Specify Dimensions And Measurements Free _HOT

Why do you have to specify the number of columns, but not the number of rows when passing an 2d array as a parameter? I've probably looked at five or more forum threads that give the syntax, but none of them explained the reasoning behind it. I am okay with the compiler needing to know the size of an array to operate on it, but isn't a bidimensional array basically an array of arrays?

I have read other threads, and they all seem to do conversions to inches and then specify the dimensions of the figure in inches and adjust dpi's in some way. I would like to avoid dealing with the potential loss of accuracy that could result from pixel-to-inches conversions.

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where the filename has the "png" extension in this example (but you must still specify the format with format='png' anyway as far as I can tell), the image array is arr, and we chose the inverted grayscale "gray_r" as the colormap. I usually add vmin and vmax to specify the dynamic range but these are optional.

Because the subplots_adjust setting makes the axis fill the figure, you don't want to specify a bbox_inches='tight', as it actually creates whitespace padding in this case. This solution works when you have more than 1 subplot also.

For example, imagine that you have a small rectangular table that you want to fit into an office layout diagram. The table top is 1 foot, 9 inches by 1 foot, 5 inches. When you drag a rectangular table from the Office Furniture stencil, you see that the dimensions are 3 feet, 6 inches by 6 feet. Instead of using the resizing handles on the table shape to make it smaller, use the Size & Position window to set the exact size.

szdim = size(A,dim) returns the length of dimension dim when dim is a positive integer scalar. You can also specify dim as a vector of positive integers to query multiple dimension lengths at a time. For example, size(A,[2 3]) returns the lengths of the second and third dimensions of A in the 1-by-2 row vector szdim.

Queried dimensions, specified as a positive integer scalar, a vector of positive integer scalars, or an empty array of size 0-by-0, 0-by-1, or 1-by-0. If an element of dim is larger than ndims(A), then size returns 1 in the corresponding element of the output. If dim is an empty array, then size returns a 1-by-0 empty array.

List of queried dimensions, specified as positive integer scalars separated by commas. If an element of the list is larger than ndims(A), then size returns 1 in the corresponding element of the output.

Is there a way to set absolute dimensions of an object. Once I've created a cylinder for example, how can I go back and change the length? I know I can scale it, but I want to set an absolute length and cannot find any panels, tools, etc., to show / edit this data.

To do this, while still in Object Mode and the object selected, key Ctrl+A then select Scale, this will convert the scale back to 1.000, this in effect removes the scale transformation, and sets the data such that no transformation applies and any scaling will no longer affect your 'absolute' dimensions. It is particularly useful when using absolute units.

Metrics are uniquely defined by a name, a namespace, and zero or more dimensions.Each data point in a metric has a time stamp, and (optionally) a unit of measure. You can retrieve statistics from CloudWatch for any metric.

Every metric has specific characteristics that describe it, and you can think ofdimensions as categories for those characteristics. Dimensions help you design astructure for your statistics plan. Because dimensions are part of the uniqueidentifier for a metric, whenever you add a unique name/value pair to one of yourmetrics, you are creating a new variation of that metric.

AWS services that send data to CloudWatch attach dimensions to each metric. You can use dimensions to filter the results that CloudWatch returns. For example, you can get statistics for a specific EC2 instance by specifying the InstanceId dimension whenyou search for metrics.

For metrics produced by certain AWS services, such as Amazon EC2, CloudWatch can aggregate data acrossdimensions. For example, if you search for metrics in the AWS/EC2 namespacebut do not specify any dimensions, CloudWatch aggregates all data for the specified metricto create the statistic that you requested. CloudWatch does not aggregate acrossdimensions for your custom metrics.

CloudWatch treats each unique combination of dimensions as a separate metric, even if themetrics have the same metric name. You can only retrieve statistics usingcombinations of dimensions that you specifically published. When you retrievestatistics, specify the same values for the namespace, metric name, anddimension parameters that were used when the metrics were created. You can alsospecify the start and end times for CloudWatch to use for aggregation.

You can't retrieve statistics for the following dimensions or if you specify no dimensions. (The exception is by using the metric math SEARCH function, which can retrievestatistics for multiple metrics. For more information, see Use search expressions in graphs.)

If you set an alarm on a high-resolution metric, you can specify a high-resolution alarm with a period of 10 seconds or 30 seconds, or you can set a regular alarm with a period of any multiple of 60 seconds. There is a higher charge for high-resolution alarmswith a period of 10 or 30 seconds.

Statistics are metric data aggregations over specifiedperiods of time. CloudWatch provides statistics based on the metric data points providedby your custom data or provided by other AWS services to CloudWatch. Aggregations are madeusing the namespace, metric name, dimensions, and the data point unit of measure,within the time period you specify.

You can specify a unit when you create a custom metric. If you do not specify a unit, CloudWatch uses None as the unit.Units help provide conceptual meaning to your data. Though CloudWatch attaches no significance to a unit internally, other applications canderive semantic information based on the unit.

Metric data points that specify a unit of measure are aggregated separately. When you getstatistics without specifying a unit, CloudWatch aggregates all data points of the sameunit together. If you have two otherwise identical metrics with different units, twoseparate data streams are returned, one for each unit.

A period is the length of time associated with a specific Amazon CloudWatch statistic. Each statistic represents an aggregation of the metrics data collected for a specifiedperiod of time. Periods are defined in numbers of seconds, and valid values for period are 1, 5, 10, 30, or any multiple of 60. For example, to specify a period of six minutes, use 360 as the period value.You can adjust how the data is aggregated by varying the length of the period. Aperiod can be as short as one second or as long as one day (86,400seconds). The default value is 60 seconds.

When you retrieve statistics, you can specify a period, start time, and end time. Theseparameters determine the overall length of time associated with the statistics.The default values for the start time and end time get you the last hour's worthof statistics. The values that you specify for the start time and end timedetermine how many periods CloudWatch returns. For example, retrieving statisticsusing the default values for the period, start time, and end time returns anaggregated set of statistics for each minute of the previous hour. If you preferstatistics aggregated in ten-minute blocks, specify a period of 600. Forstatistics aggregated over the entire hour, specify a period of 3600.

Periods are also important for CloudWatch alarms. When you create an alarm to monitor a specificmetric, you are asking CloudWatch to compare that metric to the threshold value thatyou specified. You have extensive control over how CloudWatch makes that comparison.Not only can you specify the period over which the comparison is made, but youcan also specify how many evaluation periods are used to arrive at a conclusion.For example, if you specify three evaluation periods, CloudWatch compares a window ofthree data points. CloudWatch only notifies you if the oldest data point is breachingand the others are breaching or missing.

Amazon CloudWatch aggregates statistics according to the period length that you specify whenretrieving statistics. You can publish as many data points as you want with thesame or similar time stamps. CloudWatch aggregates them according to the specified period length. CloudWatch does not automatically aggregate data across Regions, but you can use metric math to aggregate metrics from different Regions.

You can publish data points for a metric that share not only the same time stamp, but alsothe same namespace and dimensions. CloudWatch returns aggregated statistics for thosedata points. You can also publish multiple data points for the same or differentmetrics, with any time stamp.

Amazon CloudWatch doesn't differentiate the source of a metric. If you publish a metricwith the same namespace and dimensions from different sources, CloudWatch treats this as asingle metric. This can be useful for service metrics in a distributed, scaledsystem. For example, all the hosts in a web server application could publishidentical metrics representing the latency of requests they are processing. CloudWatchtreats these as a single metric, allowing you to get the statistics for minimum,maximum, average, and sum of all requests across your application.

Some CloudWatch metrics support percentiles as a statistic. For these metrics, you can monitor your system and applications using percentiles as you would when using the other CloudWatch statistics (Average, Minimum, Maximum, and Sum). For example, when you create an alarm, you can use percentiles as the statistical function. You can specify the percentile with up to ten decimal places (for example, p95.0123456789).