arcgis.raster.orthomapping module¶
The orthomapping python API allows automating orthomapping tasks in the server environment.
For more information about orthomapping workflows in ArcGIS, please visit the help documentation at http://desktop.arcgis.com/en/arcmap/10.4/manage-data/raster-and-images/block-adjustment-for-mosaic-datasets.htm.
is_supported¶
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orthomapping.
is_supported
()¶ Returns True if the GIS supports orthomapping. If a gis isn’t specified, checks if arcgis.env.active_gis supports raster analytics
compute_sensor_model¶
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orthomapping.
compute_sensor_model
(mode='QUICK', location_accuracy='High', context=None, gis=None)¶ compute_sensor_model computes the bundle block adjustment for the image collection and applies the frame xform to the images. It will also generate the control point table, solution table, solution points table and flight path table. These tables will not be published as Portal items.
Argument
Description
image_collection
Required, the input image collection on which to compute the sensor model. The image_collection can be a portal Item or an image service URL or a URI
The image_collection must exist.
mode
Optional string. the mode to be used for bundle block adjustment Only the following modes are supported:
‘Quick’ : Computes tie points and adjustment at 8x of the source imagery resolution
‘Full’ : adjust the images in Quick mode then at 1x of the source imagery resolution
‘Refine’ : adjust the image at 1x of the source imagery resolution
By default, ‘Quick’ mode is applied to compute the sensor model.
location_acuracy
Optional string. this option allows users to specify the GPS location accuracy level of the source image. It determines how far the underline tool will search for neighboring matching images, then calculate tie points and compute adjustments.
Possible values for location_accuracy are:
‘High’ : GPS accuracy is 0 to 10 meters, and the tool uses a maximum of 4 by 3 images
‘Medium’ : GPS accuracy of 10 to 20 meters, and the tool uses a maximum of 4 by 6 images
‘Low’ : GPS accuracy of 20 to 50 meters, and the tool uses a maximum of 4 by 12 images
‘Verylow’ : GPS accuracy is more than 50 meters, and the tool uses a maximum of 4 by 20 images
The default location_accuracy is ‘High’
context
Optional dictionary. The context parameter is used to configure additional client settings for block adjustment. The supported configurable parameters are for compute mosaic dataset candidates after the adjustment.
Example: { “computeCandidate”: False, “maxoverlap”: 0.6, “maxloss”: 0.05, }
gis
Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
The imagery layer url
alter_processing_states¶
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orthomapping.
alter_processing_states
(new_states, gis=None)¶ Alter the processing states of the image collection. The states are stored as key property “Orthomapping”. The content of the state is a dictionary including several properties which can be set based on the process done on the image collection.
Argument
Description
image_collection
Required, This is the image collection that will be adjusted.
The image_collection can be a portal Item or an image service URL or URI
The image_collection must exist.
new_states
Required dictionary. The state to set on the image_collection
This a dictionary of states that should be set on the image collection The new states that can be set on the image collection are: blockadjustment, dem, gcp, seamlines, colorcorrection, adjust_index, imagetype
Example: {“blockadjustment”: “raw”,
“dem”: “Dense_Natual_Neighbor”, “seamlines”:”VORONOI”, “colorcorrection”:”SingleColor”, “imagetype”: “UAV/UAS”, “adjust_index”: 0}
gis
Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
The result will be the newly set states dictionary
get_processing_states¶
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orthomapping.
get_processing_states
(gis=None)¶ Retrieve the processing states of the image collection
Argument
Description
image_collection
Required, This is the image collection that will be adjusted.
The image_collection can be a portal Item or an image service URL or URI
The image_collection must exist.
gis
Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
The result will be the newly set states dictionary
match_control_points¶
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orthomapping.
match_control_points
(control_points, similarity=None, context=None, gis=None)¶ If each of the ground control point has at least one matching tie point. Then, this function will help find all remaining tie points on all other image items of the image collection.
Argument
Description
image_collection
Required, the input image collection that will be adjusted.
The image_collection can be a portal Item or an image service URL or a URI
The image_collection must exist.
control_points
Required, a list of control point sets objects.
The schema of control points follows the schema of the mosaic dataset control point table.
The control point object should contain the point geometry, pointID, type, status and the imagePoints. (the imagePoints attribute inside the control points object lists the imageIDs)
– pointID (int) - The ID of the point within the control point table.
- – type (int) - The type of the control point as determined by its numeric value
1: Tie Point 2: Ground Control Point. 3: Check Point
- – status (int) - The status of the point. A value of 0 indicates that the point will
not be used in computation. A non-zero value indicates otherwise.
– imageID (int) - Image identification using the ObjectID from the mosaic dataset footprint table.
Example: [{ “status”: 1, “type”: 2, “x”: -117.0926538, “y”: 34.00704253, “z”: 634.2175, “spatialReference”: {
“wkid”: 4326
}, // default WGS84 “imagePointSpatialReference”: {}, // default ICS “pointId”: 1, “xyAccuracy”: “0.008602325”, “zAccuracy”: “0.015”, “imagePoints”: [{
“imageID”: 1, “x”: 2986.5435987557084, “y”: -2042.5193648409431, “u”: 3057.4580682832734, “v”: -1909.1506872159698
}, {
“imageID”: 2, “x”: 1838.2814361401108, “y”: -2594.5280063817972, “u”: 3059.4079724863363, “v”: -2961.292545463305
}, {
“imageID”: 12, “x”: 5332.855578204663, “y”: -2533.2805429751907, “u”:<PHONE_NUMBER>573158, “v”: -165.10836768947297
}, {
“imageID”: 13, “x”: 4932.0895715254455, “y”: -1833.8401744114287, “u”:<PHONE_NUMBER>182223, “v”: -1243.1445126959693
}] }, … … ]
similarity
Optional string. Choose the tolerance level for your control point matching.
Low- The similarity tolerance for finding control points will be low. This option will produce the most control points, but some may have a higher level of error.
Medium - The similarity tolerance for finding control points will be medium.
High - The similarity tolerance for finding control points will be high. This option will produce the least number of control points, but each matching pair will have a lower level of error. This is the default.
context
Optional dictionary.Additional settings such as the input control points spatial reference can be specified here.
For example: {“groundControlPointsSpatialReference”: {“wkid”: 3459}, “imagePointSpatialReference”: {“wkid”: 3459}}
Note: The ground control points spatial reference and image point spatial reference spatial reference set in the context parameter is to decide the returned point set’s ground control points spatial reference and image point spatial reference. If these two parameters are not set here, the tool will use the spatial reference defined in the input point set. And if no spatial reference is defined in the point set, then the default ground control points coordinates are in lon/lat and image points coordinates are in image coordinate system.
gis
Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
A dictionary object
color_correction¶
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orthomapping.
color_correction
(color_correction_method, dodging_surface_type, target_image=None, context=None, gis=None)¶ Color balance the image collection. Refer to the “Color Balance Mosaic Dataset” GP tool for documentation on color balancing mosaic datasets. http://pro.arcgis.com/en/pro-app/tool-reference/data-management/color-balance-mosaic-dataset.htm
Argument
Description
image_collection
Required. This is the image collection that will be adjusted.
The image_collection can be a portal Item or an image service URL or a URI
The image_collection must exist.
color_correction_method
Required string. This is the method that will be used for color correction computation. The available options are:
Dodging-Change each pixel’s value toward a target color. With this technique, you must also choose the type of target color surface, which affects the target color. Dodging tends to give the best result in most cases.
Histogram-Change each pixel’s value according to its relationship with a target histogram. The target histogram can be derived from all of the rasters, or you can specify a raster. This technique works well when all of the rasters have a similar histogram.
Standard_Deviation-Change each of the pixel’s values according to its relationship with the histogram of the target raster, within one standard deviation. The standard deviation can be calculated from all of the rasters in the mosaic dataset, or you can specify a target raster. This technique works best when all of the rasters have normal distributions.
dodging_surface_type
Required string.When using the Dodging balance method, each pixel needs a target color, which is determined by the surface type.
Single_Color-Use when there are only a small number of raster datasets and a few different types of ground objects. If there are too many raster datasets or too many types of ground surfaces, the output color may become blurred. All the pixels are altered toward a single color point-the average of all pixels.
Color_Grid- Use when you have a large number of raster datasets, or areas with a large number of diverse ground objects. Pixels are altered toward multiple target colors, which are distributed across the mosaic dataset.
First_Order- This technique tends to create a smoother color change and uses less storage in the auxiliary table, but it may take longer to process compared to the color grid surface. All pixels are altered toward many points obtained from the two-dimensional polynomial slanted plane.
Second_Order-This technique tends to create a smoother color change and uses less storage in the auxiliary table, but it may take longer to process compared to the color grid surface. All input pixels are altered toward a set of multiple points obtained from the two-dimensional polynomial parabolic surface.
Third_Order-This technique tends to create a smoother color change and uses less storage in the auxiliary table, but it may take longer to process compared to the color grid surface. All input pixels are altered toward multiple points obtained from the cubic surface.
target_image
Optional. The image service you want to use to color balance the images in the image collection. It can be a portal Item or an image service URL or a URI
context
Optional dictionary. It contains additional settings that allows users to customize the statistics computation settings.
Example: {“skipRows”: 10, “skipCols”: 10, “reCalculateStats”: “OVERWRITE”}
gis
Optional GIS. the GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
The imagery layer url
compute_control_points¶
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orthomapping.
compute_control_points
(reference_image=None, image_location_accuracy='High', context=None, gis=None)¶ This service tool is used for computing matching control points between images within an image collection and/or matching control points between the image collection images and the reference image. http://pro.arcgis.com/en/pro-app/tool-reference/data-management/compute-control-points.htm
Argument
Description
image_collection
Required. This is the image collection that will be adjusted.
The image_collection can be a portal Item or an image service URL or a URI
The image_collection must exist.
reference_image
This is the reference image service that can be used to generate ground control points set with the image service. It can be a portal Item or an image service URL or a URI
image_location_accuracy
Optional string. This option allows users to specify the location accuracy of the imagery. VERYLOW, LOW, MEDIUM, HIGH
- LOW-Images have a large shift and a large rotation (> 5 degrees).
The SIFT algorithm will be used in the point matching computation.
- MEDIUM-Images have a medium shift and a small rotation (<5 degrees).
The Harris algorithm will be used in the point matching computation.
- HIGH-Images have a small shift and a small rotation.
The Harris algorithm will be used in the point matching computation.
Default is HIGH
context
Optional dictionary. Context contains additional environment settings that affect output control points generation. { “pointSimilarity”:”MEDIUM”, “pointDensity”: “MEDIUM”, “pointDistribution”: “RANDOM” }
gis
Optional GIS. the GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
The imagery layer url
compute_seamlines¶
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orthomapping.
compute_seamlines
(seamlines_method, context=None, gis=None)¶ Compute seamlines on the image collection. This service tool is used to compute seamlines for the image collection, usually after the image collection has been block adjusted. Seamlines are helpful for generating the seamless mosaicked display of overlapped images in image collection. The seamlines are computed only for candidates that will eventually be used for generating the result ortho-mosaicked image. http://pro.arcgis.com/en/pro-app/tool-reference/data-management/build-seamlines.htm
Argument
Description
image_collection
Required, the input image collection that will be adjusted. The image_collection can be a portal Item or an image service URL or a URI The image_collection must exist.
seamlines_method
Required string. These are supported methods for generated seamlines for the image collection.
VORONOI-Generate seamlines using the area Voronoi diagram.
DISPARITY-Generate seamlines based on the disparity images of stereo pairs.
GEOMETRY - Generate seamlines for overlapping areas based on the intersection of footprints. Areas with no overlapping imagery will merge the footprints.
RADIOMETRY - Generate seamlines based on the spectral patterns of features within the imagery.
EDGE_DETECTION - Generate seamlines over intersecting areas based on the edges of features in the area.
This method can avoid seamlines cutting through buildings.
context
Optional dictionary. Context contains additional settings that allows users to customize the seamlines generation. Example: {“minRegionSize”: 100, “pixelSize”: “”, “blendType”: “Both”, “blendWidth”: null, “blendUnit”: “Pixels”, “requestSizeType”: “Pixels”, “requestSize”: 1000, “minThinnessRatio”: 0.05, “maxSilverSize”: 20 }
Allowed keys are: “minRegionSize”, “pixelSize”, “blendType”, “blendWidth”, “blendUnit”, “requestSizeType”, “requestSize”, “minThinnessRatio”, “maxSilverSize”
gis
Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
The Imagery layer url
edit_control_points¶
-
orthomapping.
edit_control_points
(control_points, gis=None)¶ This service can be used to append additional ground control point sets to the image collection’s control points. It is recommended that a ground control point (GCP) set should contain one ground control point and multiple tie points. The service tool can also be used to edit tie point sets. The input control points dictionary will always replace the points in the tie points table if the point IDs already exist.
Argument
Description
image_collection
Required. The image_collection can be a portal Item or an image service URL or a URI The image_collection must exist.
control_points
Required, a list of control point sets objects.
The schema of control points follows the schema of the mosaic dataset control point table.
The control point object should contain the point geometry, pointID, type, status and the imagePoints. (the imagePoints attribute inside the control points object lists the imageIDs)
– pointID (int) - The ID of the point within the control point table.
- – type (int) - The type of the control point as determined by its numeric value
1: Tie Point 2: Ground Control Point. 3: Check Point
- – status (int) - The status of the point. A value of 0 indicates that the point will
not be used in computation. A non-zero value indicates otherwise.
– imageID (int) - Image identification using the ObjectID from the mosaic dataset footprint table.
Example: [{ “status”: 1, “type”: 2, “x”: -117.0926538, “y”: 34.00704253, “z”: 634.2175, “spatialReference”: {
“wkid”: 4326
}, // default WGS84 “imagePointSpatialReference”: {}, // default ICS “pointId”: 1, “xyAccuracy”: “0.008602325”, “zAccuracy”: “0.015”, “imagePoints”: [{
“imageID”: 1, “x”: 2986.5435987557084, “y”: -2042.5193648409431, “u”: 3057.4580682832734, “v”: -1909.1506872159698
}, {
“imageID”: 2, “x”: 1838.2814361401108, “y”: -2594.5280063817972, “u”: 3059.4079724863363, “v”: -2961.292545463305
}, {
“imageID”: 12, “x”: 5332.855578204663, “y”: -2533.2805429751907, “u”:<PHONE_NUMBER>573158, “v”: -165.10836768947297
}, {
“imageID”: 13, “x”: 4932.0895715254455, “y”: -1833.8401744114287, “u”:<PHONE_NUMBER>182223, “v”: -1243.1445126959693
}] }, … … ]
gis
Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
The Imagery layer url
generate_dem¶
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orthomapping.
generate_dem
(out_dem, cell_size, surface_type, matching_method=None, context=None, gis=None)¶ Generate a DEM from the image collection. Refer to “Interpolate From Point Cloud” GP tool for more documentation http://pro.arcgis.com/en/pro-app/tool-reference/data-management/interpolate-from-point-cloud.htm
Argument
Description
image_collection
Required. The input image collection that will be used to generate the DEM from. The image_collection can be a portal Item or an image service URL or a URI The image_collection must exist.
out_dem
This is the output digital elevation model image url or name. Like Raster Analysis services, the service can be an existing multi-tenant service URL or this service tool can create it. It can be a url, uri, portal item, string representing the name of output image service
cell_size
Required, The cell size of the output raster dataset. This is a single numeric input. Rectangular cell size such as {“x”: 10, “y”: 10} is not supported. The cell size unit will be the unit used by the image collection’s spatial reference.
surface_type
Required string. Create a digital terrain model or a digital surface model. Refer to “surface_type” parameter of the GP tool. The available choices are:
DTM - Digital Terrain Model, the elevation is only the elevation of the bare earth, not including structures above the surface.
DSM - Digital Surface Model, the elevation includes the structures above the surface, for example, buildings, trees, bridges.
matching_method
Optional string. The method used to generate 3D points.
ETM-A feature-based stereo matching that uses the Harris operator to detect feature points. It is recommended for DTM generation.
SGM- Produces more points and more detail than the ETM method. It is suitable for generating a DSM for urban areas. This is more computationally intensive than the ETM method1.
MVM (Multi-view image matching (MVM) - is based on the SGM matching method followed by a fusion step in which the redundant depth estimations across single stereo model are merged. It produces dense 3D points and is computationally efficient
References: Heiko Hirschmuller et al., “Memory Efficient Semi-Global Matching,” ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume 1-3, (2012): 371-376.
Refer to the documentation of “matching_method” parameter of the “Generate Point Cloud” GP tool @ http://pro.arcgis.com/en/pro-app/tool-reference/data-management/generate-point-cloud.htm
context
Optional dictionary. Additional allowed point cloud generation parameter and DEM interpolation parameter can be assigned here. For example: Point cloud generation parameters - {“maxObjectSize”: 50, “groundSpacing”: None, “minAngle”: 10, “maxAngle”: 70, “minOverlap”: 0.6, “maxOmegaPhiDif”: 8, “maxGSDDif”: 2, “numImagePairs”: 2, “adjQualityThreshold”: 0.2, “regenPointCloud”: False }
DEM interpolation parameters - {“method”: “TRIANGULATION”, “smoothingMethod”: “GAUSS5x5”, “applyToOrtho”: True, “fillDEM”: “https://….” }
Note: The “applyToOrtho” flag can apply the generated DEM back into the mosaic dataset’s geometric function to achieve more accurate orthorectification result. The “fillDEM” flag allows the user to specify an elevation service URL as background elevation to fill the area when elevation model pixels cannot be interpolated from the point cloud.
gis
Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
The DEM layer item
generate_orthomosaic¶
-
orthomapping.
generate_orthomosaic
(out_ortho, regen_seamlines=True, recompute_color_correction=True, context=None, gis=None)¶ Function can be used for generating single ortho-rectified mosaicked image from image collection after the block adjustment.
Argument
Description
image_collection
Required. The input image collection that will be used to generate the ortho-mosaic from. The image_collection can be a portal Item or an image service URL or a URI The image_collection must exist.
out_ortho
Required. This is the output ortho-mosaicked image converted from the image collection after the block adjustment. It can be a url, uri, portal item, string representing the name of output image service
regen_seamlines
Optional, boolean.
Choose whether to apply seamlines before the orthomosaic image generation or not. The seamlines will always be regenerated if this parameter is set to True. The user can set the seamline options through the context parameter. If the seamline generation options are not set, the default will be used.
Default value is True
recompute_color_correction
Optional, boolean. Choose whether to apply color correction settings to the output ortho-image or not. Color correction will always be recomputed if this option is set to True. The user can configure the compute color correction settings through the context parameter. If there is no color collection setting, the default will be used.
Default value is True
context
Optional dictionary. Context contains additional environment settings that affect output image. The supported environment settings for this tool are:
Output Spatial Reference (outSR)-the output features will be projected into the output spatial reference.
Extent (extent) - extent that would clip or expand the output image
gis
Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
The Orthomosaicked Imagery layer item
generate_report¶
-
orthomapping.
generate_report
(gis=None)¶ This function is used to generate orthomapping report with image collection that has been block adjusted. The report would contain information about the quality of the adjusted images, the distribution of the control points, etc. The output of this service tool is a downloadable html page.
Argument
Description
image_collection
Required. the input image collection that should be used to generate a report from. The image_collection can be a portal Item or an image service URL or a URI The image_collection must exist.
gis
Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
The URL of a single html webpage that is a formatted orthomapping report
query_camera_info¶
-
orthomapping.
query_camera_info
(gis=None)¶ This service tool is used to query specific or the entire digital camera database. The digital camera database contains the specs of digital camera sensors that were used to capture drone images.
Argument
Description
camera_query
Required String. This is a SQL query statement that can be used to filter a portion of the digital camera database.
gis
Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
Data Frame representing the camera database
query_control_points¶
-
orthomapping.
query_control_points
(query, gis=None)¶ Query for control points in an image collection. It allows users to query among certain control point sets that has ground control points inside.
Argument
Description
image_collection
Required, the input image collection on which to query the the control points.
The image_collection can be a portal Item or an image service URL or a URI.
The image_collection must exist.
query
Required string. a SQL statement used for querying the point;
e.g. “pointID > 100”
gis
Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
A dictionary object
reset_image_collection¶
-
orthomapping.
reset_image_collection
(gis=None)¶ Reset the image collection. It is used to reset the image collection to its original state. The image collection could be adjusted during the orthomapping workflow and if the user is not satisfied with the result, they will be able to clear any existing adjustment settings and revert the images back to un-adjusted state
Argument
Description
image_collection
Required, the input image collection to reset The image_collection can be a portal Item or an image service URL or a URI.
The image_collection must exist.
gis
Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.
- Returns
A boolean indicating whether the reset was successful or not
compute_spatial_reference_factory_code¶
-
orthomapping.
compute_spatial_reference_factory_code
(longitude)¶ Computes spatial reference factory code. This value may be used as out_sr value in create image collection function
latitude : latitude value in decimal degress that will be used to compute UTM zone longitude : longitude value in decimal degress that will be used to compute UTM zone
factory_code : spatial reference factory code


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AutoComposerMidi
Class responsible for playing audio and generating MIDI files for users.
Constructor Summary
| Public Constructor | ||
| public |
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Member Summary
| Public Members | ||
| public |
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| public |
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| public |
audioContext: * |
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| public |
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| public |
instrumentData: {"melody": *, "accompaniment": *, "bass": *, "getByName": *} |
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player: * |
Method Summary
| Public Methods | ||
| public |
buildMelodyMidiWithAccompaniment(arrMelody: string[], arrAcompanimentLine: string[], arrBassLine: string[]): string Gets the MIDI data for a given melody, with accompaniment. |
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| public |
playMelodySolo(melodySolo: string[]) Plays the given melody. |
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| public |
playMelodyWithAccompaniment(melodySolo: string[], melodyAccomp: string[], melodyBass: string[]) Plays the given melodies. |
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| public |
Stops all playback |
Public Constructors
public constructor() source
Public Members
public audioContext: * source
public instrumentData: {"melody": *, "accompaniment": *, "bass": *, "getByName": *} source
public player: * source
Public Methods
public buildMelodyMidiWithAccompaniment(arrMelody: string[], arrAcompanimentLine: string[], arrBassLine: string[]): string source
Gets the MIDI data for a given melody, with accompaniment.
public playMelodySolo(melodySolo: string[]) source
Plays the given melody.
Params:
| Name | Type | Attribute | Description |
| melodySolo | string[] | solo melody (violin) |


GOOGLE ACCOUNT UI IMPLEMENTATION
In 2015, Google launched a new identity with stronger emphasis on clean, minimal layouts for frictionless and extensible design. As a result, Google Account sign-in and sign-up flow on all devices and platforms need to be updated. My project is to implement the new design on iOS and macOS.
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Control structure
In centigrade the sentences in the definition are just executed sequentially, one after the other. To conditionally control which sentences are executed you use control structures.
Control structures are built with control words and sentences. The following is an example of a control structure:
if. x = 'c'
do. centigrade y
else. fahrenheit y
end.
The if. control word starts the control structure and the end. control word ends it. The result of the x = 'c' sentence is the test result and it determines which of the other sentences in the control structure are executed. If the test result is 1, then the sentence after the do. control word is executed. If the test result is any other value then the sentence after the else. control word is executed. In English: if the left argument equals the letter c, then execute centigrade, otherwise execute fahrenheit.
Use this capability to add a new verb to your cf.ijs script that will convert a number from Fahrenheit to centigrade or from centigrade to Fahrenheit depending on the value of the left argument. Open your cf.ijs script and add the following definition at the end.
NB. convert f to c if x is 'c', otherwise c to f
convert =: dyad : 0
if. x = 'c'
do. centigrade y
else. fahrenheit y
end.
)
This defines the dyadic case of the verb. The dyad has a left argument with the name x and a right argument with the name y . The verb convert takes a left argument of 'c' to convert a Fahrenheit value to centigrade. Any left argument other than 'c' will convert a centigrade value to Fahrenheit.
Note that you use your verbs fahrenheit and centigrade just as you would use primitive verbs.
Run the script and test convert.
'c' convert 212
100
'f' convert 100
212
Normally a sentence is a line in a script. However, with control words separating a line into several sentences it is possible to have more than one sentence on a line.
The following line is equivalent to the multiple lines used earlier.
if. x = 'c' do. centigrade y else. fahrenheit y end.
Control structures are only allowed in definitions and you cannot type one directly into the ijx window for execution.
There are nine control structure patterns:
if. T do. B end.
if. T do. B else. B1 end.
if. T do. B elseif. T1 do. B1 elseif. T2 do. B2 end.
try. B catch. B1 end.
while. T do. B end.
whilst. T do. B end.
for. T do. B end.
for_i. T do. B end.
select. T
case. T0 do. B0
case. T1 do. B1
fcase.T2 do. B2
case. T3 do. B3
end.
A control structure starts with if. , try. , while. , whilst , for. , for_i. , or select. and ends with a matching end. .
Words beginning with T or B denote a block of 0 or more sentences and can contain nested control structures.
The result of the last sentence in a T block determines which block is executed next and whether execution in the control structure is finished.
Often the T block is a single sentence that makes a simple test like the one in the example.
The try. control structure is an interesting one. It executes the B block of sentences, and if there are no errors it skips to the end of the structure. However, if there is an error, then the B1 block is executed.
The while. control structure executes the T block and if its result is not 0 then it executes the B block and continues this until the T block has a 0 result. If the T block is 0 the first time, then the B block is not executed.
The whilst. control structure is the same as while. except that the T block is skipped the first time. This means that the B block is always executed at least once.
In the for. structure, the B block is evaluated once for each item of the array A that results from evaluating the T block. In the for_i. form, the local name i is set to the value of an item on each evaluation of the B block and i_index is set to the index of the item. A break. goes to the end of the for. control structure, and continue. goes to the evaluation of B for the next item.
In the select. structure, the result R of T is compared to the elements of the result Ri of Ti , and the Bi block of the first case. or fcase. with a match is evaluated. Evaluation of the select. control structure then terminates for a case. , or continues with the next B(i+1) block for an fcase. (and further continues if it is an fcase.).
See the J Dictionary for more information on control structures.
>>
<<
Usr
Pri
JfC
LJ
Phr
Dic
Voc
!:
Help
Primer


IS F311 Computer Graphics Assignment 1
Exercise 1:
Implement MidpointLine Drawing algorithm for line with any slopein openGL.
Exercise 2:
Implement Midpoint Circle Drawing algorithm using openGL.
Exercise 3:
The assignment objective is to read the below paper (Reference 1) and implementit to draw binary trees.When you draw the tree, use Bresenham’s Line Drawing and Circle Drawing to draw the edges and nodes.
Exercise 4:
Be creative, and experiment with many examples.Record your experimental results along with thedocumentation of algorithm. Develop HTML pages to document the results produced by your code, issues in coding, general discussion on the algorithm, timing analysis, references, and any other remarks.Work towards producing aesthetically pleasing outputs.Credits will be given for creative outputs.
Exercise 5:
Use software Doxygen to produce the code documentation.
We have completed this assignment using Visual Studio Community Edition 2019. In addition, the software "Doxygen" has been used to document the code.
The code has been uploaded on Github as well. The link to it is here.
Made by
1. Param Bhatt ( 2018A8PS0862H )
2. Siddhant Kulkarni ( 2018A7PS0185H )
3. Sravani Garapati ( 2018A7PS0097H )


Git and Github Version Control Fun
How git and github makes your coding life easier!
August 1, 2015
What is yak shaving?
John Willis
State of the Union
Docker, Inc
Containers are good, supply chains.
chaos monkey
Charity - Bootstrapping an ops team
Parse at Facebook
inovation tolkens
do you need a deops team or do your engineers need to be trained on it.
Brainstorming Failure
Monitoring is detecting failure
grubhub
Jeff smith - @darkandnerdy
allthingsdork.com
Systems Metaphore
Feedback -
metric and mot
FMEA - Failure Mode Effects Analysis - step-by-step approach for idnetiy
cross funtional team key
My maps - brainstorming tool
Detection ranking - detect prior to a customer detecting it
RPN number
Reduce it
Leading and lagging indicators - hints it's coming or reportings
toggles need to be explicit
deployment kata - Japanese word for testing or staging or practicing something
@steveelsewhere
the devops pipeline
HP laser printer - history
facebook chat - history
Testing:
smoke
security
performacne
exploratory
acceptance
Automation is doing things more efficiently
what is artifcation?
when you map the deployment process, its more effective to map it backwards. From proction backwards
measurement show progress.
What is test coverage?
RTFM - Remove the F#@!#%# manual (manual actions required)
What is the phonix projects?
backlogn prioritization -
Defintion of done
Goal is continuous awesome
Day of the Donkey
pivotal.io/devopsdays-chicago
@cote
Cloud native?
meatware?
software defined business
Ignite talks
Trevor Hess - @trevorghess
Open source
What's a cookbook?
Contribute on github
Submit an issue
fork edit
pull request to main repository - Add comments
Rejection - don't get it done
Own your own but your need to maintain it
Test what you put our
Publicizing - twitter, meetup, Conference
Review sessions - Microsoft C++
CI Pipelines
Monitor first


Selected style:
You'll need to run your own local server on http://localhost:8080/tmp.png.
Check
the GitHub repository
for a CycleGAN-powered Python server example.
You'll need to get a Runway model running as a local HTTP server. Tested version: Beta 0.2.1
Runway /query url:Open OpenStreetMap.org to see the results!


Class FPDF
Located at vendor/setasign/fpdf/fpdf.php
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$WithAlpha
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$images
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$PageLinks
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$AutoPageBreak
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$InHeader
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$AliasNbPages
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$ZoomMode
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$LayoutMode
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$metadata
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$PDFVersion
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Home
Lectures
01: Tools & Standards
02: HTML5
03: Advanced CSS
04: CSS Layouts
05: Responsive Design
06: CSS3
07: Javascript Frameworks
08: Server Architecture
09: Templates, Tools
10: Methodology
Resources
Useful Links
About
Contact


{% extends "tutorial.html" %} {% block head %}{% endblock %} {% block onload %}{% endblock %} {% block iscompatible %} {% endblock %} {% block content %}
In the summer of 2010, we created Sand Trap, a game that we entered in a competition on HTML5 games for mobile phones. But most mobile phones either displayed only part of the game or made the game too small—making it completely unplayable. So we took it upon ourselves to make the game fluidly adjust to match any resolution. After a bit of re-programming and using ideas outlined in this article, we had a game that scaled across any modern browser, whether it ran in a desktop or a mobile device.
This approach worked well for Sand Trap, so we used the same method on our latest game, Thwack!!. The game automatically adjusts screen resolutions to fit both full-screen and custom-sized windows, as shown in the screenshots below.
Implementing this required taking advantage of both CSS and JavaScript. Using CSS to fill the whole screen is trivial, but CSS does not allow you to maintain the same width-to-height ratio to prevent stretching of the canvas and game area. That's where JavaScript comes in. You can rescale document elements with JavaScript and trigger the resize on window events.
The first step is to designate the area on the page where the game will take place. If you include this as a div block, you can place other tags or a canvas element within it. By setting it up correctly, these child elements will inherit the scaling of the parent div block.
If you have two parts to your game area, a play area and a score-keeping area, it might look like this:

 <canvas id=”gameCanvas”></canvas>

Once you have a basic document structure, you can give these elements a few CSS properties to prepare them for resizing. Many of the CSS properties for “gameArea” are manipulated directly by JavaScript, but in order for them to work, set up a few other CSS properties starting with the parent gameArea div block:
#gameArea { position: absolute; left: 50%; top: 50%; }
This puts the top left corner of the canvas in the center of the screen. The JavaScript auto-resize function described in the next section manipulates additional CSS properties to resize the game area and center it in the window.
Since the game area is automatically resized according to the dimensions of the window, you do not want the dimensions in pixels for the gameArea div block’s child elements; instead, you want it in percentages. Pixel values do not allow inner elements to scale with the parent div as it changes. However, it may be helpful to start with pixels and then convert them to percentages once you have a layout that you like.
For this example, start with the game area being 300 pixels tall and 400 pixels wide. The canvas covers the entire game area, and a semitransparent stats panel runs along the bottom at 24 pixels tall, as shown in Figure 1.
Translating these values to percentages makes the canvas 100% in width and 100% in height (of gameArea, not the window). Dividing 24 by 300 gives the height of the stats panel at 8%, and, since it will cover the bottom of the game area, it’s width will also be 100%, as seen in Figure 2.
Now that you have determined the dimensions of the game area and its child elements, you can put together the CSS properties for the two inside elements as follows:
#gameCanvas { width: 100%; height: 100%; }
#statsPanel { position: absolute; width: 100%; height: 8%; bottom: 0; opacity: 0.8; }
Now you are ready to create a function to handle the window being resized. First, grab a reference to the parent gameArea document element.
var gameArea = document.getElementById('gameArea');
Since you are not concerned about the exact width or height, the next piece of information you need to set is the ratio of width to height. Using your earlier reference of a game area of 400 pixels wide and 300 pixels high, you know that you want to set the aspect ratio at 4 units wide and 3 units high.
var widthToHeight = 4 / 3;
Since this function is called whenever the window is resized, you also want to grab the window’s new dimensions so you are able to adjust your game’s dimensions to match. Find this by using the window’s innerWidth and innerHeight properties.
var newWidth = window.innerWidth; var newHeight = window.innerHeight;
Just as you determined the ratio of width to height you want, now you can determine the window’s current width to height ratio:
var newWidthToHeight = newWidth / newHeight;
This allows you to decide whether to make the game fill the screen vertically or horizontally, as shown in Figure 3.
If the desired game area shape is wider than the window’s shape (and height is shorter), you need to fill up the window horizontally and leave margins along the top and bottom. Likewise, if the desired game area shape is higher than the window’s shape (and the width is narrower), you need to fill up the window vertically and leave margins along the left and right.
To do this, test your desired ratio of width to height with the current window’s ratio of width to height and make the appropriate adjustments as follows:
if (newWidthToHeight > widthToHeight) { // window width is too wide relative to desired game width newWidth = newHeight * widthToHeight; gameArea.style.height = newHeight + 'px'; gameArea.style.width = newWidth + 'px'; } else { // window height is too high relative to desired game height newHeight = newWidth / widthToHeight; gameArea.style.width = newWidth + 'px'; gameArea.style.height = newHeight + 'px'; }
Now that you have adjusted the width and height of the game area, you need to center things up by placing a negative margin on the top that is half of the height and on the left that is half of the width. Remember that CSS is already placing the top-left corner of the gameArea div at the exact center of the window, so this centers the game area in the window:
gameArea.style.marginTop = (-newHeight / 2) + 'px'; gameArea.style.marginLeft = (-newWidth / 2) + 'px';
You would also want to automatically adjust the font size. If you have all of the child elements using em, you can simply set the fontSize CSS property of the gameArea div block to a value determined by its size.
gameArea.style.fontSize = (newWidth / 400) + 'em';
Lastly, you want to make the canvas drawing dimensions match its new width and height. Note that the rest of the game code must keep game engine dimensions separate from the canvas drawing dimensions to accommodate for a dynamic canvas resolution.
var gameCanvas = document.getElementById('gameCanvas'); gameCanvas.width = newWidth; gameCanvas.height = newHeight;
So the completed resize function might look something like this:
function resizeGame() { var gameArea = document.getElementById('gameArea'); var widthToHeight = 4 / 3; var newWidth = window.innerWidth; var newHeight = window.innerHeight; var newWidthToHeight = newWidth / newHeight; if (newWidthToHeight > widthToHeight) { newWidth = newHeight * widthToHeight; gameArea.style.height = newHeight + 'px'; gameArea.style.width = newWidth + 'px'; } else { newHeight = newWidth / widthToHeight; gameArea.style.width = newWidth + 'px'; gameArea.style.height = newHeight + 'px'; } gameArea.style.marginTop = (-newHeight / 2) + 'px'; gameArea.style.marginLeft = (-newWidth / 2) + 'px'; var gameCanvas = document.getElementById('gameCanvas'); gameCanvas.width = newWidth; gameCanvas.height = newHeight; }
Now, you want these adjustments to be made automatically whenever the window is resized or, in the case of mobile devices, the screen orientation is changed. Handle these events by having them call your resizeGame() function like so:
window.addEventListener('resize', resizeGame, false); window.addEventListener('orientationchange', resizeGame, false);
If the window is resized too high or the screen’s orientation is vertical, you are making width 100% of the window, and if the window is resized too wide or the screen’s orientation is horizontal, you are making height 100% of the window. The remaining dimension is sized according to the predetermined width-to-height aspect ratio.
Gopherwood Studios has used versions of this structure for all of our HTML5 games and it has proved very useful for accommodating multiple screen resolutions and various mobile devices. Additionally, with the aid of a full screen browser, this gives our web games an immersive experience more akin to traditional desktop gaming than many browser-based games. We look forward to more innovations in web games as HTML5 and web technologies continue to evolve.
{% endblock %}


As part of Fate/Grand Order 3rd Anniversary's The Cumulative Login Bonus for the 100th Day,
and for every 50 days will be raised from 20sq to 30sq.
Players with 100 days or more will get a bonus based on their total logins!
How many SQ will I receive?
Check your master profile and type your total logins in the box.


Post Office¶
This example sets up a post office, with a Postman
who routes letters, instances of Author
who send letters, and instances of Receiver
who receive letters.
Each author, when instantiated, will immediately send letters to five of their friends.
DAML Model¶
This example assumes the following DAML:
daml 1.2
module Main where
-- Roles -----------------------------------------------------------------------
template PostmanRole
with
postman : Party
where
signatory postman
controller postman can
nonconsuming InviteParticipant : (ContractId InviteAuthorRole, ContractId InviteReceiverRole)
with
party : Party; address: Text
do
c <- create InviteAuthorRole with postman; author = party
d <- create InviteReceiverRole with postman; receiver = party; address
return (c, d)
template AuthorRole
with
postman : Party
author: Party
where
signatory postman
controller author can
nonconsuming CreateLetter : ContractId UnsortedLetter
with
address : Text
content : Text
do
create UnsortedLetter
with
postman
sender = author
address
content
nonconsuming CreateIntLetter : ContractId UnsortedLetter
with
address : Text
content : Int
do
create UnsortedLetter
with
postman
sender = author
address
content = (show content)
nonconsuming CreateDecimalLetter : ContractId UnsortedLetter
with
address : Text
content : Decimal
do
create UnsortedLetter
with
postman
sender = author
address
content = (show content)
nonconsuming CreateTimeLetter : ContractId UnsortedLetter
with
address : Text
content : Time
do
create UnsortedLetter
with
postman
sender = author
address
content = (show content)
nonconsuming CreateListIntLetter : ContractId UnsortedLetter
with
address : Text
content : [Int]
do
create UnsortedLetter
with
postman
sender = author
address
content = (show content)
template ReceiverRole
with
postman : Party
receiver : Party
address : Text
where
signatory postman
controller receiver can
AcceptLetter : ContractId AcknowlegedLetter
with
sentLetterCid : ContractId SentLetter
do
sentLetterCid2 <- fetch sentLetterCid
assert $ sentLetterCid2.receiver == receiver
assert $ sentLetterCid2.receiverAddress == address
create AcknowlegedLetter
with
sender = sentLetterCid2.sender
receiver
receiverAddress = address
content = sentLetterCid2.content
controller postman can
Deactivate : ()
do
assert $ postman == postman
template InviteAuthorRole
with
postman : Party
author : Party
where
signatory postman
controller author can
AcceptInviteAuthorRole : ContractId AuthorRole
do
create AuthorRole with postman; author
template InviteReceiverRole
with
postman : Party
receiver : Party
address : Text
where
signatory postman
controller receiver can
AcceptInviteReceiverRole : ContractId ReceiverRole
do
create ReceiverRole with postman; receiver; address
-- Letters ---------------------------------------------------------------------
template UnsortedLetter
with
postman : Party
sender : Party
address : Text
content : Text
where
signatory sender
controller postman can
Sort : ContractId SortedLetter
with
receiverCid : ContractId ReceiverRole
do
receiverCid2 <- fetch receiverCid
assert $ receiverCid2.address == address
assert $ receiverCid2.postman == postman
create SortedLetter
with
postman
sender
receiver = receiverCid2.receiver
receiverAddress = receiverCid2.address
content
template SortedLetter
with
postman : Party
sender : Party
receiver : Party
receiverAddress : Text
content : Text
where
signatory sender
controller postman can
Deliver : ContractId SentLetter
do
create SentLetter with sender; receiver; receiverAddress; content
template SentLetter
with
sender : Party
receiver : Party
receiverAddress : Text
content : Text
where
signatory sender
controller receiver can
AcceptSentLetter : ContractId AcknowlegedLetter
do
create AcknowlegedLetter with sender; receiver; receiverAddress; content
template AcknowlegedLetter
with
sender : Party
receiver : Party
receiverAddress : Text
content : Text
where
signatory receiver
agreement (show sender) <> " sent" <> content <> " to " <> (show receiver) <> " at " <> (show receiverAddress)
Create the Postman¶
The Postman serves as the operator of this market, and its role contract must be defined before anything else can happen:
- If you are running this code example through the SDK, it will:
start up a Ledger Sandbox in the background, point it to the above DAML model,
run the code against that Ledger Sandbox, and
stop the Ledger Sandbox.
First, a few important imports:
from os import path
from dazl import create, sandbox
from dazl.client import create_client
DAML_FILE = path.realpath(path.join(path.dirname(__file__), './Main.daml'))
POSTMAN_PARTY = 'Postman'
MEMBER_PARTY_COUNT = 10
Then the main dish:
def run_test(url):
all_parties = [POSTMAN_PARTY]
with create_client(parties=all_parties, participant_url=url) as client_mgr:
postman_client = client_mgr.new_client(POSTMAN_PARTY)
postman_client.on_ready(
lambda _, __: create('Main.PostmanRole', dict(postman=POSTMAN_PARTY)))
ledger_run = client_mgr.run_until_complete()
return ledger_run.exit_code
Lastly, the code that actually runs everything:
if __name__ == '__main__':
import sys
with sandbox(DAML_FILE) as server:
exit_code = run_test(server.url)
sys.exit(int(exit_code))
Note
dazl.sandbox()
is a helper function for creating a disposable sandbox, running
a test, and terminating the process. You wouldn’t use it when pointing to a production instance,
but it is very useful for testing. All of these examples assume that you are using a blank
ledger every single time. As you iterate through the steps of the tutorial, make sure to stop and
start the ledger each time if you’re using dazl.sandbox()
.
dazl.simple_client()
is a helper function for creating a LedgerClientManager
.
At a minimum, you must provide it a list of parties to listen as, and a URL to the Sandbox
(or Ledger Server participant node when running against a real instance).
To create a client for a specific party, call LedgerClientManager.new_client()
. There are
several key methods on it; this example introduces ParticipantLedgerClient.on_ready
, which is
called when the connection to the ledger is initialized. The parameters are ignored at this point.
The callback, like most callbacks, can return a Command
to submit to the ledger. In this
example, a Main.postmanRole
contract is to be created with one argument named postman
and a value of 'Postman'
Finally, to actually start the manager and all the clients, call
LedgerClientManager.run_until_complete
. The code should run and return an exit code of 0,
indicating that the script successfully ran. But what if you wanted to actually see what happened
to the ledger afterwards?
Inspect the Ledger¶
Using the convenience sandbox()
method makes development a bit quicker, but it is difficult to
actually see what is happening afterwards because it tears down the ledger and all of its state.
You could either start a Sandbox instance manually through the SDK, or you could output the ledger
after every run:
from dazl.plugins import LedgerCapturePlugin
def run_test(url):
all_parties = [POSTMAN_PARTY]
with create_client(parties=all_parties, participant_url=url) as client_mgr:
inspector = LedgerCapturePlugin.stdout()
try:
postman_client = client_mgr.new_client(POSTMAN_PARTY)
postman_client.on_ready(
lambda _, __: create('Main.PostmanRole', dict(postman=POSTMAN_PARTY)))
client_mgr.register(inspector)
ledger_run = client_mgr.run_until_complete()
return ledger_run.exit_code
finally:
inspector.dump_all()
We have added dazl.plugin.LedgerCapturePlugin
, which listens for events from the ledger and
stores them internally to be drawn out later. The main body of run_test
outputs the result of
the ledger in a try
/finally
block so that the ledger is always printed out, even if an
exception occurs.
dazl.plugin.LedgerCapturePlugin
exposes several class methods for easily creating an
instance; in this example, LedgerCapturePlugin
outputs its results to stdout
when
dump_all
is called.
Set up participants¶
We have now created the postman and can see that on the ledger; now we’ll add the other participants
of this market. For readability, let’s also split out all the registration methods into a separate
set_up
function so that we can keep the focus on adding listeners to the ledger:
def run_test(url):
members = [dict(party=f'Member {i}', address=address(i)) for i in
range(0, MEMBER_PARTY_COUNT)]
all_parties = [POSTMAN_PARTY] + [member['party'] for member in members]
with create_client(parties=all_parties, participant_url=url) as client_mgr:
inspector = LedgerCapturePlugin.stdout()
try:
set_up(client_mgr, members)
client_mgr.register(inspector)
ledger_run = client_mgr.run_until_complete()
return ledger_run.exit_code
finally:
inspector.dump_all()
def set_up(client_mgr, members):
postman_client = client_mgr.new_client(POSTMAN_PARTY)
postman_client.on_ready(
lambda _, __: create('Main.PostmanRole', dict(postman=POSTMAN_PARTY)))
postman_client.on_created(
'Main.PostmanRole',
lambda cid, cdata: [cid.exercise('InviteParticipant', m) for m in members])
def address(index):
return '{} Member Lane'.format(index)
The on_created
method allows you to add an event handler for templates as they are created on
the ledger. Like the on_ready
method above, you can return a Command
(or in this case, a
list
of Command
) that is to be executed in response to this event.
After running the script, you should see a few more columns in the output for all the new parties,
and you can see that the parties now see invitation contracts that they can exercise choices on. To
further progress the workflow, let’s add more callbacks in set_up
:
def set_up(client_mgr, members):
postman_client = client_mgr.new_client(POSTMAN_PARTY)
postman_client.on_ready(
lambda _, __: create('Main.PostmanRole', dict(postman=POSTMAN_PARTY)))
postman_client.on_created(
'Main.PostmanRole',
lambda cid, cdata: [cid.exercise('InviteParticipant', m) for m in members])
member_clients = [client_mgr.new_client(m['party']) for m in members]
for member_client in member_clients:
# every member automatically accepts
member_client.on_created(
'Main.InviteAuthorRole', lambda cid, cdata: cid.exercise('AcceptInviteAuthorRole'))
member_client.on_created(
'Main.InviteReceiverRole', lambda cid, cdata: cid.exercise('AcceptInviteReceiverRole'))
Now notice that the inviteAsAuthor
and inviteAsReceiver
contracts are no longer in the
output, instead replaced with authorRole
and receiverRole
contracts; that’s because the
accept
choice on these contracts is a consuming choice.
In order to respond to these contracts as other parties, we have also created new clients, one for every additional party. Now that we have a universe of participants fully set up and ready to go, let’s do some actual work.
Send some “letters” through the post office¶
Once a participant’s Main.authorRole
is created, that participant is now granted the ability to
send letters to other participants in the market.
– TBC –


There are several different components to the light alarm clock firmware:
I'll use the FFAT file system to store web pages and persistent data on the EEPROM. Be sure to set the
partition scheme to "Default with FFat" in the tools menu, or you won't be able to load the file system.
If you don't have this option in the tools menu (the DOIT boards don't), you'll have to manually backup
the defaults.csv and copy over it using the defaults_ffat.csv file found in your Arduino settigs under
~/.arduino15/packages/esp32/hardware/esp32/1.0.2/tools/partitions
(on linux, anyway).


class: center, middle # Lightweight Higher-kinded Polymorphism Tim McGilchrist (@lambda_foo) .bottom[![lambda](/talks/fp-syd-higher-2015/lambda.png)] --- # OCaml in 1 Minute * Types are in lower case * Type variables are written with a single quote `'a` * Type constructors are reversed ``` Haskell (Int, Int) -- Haskell int * int -- OCaml [Bool] -- Haskell bool list -- OCaml foldl :: (b -> a -> b) -> b -> [a] -> b fold_left : ('a -> 'b -> 'a) -> 'a -> 'b list -> 'a data Tree a = Node a (Tree a) (Tree a) | Leaf type 'a tree = Node of 'a * 'a tree * 'a tree | Leaf ``` --- # OCaml in 1 Minute cont. * structs group together data types and functions * signature defines an interface for a struct * functors are parameterised structs ??? structs similar to modules in haskell think about as lifting functions into the module language --- # Introduction * polymorphism abstracts types, just as functions abstract values * higher-order functions abstract first-order values and type constructors * higher-kinded polymorphism, abstracts both types and type constructors ``` haskell Prelude> let when b m = if b then m else return () Prelude> :t when when :: Monad m => Bool -> m () -> m () ``` ??? * implied forall on m in Haskell --- # Introduction cont. ``` ocaml module type Monad = sig type 'a t val bind: 'a t -> ('a -> 'b t) -> 'b t val return: 'a -> 'a t end;; module When (M : Monad) = struct let f b m = if b then m else M.return () end;; (* Gives the following type module When : functor (M : Monad) -> sig val f : bool -> unit M.t -> unit M.t end *) ``` --- # Introduction cont. ``` ocaml module Unless(M : Monad) = struct module W = When(M) let f b m = W.f (not b) m end;; let module U = Unless(StateM) in U.unless (v < 0) (StateM.put v);; ``` ??? * defined using functors * work quite hard to get this result --- # Why is OCaml being difficult? * Lack of overloading * OCaml implicits proposal * Lack of higher kinded polymorphism * addressing this issue here ??? * we need to pass around dictionaries of functions * functors are only way to abstract over type constructors * first issue may be addressed by OCaml implicits * addressing the second issue --- # Alias Problem * Why not just do a Haskell? * `data` and `newtype` definitions create fresh data types * Association bewteen type name and data type it denotes cannot be abstracted * easy to check two types denote the same data type ??? * fundamental difference between type constructors in the two langauges * Straight forward to check two type names denote the same data type * expand synonyms, type names denote the same data types when the names are the same --- # OCaml is more flexible ```ocaml type t (* type in a signature *) type t = T of int (* new data type *) type t = int (* alias to int *) module Y = struct type t = int; end module M (X: Y.t) = struct type t = Y.t; end ``` ??? * OCaml is more flexible around creating abstract types * Abstracting types via signature / functor can be temporary * Checking type equality is a more subtle matter --- # Alias Example ``` ocaml 'a 't ~ (int * int) list type 'a plist = ('a * 'a) list type 'a iplist = (int * int) list ``` ??? * first line, unifying is simple 'a with (int * int) and 'f with list * after introducing type aliases, it's not so simple. * no longer a most general unifier --- # Defunctionalization Problem: abstracting over type expressions of higher kind in a language where all type variables have base kind. ??? * where does that leave us? * river, paddle, wrong spot right? --- # Type Defunctionalization Change a program with higher-kinded type expressions (\* -> \*) into a program where all type expressions are of kind *, the kind of types. ``` ocaml type ('a, 'f) app module type List = sig type t val inj : 'a list -> ('a, t) app val prj : ('a, t) app -> 'a list end let when_ (d: _ #monad) b m = if b then m else d#return() ``` ??? * The type expression (s, t) app represents the application of the type expression t to the type expression s. * eliminate higher-kinded type expressions we associate each type expression with a distinct instantiation of app * #monad is a dictionary of monad operations (similar to type class dictionaries) --- # Dictionary as Class ``` ocaml class virtual ['m] monad = object method virtual return : 'a. 'a -> ('a, 'm) app method virtual bind : 'a 'b. ('a, 'm) app -> ('a -> ('b, 'm) app) -> ('b, 'm) app end ``` --- # Higher * available as higher via opam ``` ocaml type (’p, ’f) app module Newtype1 (T : sig type ’a t end) = struct type ’a s = ’a T.t type t let inj : ’a s -> (’a, t) app = "%identity" let prj : (’a, t) app -> ’a s = "%identity" end ``` ??? * unchecked cast, the module system ensures that type safety is preserved. * creating a value of ('a, t) app only via inj * nothing to do to change the function's parameter to its return value. the identity function aka `Obj.magic` --- # Example Higher-kinded folds ``` ocaml open Higher type 'a perfect = Zero of 'a | Succ of ('a * 'a) perfect type 'f perfect_folder = { zero: 'a. 'a -> ('a, 'f) app; succ: 'a. ('a * 'a, 'f) app -> ('a, 'f) app; } let rec foldp : 'f 'a. 'f perfect_folder -> 'a perfect -> ('a, 'f) app = fun { zero; succ } -> function | Zero l -> zero l | Succ p -> succ (foldp { zero; succ } p) ``` --- # Example Higher-kinded folds cont ``` ocaml module Perfect = Newtype1(struct type 'a t = 'a perfect end) let idp p = Perfect.(prj (foldp { zero = (fun l -> inj (Zero l)); succ = (fun b -> inj (Succ (prj b)))} p)) ``` --- # Example the Codensity Transform see example-3-codensity.ml --- # Resources * Lightweight Higher Kinded Polymorphism by Jeremy Yallop and Leo White * https://github.com/ocamllabs/higher * Oleg Kiselyov: Embedding and optimizing domain-specific languages in the typed final style http://cufp.org/2015/t4-oleg-kiselyov-dsl-in-typed.html --- class: center, middle # Thanks! Tim McGilchrist @lambda_foo Software Engineer @ Ambiata Thanks!


Statistical data set
Management information of inspections that took place from 2014, published in the interest of transparency.
These figures are not official statistics.
MS Excel Spreadsheet , 211KB
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Published: 24 February 2015
Updated: 24 February 2017
From: Ofsted
Part of: Initial teacher education: inspections and outcomes


I've been very lucky to have the opportunity to work with the 'Full Stack'. Many different languages, frameworks, and CMS's. I have even dabbled in User experience, Search Marketing, SEO, and even a few iOS applications.
I wear many hats, especially for my small business clients, but I mostly handle Front-end development for clients with larger development teams. When it comes to web design or dev, you name it, I have probably done it :)
Brands I've worked with...
Give me a holler
Branding, Web Development
Canyon.Media is a kick-awesome side project that small group of friends of mine and I have collaborated to take of the world of Digital Media. I was tasked with curating a brand from scratch and I did just that. I handled almost everything from sketch to code with the exeception of copy.
The best company I have had the opportunity to work for is Pier 1 imports. They go out of their way to provide their employees with the very best work environment and amenities. I work on the eCommerce team, specifically the Front End or "Web Production" team as it’s referred to at Pier 1 imports. I wear many hats but my primary duties include developing and maintaining online digital marketing content on Pier1.com and Pier1.ca, for both customers and internal associates.
In just a little over two years, I have been privileged to help Pier 1 with launching their mobile eCommerce site, as well as retrofitting the desktop design to match. I also played an integral part in launching personalization testing for Pier1.com using Monetate.com. Some other duties include development of marketing and transactional emails, and maintaining online publications through Zmags.com.
Services:
Features, Marketing Email Templates, Transactional Email templates, User Experience / Personalization testing, Mobile Integration, and Digital Marketing Content.
Scroll to see more
CMS Integration
UX/UI design, CMS integration, server/database setup and configuration, CMS customization and plugin development.


Ryanair says 'real risk' it will have no MAX aircraft to fly next summer
DUBLIN (Reuters) - Ryanair (RYA.I) on Monday said there was a real risk that it would have no Boeing (BA.N) 737 MAX aircraft flying next summer if there are additional delays to the return to service of the grounded aircraft.
“We have now reduced our expectation of 30 MAX aircraft being delivered to us in advance of peak summer 2020 down to 20 aircraft and there is a real risk of none,” Chief Executive Michael O’Leary said in a video presentation.
“We have already reduced our passenger growth forecast ... we may have to cut that again but frankly there is no point in keeping on changing the number until we get more certainty,” he said.


Before Change
num_rollout_goals:last_env_goal_idx] = \
env_goals[goal_key]
if num_future_goals > 0:
future_obs_idxs = []
for i in indices[-num_future_goals:]:
possible_future_obs_idxs = self._idx_to_future_obs_idx[i]
// This is generally faster than random.choice. Makes you wonder what
// random.choice is doing
num_options = len(possible_future_obs_idxs)
next_obs_i = int(np.random.randint(0, num_options))
future_obs_idxs.append(possible_future_obs_idxs[next_obs_i])
future_obs_idxs = np.array(future_obs_idxs)
resampled_goals[-num_future_goals:] = self._next_obs[
self.achieved_goal_key
][future_obs_idxs]
for goal_key in self.goal_keys:
new_obs_dict[goal_key][-num_future_goals:] = \
self._next_obs[goal_key][future_obs_idxs]
new_next_obs_dict[goal_key][-num_future_goals:] = \
self._next_obs[goal_key][future_obs_idxs]
new_obs_dict[self.desired_goal_key] = resampled_goals
new_next_obs_dict[self.desired_goal_key] = resampled_goals
new_obs_dict = postprocess_obs_dict(new_obs_dict)
new_next_obs_dict = postprocess_obs_dict(new_next_obs_dict)
// resampled_goals must be postprocessed as well
resampled_goals = new_next_obs_dict[self.desired_goal_key]
new_actions = self._actions[indices]
For example, the environments in this repo have batch-wise
implementations of computing rewards:
https://github.com/vitchyr/multiworld
if hasattr(self.env, "compute_rewards"):
new_rewards = self.env.compute_rewards(
new_actions,
new_next_obs_dict,
)
else: // Assuming it"s a (possibly wrapped) gym GoalEnv
new_rewards = np.ones((batch_size, 1))
for i in range(batch_size):
new_rewards[i] = self.env.compute_reward(
new_next_obs_dict[self.achieved_goal_key][i],
new_next_obs_dict[self.desired_goal_key][i],
None
After Change
if num_future_goals > 0:
//// better future obs sample algorithm
future_indices = indices[-num_future_goals:]
possible_future_obs_lens = np.array([len(self._idx_to_future_obs_idx[i]) for i in future_indices])
next_obs_idxs = (np.random.random(num_future_goals) * possible_future_obs_lens).astype(np.int)
future_obs_idxs = np.array([self._idx_to_future_obs_idx[ids][next_obs_idxs[i]] for i, ids in enumerate(future_indices)])
resampled_goals[-num_future_goals:] = self._next_obs[
self.achieved_goal_key
][future_obs_idxs]
for goal_key in self.goal_keys:
new_obs_dict[goal_key][-num_future_goals:] = \
self._next_obs[goal_key][future_obs_idxs]
new_next_obs_dict[goal_key][-num_future_goals:] = \
self._next_obs[goal_key][future_obs_idxs]
new_obs_dict[self.desired_goal_key] = resampled_goals
new_next_obs_dict[self.desired_goal_key] = resampled_goals
new_obs_dict = postprocess_obs_dict(new_obs_dict)
new_next_obs_dict = postprocess_obs_dict(new_next_obs_dict)
// resampled_goals must be postprocessed as well
resampled_goals = new_next_obs_dict[self.desired_goal_key]
new_actions = self._actions[indices]
For example, the environments in this repo have batch-wise
implementations of computing rewards:
https://github.com/vitchyr/multiworld
if hasattr(self.env, "compute_rewards"):
new_rewards = self.env.compute_rewards(
new_actions,
new_next_obs_dict,
)
else: // Assuming it"s a (possibly wrapped) gym GoalEnv
new_rewards = np.ones((batch_size, 1))
for i in range(batch_size):
new_rewards[i] = self.env.compute_reward(
new_next_obs_dict[self.achieved_goal_key][i],
new_next_obs_dict[self.desired_goal_key][i],
None


new
Women's Blouse Top
$18.50
$25.30
ADD TO CART
new
Men's jacket
$30.00
$20.00
ADD TO CART
new
Women's Shirt
$25.30
$15.50
ADD TO CART
new
Men's jacket
$29.50
$25.30
ADD TO CART


DNA Barcodes analysis
This is a project developed during the university course Big Data. The purpose of this project is to perform an analysis of DNA subsequences samples, named barcodes, with the aim to classify and predict the species bolonging from a specific genomic sequence. In particular we conducted the analysis basing on the concept of multi-locus, comparating the results with the past mono-locus research.
This work is based on the data stored in the BOLD database. Specifically we considered species related to the families of plants and fungi.
The tool is realized by the combination of several components, developed by Bash Scripting and Python languages, along with a map-reduce step. To use it, put the data in a folder named “data” and start “fastaSplitter.sh” from a bash terminal.
More detailed information about the project can be found on this paper (located in italian).
Date
July 2014
See on GitHub
https://github.com/Pausa90/BOLDProject
Authors and Contributors
This Project is developed by @V1LL0 and @Pausa90


{% extends 'pages/page.html' %} {% load pages_tags mezzanine_tags %} {% block main %}
My Health Peace of Mind offers you a chance to connect the dots between the health care you want and to the people who might be called on to make those decisions on your behalf. In a way, we see My Health Peace of Mind as helping you to own your own health.
My Health Peace of Mind is a free tool for you, funded by a generous grant from The Duke Endowment.
My Health Peace of Mind encourages people to have important conversations about the healthcare they would like to receive in the future if they were facing a life limiting condition. By encouraging these conversations with those closest to you, you can formalize your wishes into legal documents called Advance Directives. Advance Directives include a Living Will (a document that states your healthcare preferences) and a Healthcare Power of Attorney (a document that lets you name a trusted person to make healthcare decisions on your behalf if you are unable to make the decisions yourself).
My Health Peace of Mind allows you to upload your documents online where they can be shared with the people who might be called on to make decisions one day. This can include anyone you name – members of your family, a friend, your physician or some other trusted person. Uploading and sharing your documents increases the chance that your healthcare wishes will be honored. And through a secure partnership with hospitals or Vynca, My Health Peace of Mind will allow your Advance Directives to be accessed if you need emergency care.
My Health Peace of Mind will provide you with the ability to explore and discover information about health conditions, aging in general and how to have conversations about your future healthcare preferences, no matter what you choose. What’s important to us is that your voice is heard, documented and shared with the people closest to you.
By joining My Health Peace of Mind, you begin a journey of making important personal decisions that are a gift to your loved ones.
My Health Peace of Mind is a collaborative project of The Carolinas Center, a member organization that has led the way for patient-centered care at the end of life in the Carolinas. Together with our members and project partners (need page with project partners named), we want you to receive the care you desire when it is needed. Without planning in advance, your healthcare preferences might not be known or honored.


Governor invites Shiv Sena to stake claim to form govt in Maharashtra
"The Sena will have to inform the governor about its stand by Monday (November 11) evening 7.30 pm," a Raj Bhavan official said
by Press Trust of IndiaMaharashtra Governor Bhagat Singh Koshyari on Sunday invited the Shiv Sena, the second largest party, to stake claim to form government, hours after the BJP declined such attempt.
"The Sena will have to inform the governor about its stand by Monday (November 11) evening 7.30 pm," a Raj Bhavan official said.
In the 288-member Assembly, the BJP and the Sena each has 105 and 56 MLAs, respectively.
Opposition Congress and NCP won 44 and 54 seats, respectively in recent assembly polls. Halfway mark is 145.


About Me
My name is Danny Goulter and I am learning to be a coder/developer with a view to getting a job working in Tech.
I have a limited background in Tech, learning html now reminds me of making a blog in the early 2000's (because it was the cool thing to do back then) - I didn't really learn the code because I used Microsoft Frontpage to edit the pages and content, but I did learn enough commands to get by. Speaking of commands, working with the command line also reminded of working with MS-DOS back in the early-mid 90's.
Please find links on the right to my technical blog posts and my thoughts on Core Concepts.


Functions for clustering time-course gene expression and reconstructing of gene regulatory network based on Dynamic Bayesian Network.
| Version: | 1.0.1 |
| Depends: | R (≥ 3.1.0) |
| Imports: | MASS, G1DBN, igraph |
| Published: | 2017-01-13 |
| Author: | Yaqun Wang, Zhengyang Shi and Xiang Zhan |
| Maintainer: | Yaqun Wang <yw505 at sph.rutgers.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | GeneClusterNet results |
| Reference manual: | GeneClusterNet.pdf |
| Package source: | GeneClusterNet_1.0.1.tar.gz |
| Windows binaries: | r-devel: GeneClusterNet_1.0.1.zip, r-release: GeneClusterNet_1.0.1.zip, r-oldrel: GeneClusterNet_1.0.1.zip |
| OS X binaries: | r-release: GeneClusterNet_1.0.1.tgz, r-oldrel: GeneClusterNet_1.0.1.tgz |
Please use the canonical form https://CRAN.R-project.org/package=GeneClusterNet to link to this page.


Welcome
All that is good begins with a SMILE.
Your smile is our top priority.
Our entire team is dedicated to providing you with the personalized, quality dental care that you deserve.
When you visit our office you will experience all that modern dentistry has to offer, including a comprehensive list of general, restorative and cosmetic dental services to meet the needs of the whole family. Our goal is to assist each patient in achieving and maintaining long term dental health and a beautiful smile. Our wide ranges of dental services include:


Mountaintop removal mining is a coal mining process that removes the surface of mountains to allow access to the coal seams that run along ridges. Explosives are used to blast the top layer, known as the overburden, off to allow access to the coal. It is practiced in the United States throughout the Appalachian Mountain Range. It irreversably changes the topography of the region, which has effects on the vegetation, animal life, water flows, and soil of the region. In many places, entire sections of the Appalachian range have been flattened out. But companies tend to favor the process because it is cheaper and less high risk than underground mining, requiring fewer employees to generate the same output.
In West Virginia, the coal industry has formed the backbone of the state's economy. At its peak, over 178,300 were employed in the coal industry. But the reliance on coal is fading, with just over 50,000 jobs per year in recent measures. President Donald Trump promised to bring back coal jobs and revitalize the industry during the 2016 campaign, hinting at deregulating the mining industry with fewer clean water restrictions.
Coal has long been linked to diseases in miners like black lung, which is caused by inhaling the dust that hangs in mine shafts. Recent research seems to indicate that coal mining's health effects seep beyond the mine sites, a phenonmenon that is turning into a growing public health crisis in the Appalachian regions that have long relied on coal for their economy. If unregulated, larger-scale coal mining could further endanger the region's health as particulates and carcinogens more freely enter surrounding water supplies and pollute the air.
The Last Mountain (2011), a documentary about mountaintop-removal mining, gave some startling statistics about the health of people near mountaintop removal mine sites. While the national average for brain tumors was 1/100,000 people, a small town in West Virginia under a Massey Energy mountaintop mine had 6 deaths from brain tumors within years, all neighboring each other. It was suggested that their well water, contaminated with heavy metals spread through the blasting dust from the mine, was the cause.
In this project, we mapped the incidence of brain and other nervous system cancers and lung disease by county in West Virginia. We also show the location of mines in the state to illustrate how proximity correlates with disease. The project also includes two 3-dimensional models of how the landscape has changed near Coal River Mountain. Viewers can see for themselves how the mountain range has flattened as a result of mountaintop removal mining in the state.
— Allegra Codamon and Annie Ma


Welcome to This Most Excellent Pizza Site
Please select a size for your pizza
Small $12
Medium $14
Large $16
Please select your toppings
Eggplant $1
Peeps $2
Anchovies $3
Lucky Charms $4
Make My Pizza!
This pizza will cost you:
Righteous!


Be able to select an origin.
Be able to select a destination.
Retrieve a fare offer for the given origin-destination combination.


ThreadedSeedGeneratorRng Members
The ThreadedSeedGeneratorRng type exposes the following members.
Methods
| Name | Description | |
|---|---|---|
| ~ThreadedSeedGeneratorRng | ||
| Dispose |
When overridden in a derived class, releases the unmanaged resources used by the RandomNumberGenerator and optionally releases the managed resources.
|
|
| Equals(System.Object) |
Determines whether the specified object is equal to the current object. (Inherited from Object.) |
|
| Finalize |
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) |
|
| GetAvailableBytes | ||
| GetBytes | ||
| GetHashCode |
Serves as the default hash function. (Inherited from Object.) |
|
| GetNonZeroBytes | ||
| GetType |
Gets the Type of the current instance. (Inherited from Object.) |
|
| MainThreadLoop | ||
| MemberwiseClone |
Creates a shallow copy of the current Object. (Inherited from Object.) |
|
| Read | ||
| ToString |
Returns a string that represents the current object. (Inherited from Object.) |
Fields
| Name | Description | |
|---|---|---|
| _disposed | ||
| _fifoStreamLock | ||
| _mainThread | ||
| _myThreadedSeedGenerator | ||
| _poolFullAre | ||
| _safeStream | ||
| FalseInt | ||
| TrueInt |
Properties
| Name | Description | |
|---|---|---|
| MaxPoolSize |
ThreadedSeedGeneratorRNG will always try to fill up to MaxPoolSize bytes available for read
|


Welcome to Samad Farooqui's website!
I'm a sophomore Computer Science / Information
Technology & Web Science Major at Rensselaer
Polytechnic Institute. I am looking for an internship
for the summer of 2017. Feel free to contact me!
Hobbies: Boxing, learning about other cultures, and watching Netflix.