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A few weeks ago in Office Hours, a Seeq user asked how to perform iterative calculation in which the next value of the calculation relies on its previous values. This functionality is currently logged as a feature request. In the meantime, users can utilize Seeq Data Lab and push the calculated result from Seeq Data Lab to Seeq Workbench. Let's check out the example below: There are a total of 4 signals, Signal G, Signal H, Signal J, and Signal Y added to Seeq workbench. The aim is to calculate the value of Signal Y, under the selected period. Step 1: Set the start date and end date of the calculation. #Set the start date and end date of calculation startdate = '2023-01-01' enddate = '2023-01-09' Step 2: Set the workbook URL and workbook ID. #Set the workbook URL and workbook ID workbook_url = 'workbook_url' workbook_id = 'workbook_id' Step 3: Retrieve all raw data points for the time interval specified in Step 1 using spy.pull(). #Retrieve all raw data points for the time internal specified in Step 1: data = spy.pull(workbook_url, start = startdate, end = enddate, grid = None) data Step 4: Calculate the value of Signal Y, (Yi = Gi * Y(i-1) + Hi * Ji) #Calculate the value of Signal Y (Yi = Gi * Y(i-1) + Hi * Ji) for n in range(len(data)-1): data['Signal Y'][n+1] = data['Signal G'][n+1] * data['Signal Y'][n] + data['Signal H'][n+1] * data['Signal J'][n+1] data Step 5: Push the calculated value of Signal Y to the source workbook using spy.push(). #Push the calculated result of Signal Y to the source workbook spy.push(data = data[['Signal Y']], workbook = workbook_id)

If you modify your wind_dir variable to $wind_dir = group( capsule(0, 22.5).setProperty('Value', 'ENUM{{0|N}}'), capsule(22.5, 67.5).setProperty('Value', 'ENUM{{1|NE}}'), capsule(67.5, 112.5).setProperty('Value', 'ENUM{{2|E}}'), capsule(112.5, 158.5).setProperty('Value', 'ENUM{{3|SE}}'), capsule(158.5, 202.5).setProperty('Value', 'ENUM{{4|S}}'), capsule(202.5, 247.5).setProperty('Value', 'ENUM{{5|SW}}'), capsule(247.5, 292.5).setProperty('Value', 'ENUM{{6|W}}'), capsule(292.5, 337.5).setProperty('Value', 'ENUM{{7|NW}}'), capsule(337.5, 360).setProperty('Value', 'ENUM{{8|N}}') ) You will get an ordered Y axis: This is how Seeq handles enum Signal values from other systems - it has some limitations, but it seems like it should work well for your use case.

Hi David, It seems the handling of enum signals involves providing some buffer from the edges of the lane, which is not configurable. I was able to produce a fairly good alignment by using the Customize > Axis settings in the Details panel to turn of Auto scaling of the numeric signal and set the min and max to -90 and 450, resp.: This will work as long as all enum values appear in the time range of interest but will produce misalignment if a proper subset of these is in the time range, because for enums the axis is only labeled with the values of those enums that are found in the time range. Hopefully this works for your visualization; if not, it may make sense to file a support ticket for a feature request to have more control over the visualization of enumerated data.

thank you, that was it, just needed to define maximum duration of the capsule with "remove longer than" (as suggested by the program and worked)

Summary/TLDR Users commonly want to duplicate Seeq created items (Value Search, Formula, etc.) for different purposes, such as testing the effect of different calculation parameters, expanding calculations to similar areas/equipment, collaboration, etc. Guidance is summarized below to prevent unintended changes. Duplicating Seeq created items on a worksheet Creates new/independent items that can be modified without affecting the original. Duplicating worksheets within a Workbench Analysis Duplicating a worksheet simply copies the worksheet but doesn't create new/independent items. A change to a Seeq created item on one sheet modifies the same item everywhere it appears, on all other worksheets. Duplicating entire Workbench Analysis Creates new/independent items in the duplicated Workbench Analysis. You can modify them without affecting the corresponding items in the original Workbench Analysis. Details Each worksheet in an analysis can be used to help tell the story of how you got to your conclusions or give a different view into a related part of your process. Worksheets can be added/renamed/duplicated, and entire analyses can also be duplicated: Worksheet and Document Organization Confusion sometimes arises for Seeq users related to editing existing calculation items (Value Searches, Formulas, etc.) that appear on multiple worksheets, within the same analysis. Often a user will duplicate a worksheet within an analysis and not realize that editing existing items on the new worksheet also changes the same items everywhere else they are used within the analysis. They assume that each individual worksheet is independent of the others, but this is not the case. The intent of this post is to eliminate this confusion and to prevent users making unintended changes to calculations. Working with the same item on a Duplicated Worksheet When duplicating worksheets, remember that everything within a single Workbench Analysis, no matter what worksheet it is on, is "scoped" to the entire analysis. Duplicating a worksheet simply copies the worksheet but doesn't create new/independent items. A change to an item on one sheet modifies it everywhere it appears (on all other worksheets). For some use cases, duplicating a worksheet is a quick way to expand the calculations further or to create alternate visualizations, and the user wants to continues working with the original items. In other situations, worksheet duplication may be a first step in creating new versions of existing items. To avoid modifying an original item on a duplicated worksheet, from the Item Properties (Detail Pane "i" symbol) for the calculated signal/condition of interest, click to DUPLICATE the item. You can edit the duplicated version without affecting the original. Duplicating worksheets is often useful when you are doing multiple calculation steps on different worksheets, when you want trends on one worksheet and tables or other visualizations on another, when doing asset swapping and creating a worksheet for each unique asset, etc. Working with Items in a Duplicated Workbench Analysis If you duplicate the entire Workbench Analysis (for example, from the Seeq start page, see screenshot below), new/independent items are created in the duplicated Workbench Analysis. You can modify the items in the duplicated Workbench Analysis, without affecting the original (corresponding) items in the original Workbench Analysis. This is often a good approach when you have created a lengthy set of calculations and you would like to modify them or apply them in a similar way for another piece of equipment, processing line, etc., and an asset group approach isn’t applicable. There is one exception to this: Seeq created items that have been made global. Global items can be searched for and accessed outside of an individual Workbench Analysis. Editing a global item in a duplicated analysis will change it everywhere else it appears. There are many considerations for best practices when testing new parameter values and modifications for existing calculations. Keep in mind the differences between duplicating worksheets and duplicating entire analyses, and of course consider the potential use of asset groups when needing to scale similar calculations across many assets, pieces of equipment, process phases, etc. There are in-depth posts here with further information on asset groups: Asset Groups 101 - Part 1 Asset Groups 101 - Part 2

Seasonal variation can influence specific process parameters whose values are influenced by ambient conditions, or perhaps raw material make up changes over the year's seasons based on scheduled orders from different vendors. For these reasons and more, it may not suffice to compare your previous month's process parameters against current. For these situations, it may be best to compare current product runs against previous product runs occurring the same month, but a year ago in order to assess consistency or deviations. In Seeq, this can be achieved through utilizing Condition Properties. 1. Bring in raw data. For this example, I will utilize a single parameter (Viscosity) and a grade code signal. 2. Convert Product step-signal into a condition. Add properties of Product ID, Variable statistic(s), and month start/end times. // Create a month condition. Be sure to specify your time zone so that start/end times are at 12:00 AM $m = months('US/Eastern') // Create a signal for start and end times to add into "Product ID" condition $start_signal = $m.toSignal('Start', startKey()).toStep() $end_signal = $m.toSignal('End', startKey()).toStep() $p.toCondition('Product ID') // Convert string signal into a condition, with a capsule at each unique string // Specifying 'Product ID' ensures the respective values in Signal populate // a property named 'Product ID' .removeLongerThan(100d) // Bound condition. 100d as arbitrary limit .setProperty('Avg Visc', $vs, average()) // Set 'Avg Visc' property reflecting avg visc over each Product ID .setProperty('Month Start', $start_signal, startValue()) // Set 'Month Start' property to know what month Product ID ran .setProperty('Month End', $end_signal, startValue()) // Set 'Month End' property to know what month Product ID ran 3. Create another condition that has a capsule ranging the entire month for each product run within the month. Add similar properties, but note naming differences of 'Previous Month Start' and 'Previous Month Avg Visc'. This is because in the next step we will move this condition forward by one year. $pi.grow(60d) // Need to grow capsules in the condition to ensure they consume the entire month .transform($capsule -> // For each capsule (Product Run) in 'Product ID'.... capsule($capsule.property('Month Start'), $capsule.property('Month End')) // Create a capsule ranging the entire month .setProperty('Product ID', $capsule.property('Product ID')) // Add property of Product ID .setProperty('Previous Month Start', $capsule.property('Month Start')) // Add property of Month Start named 'Previous Month Start' .setProperty('Previous Month Avg Visc', $capsule.property('Avg Visc')) // Add property of Avg Visc named 'Previous Month Avg Visc' ) Notice we now have many overlapping capsules in our new condition ranging an entire month -- one for each Product Run that occurred within the month. 4. Move the previous 'Month's Product Runs' condition forward a year and merge with existing 'Product ID' condition. Aggregate properties of 'Previous Month Avg Visc'. This ensures that if a product was ran multiple times and had different avg visc values in each run, then what is displayed will be the average of all the avg visc values for each product. $previousYearMonthProductRun = $mspi.move(1y) // Move condition forward a year $pi.mergeProperties($previousYearMonthProductRun, 'Product ID', // Merge the properties of both conditions only if their // capsules share a common value of 'Product ID' keepProperties(), // keepProperties() will preserve all existing properties aggregateProperty('Previous Month Avg Visc', average())) // aggregateProperty() will take the average of all 'Previous // Month Avg Visc' properties if multiple exist... I.e. if // there were multiple Product Runs, each with a different value // for 'Previous Month Avg Visc', then take the average of all of // them. The resulting condition will match our original condition, except now with two new properties: 'Previous Month Start' & 'Previous Month Avg Visc' We can then add these properties in a condition table to create a cleaner view. We could also consider creating any other statistics of interest such as % difference of current Avg Visc vs Previous Month Avg Visc. To do this, we could use a method similar to gathering $start_signal and $end_signal in Step 2, create the calculation using the signals, then add back to the condition as a property.

Hi Javad, I got a solution based on this starting point: The following formula compares the durations of the first capsules for conditions B,C and D bounded by each capsule of condition A and sets a property on capsules of condition A indicating if these should be shown. The keep function on the end only displays capsules where the property is set to true $a.transform($a_capsule -> { $b_capsule = $b.toGroup($a_capsule).first() $c_capsule = $c.toGroup($a_capsule).first() $d_capsule = $d.toGroup($a_capsule).first() $show_a = ($b_capsule.duration() > $d_capsule.duration() and $d_capsule.duration() > $c_capsule.duration()) $a_capsule.setProperty('show', $show_a) }, 40h).keep('show', isequalTo(true) ) Changing capsule duration of B gets no capsule for result, which is expected: If you want to show another capsule for the last case, you can adjust the formula to generate another condition with the property show set to the inverse and select one of the conditions based on that value. Therefore you have to do the transform twice: $tempCondition1 = $a.transform($a_capsule -> { $b_capsule = $b.toGroup($a_capsule).first() $c_capsule = $c.toGroup($a_capsule).first() $d_capsule = $d.toGroup($a_capsule).first() $show_a = ($b_capsule.duration() > $d_capsule.duration() and $d_capsule.duration() > $c_capsule.duration()) $a_capsule.setProperty('show', $show_a) }, 40h) $tempCondition2 = $tempCondition1.transform($a_capsule -> { $d_capsule = $d.toGroup($a_capsule).first() $d_capsule.setProperty('show', not $a_capsule.property('show')) }, 40h) $tempCondition1.keep('show', isequalTo(true)) or $tempCondition2.keep('show', isequalTo(true)) As a result capsules for condition D are shown: Changing duration of capsule B to its original value show capsules of A as the result: Hope this helps. Regards, Thorsten

The SPy library supports the creation of asset trees through the spy.assets models. These asset trees can include various types of items such as signals and conditions, calculations like scorecard metrics, and can be used to create numerous Workbench Analysis Worksheets and Organizer Topic Documents. One question that commonly comes up when making these trees is how to reference attributes that are located in other parts of the tree. Roll-Ups The first example of referencing other items in the tree is through roll-ups. These type of calculations "roll-up" attributes from levels below where the roll-up calculation is being performed, whether the level is directly beneath or multiple levels below. These attributes are then combined using logic you provide. For signals and scalars, the options are Average, Maximum, Minimum, Range, Sum and Multiply. For conditions, the options are Union, Intersect, Counts, Count Overlaps, and Combine With. Below are examples where .Cities() are a component beneath the current class. All attributes and assets beneath the Cities component will be searched through and included in the roll-up based on the criteria given in the pick function. Here, we're filtering based on Name but any property such as Type can be supplied. Note Seeq Workbench's search mechanism is used here, so wildcards and regular expressions can be included. Lastly, we specify the kind of roll-up we'd like to perform. @Asset.Attribute() def Regional_Compressor_Running_Poorly(self,metadata): return self.Cities().pick({'Name':'Compressor Running Poorly'}).roll_up('union') @Asset.Attribute() def Regional_Total_Energy_Consumption(self,metadata): return self.Cities().pick({'Name':'Total Daily Energy Consumption'}).roll_up('sum') Child Attributes The second example looks at how to reference child attributes without rolling them up. Maybe there's a particular attribute that needs to be included in a calculation used at a higher level in the asset tree. For this scenario, the pick function can be used once again. Rather than do a roll-up, we'll just index the particular item we want. Most of the time the goal is to reference a specific item using this method so the criteria passed into the pick function should be specific enough to find one item so the index will always be 0. One property that may be of interest for this is Template, where you can specify the particular class used that will contain the item wanted. @Asset.Attribute() def Child_Power_Low(self, metadata): child_power = self.Cities().pick({"Name": "Compressor Power", "Asset": "/Area (A|C|D)/"})[0] return { 'Name': "Child Power Low", 'Type': "Condition", "Formula": "$child_power < 5", "Formula Parameters" : {"child_power":child_power} } Parent Attributes The next example looks at how we can reference parent attributes in calculations that are beneath it. Rather than reference a particular component, we'll use the parent. From there we'll include the attribute we'd want to reference from our parent asset. If looking to reference attributes at higher levels of the tree, chain multiple ".parent". For example, "self.parent.parent" will look two levels above the current level. @Asset.Attribute() def Parent_Temp_Multiplied(self, metadata): parent_temp = self.parent.Temperature() return { 'Name': "Parent Temp Multiplied", 'Type': "Signal", "Formula": "$parent_temp * 10", "Formula Parameters" : {"parent_temp":parent_temp} } Advanced Selection In this example, we'll look at how can we combine the previously mentioned options to find items located in other parts of the tree. Here, we're looking to reference items located at the same level of the tree but in another class so it's not located beneath the same asset. We have two separate assets beneath the regions, Temperature Items and Power Items. The Temperature Item class has a calculation called Max Temperature 1 When Compressor Is On which references an attribute beneath its corresponding Power Item class. To fetch this attribute, we go up a level to the parent, navigate down to the Power_Items and then pick that attribute. class Region(Asset): @Asset.Component() def Temperature_Items(self,metadata): return self.build_components(template=Temperature_Item, metadata=metadata, column_name='Region Temp') @Asset.Component() def Power_Items(self,metadata): return self.build_components(template=Power_Item, metadata=metadata, column_name='Region Power') class Power_Item(Asset): @Asset.Attribute() def Power_1(self,metadata): return { 'Name':'Power 1', 'Type':'Signal', 'Formula':'$power', 'Formula Parameters': {'$power':metadata[metadata['Name'].str.contains('Power')].iloc[0]['ID']} } class Temperature_Item(Asset): @Asset.Attribute() def Temperature_1(self,metadata): return { 'Name':'Temperature 1', 'Type':'Signal', 'Formula':'$temp', 'Formula Parameters': {'$temp':metadata[metadata['Name'].str.contains('Temperature')].iloc[0]['ID']} } @Asset.Attribute() def Temp_When_Comp_On(self, metadata): power_adjacent_class = self.parent.Power_Items().pick({'Name':"Power 1"})[0] return { 'Name': "Max Temperature 1 When Compressor Is On", 'Type': 'Signal', 'Formula': '$temp1.aggregate(maxValue(), ($power1<5).removeLongerThan(7d), durationKey())', 'Formula Parameters':{ 'temp1':self.Temperature_1(), 'power1': power_adjacent_class } } Item Group To help with even more complex attribute selections, we introduced the ability to include ItemGroup rather than using the pick and parent functions. ItemGroup provides an alternate way of findings items located in other parts of the tree using established Python logic. Below are two examples using ItemGroup to perform selections that would be very complex to do with the pick function Advanced Roll-up Roll-ups using the pick reference one component beneath your class but what if there was a need for a roll-up across multiple components. ItemGroup can be used for a simple roll-up as well as this complex example. Rather than specifying a particular component and picking in it, we can use ItemGroup to iterate over every asset. Here, we retrieve every High Power attribute beneath the assets if the asset is a child of the current asset. @Asset.Attribute() def Compressor_High_Power(self, metadata): # Helpful functions: # asset.is_child_of(self) - Is the asset one of my direct children? # asset.is_parent_of(self) - Is the asset my direct parent? # asset.is_descendant_of(self) - Is the asset below me in the tree? # asset.is_ancestor_of(self) - Is the asset above me? (i.e. parent/grandparent/great-grandparent/etc) return ItemGroup([ asset.High_Power() for asset in self.all_assets() if asset.is_child_of(self) ]).roll_up('union') Referencing Items In A Different Section In this example, we're looking to reference attributes in other similar assets, but these assets are located in different sections of the tree. We can use the previous option in the Advanced Selection section but what if these compressors weren't necessarily at the same level of the tree or were beneath different components. This would mean they have different pathways and the method previously stated wouldn't work. Using ItemGroup we can iterate through all assets and find any that are also based on the Compressor class. Here we also exclude the current asset and then perform a roll-up based on all of the other High Powers. @Asset.Attribute() def Other_Compressors_Are_High_Power(self, metadata): return ItemGroup([ asset.High_Power() for asset in self.all_assets() if isinstance(asset, Compressor) and self != asset ]).roll_up('union')