 3 194 -452 9.43 0.63 479 489 | 481 3 195.2 -454 9.84 0.63 480 490 | 482 3 196.4 -456 9.84 0.565 481 491 | 483 3 197.2 -458 10.25 0.565 482 492 | 484 3 197.6 -460 11.07 0.6 483 493 | 485 3 198.4 -462 11.48 0.6 484 494 | 486 3 199.2 -464 11.89 0.63 485 495 | 487 3 200 -466 12.3 0.63 486 496 | 488 3 200.8 -467.6 13.53 0.63 487 497 | 489 3 201.2 -468.8 13.94 0.6 488 498 | 490 3 201.6 -470.8 15.17 0.4 489 499 | 491 3 202.4 -472.8 16.8 0.4 490 500 | 492 3 202.8 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518 3 186.4 -412.8 -20.09 0.63 517 527 | 519 3 187.2 -414.8 -20.09 0.63 518 528 | 520 3 187.6 -416.8 -20.09 0.6 519 529 | 521 3 187.6 -418.8 -19.68 0.6 520 530 | 522 3 187.2 -420.8 -19.68 0.4 521 531 | 523 3 187.2 -422.8 -19.27 0.4 522 532 | 524 3 186.8 -424.8 -19.27 0.4 523 533 | 525 3 186.4 -426.8 -19.27 0.4 524 534 | 526 3 186 -428.8 -18.86 0.6 525 535 | 527 3 185.6 -430.8 -18.86 0.6 526 536 | 528 3 185.2 -432.8 -18.86 0.6 527 537 | 529 3 185.2 -434.8 -18.45 0.6 528 538 | 530 3 185.2 -436.8 -18.04 0.6 529 539 | 531 3 185.2 -438.8 -17.22 0.4 530 540 | 532 3 185.2 -440.8 -16.8 0.4 531 541 | 533 3 184.8 -442.8 -16.39 0.4 532 542 | 534 3 184.4 -444.8 -15.58 0.4 533 543 | 535 3 184.4 -446.8 -14.76 0.4 534 544 | 536 3 184.4 -448.8 -14.35 0.6 535 545 | 537 3 184 -450.8 -13.94 0.6 536 546 | 538 3 184 -452 -13.53 0.4 537 547 | 539 3 183.6 -454 -13.12 0.4 538 548 | 540 3 183.2 -456 -12.71 0.4 539 549 | 541 3 182.8 -458 -12.3 0.4 540 550 | 542 3 182.8 -460 -11.89 0.6 541 551 | 543 3 182.8 -462 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571 3 183.6 -516 3.69 0.6 570 580 | 572 3 183.6 -518 4.51 0.6 571 581 | 573 3 184 -520 5.74 0.6 572 582 | 574 3 184.4 -522 6.97 0.6 573 583 | 575 3 184.8 -524 8.19 0.565 574 584 | 576 3 185.6 -526 9.84 0.565 575 585 | 577 3 187.2 -528 10.66 0.72 576 586 | 578 3 188.4 -530 12.3 0.72 577 587 | 579 3 181.2 -469.6 -11.89 0.4 546 588 | 580 3 180.8 -471.6 -12.3 0.4 579 589 | 581 3 179.6 -473.6 -12.71 0.6 580 590 | 582 3 178.8 -474.8 -13.12 0.6 581 591 | 583 3 178.4 -476.8 -13.53 0.4 582 592 | 584 3 178.4 -478.8 -13.53 0.4 583 593 | 585 3 178 -480.8 -13.94 0.4 584 594 | 586 3 178 -482.8 -13.94 0.4 585 595 | 587 3 177.6 -484.8 -13.94 0.4 586 596 | 588 3 176.8 -486.8 -13.94 0.4 587 597 | 589 3 176.4 -488.8 -13.53 0.4 588 598 | 590 3 175.6 -490.8 -12.71 0.4 589 599 | 591 3 174.8 -492.8 -12.3 0.72 590 600 | 592 3 173.6 -494.8 -11.89 0.72 591 601 | 593 3 172.8 -497.2 -11.07 0.6 592 602 | 594 3 172 -499.2 -10.66 0.6 593 603 | 595 3 171.6 -501.2 -10.25 0.6 594 604 | 596 3 171.2 -503.2 -9.43 0.6 595 605 | 597 3 170.8 -505.2 -8.61 0.6 596 606 | 598 3 170.4 -507.2 -8.19 0.6 597 607 | 599 3 170.8 -509.2 -7.38 0.4 598 608 | 600 3 170.8 -511.2 -6.97 0.4 599 609 | 601 3 170.4 -513.2 -6.56 0.4 600 610 | 602 3 170 -515.2 -5.74 0.6 601 611 | 603 3 169.6 -517.2 -5.33 0.6 602 612 | 604 3 169.6 -519.2 -4.92 0.6 603 613 | 605 3 169.6 -521.2 -4.51 0.6 604 614 | 606 3 169.2 -523.2 -4.09 0.6 605 615 | 607 3 168.8 -525.2 -3.69 0.63 606 616 | 608 3 168 -527.6 -4.09 0.63 607 617 | 609 3 167.2 -529.6 -4.09 0.63 608 618 | 610 4 172.57 -386.3 -11.48 1.2 1 619 | 611 4 173.9 -376.6 -11.48 1.2 610 620 | 612 4 174.8 -377 -11.48 0.8 611 621 | 613 4 174.8 -377.6 -11.89 0.8 612 622 | 614 4 175.2 -379.6 -9.43 0.85 613 623 | 615 4 176.8 -382 -7.38 0.85 614 624 | 616 4 178.8 -383.2 -6.15 0.72 615 625 | 617 4 180.8 -384.4 -5.33 0.72 616 626 | 618 4 182 -385.2 -4.92 0.72 617 627 | 619 4 182.5 -385.4 -4.92 0.72 618 628 | 620 4 184.4 -385.6 -3.28 0.72 619 629 | 621 4 186.4 -386.8 -2.46 0.72 620 630 | 622 4 188.4 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4 240 -410.8 15.99 0.565 647 657 | 649 4 241.2 -412.8 16.39 0.565 648 658 | 650 4 242.8 -414.8 16.8 0.445 649 659 | 651 4 243.6 -416.8 16.8 0.4 650 660 | 652 4 244.4 -418.8 17.63 0.4 651 661 | 653 4 245.6 -420.8 18.45 0.72 652 662 | 654 4 246.8 -422.4 19.27 0.72 653 663 | 655 4 248 -424.4 19.27 0.72 654 664 | 656 4 250.4 -426.4 19.68 0.565 655 665 | 657 4 252.4 -428.4 20.09 0.565 656 666 | 658 4 254.4 -430.4 20.5 0.565 657 667 | 659 4 255.6 -432.4 20.5 0.565 658 668 | 660 4 257.6 -434.4 20.5 0.63 659 669 | 661 4 258.8 -436.4 20.5 0.63 660 670 | 662 4 259.6 -438.8 20.5 0.6 661 671 | 663 4 260 -441.2 20.91 0.6 662 672 | 664 4 260 -443.2 22.14 0.6 663 673 | 665 4 260.39 -445.2 22.96 0.6 664 674 | 666 4 182 -386.8 -4.92 0.565 619 675 | 667 4 181.2 -387.6 -2.87 0.565 666 676 | 668 4 180.31 -388.49 -2.87 0.565 667 677 | 669 4 179.6 -389.2 -2.87 0.565 668 678 | 670 4 178.8 -390 -0.82 0.85 669 679 | 671 4 177.2 -391.6 1.23 0.85 670 680 | 672 4 177.7 -392.2 1.23 0.85 671 681 | 673 4 176 -393.2 3.28 0.85 672 682 | 674 4 174.4 -395.6 4.51 0.85 673 683 | 675 4 173.2 -397.6 6.15 0.85 674 684 | 676 4 172 -399.6 7.79 1 675 685 | 677 4 171.2 -401.2 10.25 1 676 686 | 678 4 170.4 -403.2 11.89 0.72 677 687 | 679 4 169.6 -405.2 13.12 0.72 678 688 | 680 4 167.6 -407.2 14.35 0.565 679 689 | 681 4 166.4 -409.2 15.99 0.565 680 690 | 682 4 164.4 -410.8 18.04 0.565 681 691 | 683 4 163.19 -412.8 19.68 0.72 682 692 | 684 4 162 -414.8 21.32 0.72 683 693 | 685 4 161.19 -416.4 21.73 0.63 684 694 | 686 4 160.4 -418.8 22.55 0.63 685 695 | 687 4 159.6 -420.8 24.19 0.63 686 696 | 688 4 158.8 -422.8 25.01 0.63 687 697 | 689 4 157.6 -424.8 25.83 0.63 688 698 | 690 4 156.8 -426.8 27.47 0.6 689 699 | 691 4 156.4 -428.8 28.29 0.6 690 700 | 692 4 156 -430.8 29.11 0.6 691 701 | 693 4 155.6 -432.8 29.93 0.6 692 702 | 694 4 155.19 -434.8 30.75 0.6 693 703 | 695 4 155.19 -436.8 31.98 0.6 694 704 | 696 4 154.8 -438.8 32.79 0.6 695 705 | 697 4 154.4 -440.8 33.61 0.6 696 706 | 698 4 154.4 -442.8 34.44 0.6 697 707 | 699 4 154 -444.8 35.67 0.6 698 708 | 700 4 153.6 -446.8 36.9 0.6 699 709 | 701 4 153.19 -448.4 38.54 0.6 700 710 | 702 4 152.8 -450.8 39.36 0.6 701 711 | 703 4 152.4 -452.8 41.41 0.6 702 712 | 704 4 151.6 -454.8 42.23 0.63 703 713 | 705 4 150.8 -456.8 43.05 0.63 704 714 | 706 4 150 -458.8 44.69 0.72 705 715 | 707 4 148.8 -460.8 45.51 0.72 706 716 | 708 4 146.8 -462.8 46.74 0.72 707 717 | 709 4 144.8 -464 47.56 0.72 708 718 | 710 4 142.8 -465.2 47.97 0.72 709 719 | 711 4 185.6 -390.8 1.23 0.4 672 720 | 712 4 186 -390.8 3.28 0.4 711 721 | 713 4 186.8 -391.2 5.33 0.445 712 722 | 714 4 188 -391.6 7.38 0.445 713 723 | 715 4 188.8 -391.6 9.43 0.72 714 724 | 716 4 189.6 -392 11.48 0.72 715 725 | 717 4 190.4 -392.4 13.53 0.72 716 726 | 718 4 191.6 -393.2 15.58 0.72 717 727 | 719 4 192 -393.6 17.63 0.63 718 728 | 720 4 193.2 -393.2 19.68 0.63 719 729 | 721 4 194.8 -392.8 22.14 0.63 720 730 | 722 4 196.8 -393.2 23.37 0.6 721 731 | 723 4 198.8 -393.2 25.42 0.6 722 732 | 724 4 203.4 -388.8 26.65 0.6 723 733 | 725 4 174.15 -376.3 -11.48 1.2 611 734 | 726 4 170.8 -376.8 -11.48 0.8 725 735 | 727 4 168.8 -376.8 -10.66 0.6 726 736 | 728 4 166.8 -376.4 -9.84 0.6 727 737 | 729 4 164.8 -376.4 -9.02 0.6 728 738 | 730 4 162.8 -376.8 -8.61 0.6 729 739 | 731 4 160.8 -377.2 -8.19 0.6 730 740 | 732 4 158.8 -378 -7.79 0.6 731 741 | 733 4 156.8 -378.4 -7.79 0.6 732 742 | 734 4 154.8 -378.8 -7.38 0.4 733 743 | 735 4 152.8 -379.2 -6.97 0.4 734 744 | 736 4 150.8 -379.2 -6.97 0.4 735 745 | 737 4 148.8 -379.2 -6.97 0.6 736 746 | 738 4 146.8 -379.2 -6.56 0.6 737 747 | 739 4 144.8 -379.2 -5.74 0.6 738 748 | 740 4 143.6 -379.6 -5.74 0.4 739 749 | 741 4 141.6 -380 -5.74 0.4 740 750 | 742 4 139.6 -380.4 -5.33 0.6 741 751 | 743 4 137.6 -380.8 -4.51 0.6 742 752 | 744 4 135.6 -381.2 -3.28 0.6 743 753 | 745 4 133.6 -381.6 -2.04 0.6 744 754 | 746 4 131.6 -382 -0.82 0.6 745 755 | 747 4 129.6 -382.8 0 0.72 746 756 | 748 4 127.6 -384 0.41 0.72 747 757 | 749 4 125.6 -385.2 0.41 0.72 748 758 | 750 4 124.94 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-439 20.91 0.72 775 785 | 777 4 120.8 -384.8 0.41 0.6 750 786 | 778 4 118.8 -384.4 0.41 0.6 777 787 | 779 4 116.8 -383.6 0.41 0.4 778 788 | 780 4 114.8 -382.8 0 0.4 779 789 | 781 4 112.8 -381.6 0 0.72 780 790 | 782 4 110.8 -380.4 0.82 0.72 781 791 | 783 4 108.8 -379.2 0.82 0.72 782 792 | 784 4 107.6 -378.4 1.23 0.72 783 793 | 785 4 105.6 -377.2 1.64 0.565 784 794 | 786 4 103.6 -375.6 2.04 0.565 785 795 | 787 4 101.6 -374.8 2.46 0.6 786 796 | 788 4 99.6 -374 2.46 0.6 787 797 | 789 4 97.6 -373.6 2.46 0.6 788 798 | 790 4 95.6 -373.2 2.87 0.6 789 799 | 791 4 93.6 -373.2 3.28 0.6 790 800 | 792 4 91.6 -373.6 3.69 0.6 791 801 | 793 4 89.6 -373.6 4.51 0.6 792 802 | 794 4 87.6 -373.6 5.74 0.6 793 803 | 795 4 85.6 -374.4 6.15 0.63 794 804 | 796 4 83.6 -375.6 6.56 0.63 795 805 | 797 4 81.59 -376.4 6.97 0.4 796 806 | 798 4 79.59 -376.8 7.38 0.4 797 807 | 799 4 77.59 -376.8 7.38 0.4 798 808 | 800 4 75.59 -376.4 7.38 0.4 799 809 | 801 4 73.59 -376 6.97 0.4 800 810 | 802 4 71.59 -375.2 6.56 0.4 801 811 | 803 4 69.59 -375.2 6.56 0.6 802 812 | 804 4 67.59 -375.2 6.15 0.6 803 813 | 805 4 65.59 -375.2 4.92 0.6 804 814 | 806 4 63.6 -374.8 4.51 0.6 805 815 | 807 4 61.6 -374 4.09 0.6 806 816 | 808 4 174.4 -376 -11.48 1.2 725 817 | 809 4 174.4 -374 -11.89 1.2 808 818 | 810 4 174.8 -372 -11.89 0.825 809 819 | 811 4 175.2 -370 -11.89 0.6 810 820 | 812 4 175.6 -368 -11.89 0.6 811 821 | 813 4 176 -366 -11.89 0.6 812 822 | 814 4 176.4 -364 -11.89 0.8 813 823 | 815 4 176.8 -362 -12.3 0.8 814 824 | 816 4 176.8 -360 -12.3 0.8 815 825 | 817 4 176.8 -358 -12.3 0.8 816 826 | 818 4 176.8 -356 -12.3 0.8 817 827 | 819 4 176.8 -354 -12.3 0.8 818 828 | 820 4 176.8 -352 -13.12 0.8 819 829 | 821 4 176.6 -350.4 -13.53 0.8 820 830 | 822 4 178.8 -340.4 -6.15 0.6 821 831 | 823 4 178.8 -338.4 -4.92 0.6 822 832 | 824 4 178.8 -336.4 -3.69 0.6 823 833 | 825 4 178.8 -334.4 -2.46 0.6 824 834 | 826 4 178.8 -332.4 -1.23 0.8 825 835 | 827 4 179.2 -330.4 0 0.8 826 836 | 828 4 179.6 -328.4 1.23 0.63 827 837 | 829 4 180.4 -326 2.46 0.63 828 838 | 830 4 180.8 -324 3.69 0.8 829 839 | 831 4 181.2 -322 4.92 0.8 830 840 | 832 4 181.6 -320.8 5.74 0.72 831 841 | 833 4 181.34 -318.8 5.74 0.72 832 842 | 834 4 182.4 -318.8 6.56 0.72 833 843 | 835 4 183.6 -316.8 7.38 0.72 834 844 | 836 4 184.8 -314.8 8.19 0.72 835 845 | 837 4 186 -312.8 8.61 0.72 836 846 | 838 4 186.8 -310.8 9.02 0.72 837 847 | 839 4 188 -308.8 9.43 0.72 838 848 | 840 4 190 -306.8 10.66 0.85 839 849 | 841 4 192 -304.8 11.89 0.85 840 850 | 842 4 194 -302.8 13.12 0.85 841 851 | 843 4 195.6 -301.6 15.17 0.85 842 852 | 844 4 197.2 -299.6 17.63 0.85 843 853 | 845 4 198.4 -297.6 18.86 0.445 844 854 | 846 4 198.8 -295.6 19.27 0.445 845 855 | 847 4 200 -293.6 20.09 0.565 846 856 | 848 4 202 -292 21.32 0.72 847 857 | 849 4 204 -290.8 22.96 0.72 848 858 | 850 4 206 -289.6 24.6 0.72 849 859 | 851 4 208 -288.39 26.24 0.72 850 860 | 852 4 210 -287.2 27.88 0.445 851 861 | 853 4 212 -286.39 28.7 0.4 852 862 | 854 4 212.98 -286.01 28.7 0.4 853 863 | 855 4 214 -285.6 29.52 0.4 854 864 | 856 4 216 -284.8 30.75 0.565 855 865 | 857 4 218 -283.6 32.39 0.565 856 866 | 858 4 220 -281.6 34.03 0.565 857 867 | 859 4 221.2 -279.6 35.67 0.565 858 868 | 860 4 223.2 -277.6 36.9 0.565 859 869 | 861 4 225.2 -276.39 37.72 0.565 860 870 | 862 4 227.2 -274.39 38.95 0.72 861 871 | 863 4 229.2 -273.2 39.77 0.72 862 872 | 864 4 231.2 -272 41.41 0.72 863 873 | 865 4 233.2 -270 42.23 0.72 864 874 | 866 4 234.4 -268 42.64 0.565 865 875 | 867 4 236.4 -266 43.87 0.565 866 876 | 868 4 238.4 -264 45.1 0.565 867 877 | 869 4 240.4 -262.8 45.51 0.565 868 878 | 870 4 242.4 -261.6 45.51 0.565 869 879 | 871 4 244.4 -260.8 45.92 0.565 870 880 | 872 4 246.4 -259.6 45.92 0.565 871 881 | 873 4 248.4 -257.6 46.74 0.565 872 882 | 874 4 250 -256 47.15 0.565 873 883 | 875 4 255.6 -254 49.2 0.4 874 884 | 876 4 257.6 -253.2 49.61 0.4 875 885 | 877 4 259.6 -252.8 49.61 0.4 876 886 | 878 4 261.6 -252.4 49.61 0.4 877 887 | 879 4 263.6 -252 49.61 0.4 878 888 | 880 4 265.6 -251.6 50.02 0.4 879 889 | 881 4 267.6 -251.2 50.02 0.4 880 890 | 882 4 269.6 -250.8 50.84 0.4 881 891 | 883 4 270.8 -250.8 51.25 0.4 882 892 | 884 4 272.8 -250.8 51.66 0.4 883 893 | 885 4 274.8 -250.8 52.07 0.4 884 894 | 886 4 276.8 -250.4 52.07 0.4 885 895 | 887 4 278.8 -250 51.66 0.4 886 896 | 888 4 280.8 -249.2 51.66 0.4 887 897 | 889 4 282.8 -248.8 51.66 0.4 888 898 | 890 4 284.8 -248.4 52.07 0.4 889 899 | 891 4 286.8 -248 52.07 0.6 890 900 | 892 4 288.8 -247.6 52.07 0.6 891 901 | 893 4 290.8 -247.6 52.07 0.6 892 902 | 894 4 292.8 -248 51.66 0.4 893 903 | 895 4 294.8 -248.4 51.25 0.4 894 904 | 896 4 296.8 -248.8 51.25 0.4 895 905 | 897 4 298.8 -249.2 51.66 0.4 896 906 | 898 4 300.8 -249.6 51.66 0.4 897 907 | 899 4 302.8 -250 51.66 0.4 898 908 | 900 4 304.8 -250 51.66 0.4 899 909 | 901 4 306.8 -250 51.66 0.4 900 910 | 902 4 308.8 -250 52.07 0.4 901 911 | 903 4 310.8 -250 52.48 0.4 902 912 | 904 4 312.8 -249.6 52.89 0.4 903 913 | 905 4 314.8 -249.2 53.3 0.4 904 914 | 906 4 316.8 -249.2 53.3 0.4 905 915 | 907 4 318.8 -248.8 54.12 0.4 906 916 | 908 4 320.8 -248.4 55.35 0.4 907 917 | 909 4 322.8 -248.4 56.58 0.4 908 918 | 910 4 324.8 -248 57.4 0.6 909 919 | 911 4 326.8 -247.2 59.04 0.6 910 920 | 912 4 328.8 -246.8 60.27 0.6 911 921 | 913 4 330.8 -246.4 61.09 0.6 912 922 | 914 4 332.8 -246 61.5 0.6 913 923 | 915 4 334.8 -245.6 61.5 0.6 914 924 | 916 4 336.8 -245.6 61.5 0.6 915 925 | 917 4 338.8 -245.6 61.5 0.6 916 926 | 918 4 340.8 -245.6 61.5 0.4 917 927 | 919 4 342.8 -245.2 61.5 0.4 918 928 | 920 4 344.8 -245.2 61.5 0.4 919 929 | 921 4 346.8 -244.8 61.5 0.4 920 930 | 922 4 348.8 -244.4 61.5 0.4 921 931 | 923 4 350.8 -244 61.91 0.4 922 932 | 924 4 352.8 -242.8 62.73 0.565 923 933 | 925 4 354.8 -241.6 63.55 0.565 924 934 | 926 4 213.2 -286.39 30.75 0.72 854 935 | 927 4 213.2 -286 32.79 0.72 926 936 | 928 4 213.2 -286 34.85 0.63 927 937 | 929 4 213.6 -285.2 36.9 0.4 928 938 | 930 4 214 -284 38.95 0.4 929 939 | 931 4 214 -283.2 41 0.4 930 940 | 932 4 214 -282 43.05 0.4 931 941 | 933 4 214 -280 45.1 0.4 932 942 | 934 4 214 -278 46.33 0.4 933 943 | 935 4 214 -276.8 47.56 0.4 934 944 | 936 4 214 -274.8 49.61 0.6 935 945 | 937 4 214 -272.8 51.66 0.6 936 946 | 938 4 214 -271.6 53.71 0.6 937 947 | 939 4 214.4 -271.2 55.76 0.6 938 948 | 940 4 214.4 -270.8 57.81 0.6 939 949 | 941 4 214.4 -270 59.86 0.6 940 950 | 942 4 214.8 -269.6 61.91 0.63 941 951 | 943 4 215.2 -269.2 63.96 0.63 942 952 | 944 4 224 -261.2 63.96 1.02 943 953 | 945 4 224 -260.8 66.01 1.02 944 954 | 946 4 224.4 -260.39 68.06 0.6 945 955 | 947 4 225.2 -260.39 70.11 0.6 946 956 | 948 4 226.23 -260.39 70.11 0.6 947 957 | 949 4 174 -309.39 14.76 0.63 833 958 | 950 4 172 -304 15.58 0.63 949 959 | 951 4 170.8 -302.39 16.8 0.72 950 960 | 952 4 169.6 -300.39 19.27 0.72 951 961 | 953 4 168 -299.2 21.73 0.565 952 962 | 954 4 167.2 -298.39 24.19 0.445 953 963 | 955 4 166 -296.39 26.24 0.445 954 964 | 956 4 164.8 -294 27.88 0.445 955 965 | 957 4 163.6 -292 29.52 0.445 956 966 | 958 4 162.8 -290 31.16 0.445 957 967 | 959 4 161.6 -287.6 32.79 0.565 958 968 | 960 4 160.4 -285.6 34.44 0.72 959 969 | 961 4 158 -283.6 35.67 0.72 960 970 | 962 4 157.19 -282.8 36.08 0.72 961 971 | 963 4 156 -280.8 36.9 0.72 962 972 | 964 4 154.8 -279.2 38.13 0.565 963 973 | 965 4 153.6 -277.2 38.54 0.565 964 974 | 966 4 151.6 -275.2 38.54 0.565 965 975 | 967 4 150.69 -273.7 38.54 0.565 966 976 | 968 4 150.4 -273.2 38.54 0.72 967 977 | 969 4 149.19 -271.2 38.54 0.72 968 978 | 970 4 148 -269.2 38.54 0.72 969 979 | 971 4 146 -267.2 38.95 0.72 970 980 | 972 4 144.8 -265.2 38.95 0.72 971 981 | 973 4 143.6 -263.2 38.95 0.72 972 982 | 974 4 142.4 -261.2 39.36 0.72 973 983 | 975 4 141.19 -259.2 40.59 0.72 974 984 | 976 4 140 -257.2 41 0.565 975 985 | 977 4 138 -255.2 41.41 0.565 976 986 | 978 4 136 -253.2 41.41 0.72 977 987 | 979 4 135.15 -252.4 41.41 0.72 978 988 | 980 4 134 -252 41 0.72 979 989 | 981 4 132 -251.2 40.18 0.72 980 990 | 982 4 130.4 -250.4 38.95 0.72 981 991 | 983 4 130.4 -249.6 38.13 0.565 982 992 | 984 4 128.4 -248.4 36.49 0.565 983 993 | 985 4 126.4 -247.6 34.85 0.565 984 994 | 986 4 124.4 -246.8 33.61 0.565 985 995 | 987 4 123.9 -246.68 33.61 0.565 986 996 | 988 4 122.8 -246.4 31.16 0.4 987 997 | 989 4 120.8 -246.4 29.93 0.4 988 998 | 990 4 119.6 -246.4 29.11 0.6 989 999 | 991 4 117.6 -246.4 27.88 0.6 990 1000 | 992 4 116 -246.8 26.65 0.6 991 1001 | 993 4 114 -247.2 25.42 0.4 992 1002 | 994 4 112 -247.2 24.6 0.4 993 1003 | 995 4 110 -247.6 24.19 0.4 994 1004 | 996 4 108 -248 23.37 0.4 995 1005 | 997 4 106 -248.4 22.55 0.4 996 1006 | 998 4 104 -248.8 21.73 0.4 997 1007 | 999 4 102 -248.8 20.91 0.4 998 1008 | 1000 4 100 -248.4 20.09 0.4 999 1009 | 1001 4 98 -247.6 19.68 0.4 1000 1010 | 1002 4 96.4 -247.2 19.27 0.63 1001 1011 | 1003 4 94.4 -246.4 18.86 0.63 1002 1012 | 1004 4 92.4 -245.2 18.86 0.4 1003 1013 | 1005 4 90.4 -244.4 18.04 0.4 1004 1014 | 1006 4 88.4 -243.6 18.04 0.4 1005 1015 | 1007 4 86.4 -243.2 18.45 0.4 1006 1016 | 1008 4 84.4 -243.2 18.45 0.4 1007 1017 | 1009 4 82.4 -243.2 18.45 0.4 1008 1018 | 1010 4 80.4 -243.6 18.45 0.6 1009 1019 | 1011 4 78.4 -243.6 18.45 0.6 1010 1020 | 1012 4 76.4 -244 18.45 0.6 1011 1021 | 1013 4 74.4 -244.8 18.45 0.4 1012 1022 | 1014 4 72.4 -245.6 18.86 0.4 1013 1023 | 1015 4 70.4 -246.4 18.86 0.4 1014 1024 | 1016 4 68.4 -247.2 18.86 0.6 1015 1025 | 1017 4 66.4 -247.6 18.45 0.6 1016 1026 | 1018 4 64.4 -248 18.04 0.6 1017 1027 | 1019 4 62.4 -248.4 17.63 0.6 1018 1028 | 1020 4 60.4 -248.4 17.63 0.6 1019 1029 | 1021 4 58.4 -248.4 17.63 0.6 1020 1030 | 1022 4 56.4 -248.4 17.22 0.6 1021 1031 | 1023 4 54.4 -248 16.39 0.6 1022 1032 | 1024 4 123.2 -244.4 32.79 0.85 987 1033 | 1025 4 121.2 -242.4 33.21 0.85 1024 1034 | 1026 4 119.2 -241.2 34.03 0.72 1025 1035 | 1027 4 117.2 -240 34.85 0.72 1026 1036 | 1028 4 114.8 -238 35.26 0.72 1027 1037 | 1029 4 113.6 -236 35.67 0.72 1028 1038 | 1030 4 112.8 -234 36.08 0.4 1029 1039 | 1031 4 112.4 -232 36.49 0.4 1030 1040 | 1032 4 112 -230 36.9 0.4 1031 1041 | 1033 4 112 -228 37.72 0.6 1032 1042 | 1034 4 112 -226 38.95 0.6 1033 1043 | 1035 4 111.6 -224 39.77 0.63 1034 1044 | 1036 4 110.8 -223.2 40.59 0.63 1035 1045 | 1037 4 110 -221.2 41 0.63 1036 1046 | 1038 4 108.8 -219.2 41.82 0.63 1037 1047 | 1039 4 108 -217.2 42.64 0.4 1038 1048 | 1040 4 107.6 -215.2 43.46 0.4 1039 1049 | 1041 4 107.2 -213.6 44.69 0.4 1040 1050 | 1042 4 135.25 -250.8 41.41 0.05 979 1051 | 1043 4 131.75 -247.5 41.41 0.05 1042 1052 | 1044 4 131.65 -245.7 41.41 0.05 1043 1053 | 1045 4 126.95 -241.7 41.41 0.05 1044 1054 | 1046 4 122.45 -238.7 41.41 0.05 1045 1055 | 1047 4 119.95 -235.7 41.41 0.05 1046 1056 | 1048 4 117.5 -233.8 41.41 0.1 1047 1057 | 1049 4 152.4 -269.2 47.97 0.4 967 1058 | 1050 4 151.6 -268.8 50.02 0.4 1049 1059 | 1051 4 150.8 -269.2 52.07 0.63 1050 1060 | 1052 4 150 -269.2 54.12 0.63 1051 1061 | 1053 4 149.6 -269.2 56.17 0.63 1052 1062 | 1054 4 149.19 -269.2 58.22 0.63 1053 1063 | 1055 4 149.19 -269.2 60.27 0.63 1054 1064 | 1056 4 148.4 -269.6 62.32 0.63 1055 1065 | 1057 4 148 -269.2 64.37 0.63 1056 1066 | 1058 4 147.19 -269.6 66.42 0.63 1057 1067 | 1059 4 145.6 -270.39 68.47 0.72 1058 1068 | 1060 4 144.8 -270.8 70.11 0.72 1059 1069 | 1061 4 143.6 -270.8 72.16 0.72 1060 1070 | 1062 4 176.8 -350 -13.53 0.8 821 1071 | 1063 4 177.6 -348 -14.35 0.8 1062 1072 | 1064 4 178 -346 -14.35 0.6 1063 1073 | 1065 4 178.6 -344.9 -14.35 0.6 1064 1074 | 1066 4 178.5 -344 -14.76 0.6 1065 1075 | 1067 4 180.6 -343.2 -14.76 0.895 1066 1076 | 1068 4 181.8 -342.6 -15.17 0.895 1067 1077 | 1069 4 181.6 -343.2 -15.58 0.6 1068 1078 | 1070 4 183.6 -343.6 -15.58 0.6 1069 1079 | 1071 4 185.6 -344 -15.17 0.6 1070 1080 | 1072 4 186.8 -344 -15.17 0.6 1071 1081 | 1073 4 188.8 -344 -15.17 0.6 1072 1082 | 1074 4 190.8 -344 -15.17 0.4 1073 1083 | 1075 4 192.8 -344.4 -15.17 0.4 1074 1084 | 1076 4 194.8 -344.8 -15.17 0.4 1075 1085 | 1077 4 196.8 -345.6 -15.17 0.4 1076 1086 | 1078 4 198.8 -346 -15.17 0.4 1077 1087 | 1079 4 200.8 -346 -15.17 0.4 1078 1088 | 1080 4 202.8 -346 -15.58 0.4 1079 1089 | 1081 4 204.8 -346 -15.99 0.6 1080 1090 | 1082 4 206.8 -345.2 -15.99 0.63 1081 1091 | 1083 4 208.8 -344.4 -16.8 0.63 1082 1092 | 1084 4 210.8 -343.2 -17.63 0.72 1083 1093 | 1085 4 212.8 -342 -17.63 0.72 1084 1094 | 1086 4 214.8 -340.4 -17.63 0.63 1085 1095 | 1087 4 216.8 -339.6 -18.04 0.6 1086 1096 | 1088 4 218.8 -339.2 -18.45 0.6 1087 1097 | 1089 4 220.8 -338.8 -18.45 0.6 1088 1098 | 1090 4 222.8 -338.4 -18.04 0.6 1089 1099 | 1091 4 224.8 -338.4 -18.04 0.6 1090 1100 | 1092 4 226.8 -337.6 -17.63 0.72 1091 1101 | 1093 4 228.4 -336.4 -17.22 0.72 1092 1102 | 1094 4 237.2 -332 -15.58 0.6 1093 1103 | 1095 4 238.4 -331.2 -15.17 0.6 1094 1104 | 1096 4 240.4 -331.6 -14.76 0.6 1095 1105 | 1097 4 242.4 -332 -14.35 0.63 1096 1106 | 1098 4 244.4 -331.6 -13.53 0.63 1097 1107 | 1099 4 246.4 -331.2 -13.12 0.445 1098 1108 | 1100 4 248.4 -330.4 -12.71 0.4 1099 1109 | 1101 4 250.4 -330 -12.71 0.4 1100 1110 | 1102 4 252.4 -329.2 -13.12 0.63 1101 1111 | 1103 4 254.8 -328 -13.12 0.63 1102 1112 | 1104 4 256.8 -327.2 -13.53 0.63 1103 1113 | 1105 4 258.8 -326.39 -13.53 0.6 1104 1114 | 1106 4 260.8 -326 -13.12 0.4 1105 1115 | 1107 4 262.8 -325.6 -13.53 0.4 1106 1116 | 1108 4 264.8 -324.8 -14.35 0.63 1107 1117 | 1109 4 266.8 -324 -14.35 0.72 1108 1118 | 1110 4 268.8 -322.8 -14.35 0.72 1109 1119 | 1111 4 270.8 -321.6 -14.35 0.72 1110 1120 | 1112 4 272.8 -320.8 -14.76 0.72 1111 1121 | 1113 4 274.8 -319.6 -14.76 0.72 1112 1122 | 1114 4 276.8 -317.6 -14.35 0.72 1113 1123 | 1115 4 178.8 -342 -14.76 0.63 1066 1124 | 1116 4 179.03 -341.42 -14.76 0.63 1115 1125 | 1117 4 182.8 -338 -14.76 0.565 1116 1126 | 1118 4 184.8 -336 -14.35 0.565 1117 1127 | 1119 4 186.8 -334 -14.35 0.565 1118 1128 | 1120 4 188.8 -332 -14.35 0.72 1119 1129 | 1121 4 189.6 -330.8 -13.94 0.72 1120 1130 | 1122 4 191.6 -329.6 -13.53 0.72 1121 1131 | 1123 4 193.6 -328.4 -13.12 0.565 1122 1132 | 1124 4 195.6 -327.2 -12.3 0.565 1123 1133 | 1125 4 197.6 -326 -11.48 0.565 1124 1134 | 1126 4 199.6 -324 -11.07 0.565 1125 1135 | 1127 4 201.6 -322 -9.84 0.63 1126 1136 | 1128 4 203.6 -320.8 -9.02 0.63 1127 1137 | 1129 4 206 -320 -9.02 0.63 1128 1138 | 1130 4 208 -319.2 -8.19 0.565 1129 1139 | 1131 4 210 -318.39 -6.97 0.565 1130 1140 | 1132 4 212 -317.6 -6.56 0.565 1131 1141 | 1133 4 214 -316.8 -6.15 0.565 1132 1142 | 1134 4 216 -315.6 -5.33 0.565 1133 1143 | 1135 4 218 -314.39 -4.92 0.565 1134 1144 | 1136 4 220 -312.39 -4.92 0.565 1135 1145 | 1137 4 222 -310.39 -4.92 0.565 1136 1146 | 1138 4 224 -308.39 -4.92 0.565 1137 1147 | 1139 4 226 -306.39 -4.92 0.565 1138 1148 | 1140 4 228 -304.39 -4.92 0.565 1139 1149 | 1141 4 230 -302.39 -5.33 0.565 1140 1150 | 1142 4 231.2 -300.39 -5.74 0.72 1141 1151 | 1143 4 232.8 -298.8 -5.74 0.72 1142 1152 | 1144 4 234.8 -296.8 -5.74 0.72 1143 1153 | 1145 4 236.8 -294.8 -5.33 0.72 1144 1154 | 1146 4 238.8 -293.6 -4.09 0.72 1145 1155 | 1147 4 240.8 -291.6 -3.69 0.72 1146 1156 | 1148 4 242 -289.6 -4.09 0.72 1147 1157 | 1149 4 243.2 -287.6 -3.69 0.72 1148 1158 | 1150 4 244.4 -285.6 -3.69 0.72 1149 1159 | 1151 4 244.8 -285.6 -3.69 0.72 1150 1160 | 1152 4 246.8 -284 -2.04 0.72 1151 1161 | 1153 4 248.8 -282.8 -1.23 0.72 1152 1162 | 1154 4 250.8 -281.6 -0.41 0.72 1153 1163 | 1155 4 252.8 -280.39 0.41 0.72 1154 1164 | 1156 4 254 -279.6 0.82 0.72 1155 1165 | 1157 4 256 -278.8 1.23 0.72 1156 1166 | 1158 4 258 -277.6 1.23 0.4 1157 1167 | 1159 4 260 -276.8 1.23 0.4 1158 1168 | 1160 4 262 -276 1.64 0.4 1159 1169 | 1161 4 264 -275.2 2.04 0.4 1160 1170 | 1162 4 266 -274.8 2.04 0.6 1161 1171 | 1163 4 268 -274.8 2.04 0.6 1162 1172 | 1164 4 277.1 -262.54 2.04 0.6 1163 1173 | 1165 4 179.6 -340 -14.76 0.63 1116 1174 | 1166 4 180 -338 -15.17 0.6 1165 1175 | 1167 4 180 -336 -15.58 0.6 1166 1176 | 1168 4 180.4 -334 -16.8 0.6 1167 1177 | 1169 4 180.8 -332 -17.22 0.6 1168 1178 | 1170 4 181.2 -330 -18.04 0.6 1169 1179 | 1171 4 181.6 -328 -18.86 0.63 1170 1180 | 1172 4 182 -326 -20.09 0.63 1171 1181 | 1173 4 182 -324 -20.91 0.6 1172 1182 | 1174 4 182 -322 -21.32 0.6 1173 1183 | 1175 4 182 -320 -21.73 0.8 1174 1184 | 1176 4 182 -318 -22.55 0.8 1175 1185 | 1177 4 182.8 -316 -23.37 0.6 1176 1186 | 1178 4 182.8 -314 -24.6 0.6 1177 1187 | 1179 4 182.8 -312 -25.42 0.6 1178 1188 | 1180 4 183.2 -311.01 -25.42 0.6 1179 1189 | 1181 4 183.6 -310 -25.42 0.6 1180 1190 | 1182 4 184 -308 -26.24 0.6 1181 1191 | 1183 4 184 -306 -27.06 0.6 1182 1192 | 1184 4 184.4 -304 -27.47 0.6 1183 1193 | 1185 4 184.8 -302 -28.29 0.63 1184 1194 | 1186 4 185.6 -300 -28.7 0.63 1185 1195 | 1187 4 186.4 -298 -29.11 0.63 1186 1196 | 1188 4 187.2 -296 -29.52 0.63 1187 1197 | 1189 4 187.6 -294 -29.93 0.6 1188 1198 | 1190 4 187.6 -292 -29.93 0.6 1189 1199 | 1191 4 188 -290 -30.34 0.6 1190 1200 | 1192 4 188.4 -288 -30.75 0.6 1191 1201 | 1193 4 188.8 -286 -31.16 0.6 1192 1202 | 1194 4 189.2 -284 -31.57 0.6 1193 1203 | 1195 4 189.2 -283.98 -31.98 0.6 1194 1204 | 1196 4 190.8 -281.2 -31.57 0.63 1195 1205 | 1197 4 192 -279.2 -31.98 0.63 1196 1206 | 1198 4 194 -277.2 -31.98 0.63 1197 1207 | 1199 4 195.2 -275.2 -31.98 0.72 1198 1208 | 1200 4 196.4 -273.2 -31.98 0.72 1199 1209 | 1201 4 198.4 -271.2 -32.39 0.72 1200 1210 | 1202 4 199.6 -269.2 -32.79 0.72 1201 1211 | 1203 4 201.65 -267.3 -32.79 0.72 1202 1212 | 1204 4 201.6 -267.2 -33.21 0.72 1203 1213 | 1205 4 202.8 -265.2 -33.61 0.72 1204 1214 | 1206 4 204.8 -263.2 -33.61 0.72 1205 1215 | 1207 4 206.8 -262 -34.03 0.72 1206 1216 | 1208 4 208.8 -260 -34.44 0.565 1207 1217 | 1209 4 210.8 -258 -35.26 0.565 1208 1218 | 1210 4 212 -256.8 -36.08 0.565 1209 1219 | 1211 4 214 -255.6 -36.49 0.565 1210 1220 | 1212 4 216 -253.6 -36.9 0.565 1211 1221 | 1213 4 218 -251.6 -38.13 0.565 1212 1222 | 1214 4 220 -249.6 -38.54 0.895 1213 1223 | 1215 4 221.6 -248 -38.54 0.895 1214 1224 | 1216 4 223.2 -246 -39.77 0.72 1215 1225 | 1217 4 224.4 -244 -41 0.72 1216 1226 | 1218 4 225.6 -242 -41.41 0.565 1217 1227 | 1219 4 226.8 -240 -41.82 0.565 1218 1228 | 1220 4 228 -238 -42.23 0.6 1219 1229 | 1221 4 228.11 -237.72 -42.23 0.6 1220 1230 | 1222 4 228.8 -236 -42.23 0.6 1221 1231 | 1223 4 229.2 -234 -41.82 0.6 1222 1232 | 1224 4 229.6 -232 -41.82 0.6 1223 1233 | 1225 4 230.4 -230 -41.41 0.6 1224 1234 | 1226 4 231.6 -228 -41 0.6 1225 1235 | 1227 4 232.8 -226 -40.18 0.6 1226 1236 | 1228 4 233.6 -224 -39.77 0.6 1227 1237 | 1229 4 234.8 -222 -38.95 0.6 1228 1238 | 1230 4 235.6 -220 -38.13 0.6 1229 1239 | 1231 4 236 -218 -37.72 0.4 1230 1240 | 1232 4 236.4 -216 -37.31 0.4 1231 1241 | 1233 4 237.2 -214 -36.49 0.4 1232 1242 | 1234 4 237.39 -213.04 -36.49 0.4 1233 1243 | 1235 4 237.6 -212 -35.26 0.4 1234 1244 | 1236 4 238.4 -210 -34.44 0.565 1235 1245 | 1237 4 239.6 -208 -32.79 0.565 1236 1246 | 1238 4 240.8 -206 -31.16 0.565 1237 1247 | 1239 4 242.4 -204.4 -29.11 0.565 1238 1248 | 1240 4 244.8 -203.2 -27.88 0.565 1239 1249 | 1241 4 245.2 -203.2 -26.24 0.72 1240 1250 | 1242 4 246.4 -201.2 -25.01 0.72 1241 1251 | 1243 4 247.6 -199.2 -22.96 0.6 1242 1252 | 1244 4 248 -198 -20.91 0.6 1243 1253 | 1245 4 248.8 -196 -18.86 0.63 1244 1254 | 1246 4 249.6 -194.4 -17.22 0.63 1245 1255 | 1247 4 251.2 -192.8 -15.17 0.565 1246 1256 | 1248 4 251.66 -192.34 -15.17 0.565 1247 1257 | 1249 4 252.8 -191.2 -15.17 0.565 1248 1258 | 1250 4 253.6 -190.4 -13.94 0.565 1249 1259 | 1251 4 254.8 -188.8 -11.89 0.565 1250 1260 | 1252 4 257.2 -185 -9.84 0.565 1251 1261 | 1253 4 264.39 -185.4 -7.79 0.72 1252 1262 | 1254 4 266.39 -189.2 -5.74 0.72 1253 1263 | 1255 4 275.39 -191.4 -3.69 0.72 1254 1264 | 1256 4 238.8 -208 -34.85 0.4 1234 1265 | 1257 4 239.2 -206 -34.44 0.4 1256 1266 | 1258 4 238.8 -204 -34.03 0.4 1257 1267 | 1259 4 238.8 -202 -33.61 0.4 1258 1268 | 1260 4 239.2 -200 -33.21 0.4 1259 1269 | 1261 4 239.2 -198 -32.79 0.4 1260 1270 | 1262 4 239.2 -196 -31.98 0.4 1261 1271 | 1263 4 239.2 -194 -31.57 0.4 1262 1272 | 1264 4 239.2 -192 -31.16 0.4 1263 1273 | 1265 4 238.8 -190 -30.75 0.4 1264 1274 | 1266 4 238.4 -188 -29.93 0.4 1265 1275 | 1267 4 238.4 -186 -29.11 0.4 1266 1276 | 1268 4 238 -184 -28.7 0.445 1267 1277 | 1269 4 237.2 -182 -28.29 0.445 1268 1278 | 1270 4 236.4 -180 -27.06 0.445 1269 1279 | 1271 4 235.2 -178 -25.42 0.445 1270 1280 | 1272 4 234.8 -176.8 -25.01 0.565 1271 1281 | 1273 4 233.6 -174.8 -24.19 0.63 1272 1282 | 1274 4 232.4 -172.8 -23.37 0.63 1273 1283 | 1275 4 232 -170.4 -22.55 0.63 1274 1284 | 1276 4 230.4 -236.4 -43.46 0.565 1221 1285 | 1277 4 232 -234.8 -45.1 0.565 1276 1286 | 1278 4 232.8 -233.6 -45.92 0.565 1277 1287 | 1279 4 234 -231.6 -47.56 0.63 1278 1288 | 1280 4 235.2 -230 -49.2 0.63 1279 1289 | 1281 4 236 -228 -50.02 0.6 1280 1290 | 1282 4 236.48 -226.81 -50.02 0.6 1281 1291 | 1283 4 236.8 -226 -50.84 0.6 1282 1292 | 1284 4 237.6 -224 -51.66 0.72 1283 1293 | 1285 4 239.2 -222 -53.3 0.72 1284 1294 | 1286 4 240.4 -220 -54.94 0.72 1285 1295 | 1287 4 242 -218 -55.76 0.72 1286 1296 | 1288 4 244.4 -216 -57.81 0.72 1287 1297 | 1289 4 245.6 -214 -58.63 0.72 1288 1298 | 1290 4 246.8 -212 -59.04 0.565 1289 1299 | 1291 4 248 -210 -59.45 0.565 1290 1300 | 1292 4 249.6 -208.4 -60.68 0.565 1291 1301 | 1293 4 238.8 -226.8 -50.02 1.02 1282 1302 | 1294 4 240.8 -226.8 -49.61 1.02 1293 1303 | 1295 4 242 -226.8 -49.61 1.02 1294 1304 | 1296 4 244 -226.4 -49.61 0.6 1295 1305 | 1297 4 246 -226 -50.02 0.6 1296 1306 | 1298 4 248 -226 -50.84 0.6 1297 1307 | 1299 4 250 -226.4 -51.25 0.6 1298 1308 | 1300 4 252 -226 -51.25 0.6 1299 1309 | 1301 4 254 -226.4 -51.25 0.6 1300 1310 | 1302 4 256 -226.8 -51.66 0.6 1301 1311 | 1303 4 258 -227.2 -52.07 0.6 1302 1312 | 1304 4 260 -227.2 -52.89 0.6 1303 1313 | 1305 4 262 -227.6 -53.71 0.6 1304 1314 | 1306 4 206 -262 -32.79 0.72 1203 1315 | 1307 4 208 -260 -30.75 0.72 1306 1316 | 1308 4 208.4 -258.8 -29.93 0.72 1307 1317 | 1309 4 209.6 -256.8 -29.11 0.565 1308 1318 | 1310 4 211.2 -254.8 -28.29 0.445 1309 1319 | 1311 4 212 -252.8 -27.06 0.4 1310 1320 | 1312 4 212.8 -250.8 -26.24 0.4 1311 1321 | 1313 4 213.6 -248.8 -25.42 0.4 1312 1322 | 1314 4 214.4 -246.8 -24.6 0.6 1313 1323 | 1315 4 214.8 -244.8 -24.19 0.6 1314 1324 | 1316 4 214.9 -243.2 -23.78 0.6 1315 1325 | 1317 4 217.2 -243 -23.78 0.6 1316 1326 | 1318 4 222.8 -237.2 -29.52 0.6 1317 1327 | 1319 4 224.6 -234.4 -29.52 0.565 1318 1328 | 1320 4 224.6 -228.8 -28.7 0.565 1319 1329 | 1321 4 228.8 -223.6 -27.47 0.565 1320 1330 | 1322 4 230.4 -222.4 -26.65 0.565 1321 1331 | 1323 4 232.4 -221.2 -25.83 0.72 1322 1332 | 1324 4 234.4 -219.6 -24.6 0.72 1323 1333 | 1325 4 236 -217.6 -22.55 0.565 1324 1334 | 1326 4 237.6 -216 -20.5 0.565 1325 1335 | 1327 4 238.8 -214.4 -18.45 0.565 1326 1336 | 1328 4 239.6 -213.6 -16.39 0.565 1327 1337 | 1329 4 241.2 -212.4 -14.35 0.565 1328 1338 | 1330 4 242.4 -212 -12.3 0.4 1329 1339 | 1331 4 244.4 -211.2 -10.25 0.4 1330 1340 | 1332 4 246.4 -210.4 -8.19 0.445 1331 1341 | 1333 4 248.4 -208.8 -6.56 0.565 1332 1342 | 1334 4 250.4 -207.6 -5.74 0.565 1333 1343 | 1335 4 252.4 -206.4 -4.92 0.565 1334 1344 | 1336 4 254.4 -205.2 -4.51 0.565 1335 1345 | 1337 4 256.39 -204.4 -3.69 0.445 1336 1346 | 1338 4 258 -203.6 -2.87 0.445 1337 1347 | 1339 4 259.2 -203.6 -2.04 0.4 1338 1348 | 1340 4 261.2 -203.6 -1.64 0.4 1339 1349 | 1341 4 263.2 -203.2 -0.41 0.4 1340 1350 | 1342 4 265.2 -202.8 0.41 0.4 1341 1351 | 1343 4 267.2 -202.4 0.41 0.4 1342 1352 | 1344 4 269.2 -202 0.41 0.4 1343 1353 | 1345 4 271.2 -201.2 0.41 0.4 1344 1354 | 1346 4 273.2 -200.8 0.41 0.4 1345 1355 | 1347 4 275.2 -200.4 0.41 0.4 1346 1356 | 1348 4 277.2 -200.4 1.23 0.6 1347 1357 | 1349 4 279.2 -200.4 2.04 0.6 1348 1358 | 1350 4 281.2 -200.8 3.28 0.6 1349 1359 | 1351 4 283.2 -201.6 3.69 0.4 1350 1360 | 1352 4 285.2 -202 4.09 0.4 1351 1361 | 1353 4 287.2 -202.4 4.51 0.4 1352 1362 | 1354 4 289.2 -203.2 4.92 0.4 1353 1363 | 1355 4 291.2 -204 5.33 0.6 1354 1364 | 1356 4 293.2 -204.4 6.15 0.6 1355 1365 | 1357 4 295.2 -204.8 6.97 0.6 1356 1366 | 1358 4 297.2 -205.2 8.19 0.6 1357 1367 | 1359 4 299.2 -205.6 9.43 0.4 1358 1368 | 1360 4 301.2 -205.6 10.66 0.4 1359 1369 | 1361 4 303.2 -205.2 11.89 0.6 1360 1370 | 1362 4 305.2 -205.2 13.12 0.6 1361 1371 | 1363 4 307.2 -205.6 14.76 0.6 1362 1372 | 1364 4 215.2 -242.8 -23.78 0.6 1316 1373 | 1365 4 215.2 -240.8 -22.96 0.4 1364 1374 | 1366 4 215.6 -238.8 -22.96 0.4 1365 1375 | 1367 4 215.6 -236.8 -22.96 0.4 1366 1376 | 1368 4 216 -234.8 -22.96 0.4 1367 1377 | 1369 4 216.8 -232.8 -22.96 0.4 1368 1378 | 1370 4 217.2 -230.8 -22.96 0.4 1369 1379 | 1371 4 217.6 -228.8 -22.96 0.4 1370 1380 | 1372 4 218 -226.8 -22.55 0.4 1371 1381 | 1373 4 218.4 -224.8 -22.14 0.4 1372 1382 | 1374 4 218.4 -222.8 -21.32 0.4 1373 1383 | 1375 4 218 -220.8 -20.91 0.4 1374 1384 | 1376 4 218 -218.8 -20.09 0.4 1375 1385 | 1377 4 218 -216.8 -18.86 0.6 1376 1386 | 1378 4 218 -214.8 -18.04 0.6 1377 1387 | 1379 4 218 -212.8 -17.63 0.6 1378 1388 | 1380 4 218 -210.8 -17.22 0.6 1379 1389 | 1381 4 218 -208.8 -16.8 0.4 1380 1390 | 1382 4 217.6 -206.8 -16.39 0.4 1381 1391 | 1383 4 217.6 -204.8 -16.39 0.4 1382 1392 | 1384 4 217.6 -202.8 -15.58 0.6 1383 1393 | 1385 4 217.6 -198.2 -14.35 0.6 1384 1394 | 1386 4 217.3 -198 -13.12 0.6 1385 1395 | 1387 4 221.3 -194.4 -13.12 0.4 1386 1396 | 1388 4 224.3 -190.2 -13.12 0.4 1387 1397 | 1389 4 223.7 -187.4 -13.12 0.4 1388 1398 | 1390 4 225.9 -186.4 -13.12 0.4 1389 1399 | 1391 4 226.3 -184 -13.12 0.4 1390 1400 | 1392 4 227.9 -185.4 -13.12 0.4 1391 1401 | 1393 4 229.1 -184.4 -13.12 0.4 1392 1402 | 1394 4 231.7 -181 -13.12 0.4 1393 1403 | 1395 4 232.9 -182.8 -13.12 0.4 1394 1404 | 1396 4 232.7 -179.4 -13.12 0.4 1395 1405 | 1397 4 231.9 -177.6 -13.12 0.4 1396 1406 | 1398 4 215.6 -188.4 -13.12 0.6 1386 1407 | 1399 4 212.8 -184.8 -11.89 0.445 1398 1408 | 1400 4 204.8 -182.8 -10.25 0.445 1399 1409 | 1401 4 189.2 -282 -31.98 0.6 1195 1410 | 1402 4 188.8 -280 -32.79 0.63 1401 1411 | 1403 4 187.6 -278 -32.79 0.63 1402 1412 | 1404 4 187.2 -276 -34.03 0.6 1403 1413 | 1405 4 186.8 -274 -35.26 0.6 1404 1414 | 1406 4 186.8 -272 -36.49 0.6 1405 1415 | 1407 4 186.8 -270.8 -37.31 0.4 1406 1416 | 1408 4 186.8 -268.8 -38.13 0.4 1407 1417 | 1409 4 186.8 -266.8 -39.36 0.4 1408 1418 | 1410 4 186.8 -264.8 -40.59 0.4 1409 1419 | 1411 4 186.4 -262.8 -41.82 0.4 1410 1420 | 1412 4 185.6 -260.8 -42.64 0.4 1411 1421 | 1413 4 185.2 -258.8 -43.46 0.4 1412 1422 | 1414 4 184.4 -256.8 -44.28 0.4 1413 1423 | 1415 4 184 -254.8 -45.51 0.4 1414 1424 | 1416 4 183.2 -252.8 -46.33 0.4 1415 1425 | 1417 4 182.8 -250.8 -47.56 0.4 1416 1426 | 1418 4 182.4 -248.8 -48.38 0.4 1417 1427 | 1419 4 182.4 -246.8 -49.2 0.4 1418 1428 | 1420 4 182.4 -244.8 -50.43 0.4 1419 1429 | 1421 4 181.6 -239 -51.25 0.4 1420 1430 | 1422 4 178.2 -234.2 -52.48 0.4 1421 1431 | 1423 4 179.2 -233 -52.89 0.4 1422 1432 | 1424 4 176.8 -228.2 -53.71 0.4 1423 1433 | 1425 3 166.8 -404.2 -17.63 0.565 1 1434 | 1426 3 166.4 -406.4 -19.27 0.4 1425 1435 | 1427 3 166.4 -408 -18.04 0.4 1426 1436 | 1428 3 165.6 -410 -17.63 0.4 1427 1437 | 1429 3 164.8 -412 -17.22 0.4 1428 1438 | 1430 3 163.6 -414 -16.8 0.445 1429 1439 | 1431 3 162.8 -416 -16.39 0.63 1430 1440 | 1432 3 162 -418 -15.99 0.63 1431 1441 | 1433 3 160.8 -420 -15.17 0.63 1432 1442 | 1434 3 160 -422 -13.53 0.445 1433 1443 | 1435 3 159.19 -424 -11.48 0.445 1434 1444 | 1436 3 158.4 -426.4 -10.25 0.445 1435 1445 | 1437 3 157.19 -428.4 -8.61 0.85 1436 1446 | 1438 3 155.6 -430.8 -7.79 0.85 1437 1447 | 1439 3 153.6 -432 -6.15 0.72 1438 1448 | 1440 3 152.8 -432.8 -4.92 0.565 1439 1449 | 1441 3 151.19 -434.4 -2.87 0.565 1440 1450 | 1442 3 149.6 -435.6 -0.82 0.565 1441 1451 | 1443 3 148 -437.2 1.23 0.565 1442 1452 | 1444 3 146 -438.8 2.46 0.565 1443 1453 | 1445 3 144 -440.8 3.69 0.565 1444 1454 | 1446 3 142 -442.8 4.09 0.565 1445 1455 | 1447 3 140 -444.8 4.51 0.565 1446 1456 | 1448 3 138 -446.8 5.74 0.565 1447 1457 | 1449 3 136.4 -448.4 6.56 0.72 1448 1458 | 1450 3 135.19 -450.4 8.19 0.72 1449 1459 | 1451 3 134 -452.4 9.84 0.72 1450 1460 | 1452 3 132.4 -454 11.48 0.72 1451 1461 | 1453 3 130.4 -456 12.71 0.72 1452 1462 | 1454 3 128.8 -457.6 13.53 0.72 1453 1463 | 1455 3 126.9 -459.8 13.53 0.72 1454 1464 | 1456 3 127.2 -460 14.76 0.72 1455 1465 | 1457 3 128 -463.6 14.76 0.4 1456 1466 | 1458 3 126.8 -465.6 15.17 0.4 1457 1467 | 1459 3 125.6 -467.6 15.17 0.565 1458 1468 | 1460 3 124.8 -469.6 15.58 0.565 1459 1469 | 1461 3 124.4 -471.6 16.39 0.6 1460 1470 | 1462 3 124 -473.6 16.8 0.6 1461 1471 | 1463 3 124 -475.6 17.63 0.6 1462 1472 | 1464 3 124 -477.6 18.04 0.6 1463 1473 | 1465 3 123.6 -479.6 18.86 0.6 1464 1474 | 1466 3 123.6 -481.6 20.09 0.6 1465 1475 | 1467 3 123.6 -483.6 20.91 0.4 1466 1476 | 1468 3 123.6 -485.6 21.73 0.4 1467 1477 | 1469 3 123.2 -486.8 22.14 0.4 1468 1478 | 1470 3 122.8 -488.8 23.37 0.6 1469 1479 | 1471 3 122.4 -490.8 24.6 0.6 1470 1480 | 1472 3 122 -492.8 25.42 0.63 1471 1481 | 1473 3 121.2 -494.8 26.24 0.63 1472 1482 | 1474 3 120.4 -496.8 26.65 0.6 1473 1483 | 1475 3 120 -498.8 26.65 0.4 1474 1484 | 1476 3 119.6 -500.8 26.65 0.4 1475 1485 | 1477 3 119.2 -502.8 27.06 0.4 1476 1486 | 1478 3 118.4 -504.8 27.88 0.4 1477 1487 | 1479 3 117.6 -506.8 28.7 0.565 1478 1488 | 1480 3 116.4 -508.8 29.11 0.565 1479 1489 | 1481 3 126.9 -464 13.53 0.1 1455 1490 | 1482 3 126.7 -469.2 13.53 0.1 1481 1491 | 1483 3 121.1 -473.2 13.53 0.1 1482 1492 | 1484 3 117.1 -478.8 13.53 0.1 1483 1493 | 1485 3 112.9 -481.4 13.53 0.1 1484 1494 | 1486 3 106.5 -481.6 13.53 0.1 1485 1495 | 1487 3 101.5 -481 13.53 0.1 1486 1496 | 1488 3 96.9 -481.4 13.53 0.1 1487 1497 | 1489 3 96.7 -486.2 13.53 0.1 1488 1498 | 1490 3 92.7 -488.4 13.53 0.1 1489 1499 | 1491 3 88.5 -489.8 13.53 0.1 1490 1500 | 1492 3 170 -401.6 -14.76 0.72 1 1501 | 1493 3 168.2 -408.4 -14.76 0.72 1492 1502 | 1494 3 168 -410.4 -14.76 0.895 1493 1503 | 1495 3 168.4 -412 -16.8 0.895 1494 1504 | 1496 3 168.8 -412.6 -18.86 0.85 1495 1505 | 1497 3 168.7 -413 -18.86 0.85 1496 1506 | 1498 3 169.2 -413.2 -18.86 0.85 1497 1507 | 1499 3 171.2 -414.8 -20.5 0.85 1498 1508 | 1500 3 172.8 -416 -22.55 0.565 1499 1509 | 1501 3 174.8 -416.8 -24.6 0.445 1500 1510 | 1502 3 175.6 -418 -25.83 0.445 1501 1511 | 1503 3 177.6 -419.6 -27.47 0.565 1502 1512 | 1504 3 179.6 -420.8 -29.11 0.565 1503 1513 | 1505 3 181.6 -422.8 -31.16 0.565 1504 1514 | 1506 3 183.6 -424 -32.79 0.565 1505 1515 | 1507 3 185.6 -426 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PDF](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/Part1_Introduction.pdf) 6 | 7 | 8 | 9 | ## 1.1 Experimental datasets 10 | 11 | [All slides in this section as single PDF](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/Part1_1_Experimental_datasets.pdf) 12 | 13 | #### Allen Cell Types Database 14 | 15 | A multimodal database of single cell characterization to enable data-driven approaches 16 | to classification. Key features include: whole cell patch clamping, raw images and 17 | morphological reconstructions, a variety of abstract point models as well as 18 | biophysically detailed compartmental models, and single cell RNA sequencing data. 19 | 20 | [Website](http://celltypes.brain-map.org/) 21 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/1_Experimental_datasets/1_CellTypesDatabase.pptx) 22 | 23 | 24 | #### Allen Brain Observatory 25 | 26 | The Allen Brain Observatory is an in vivo survey of physiological activity in the 27 | mouse visual cortex, featuring representations of visually evoked calcium responses 28 | from GCaMP6-expressing neurons in selected cortical layers, visual areas and Cre lines. 29 | 30 | [Website](http://observatory.brain-map.org/visualcoding) 31 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/1_Experimental_datasets/2_AllenBrainObservatory.pptx) 32 | 33 | 34 | #### CRCNS 35 | 36 | A public repository hosting freely available neurophysiology and behavioural data 37 | useful for computational neuroscience. Includes data from a variety of species 38 | and brain regions and species. 39 | 40 | [Website](http://crcns.org/) 41 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/1_Experimental_datasets/3_crcns_org.pptx) 42 | 43 | 47 | 48 | #### NeuroMorpho.Org 49 | 50 | NeuroMorpho.Org is a centrally curated inventory of digitally reconstructed neurons 51 | associated with peer-reviewed publications. It contains contributions from over 200 52 | laboratories worldwide and is continuously updated as new morphological reconstructions 53 | are collected, published, and shared. To date, NeuroMorpho.Org is the largest collection 54 | of publicly accessible 3D neuronal reconstructions and associated metadata. 55 | 56 | [Website](http://neuromorpho.org/) 57 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/1_Experimental_datasets/5_NeuroMorpho.org.pptx) 58 | 59 | ## 1.2 Structured data from literature 60 | 61 | [All slides in this section as single PDF](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/Part1_2_Structured_data_from_literature.pdf) 62 | 63 | 64 | #### Neuroelectro 65 | 66 | The goal of the NeuroElectro Project is to extract information about the intrinsic 67 | electrophysiological properties of diverse neuron types from the neuroscience 68 | literature and place it into a centralized database for widespread comparison, 69 | reuse, and reanalysis. 70 | 71 | [Website](http://neuroelectro.org) 72 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/2_Structured_data_from_literature/1_NeuroElectro.pptx) 73 | 74 | #### Hippocampome.org 75 | 76 | Hippocampome.org is a resource that combines approximately 21,000 pieces of experimental 77 | evidence about neuron types in the rodent hippocampus into a unified database. 78 | Analyzing these data has revealed about 10,500 different neuron properties and has 79 | identified over one hundred different neuron types. 80 | 81 | [Website](http://hippocampome.org) 82 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/2_Structured_data_from_literature/2_Hippocampome.pptx) 83 | 84 | #### Bezaire et al. CA1 data/model 85 | 86 | An interactive anatomical database, graphical representation and full scale model 87 | of hippocampal area CA1 88 | 89 | [Website](http://www.mariannebezaire.com/ca1_graphic) 90 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/2_Structured_data_from_literature/3_CA1.pptx) 91 | 92 | 93 | #### Ion Channel Genealogy 94 | 95 | The ICG database provides a comprehensive and quantitative assay of 96 | ion channel models currently available in the neuroscientific modeling 97 | community, all browsable in interactive visualizations. 98 | 99 | [Website](https://icg.neurotheory.ox.ac.uk) 100 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/2_Structured_data_from_literature/4_ICG.pptx) 101 | 102 | 103 | ## 1.3 Analysis tools 104 | 105 | [All slides in this section as single PDF](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/Part1_3_Analysis_tools.pdf) 106 | 107 | 108 | #### Neo 109 | 110 | Neo is a package for representing electrophysiology data in Python, 111 | together with support for reading a wide range of neurophysiology file formats, 112 | including Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, 113 | and support for writing to a subset of these formats, plus non-proprietary formats including HDF5. 114 | 115 | [Website](http://neuralensemble.org/Neo/) 116 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/3_Analysis_tools/1_Neo.pptx) 117 | 118 | 119 | #### Elephant 120 | 121 | Elephant (Electrophysiology Analysis Toolkit) is an open-source, community centered library 122 | for the analysis of electrophysiology data in the Python programming language. 123 | 124 | [Website](http://neuralensemble.org/Elephant/) 125 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/3_Analysis_tools/2_Elephant.pptx) 126 | 127 | 128 | 129 | #### NeuronUnit 130 | 131 | NeuronUnit facilitates data-driven validation of neurophysiology models, testing 132 | these models for agreement with experimental data. Progress in model development 133 | or appropriateness of published models can be evaluated according to performance 134 | on these tests. 135 | 136 | [Website](http://neuronunit.scidash.org) 137 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/3_Analysis_tools/3_NeuronUnit.pptx) 138 | 139 | 140 | #### Neurodata Without Borders & related tools 141 | 142 | A data format designed for storing neurophysiology data and related metadata in 143 | a structured manner. It currently stores the data within HDF5 files. A write 144 | API is available in Python and Matlab. 145 | 146 | [Website](http://nwb.org) 147 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/3_Analysis_tools/4_NWB.pptx) 148 | 149 | 150 | 151 | 152 | ## 1.4 Simulation environments 153 | 154 | [All slides in this section as single PDF](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/Part1_4_Simulation_environments.pdf) 155 | 156 | 157 | #### NEURON 158 | 159 | NEURON is a tool for developing, simulating, and analysing empirically-based models 160 | of neurons and networks of neurons. NEURON supports all classes of spiking models 161 | and runs on both desktops and supercomputers. 162 | 163 | [Website](http://neuron.yale.edu) 164 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/4_Simulation_environments/1_NEURON.pptx) 165 | 166 | 167 | #### Brian 2 168 | 169 | Brian 2 is a free, open source simulator for spiking neural networks. It is 170 | designed to be easy to learn and use, highly flexible and easily extensible. 171 | 172 | [Website](http://briansimulator.org/) 173 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/4_Simulation_environments/2_Brian.pptx) 174 | 175 | 176 | #### NEST 177 | 178 | NEST is a simulator for spiking neural network models focussing on the dynamics, 179 | size and structure of neural systems rather than on the exact morphology of 180 | individual neurons. NEST is ideal for networks of spiking neurons of any size, 181 | from individual neurons to whole-brain models. 182 | 183 | [Website](http://www.nest-simulator.org/) 184 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/4_Simulation_environments/3_NEST.pptx) 185 | 186 | #### MOOSE 187 | 188 | MOOSE is designed to simulate neural systems ranging from biochemical signaling to 189 | complex models of single neurons, circuits, and large networks. MOOSE can operate 190 | at many levels of detail, from stochastic chemical computations, to multicompartment 191 | single-neuron models, to spiking neuron network models. 192 | 193 | [Website](https://github.com/BhallaLab/moose) 194 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/4_Simulation_environments/4_MOOSE.pptx) 195 | 196 | 197 | #### Nengo 198 | 199 | Nengo is a graphical and scripting based software package for simulating large-scale 200 | spiking and non-spiking neural systems. It supports CPUs, GPUs (single and multi), 201 | MPI, and neuromorphic chips. 202 | 203 | [Website](http://nengo.github.io/) 204 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/4_Simulation_environments/5_Nengo.pptx) 205 | 206 | 207 | #### The Virtual Brain 208 | 209 | The Virtual Brain (TVB) is a neuroinformatics platform for full brain network 210 | simulations using biologically realistic connectivity. Itenables the model-based 211 | inference of neurophysiological mechanisms across different brain scales that 212 | underlie the generation of macroscopic neuroimaging signals including functional 213 | MRI (fMRI), EEG and MEG. 214 | 215 | [Website](http://www.thevirtualbrain.org) 216 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/4_Simulation_environments/6_TVB.pptx) 217 | 218 | 219 | 220 | 221 | ## 1.5 Model sharing 222 | 223 | [All slides in this section as single PDF](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/Part1_5_Model_sharing.pdf) 224 | 225 | #### ModelDB 226 | 227 | ModelDB promotes discoverability and reproducibility of computational neuroscience 228 | research by serving as a platform for curated sharing and visualization of published models. 229 | 230 | [Website](http://modeldb.yale.edu) 231 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/5_Model_sharing/1_ModelDB.pptx) 232 | 233 | 234 | #### OSB 235 | 236 | The Open Source Brain initiative (OSB) makes computational models of neurons and 237 | networks available in open source, standardized formats such as NeuroML and PyNN, 238 | encouraging collaborative development. Models and model components can be viewed, 239 | analysed and their functional behaviour explored through online simulations in 240 | standard web browsers. 241 | 242 | [Website](http://www.opensourcebrian.org) 243 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/5_Model_sharing/2_OSB.pptx) 244 | 245 | #### NeuroML 246 | 247 | NeuroML is a language for expressing models in computational neuroscience in a 248 | simulator independent, standardised format. It can express models from integrate 249 | and fire cells to complex networks of multicompartmental neurons. 250 | 251 | [Website](http://www.neuroml.org) 252 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/5_Model_sharing/3_NeuroML.pptx) 253 | 254 | #### PyNN 255 | 256 | PyNN (pronounced 'pine') is a simulator-independent language for building neuronal network models. 257 | In other words, you can write the code for a model once, using the PyNN API 258 | and the Python programming language, and then run it without modification 259 | on any simulator that PyNN supports (currently NEURON, NEST, and Brian), 260 | and on the SpiNNaker and BrainScaleS neuromorphic hardware systems. 261 | 262 | [Website](http://neuralensemble.org/PyNN/) 263 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/5_Model_sharing/4_PyNN.pptx) 264 | 265 | #### Geppetto 266 | 267 | Geppetto is a web-based visualisation and simulation platform engineered to 268 | explore complex biological systems. In use by a number of neuroinformatics resources 269 | including Open Source Brain and Virtual Fly Brain, Geppetto facilitates integration of 270 | diverse data and models, and can support different standard formats for both experimental 271 | and computational data. 272 | 273 | 274 | [Website](http://geppetto.org) 275 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/5_Model_sharing/5_Geppetto.pptx) 276 | 277 | 278 | #### GitHub 279 | 280 | GitHub is a web-based version control repository based on Git and Internet hosting 281 | service. It is mostly used for open source code development. It offers all of the 282 | distributed version control and source code management functionality of Git as well 283 | as adding its own features. 284 | 285 | [Website](https://github.com) 286 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/5_Model_sharing/6_GitHub.pptx) 287 | 288 | #### Rescience 289 | 290 | Reproducible Science is good, Replicated Science is Better. ReScience is a 291 | scientific journal dedicated to the publication of replication in computational sciences. 292 | 293 | 294 | [Website](http://rescience.github.io) 295 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/5_Model_sharing/7_ReScience.pptx) 296 | 297 | 298 | ## 1.6 Computing infrastructure 299 | 300 | [All slides in this section as single PDF](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/Part1_6_Computing_infrastructure.pdf) 301 | 302 | #### NSG 303 | 304 | NSG facilitates access and use of High Performance Computing resources freely and 305 | openly for the neuroscience community via web-based and programmatic (RESTful API) 306 | access. Various computational neuroscience tools, libraries, pipelines and data 307 | processing software are made available on HPC resources. 308 | 309 | [Website](http://www.nsgportal.org/) 310 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/6_Computing_infrastructure/1_Neuroscience_Gateway.pptx) 311 | 312 | 313 | #### Amazon Web Services 314 | 315 | Amazon Web Services (AWS) is a cloud computing platform by Amazon which provides 316 | on demand or 24/7 access to virtual computing resources such as computing (CPU & 317 | GPU), storage, databases, etc. 318 | 319 | [Website](https://aws.amazon.com/) 320 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/6_Computing_infrastructure/2_AWS.pptx) 321 | 322 | 323 | #### Binder 324 | 325 | Turn a GitHub repo into a collection of interactive notebooks. 326 | Open those notebooks in an executable environment, making your code immediately 327 | reproducible by anyone, anywhere. 328 | 329 | [Website](http://mybinder.org/) 330 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/6_Computing_infrastructure/4_Binder.pptx) 331 | 332 | 333 | 334 | ## 1.7 Open source initiatives 335 | 336 | [All slides in this section as single PDF](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/Part1_7_Open_source_initiatives.pdf) 337 | 338 | #### NeuralEnsemble 339 | 340 | NeuralEnsemble is a community-based initiative to promote and co-ordinate 341 | open-source software development in neuroscience. 342 | 343 | [Website](http://neuralensemble.org) 344 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/7_Open_source_initiatives/1_NeuralEnsemble.pptx) 345 | 346 | 347 | #### OpenWorm 348 | 349 | OpenWorm aims to build the first comprehensive computational model of the 350 | Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand 351 | cells, it solves basic problems such as feeding, mate-finding and predator avoidance. 352 | Despite being extremely well studied in biology, this organism still eludes a deep, 353 | principled understanding of its biology. 354 | 355 | [Website](http://openworm.org) 356 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/7_Open_source_initiatives/2_OpenWorm.pptx) 357 | 358 | #### BigNeuron 359 | 360 | BigNeuron is a community effort to define and advance state-of-the-art of single 361 | neuron reconstruction: an essential unsolved challenge in brain science. The 362 | project will both standardize the methods to generate high quality and consistent 363 | data, and mobilize the reconstruction community to generate interest in solving 364 | these complex and interesting algorithmic problems. 365 | 366 | [Website](https://alleninstitute.org/bigneuron) 367 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/7_Open_source_initiatives/3_BigNeuron.pptx) 368 | 369 | 370 | 371 | 372 | #### Fruit Fly Brain Observatory 373 | 374 | An open-source collaborative research platform that integrates biological data 375 | with computational models, and serves as a meeting ground for researchers to 376 | study fruit fly brain function in health and disease. 377 | 378 | [Website](http://fruitflybrain.org) 379 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/7_Open_source_initiatives/4_FruitFlyBrainObservatory.pptx) 380 | 381 | 382 | 383 | ## 1.8 Web portals 384 | 385 | [All slides in this section as single PDF](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/Part1_8_Web_portals.pdf) 386 | 387 | 388 | #### HBP Collaboratory 389 | 390 | The HBP Collaboratory collects tools from the HBP Platforms in one place and allows 391 | you to organize them into your own collaborative workspace or collab. 392 | Information on how to request an account can be found here: 393 | https://www.humanbrainproject.eu/en/hbp-platforms/getting-access 394 | 395 | [Website](https://collab.humanbrainproject.eu/) 396 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/8_Web_portals/4_HBPCollaboratory.pptx) 397 | 398 | 399 | #### NIF 400 | 401 | The Neuroscience Information Framework (NIF), an initiative of the NIH Blueprint 402 | for Neuroscience Research, is a semantically-enhanced portal to web-based 403 | neuroscience resources: data, materials, and tools. NIF has developed search 404 | tools, which expose the contents of federated databases and deep or “hidden” web 405 | resources hidden from traditional search engines. NIF is designed to serve the 406 | neuroscience research community and is actively looking for resource providers 407 | to make their resources accessible through NIF. 408 | 409 | [Website](https://neuinfo.org) 410 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/8_Web_portals/1_NeuroscienceInformationFramework.pptx) 411 | 412 | 416 | 417 | #### Virtual Fly Brain 418 | 419 | A data integration hub for Drosophila neurobiology, integrating disparate, 420 | large-scale datasets and linking them to curated literature and other resources. 421 | VFB provides the data to generate circuit hypotheses and identify research tools 422 | to test them. 423 | 424 | [Website](https://www.virtualflybrain.org) 425 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/8_Web_portals/3_VirtualFlyBrain.pptx) 426 | 427 | 428 | #### NITRC 429 | 430 | Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) is a free 431 | one-stop-shop collaboratory for science researchers that need resources such as 432 | neuroimaging analysis software, publicly available data sets, or computing power. 433 | 434 | [Website](https://www.nitrc.org/) 435 | | [Slides](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/blob/master/Part_1_Resources_for_computational_modellers/8_Web_portals/5_NITRC.pptx) 436 | 437 | 438 | -------------------------------------------------------------------------------- /Part_1_Resources_for_computational_modellers/compile.py: -------------------------------------------------------------------------------- 1 | import os 2 | import sys 3 | from subprocess import call 4 | import platform 5 | 6 | from pdfrw import PdfReader, PdfWriter 7 | 8 | sections = ['Introduction','1_Experimental_datasets', '2_Structured_data_from_literature', '3_Analysis_tools', '4_Simulation_environments', '5_Model_sharing', '6_Computing_infrastructure', '7_Open_source_initiatives', '8_Web_portals'] 9 | #sections = ['Introduction','1_Experimental_datasets', '2_Structured_data_from_literature'] 10 | 11 | only_sec = None 12 | 13 | if len(sys.argv) == 2: 14 | only_sec = sys.argv[1] 15 | print("Only doing sections starting with %s"%only_sec) 16 | 17 | for section in sections: 18 | 19 | if only_sec==None or section.startswith(only_sec): 20 | print("++++++++++++++++++++++++++++++++++\n+ Adding section: %s\n+"%section) 21 | big_file = PdfWriter() 22 | 23 | files = os.listdir(section) 24 | 25 | files = sorted(files) 26 | 27 | for f in files: 28 | fpath = section+'/'+f 29 | if os.path.isfile(fpath) and fpath.endswith('pptx') and not f=='Template.pptx': 30 | print("+ Incorporating: %s"%fpath) 31 | cmd = "libreoffice" 32 | if platform.system()=='Darwin': 33 | cmd = "/Applications/LibreOffice.app/Contents/MacOS/soffice" 34 | call([cmd, "--headless", "--invisible", "--convert-to", "pdf", fpath]) 35 | pdf_file_name = f.replace('pptx','pdf') 36 | 37 | pdf_file = PdfReader(pdf_file_name) 38 | print("+ Adding pages from %s\n+"%pdf_file_name) 39 | big_file.addpages(pdf_file.pages) 40 | if not 'ICG' in pdf_file_name: 41 | call(["mv", pdf_file_name, "temp"]) 42 | 43 | 44 | big_file.write('Part1_%s.pdf'%section) 45 | 46 | 47 | print("Done.") 48 | 49 | 50 | 51 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ## Neuroinformatics Tutorial 2 | 3 | This repository contains slide presentations for a tutorial on neuroinformatics resources for computational modellers. 4 | 5 | ![logos](Exercises/images/Logos.png) 6 | 7 | 8 | ### Summary 9 | 10 | Neuroinformatics resources are becoming an essential part of computational investigations in neuroscience. A movement towards making data and software freely available to the community means that more and more experimental datasets, general purpose analysis tools and infrastructure for computational modelling and simulation are available for computational neuroscientists to help build, constrain and validate their models. 11 | 12 | This tutorial will give an overview of the range of neuroinformatics resources currently available to the community. The [first part](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/tree/master/Part_1_Resources_for_computational_modellers) will give a brief introduction to a number of these under the headings: 13 | 14 | - **[Experimental datasets](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/tree/master/Part_1_Resources_for_computational_modellers#11-experimental-datasets)** 15 | - **[Structured data from literature](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/tree/master/Part_1_Resources_for_computational_modellers#12-structured-data-from-literature)** 16 | - **[Analysis tools](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/tree/master/Part_1_Resources_for_computational_modellers#13-analysis-tools)** 17 | - **[Simulation environments](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/tree/master/Part_1_Resources_for_computational_modellers#14-simulation-environments)** 18 | - **[Model sharing](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/tree/master/Part_1_Resources_for_computational_modellers#15-model-sharing)** 19 | - **[Computing infrastructure](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/tree/master/Part_1_Resources_for_computational_modellers#16-computing-infrastructure)** 20 | - **[Open source initiatives](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/tree/master/Part_1_Resources_for_computational_modellers#17-open-source-initiatives)** 21 | - **[Web portals](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/tree/master/Part_1_Resources_for_computational_modellers#18-web-portals)** 22 | 23 | The [second part](https://github.com/NeuralEnsemble/NeuroinformaticsTutorial/tree/master/Exercises) of the tutorial will involve hands on exercises where multiple resource will be accessed, data transformed and analysed and new models executed. 24 | 25 | This was initially developed by [Padraig Gleeson](https://github.com/pgleeson) (University College London, UK) and [Andrew Davison](https://github.com/apdavison) (CNRS, Gif-sur-Yvette, France) as part of a tutorial at [CNS 2017 in Antwerp](http://www.cnsorg.org/cns-2017-tutorials). It is intended to be developed as an open resource for the wider community. 26 | 27 | Currently this tutorial focuses on neuroinformatics resources which may be of use for those _**creating and analysing computational models of neuronal systems**_. Neuroinformatics has a much wider scope (databases of gene expression in neuronal systems, neuroimaging, clinical data, etc.) and this tutorial can potentially be expanded in future. 28 | 29 | 30 | 31 | Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License. 32 | 33 | 34 | 35 | [![DOI](https://www.zenodo.org/badge/92952750.svg)](https://www.zenodo.org/badge/latestdoi/92952750) 36 | 37 | 38 | --------------------------------------------------------------------------------