| java.lang.Object | |
| ↳ | com.google.android.gms.fitness.data.DataType |
The data type defines the schema for a stream of data being collected by, inserted into, or queried from Google Fit. The data type defines only the representation and format of the data, and not how it's being collected, the sensor being used, or the parameters of the collection.
The same underlying concept may be represented by different data types, depending on how data is
represented. For example, the com.google.step_count.delta
data type represents step
count data as delta (new steps) between different readings, while the
com.google.step_count.cumulative
data type represents step count data as a sum since the
start of the count. The platform has built-in support for converting between compatible data
types.
A data type contains one or more fields. In case of multi-dimensional data (such as location with latitude, longitude, and accuracy) each field represents one dimension. Each data type field has a unique name which identifies it. The field also defines the format of the data (int, float, etc.).
The data types in the com.google
namespace are shared with any app with the user
consent. These are fixed and can only be updated in new releases of the platform.
This class contains constants representing each of the com.google
data types,
each prefixed with TYPE_
. Custom data types can be accessed via the ConfigApi
.
Certain data types can represent aggregates, and can be computed as part of read requests by
calling aggregate(DataType, DataType)
. This class contains
constants for all the valid aggregates, each prefixed with AGGREGATE_
. In addition,
AGGREGATE_INPUT_TYPES
contains all valid input types to aggregation,
and the aggregates for each input type can be queried via
getAggregatesForInput(DataType)
.
| Constants | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| String | MIME_TYPE_PREFIX | The common prefix for data type MIME types, for use in intents. |
|
[Expand]
Inherited Constants | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
|
From interface
android.os.Parcelable
|
| Fields | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| AGGREGATE_ACTIVITY_SUMMARY |
In the com.google.activity.summary data type, each data point represents a summary
of all activity segments of a particular activity type over a time interval.
|
||||||||||
| AGGREGATE_BASAL_METABOLIC_RATE_SUMMARY |
In the com.google.bmr.summary data type, each data point represents the
average, maximum and minimum basal metabolic rate, in kcal per day, over the time interval of
the data point.
|
||||||||||
| AGGREGATE_BODY_FAT_PERCENTAGE_SUMMARY |
In the com.google.body.fat_percentage.summary data type, each data point represents
the average, maximum and minimum percentage over the time interval of the data point.
|
||||||||||
| AGGREGATE_CALORIES_CONSUMED | Aggregate calories consumed,in kcal, during a time interval. | ||||||||||
| AGGREGATE_CALORIES_EXPENDED | Aggregate calories expended,in kcal, during a time interval. | ||||||||||
| AGGREGATE_DISTANCE_DELTA | Aggregate distance, in meters, during a time interval. | ||||||||||
| AGGREGATE_HEART_RATE_SUMMARY |
In the com.google.heart_rate.summary data type, each data point represents
average, maximum and minimum beats per minute over the time interval of the data point.
|
||||||||||
| AGGREGATE_INPUT_TYPES | List of data types that are supported as input data types for aggregation. | ||||||||||
| AGGREGATE_LOCATION_BOUNDING_BOX |
In the com.google.location.bounding_box data type, a data point represents the
bounding box computed over user's location data points over a time interval.
|
||||||||||
| AGGREGATE_POWER_SUMMARY |
In the com.google.power.summary data type, each data point represents
average, maximum and minimum watts over the time interval of the data point.
|
||||||||||
| AGGREGATE_SPEED_SUMMARY |
In the com.google.speed.summary data type, each data point represents the
average, maximum and minimum speed over ground, in meters/second, over the time interval of
the data point.
|
||||||||||
| AGGREGATE_STEP_COUNT_DELTA | Aggregate number of steps during a time interval. | ||||||||||
| AGGREGATE_WEIGHT_SUMMARY |
In the com.google.weight.summary data type, each data point represents the
average, maximum and minimum weight, in kilograms, over the time interval of
the data point.
|
||||||||||
| CREATOR | |||||||||||
| TYPE_ACTIVITY_SAMPLE |
In the com.google.activity.sample data type, each data point represents an
instantaneous sample of the current activity.
|
||||||||||
| TYPE_ACTIVITY_SEGMENT |
In the com.google.activity.segment data type, each data point represents a continuous
time interval with a single activity value.
|
||||||||||
| TYPE_BASAL_METABOLIC_RATE |
In the com.google.calories.bmr data type, each data point represents the basal
metabolic rate of energy expenditure at rest of the user at the time of the reading, in kcal
per day.
|
||||||||||
| TYPE_BODY_FAT_PERCENTAGE |
In the com.google.body.fat.percentage data type, each data point represents a
measurement of the total fat mass in a person's body as a percentage of the total body mass.
|
||||||||||
| TYPE_CALORIES_CONSUMED |
In the com.google.calories.consumed data type, each data point represents the number
of calories consumed, in kcal, over the time interval of the data point.
|
||||||||||
| TYPE_CALORIES_EXPENDED |
In the com.google.calories.expended data type, each data point represents the number
of calories expended, in kcal, over the time interval of the data point.
|
||||||||||
| TYPE_CYCLING_PEDALING_CADENCE |
In the com.google.cycling,cadence data type, each data point represents an
instantaneous measurement of the pedaling rate in crank revolutions per minute.
|
||||||||||
| TYPE_CYCLING_PEDALING_CUMULATIVE |
In the com.google.cycling.pedaling.cumulative data type, each data point represents
the number of rotations taken from the start of the count.
|
||||||||||
| TYPE_CYCLING_WHEEL_REVOLUTION |
In the com.google.cycling.wheel_revolution.cumulative data type, each data point
represents the number of revolutions taken from the start of the count.
|
||||||||||
| TYPE_CYCLING_WHEEL_RPM |
In the com.google.cycling.wheel.revolutions data type, each data point represents an
instantaneous measurement of the wheel in revolutions per minute.
|
||||||||||
| TYPE_DISTANCE_DELTA |
In the com.google.distance.delta data type, each data point represents the distance
covered, in meters, since the last reading.
|
||||||||||
| TYPE_HEART_RATE_BPM |
In the com.google.heart_rate.bpm data type, each data point represents an
instantaneous measurement of the heart rate in beats per minute.
|
||||||||||
| TYPE_HEIGHT |
In the com.google.height data type, each data point represents the height of the
user at the time of the reading, in meters.
|
||||||||||
| TYPE_LOCATION_SAMPLE |
In the com.google.location.sample data type, each data point represents the user's
location at a given instant.
|
||||||||||
| TYPE_LOCATION_TRACK |
The com.google.location.track data type represents a location point that is part of a
track and which may have inexact timestamps.
|
||||||||||
| TYPE_POWER_SAMPLE |
In the com.google.power.sample data type, each data point represents an
instantaneous measurement of power in watts.
|
||||||||||
| TYPE_SPEED |
In the com.google.speed data type, each data point represents the instantaneous
speed over ground, in meters/second.
|
||||||||||
| TYPE_STEP_COUNT_CADENCE |
In the com.google.step_count.cadence data type, each data point represents an
instantaneous measurement of the cadence in steps per minute.
|
||||||||||
| TYPE_STEP_COUNT_DELTA |
In the com.google.step_count.delta data type, each data point represents the number
of steps taken since the last reading.
|
||||||||||
| TYPE_WEIGHT |
In the com.google.weight data type, each data point represents the weight of the
user at the time of the reading, in kilograms.
|
| Public Methods | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
Returns a list of output aggregate data types for the specified
inputDataType .
| |||||||||||
Returns the ordered list of fields for the data type.
| |||||||||||
Returns the MIME type for a particular
DataType .
| |||||||||||
Returns the namespaced name which uniquely identifies this data type.
| |||||||||||
Return the index of a field
| |||||||||||
|
[Expand]
Inherited Methods | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
|
From class
java.lang.Object
| |||||||||||
|
From interface
android.os.Parcelable
|
The common prefix for data type MIME types, for use in intents. The MIME type for a particular data type will be this prefix followed by the data type name. Examples:
vnd.google.fitness.data_type/com.google.heart_rate.bpm vnd.google.fitness.data_type/com.google.activity.segment vnd.google.fitness.data_type/com.example.my_typeThe data type's name is returned by
getName()
. The full MIME type can be
computed by getMimeType(DataType)
.
In the com.google.activity.summary
data type, each data point represents a summary
of all activity segments of a particular activity type over a time interval. The data type
has three fields:
FitnessActivities
, as described in
FIELD_ACTIVITY
.
Because this is an aggregate data type, start and end times should be set.
In the com.google.bmr.summary
data type, each data point represents the
average, maximum and minimum basal metabolic rate, in kcal per day, over the time interval of
the data point.
Because this is an aggregate data type, the start and end times should be set.
In the com.google.body.fat_percentage.summary
data type, each data point represents
the average, maximum and minimum percentage over the time interval of the data point.
Because this is an aggregate data type, the start and end times should be set.
Aggregate calories consumed,in kcal, during a time interval. This data type is equivalent
to the one used for non-aggregated data. The full definition can be found at
TYPE_CALORIES_CONSUMED
.
Aggregate calories expended,in kcal, during a time interval. This data type is equivalent
to the one used for non-aggregated data. The full definition can be found at
TYPE_CALORIES_EXPENDED
.
Aggregate distance, in meters, during a time interval. This data type is equivalent to the
one used for non-aggregated data. The full definition can be found at
TYPE_DISTANCE_DELTA
.
In the com.google.heart_rate.summary
data type, each data point represents
average, maximum and minimum beats per minute over the time interval of the data point.
Because this is an aggregate data type, start and end times should be set.
List of data types that are supported as input data types for aggregation. These include:
activity.segment
body.fat.percentage
calories.consumed
calories.expended
distance.delta
heart_rate.bpm
location.sample
speed
step_count.delta
weight
com.google
namespace cannot be aggregated by
the platform.
In the com.google.location.bounding_box
data type, a data point represents the
bounding box computed over user's location data points over a time interval. Each bounding
box has four fields:
In the com.google.power.summary
data type, each data point represents
average, maximum and minimum watts over the time interval of the data point.
Because this is an aggregate data type, start and end times should be set.
In the com.google.speed.summary
data type, each data point represents the
average, maximum and minimum speed over ground, in meters/second, over the time interval of
the data point.
Because this is an aggregate data type, the start and end times should be set.
Aggregate number of steps during a time interval. This data type is equivalent to the
one used for non-aggregated data. The full definition can be found at
TYPE_STEP_COUNT_DELTA
.
In the com.google.weight.summary
data type, each data point represents the
average, maximum and minimum weight, in kilograms, over the time interval of
the data point.
Because this is an aggregate data type, the start and end times should be set.
In the com.google.activity.sample
data type, each data point represents an
instantaneous sample of the current activity. The data point has two fields, the first one
representing the activity (as described in
FIELD_ACTIVITY
),
and the second representing the confidence in the sample, specified as a float between
0.0 and 100.0. If the confidence is unknown or not calculated, a negative value can be used.
Because the samples are instantaneous, start time has no meaning and should be left unset.
It's possible that more than one activity is detected at the same time with different confidence values. This can be represented as multiple data points with the same timestamp but different field values.
In the com.google.activity.segment
data type, each data point represents a continuous
time interval with a single activity value. Activity values are described in
FIELD_ACTIVITY
.
The start time of the data point must always be present as it represents the start of the activity, with the timestamp representing the activity's end time. Data point time intervals should be non-overlapping, although they do not need to be contiguous. In case when two activities happen at the same time, the most significant one should be used.
In the com.google.calories.bmr
data type, each data point represents the basal
metabolic rate of energy expenditure at rest of the user at the time of the reading, in kcal
per day.
Because the recorded BMR is instantaneous, the start time should not be set.
In the com.google.body.fat.percentage
data type, each data point represents a
measurement of the total fat mass in a person's body as a percentage of the total body mass.
Since this is an instantaneous measurement, start time should not be set.
In the com.google.calories.consumed
data type, each data point represents the number
of calories consumed, in kcal, over the time interval of the data point. The field value
is stored as a float.
Start and end times should be set to denote the duration over which the calories were consumed.
In the com.google.calories.expended
data type, each data point represents the number
of calories expended, in kcal, over the time interval of the data point. The field value
is stored as a float.
Start and end times should be set to denote the duration over which the calories were expended.
In the com.google.cycling,cadence
data type, each data point represents an
instantaneous measurement of the pedaling rate in crank revolutions per minute.
Start time should be left unset. Different data sources will need to monitor the rotations of the crank for different amounts of time before calculating the instantaneous RPM. This should be indicated as part of the data source and not the data point.
In the com.google.cycling.pedaling.cumulative
data type, each data point represents
the number of rotations taken from the start of the count. When using this
data type, each revolution can be reported multiple times, as the values of each data point
are monotonically increasing. To calculate the number of revolutions during an interval, the
value at the end of the interval should be subtracted from the value at the beginning.
Note that the count may reset to zero at different times depending on the data source. When available, the data source should indicate the beginning of the count by setting the start time of the data point to the time of the start of the count. Alternatively, a data point with a value of zero can be used to indicate the resetting of the count. If neither of these is available, the count resetting can be inferred in a best-effort basis by detecting decreases in the total value.
In the com.google.cycling.wheel_revolution.cumulative
data type, each data point
represents the number of revolutions taken from the start of the count.
When using this data type, each revolution can be reported multiple times, as the values of
each data point are monotonically increasing. To calculate the number of revolutions during
an interval, the value at the end of the interval should be subtracted from the value at the
beginning.
Note that the count may reset to zero at different times depending on the data source. When available, the data source should indicate the beginning of the count by setting the start time of the data point to the time of the start of the count. Alternatively, a data point with a value of zero can be used to indicate the resetting of the count. If neither of these is available, the count resetting can be inferred in a best-effort basis by detecting decreases in the total value.
In the com.google.cycling.wheel.revolutions
data type, each data point represents an
instantaneous measurement of the wheel in revolutions per minute.
Start time should be left unset. Different data sources will need to monitor the RPMs for different amounts of time before calculating the instantaneous RPM. This should be indicated as part of the data source and not the data point.
In the com.google.distance.delta
data type, each data point represents the distance
covered, in meters, since the last reading. The total distance over an
interval can be calculated by adding together all the values during the interval.
The start time of each data point should represent the start of the interval in which the distance was covered. The start time must be equal to or greater than the end time of the previous data point.
In the com.google.heart_rate.bpm
data type, each data point represents an
instantaneous measurement of the heart rate in beats per minute.
Start time should be left unset. Different data sources will need to monitor the heart's beat rate for different amounts of time before calculating the instantaneous heart rate. This should be indicated as part of the data source and not the data point.
In the com.google.height
data type, each data point represents the height of the
user at the time of the reading, in meters.
Because the recorded height is instantaneous, the start time should not be set.
In the com.google.location.sample
data type, each data point represents the user's
location at a given instant. The location data point has four fields:
getAccuracy()
for more details.
accuracy
). Most mobile devices produce measurements
that are up to 25 meters away from the correct altitude, so care must be taken to average
several results for increased accuracy or use another source for elevation information.
If altitude could not be determined for this location sample, this field is not set.
The com.google.location.track
data type represents a location point that is part of a
track and which may have inexact timestamps.
Its fields are the same as location.sample. The
difference between the two data types is that, while location.sample
data points
have an exact timestamp, location.track
data points have an inexact time interval.
The start time will represent the earliest time where the user may been at the
location, and the end time will represent the latest time. Start time should always be
set, even if it's the same as end time.
One use case of location.track
is capturing the path of a user during an activity
when the track for the path is known, but the exact time at each coordinate isn't.
In the com.google.power.sample
data type, each data point represents an
instantaneous measurement of power in watts. The field value
is stored as a float.
Because the recorded power is instantaneous, the start time should not be set.
In the com.google.speed
data type, each data point represents the instantaneous
speed over ground, in meters/second. The value represents the scalar magnitude of the speed,
so negative values should not occur.
Because the recorded speed is instantaneous, the start time should not be set.
In the com.google.step_count.cadence
data type, each data point represents an
instantaneous measurement of the cadence in steps per minute.
Both feet are used for calculating cadence, so if a sensor only measures one foot the value measurement is doubled.
Start time should be left unset. Different data sources will need to monitor the rotations of the crank for different amounts of time before calculating the instantaneous RPM. This should be indicated as part of the data source and not the data point.
In the com.google.step_count.delta
data type, each data point represents the number
of steps taken since the last reading. When using this data type, each
step is only ever reported once, in the reading immediately succeeding the step. By adding
all of the values together for a period of time, the total number of steps during that period
can be computed.
As an example, if a user walked a total of 5 steps, with 3 different readings, the values for each reading might be [1, 2, 2].
The start time of each data point should represent the start of the interval in which steps were taken. The start time must be equal to or greater than the end time of the previous data point.
In the com.google.weight
data type, each data point represents the weight of the
user at the time of the reading, in kilograms.
Because the recorded weight is instantaneous, the start time should not be set.
Returns a list of output aggregate data types for the specified inputDataType
.


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NSString(MBRegex) Category Reference
| Declared in | NSString+MBRegex.h |
Overview
An NSString
class extension that provides various methods for creating
and utilizing regular expressions.
To improve performance, these methods utilize the MBRegexCache
when
possible.
For additional information on the workings of regular expressions, see the
Apple documentation for NSRegularExpression
.
Tasks
Creating regular expressions
Escaping
Finding all pattern matches
-
– matchesWithRegex:
-
– matchesWithRegex:options:
-
– matchesWithRegex:options:range:
-
– matchesWithRegex:options:range:error:
Testing for pattern matches
-
– isMatchedByRegex:
-
– isMatchedByRegex:options:
-
– isMatchedByRegex:options:range:
-
– isMatchedByRegex:options:range:error:
Counting pattern matches
-
– numberOfRegexMatches:
-
– numberOfRegexMatches:options:
-
– numberOfRegexMatches:options:range:
-
– numberOfRegexMatches:options:range:error:
Finding the first pattern match
-
– firstRegexMatch:
-
– firstRegexMatch:options:
-
– firstRegexMatch:options:range:
-
– firstRegexMatch:options:range:error:
Getting the range of the first pattern match
-
– rangeOfFirstRegexMatch:
-
– rangeOfFirstRegexMatch:options:
-
– rangeOfFirstRegexMatch:options:range:
-
– rangeOfFirstRegexMatch:options:range:error:
Creating a new string by replacing pattern matches
Instance Methods
escapedRegexPattern
Creates a new regular expression pattern string by escaping metacharacters contained in the receiver.
- (NSString *)escapedRegexPattern
Return Value
The escaped pattern string.
Discussion
Affected characters are escaped by prefixing them with backslashes.
Declared In
NSString+MBRegex.h
escapedRegexTemplate
Creates a new regular expression template string by escaping metacharacters contained in the receiver.
- (NSString *)escapedRegexTemplate
Return Value
The escaped template string.
Discussion
Affected characters are escaped by prefixing them with backslashes.
Declared In
NSString+MBRegex.h
firstRegexMatch:
Returns the first occurrence of the specified regular expression pattern found within the receiver.
- (NSTextCheckingResult *)firstRegexMatch:(NSString *)pattern
Parameters
- pattern
The regular expression pattern to match.
Return Value
An NSTextCheckingResult
instance containing the results of the
match.
Declared In
NSString+MBRegex.h
firstRegexMatch:options:
Returns the first occurrence of the specified regular expression pattern found within the receiver.
- (NSTextCheckingResult *)firstRegexMatch:(NSString *)pattern options:(NSRegularExpressionOptions)options
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
Return Value
An NSTextCheckingResult
instance containing the results of the
match.
Declared In
NSString+MBRegex.h
firstRegexMatch:options:range:
Returns the first occurrence of the specified regular expression pattern found within the receiver.
- (NSTextCheckingResult *)firstRegexMatch:(NSString *)pattern options:(NSRegularExpressionOptions)options range:(NSRange)range
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
- range
The range of characters in the receiver within which matching will occur.
Return Value
An NSTextCheckingResult
instance containing the results of the
match.
Declared In
NSString+MBRegex.h
firstRegexMatch:options:range:error:
Returns the first occurrence of the specified regular expression pattern found within the receiver.
- (NSTextCheckingResult *)firstRegexMatch:(NSString *)pattern options:(NSRegularExpressionOptions)options range:(NSRange)range error:(NSError **)errPtr
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
- range
The range of characters in the receiver within which matching will occur.
- errPtr
An optional pointer to storage for an
NSError
instance. If this parameter is non-nil
and an error occurs, the memory location pointed to by this parameter will be modified to reference anNSError
instance describing the problem.
Return Value
An NSTextCheckingResult
instance containing the results of the
match.
Declared In
NSString+MBRegex.h
isMatchedByRegex:
Determines if the receiver contains at least one match of the given regular expression pattern.
- (BOOL)isMatchedByRegex:(NSString *)pattern
Parameters
- pattern
The regular expression pattern to match.
Return Value
YES
if the receiver contained at least one match of pattern
;
NO
if there were no matches.
Declared In
NSString+MBRegex.h
isMatchedByRegex:options:
Determines if the receiver contains at least one match of the given regular expression pattern.
- (BOOL)isMatchedByRegex:(NSString *)pattern options:(NSRegularExpressionOptions)options
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
Return Value
YES
if the receiver contained at least one match of pattern
;
NO
if there were no matches.
Declared In
NSString+MBRegex.h
isMatchedByRegex:options:range:
Determines if the receiver contains at least one match of the given regular expression pattern within the specified range.
- (BOOL)isMatchedByRegex:(NSString *)pattern options:(NSRegularExpressionOptions)options range:(NSRange)range
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
- range
The range of characters in the receiver within which matching will occur.
Return Value
YES
if the receiver contained at least one match of pattern
;
NO
if there were no matches.
Declared In
NSString+MBRegex.h
isMatchedByRegex:options:range:error:
Determines if the receiver contains at least one match of the given regular expression pattern within the specified range.
- (BOOL)isMatchedByRegex:(NSString *)pattern options:(NSRegularExpressionOptions)options range:(NSRange)range error:(NSError **)errPtr
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
- range
The range of characters in the receiver within which matching will occur.
- errPtr
An optional pointer to storage for an
NSError
instance. If this parameter is non-nil
and an error occurs, the memory location pointed to by this parameter will be modified to reference anNSError
instance describing the problem.
Return Value
YES
if the receiver contained at least one match of pattern
;
NO
if there were no matches.
Declared In
NSString+MBRegex.h
matchesWithRegex:
Matches the specified regular expression against the receiver.
- (NSArray *)matchesWithRegex:(NSString *)pattern
Parameters
- pattern
The regular expression pattern to match.
Return Value
An array of NSTextCheckingResult
objects representing the regular
expression pattern matches found within the receiver.
Declared In
NSString+MBRegex.h
matchesWithRegex:options:
Matches the specified regular expression against the receiver.
- (NSArray *)matchesWithRegex:(NSString *)pattern options:(NSRegularExpressionOptions)options
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
Return Value
An array of NSTextCheckingResult
objects representing the regular
expression pattern matches found within the receiver.
Declared In
NSString+MBRegex.h
matchesWithRegex:options:range:
Matches the specified regular expression against the receiver.
- (NSArray *)matchesWithRegex:(NSString *)pattern options:(NSRegularExpressionOptions)options range:(NSRange)range
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
- range
The range of characters in the receiver within which matching will occur.
Return Value
An array of NSTextCheckingResult
objects representing the regular
expression pattern matches found within the receiver.
Declared In
NSString+MBRegex.h
matchesWithRegex:options:range:error:
Matches the specified regular expression against the receiver.
- (NSArray *)matchesWithRegex:(NSString *)pattern options:(NSRegularExpressionOptions)options range:(NSRange)range error:(NSError **)errPtr
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
- range
The range of characters in the receiver within which matching will occur.
- errPtr
An optional pointer to storage for an
NSError
instance. If this parameter is non-nil
and an error occurs, the memory location pointed to by this parameter will be modified to reference anNSError
instance describing the problem.
Return Value
An array of NSTextCheckingResult
objects representing the regular
expression pattern matches found within the receiver.
Declared In
NSString+MBRegex.h
numberOfRegexMatches:
Returns the number of matches found in the receiver of the given regular expression pattern.
- (NSUInteger)numberOfRegexMatches:(NSString *)pattern
Parameters
- pattern
The regular expression pattern to match.
Return Value
The number of matches.
Declared In
NSString+MBRegex.h
numberOfRegexMatches:options:
Returns the number of matches found in the receiver of the given regular expression pattern.
- (NSUInteger)numberOfRegexMatches:(NSString *)pattern options:(NSRegularExpressionOptions)options
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
Return Value
The number of matches.
Declared In
NSString+MBRegex.h
numberOfRegexMatches:options:range:
Returns the number of matches found in the receiver of the given regular expression pattern.
- (NSUInteger)numberOfRegexMatches:(NSString *)pattern options:(NSRegularExpressionOptions)options range:(NSRange)range
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
- range
The range of characters in the receiver within which matching will occur.
Return Value
The number of matches.
Declared In
NSString+MBRegex.h
numberOfRegexMatches:options:range:error:
Returns the number of matches found in the receiver of the given regular expression pattern.
- (NSUInteger)numberOfRegexMatches:(NSString *)pattern options:(NSRegularExpressionOptions)options range:(NSRange)range error:(NSError **)errPtr
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
- range
The range of characters in the receiver within which matching will occur.
- errPtr
An optional pointer to storage for an
NSError
instance. If this parameter is non-nil
and an error occurs, the memory location pointed to by this parameter will be modified to reference anNSError
instance describing the problem.
Return Value
The number of matches.
Declared In
NSString+MBRegex.h
rangeOfFirstRegexMatch:
Determines the range of the first match of the given regular expression within the receiver.
- (NSRange)rangeOfFirstRegexMatch:(NSString *)pattern
Parameters
- pattern
The regular expression pattern to match.
Return Value
The range of the first match. Will be {NSNotFound
, 0
} if there
is no match.
Declared In
NSString+MBRegex.h
rangeOfFirstRegexMatch:options:
Determines the range of the first match of the given regular expression within the receiver.
- (NSRange)rangeOfFirstRegexMatch:(NSString *)pattern options:(NSRegularExpressionOptions)options
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
Return Value
The range of the first match. Will be {NSNotFound
, 0
} if there
is no match.
Declared In
NSString+MBRegex.h
rangeOfFirstRegexMatch:options:range:
Determines the range of the first match of the given regular expression within the receiver.
- (NSRange)rangeOfFirstRegexMatch:(NSString *)pattern options:(NSRegularExpressionOptions)options range:(NSRange)range
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
- range
The range of characters in the receiver within which matching will occur.
Return Value
The range of the first match. Will be {NSNotFound
, 0
} if there
is no match.
Declared In
NSString+MBRegex.h
rangeOfFirstRegexMatch:options:range:error:
Determines the range of the first match of the given regular expression within the receiver.
- (NSRange)rangeOfFirstRegexMatch:(NSString *)pattern options:(NSRegularExpressionOptions)options range:(NSRange)range error:(NSError **)errPtr
Parameters
- pattern
The regular expression pattern to match.
- options
The regular expression options that govern how matching will occur.
- range
The range of characters in the receiver within which matching will occur.
- errPtr
An optional pointer to storage for an
NSError
instance. If this parameter is non-nil
and an error occurs, the memory location pointed to by this parameter will be modified to reference anNSError
instance describing the problem.
Return Value
The range of the first match. Will be {NSNotFound
, 0
} if there
is no match.
Declared In
NSString+MBRegex.h
regularExpression
Returns an NSRegularExpression
instance by treating the receiver as a
regular expression pattern string.
- (NSRegularExpression *)regularExpression
Return Value
The regular expression, or nil
if the receiver could not be
interpreted as a valid regular expression.
Declared In
NSString+MBRegex.h
regularExpressionWithOptions:
Returns an NSRegularExpression
instance by treating the receiver as a
regular expression pattern string.
- (NSRegularExpression *)regularExpressionWithOptions:(NSRegularExpressionOptions)options
Parameters
- options
The options that govern the behavior of the returned regular expression.
Return Value
The regular expression, or nil
if the receiver could not be
interpreted as a valid regular expression.
Declared In
NSString+MBRegex.h
regularExpressionWithOptions:error:
Returns an NSRegularExpression
instance by treating the receiver as a
regular expression pattern string.
- (NSRegularExpression *)regularExpressionWithOptions:(NSRegularExpressionOptions)options error:(NSError **)errPtr
Parameters
- options
The options that govern the behavior of the returned regular expression.
- errPtr
An optional pointer to storage for an
NSError
instance. If this parameter is non-nil
and an error occurs, the memory location pointed to by this parameter will be modified to reference anNSError
instance describing the problem.
Return Value
The regular expression, or nil
if the receiver could not be
interpreted as a valid regular expression.
Declared In
NSString+MBRegex.h
stringByReplacingRegexMatches:withTemplate:
Returns a new string by replacing each match of the specified regular expression pattern with the replacement template provided.
- (NSString *)stringByReplacingRegexMatches:(NSString *)pattern withTemplate:(NSString *)templ
Parameters
- pattern
The regular expression pattern to match.
- templ
The template to use for replacing the regular expression matches.
Return Value
The resulting string.
Declared In
NSString+MBRegex.h
stringByReplacingRegexMatches:withTemplate:options:
Returns a new string by replacing each match of the specified regular expression pattern with the replacement template provided.
- (NSString *)stringByReplacingRegexMatches:(NSString *)pattern withTemplate:(NSString *)templ options:(NSRegularExpressionOptions)options
Parameters
- pattern
The regular expression pattern to match.
- templ
The template to use for replacing the regular expression matches.
- options
The regular expression options that govern how matching will occur.
Return Value
The resulting string.
Declared In
NSString+MBRegex.h
stringByReplacingRegexMatches:withTemplate:options:range:
Returns a new string by replacing each match of the specified regular expression pattern with the replacement template provided.
- (NSString *)stringByReplacingRegexMatches:(NSString *)pattern withTemplate:(NSString *)templ options:(NSRegularExpressionOptions)options range:(NSRange)range
Parameters
- pattern
The regular expression pattern to match.
- templ
The template to use for replacing the regular expression matches.
- options
The regular expression options that govern how matching will occur.
- range
The range of characters in the receiver within which matching will occur.
Return Value
The resulting string.
Discussion
Matching is constrained to the given range within the receiver.
Declared In
NSString+MBRegex.h
stringByReplacingRegexMatches:withTemplate:options:range:error:
Returns a new string by replacing each match of the specified regular expression pattern with the replacement template provided.
- (NSString *)stringByReplacingRegexMatches:(NSString *)pattern withTemplate:(NSString *)templ options:(NSRegularExpressionOptions)options range:(NSRange)range error:(NSError **)errPtr
Parameters
- pattern
The regular expression pattern to match.
- templ
The template to use for replacing the regular expression matches.
- options
The regular expression options that govern how matching will occur.
- range
The range of characters in the receiver within which matching will occur.
- errPtr
An optional pointer to storage for an
NSError
instance. If this parameter is non-nil
and an error occurs, the memory location pointed to by this parameter will be modified to reference anNSError
instance describing the problem.
Return Value
The resulting string.
Discussion
Matching is constrained to the given range within the receiver.
Declared In
NSString+MBRegex.h


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Function given(_:)
public func given<DeclarationType: Declaration, InvocationType, ReturnType>(
_ declarations: Mockable<DeclarationType, InvocationType, ReturnType>...
) -> StubbingManager<DeclarationType, InvocationType, ReturnType>
Stub one or more declarations to return a value or perform an operation.
Stubbing allows you to define custom behavior for mocks to perform.
given(bird.canChirp()).willReturn(true)
given(bird.canChirp()).willThrow(BirdError())
given(bird.canChirp(volume: any())).will { volume in
return volume < 42
}
This is equivalent to the shorthand syntax using the stubbing operator ~>
.
given(bird.canChirp()) ~> true
given(bird.canChirp()) ~> { throw BirdError() }
given(bird.canChirp(volume: any())) ~> { volume in
return volume < 42
}
Properties can be stubbed with their getter and setter methods.
given(bird.getName()).willReturn("Ryan")
given(bird.setName(any())).will { print($0) }
Parameters
| Name | Type | Description |
|---|---|---|
| declarations | Mockable<DeclarationType, InvocationType, ReturnType> |
One or more stubbable declarations. |


| HOME | DOWNLOAD | DOCUMENTATION | FAQ |
> Home > Documentation > Python
Gravity and Magnetics
|
Gravity routines |
|
| MakeGravGridDH | Create 2D cylindrical maps on a flattened and rotating ellipsoid of all three components of the gravity field, the gravity disturbance, and the gravitational potential. |
| MakeGravGradGridDH | Calculate the components of the gravity "gradient" tensor on a flattened ellipsoid. |
| MakeGeoidGridDH | Create a global map of the geoid. |
| CilmPlusDH | Calculate the gravitational potential exterior to relief along a spherical interface using the finite-amplitude algorithm of Wieczorek and Phillips (1998) on a Driscoll and Healy (1994) grid. |
| CilmMinusDH | Calculate the gravitational potential interior to relief along to a spherical interface using the finite-amplitude algorithm of Wieczorek and Phillips (1998) on a Driscoll and Healy (1994) grid. |
| CilmPlusRhoHDH | Calculate the gravitational potential exterior to relief along a spherical interface with laterally varying density using the finite amplitude algorithm of Wieczorek (2007) on a Driscoll and Healy (1994) grid. |
| CilmMinusRhoHDH | Calculate the gravitational potential interior to relief along a spherical interface with laterally varying density using the finite amplitude algorithm of Wieczorek (2007) on a Driscoll and Healy (1994) grid. |
| BAtoHilmDH | Calculate iteratively the relief along an interface with constant density contrast that corresponds to a given Bouguer anomaly using the algorithm of Wieczorek and Phillips (1998). |
| BAtoHilmRhoHDH | Iteratively calculate the relief along an interface with laterally varying density contrast that corresponds to a given Bouguer anomaly using the algorithm of Wieczorek and Phillips (1998). |
| DownContFilterMA | Compute the minimum-amplitude downward continuation filter of Wieczorek and Phillips (1998). |
| DownContFilterMC | Calculate a minimum-curvature downward continuation filter for a given spherical harmonic degree. |
| NormalGravity | Calculate the normal gravity on a flattened ellipsoid using the formula of Somigliana. |
|
Magnetics routines |
|
| MakeMagGridDH | Create 2D cylindrical maps on a flattened ellipsoid of all three vector components of the magnetic field, the magnitude of the magnetic field, and the magnetic potential. |
| SHMagPowerSpectrum | Compute the power spectrum of the magnetic field given the Schmidt seminormalized magnetic potential spherical harmonic coefficients. |
| SHMagPowerL | Compute the power of the magnetic field for a single degree L given the Schmidt seminormalized magnetic potential spherical harmonic coefficients. |
> Home > Documentation > Python
| Laboratoire Lagrange | Observatoire de la Côte d'Azur | © 2017 SHTOOLS |


| Home | Trees | Indices | Help |
|
|---|
|
|
A parallel flow provides the methods for parallel training / execution. Nodes in the flow which are not derived from ParallelNode are trained in the normal way. The training is also done normally if fork() raises a TrainingPhaseNotParallelException. This can be intentionally used by the node to request local training without forking. Parallel execution on the other hand should work for all nodes, since it only relies on the copy method of nodes. The stop_training method is always called locally, with no forking or copying involved. Both parallel training and execution can be done conveniently by providing a scheduler instance to the train or execute method. It is also possible to manage the tasks manually. This is done via the methods setup_parallel_training (or execution), get_task and use_results. The code of the train / execute method can serve as an example how to use these methods and process the tasks by a scheduler.
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is_parallel_executing Return True if parallel execution is underway. |
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is_parallel_training Return True if parallel training is underway. |
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task_available Return True if tasks are available, otherwise False. |
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Inherited from |
|
Initialize the internal variables. Note that the crash_recovery flag is is not supported, so it is disabled.
|
Create and return a single execution task. Returns None if data iterator end is reached. |
Create and return a single training task without callable. Returns None if data iterator end is reached. |
Perform a single training phase locally. The internal _train_callable_class is used for the training. |
Find the next phase or node for parallel training. When it is found the corresponding internal variables are set. Nodes which are not derived from ParallelNode are trained locally. If a fork() fails due to a TrainingPhaseNotParallelException in a certain train phase, then the training is done locally as well (but fork() is tested again for the next phase). |
Hook method that is called after stop_training is called. |
Train all trainable nodes in the flow. If a scheduler is provided the execution will be done in parallel on the scheduler. iterable -- An iterable or iterator that returns data arrays that are used as input to the flow. Alternatively, one can specify one data array as input. If a custom execute_callable_class is used to preprocess the data then other data types can be used as well. nodenr -- Same as in normal flow, the flow is only executed up to the nodenr. scheduler -- Value can be either None for normal execution (default value) or a Scheduler instance for parallel execution with the scheduler. execute_callable_class -- Class used to create execution callables for the scheduler. By specifying your own class you can implement data transformations before the data is actually fed into the flow (e.g. from 8 bit image to 64 bit double precision). Note that the execute_callable_class is only used if a scheduler was provided. If a scheduler is provided the default class used is NodeResultContainer. overwrite_result_container -- If set to True (default value) then the result container in the scheduler will be overwritten with an instance of OrderedResultContainer (unless it is already an instance of OrderedResultContainer). Otherwise the results might have a different order than the data chunks, which could mess up any subsequent analysis.
|
Return a task either for either training or execution. A a one task buffer is used to make task_available work. tasks are available as long as need_result returns False or all the training / execution is done. If no tasks are available a NoTaskException is raised. |
Prepare the flow for handing out tasks to do the execution. After calling setup_parallel_execution one has to pick up the tasks with get_task, run them and finally return the results via use_results. use_results will then return the result as if the flow was executed in the normal way. iterable -- An iterable or iterator that returns data arrays that are used as input to the flow. Alternatively, one can specify one data array as input. If a custom execute_callable_class is used to preprocess the data then other data types can be used as well. nodenr -- Same as in normal flow, the flow is only executed up to the nodenr. execute_callable_class -- Class used to create execution callables for the scheduler. By specifying your own class you can implement data transformations before the data is actually fed into the flow (e.g. from 8 bit image to 64 bit double precision). |
Prepare the flow for handing out tasks to do the training. After calling setup_parallel_training one has to pick up the tasks with get_task, run them and finally return the results via use_results. tasks are available as long as task_available returns True. Training may require multiple phases, which are each closed by calling use_results. data_iterables -- A list of iterables, one for each node in the flow. The iterators returned by the iterables must return data arrays that are then used for the node training. See Flow.train for more details. If a custom train_callable_class is used to preprocess the data then other data types can be used as well. train_callable_class -- Class used to create training callables for the scheduler. By specifying your own class you can implement data transformations before the data is actually fed into the flow (e.g. from 8 bit image to 64 bit double precision). |
Train all trainable nodes in the flow. If a scheduler is provided the training will be done in parallel on the scheduler. data_iterables -- A list of iterables, one for each node in the flow. The iterators returned by the iterables must return data arrays that are then used for the node training. See Flow.train for more details. If a custom train_callable_class is used to preprocess the data then other data types can be used as well. scheduler -- Value can be either None for normal training (default value) or a Scheduler instance for parallel training with the scheduler. If the scheduler value is an iterable or iterator then it is assumed that it contains a scheduler for each training phase. After a node has been trained the scheduler is shutdown. Note that you can e.g. use a generator to create the schedulers just in time. For nodes which are not trained the scheduler can be None. train_callable_class -- Class used to create training callables for the scheduler. By specifying your own class you can implement data transformations before the data is actually fed into the flow (e.g. from 8 bit image to 64 bit double precision). Note that the train_callable_class is only used if a scheduler was provided. By default NodeResultContainer is used. overwrite_result_container -- If set to True (default value) then the result container in the scheduler will be overwritten with an instance of NodeResultContainer (unless it is already an instance of NodeResultContainer). This improves the memory efficiency.
|
Use the result from the scheduler. During parallel training this will start the next training phase. For parallel execution this will return the result, like a normal execute would. results -- Iterable containing the results, normally the return value of scheduler.ResultContainer.get_results(). The individual results can be the return values of the tasks. |
|
is_parallel_executingReturn True if parallel execution is underway.
|
is_parallel_trainingReturn True if parallel training is underway.
|
task_availableReturn True if tasks are available, otherwise False. If False is returned this can indicate that results are needed to continue training.
|
| Home | Trees | Indices | Help |
|
|---|
| Generated by Epydoc 3.0.1-MDP on Mon Apr 27 21:56:24 2020 | http://epydoc.sourceforge.net |


This page shows automated results of the kappa-Cygnids 2012, based on visual observations reported by citizen scientists through the report form of the International Meteor Organization (IMO). The information on this page is generated automatically; for scientific use please refer to manual analyses published in scientific journals (such as WGN). Send your feedback regarding this page to Geert Barentsen.
Page contents:
Note that the data will finally go into the Visual Meteor Database (VMDB) with manual inspection and rectifications. We are curretly completing the files of 2008-2011. The VMDB is an enormous project - any help will be greatly appreciated.
Page generated: 2015 November 4 at 12:35 UTC.
The graph below shows the ZHR (Zenithal Hourly Rate), which is the number of meteors an observer would see under a very dark sky with the radiant of the shower in zenith.
ZHRmax = 2.8 based on 666 kappa-Cygnids reported in 1661 intervals, assuming population index r = 2.5
| Time (UTC) | Solarlon | nINT | nKCG | ZHR | Particle density | |
|---|---|---|---|---|---|---|
| 2012-08-12 07:33 | 139.821 | 345 | 100 | 1.9 | ±0.2 | 11 / 109·km3 |
| 2012-08-12 22:30 | 140.419 | 523 | 156 | 1.5 | ±0.1 | 8 / 109·km3 |
| 2012-08-13 10:11 | 140.887 | 309 | 83 | 1.3 | ±0.1 | 7 / 109·km3 |
| 2012-08-14 17:27 | 142.138 | 166 | 87 | 2.2 | ±0.2 | 12 / 109·km3 |
| 2012-08-15 10:18 | 142.813 | 77 | 35 | 1.7 | ±0.3 | 9 / 109·km3 |
| 2012-08-16 12:23 | 143.858 | 47 | 34 | 2.0 | ±0.3 | 11 / 109·km3 |
| 2012-08-17 20:45 | 145.155 | 90 | 78 | 2.0 | ±0.2 | 11 / 109·km3 |
| 2012-08-18 18:36 | 146.031 | 59 | 45 | 1.6 | ±0.2 | 9 / 109·km3 |
| 2012-08-19 11:21 | 146.703 | 32 | 35 | 2.8 | ±0.5 | 16 / 109·km3 |
| 2012-08-20 19:51 | 148.007 | 13 | 13 | 2.6 | ±0.7 | 15 / 109·km3 |
The reported intervals are automatically added together into the bins shown above, based on the number of meteors and the distribution of the intervals. For each bin, the following parameters are computed:
Data has been received from 121 observers in 25 countries. Thank you for your efforts!
Note: click on the map for an interactive version.
| Observer | Country | Teff | nKCG |
|---|---|---|---|
| Tomasz Adam | Poland | 2.75h | 2 |
| Mina Alizadeh | Iran | 0.40h | 0 |
| Rainer Arlt | Germany | 1.58h | 2 |
| Pierre Bader | Germany | 13.63h | 15 |
| Janos Bakos | Hungary | 2.30h | 5 |
| Orlando Benítez Sánchez | Spain | 1.98h | 2 |
| Jean-marie Biets | Belgium | 1.67h | 0 |
| Martina Bírosíková | Slovakia | 0.50h | 0 |
| Milesa Blagojevic | Serbia | 5.64h | 9 |
| Maksimilijan Boskovic | Serbia | 11.25h | 5 |
| Andreas Buchmann | Switzerland | 1.25h | 1 |
| Igor Bukva | Serbia | 15.42h | 10 |
| Simiao Cheng | China | 3.42h | 4 |
| Nicolae Adrian Corlaci | Romania | 3.08h | 3 |
| Daniel Cosovanu | Romania | 2.05h | 8 |
| Ilie Cosovanu | Romania | 2.76h | 7 |
| Lucian Cosovanu | Romania | 0.72h | 0 |
| Tibor Csörgei | Slovakia | 2.49h | 3 |
| Goedele Deconinck | Belgium | 2.22h | 2 |
| Vladimir Dosovic | Serbia | 7.58h | 7 |
| Vladimir Dososvic | Serbia | 2.00h | 2 |
| Audrius Dubietis | Lithuania | 0.83h | 1 |
| Jaros?aw Dygos | Poland | 11.26h | 16 |
| Motahareh Ebrahimi | Iran | 2.65h | 2 |
| Frank Enzlein | Germany | 2.16h | 2 |
| Taravat Ershadi | Iran | 1.50h | 1 |
| Reyhaneh Fallah | Iran | 1.35h | 3 |
| Stefan Fuks | Serbia | 12.05h | 4 |
| Ivanka Getsova | Bulgaria | 10.38h | 0 |
| William Godley | United States | 4.58h | 7 |
| Stevan Golubovic | Serbia | 4.16h | 3 |
| Jose Gomez Castano | Spain | 1.00h | 2 |
| Mitja Govedi? | Slovenia | 2.84h | 2 |
| Ljubica Grasic | Serbia | 14.06h | 29 |
| Joost Hartman | Netherlands | 1.49h | 1 |
| Amir Hasanzadeh | Iran | 2.37h | 1 |
| Kamil Hornoch | Czech Republic | 13.64h | 10 |
| Dilyan Hristov | Bulgaria | 2.34h | 6 |
| Dilyan Hristov | Bulgaria | 1.50h | 3 |
| Milos Igrutinovic | Serbia | 2.11h | 1 |
| Stanislav Simkovic | Slovakia | 1.50h | 4 |
| Lars Jacobs | Belgium | 0.96h | 1 |
| Carl Johannink | Germany | 6.3h | 2 |
| Karoly Jonas | Hungary | 7.89h | 10 |
| Javor Kac | Slovenia | 34.8h | 35 |
| Mario Kadl?ík | Germany | 3.50h | 1 |
| Csilla Kalup | Hungary | 5.05h | 12 |
| Desislava Kalaidjieva | Bulgaria | 4h | 1 |
| Masoume Kazemi | Iran | 2.63h | 5 |
| Roy Keeris | Netherlands | 1.26h | 1 |
| Andrija Kostic | Serbia | 10.84h | 10 |
| Ralf Koschack | Germany | 4.53h | 11 |
| Jozef Kovac | Slovakia | 9.82h | 10 |
| Martin Labudík | Slovakia | 1.50h | 6 |
| Martin Labudik | Slovakia | 1.75h | 2 |
| Greet Lembregts | Belgium | 2.51h | 2 |
| Jan Lembregts | Belgium | 2.37h | 0 |
| [-tomasz Lenart | Poland | 1.00h | 1 |
| Tomasz Lenart | Poland | 3.54h | 3 |
| Anna Levin | Israel | 1.77h | 0 |
| Sizhuang Liu | China | 2.13h | 1 |
| Robert Lunsford | United States | 3.50h | 2 |
| Boris Majic | Serbia | 3.40h | 1 |
| Pierre Martin | Canada | 4.76h | 4 |
| Alastair Mcbeath | United Kingdom | 3.00h | 4 |
| Bruce Mccurdy | Canada | 6h | 6 |
| Artem Mirgorod | Ukraine | 1.00h | 0 |
| Porya Momen | Iran | 2.40h | 3 |
| Konstantin Morozov | Belarus | 5.75h | 8 |
| Maciek Myszkiewicz | Poland | 20.09h | 18 |
| Adrienn Nagy | Hungary | 3.6h | 6 |
| Dimitrie Olenici | Romania | 0.95h | 1 |
| Jan Otrekal | Slovakia | 5.32h | 1 |
| Jaroslav Pastorek | Slovakia | 3.25h | 10 |
| Pavol Pastor | Slovakia | 9.79h | 14 |
| Elizabet Petkova | Bulgaria | 5.20h | 0 |
| Krzysztof Pieszczoch | Poland | 11.39h | 7 |
| Krzysztof Pieszczoch | Poland | 5.26h | 3 |
| Krzysztof Polakowski | Poland | 3.26h | 0 |
| Sasha Prokofyev | Russia | 1.48h | 4 |
| Constantin Psenitchi | Romania | 0.91h | 3 |
| Milo? Radulovi? | Serbia | 6.34h | 8 |
| Kitti Sazbó | Hungary | 2.19h | 4 |
| Alex Scholten | Netherlands | 1.85h | 1 |
| Kai Schultze | Germany | 1.65h | 1 |
| Marcin Skalski | Poland | 11.95h | 3 |
| Andrzej Skoczewski | Poland | 9.67h | 9 |
| Vesna Slavkovi? | Serbia | 10.59h | 13 |
| Ulrich Sperberg | Germany | 7.75h | 5 |
| Predrag Stamenkovic | Serbia | 5.83h | 9 |
| Anton Stipec | Croatia | 3.26h | 4 |
| Nikola Stojanovic | Serbia | 11.74h | 5 |
| Wesley Stone | United States | 3.32h | 3 |
| Matej Sustr | Slovakia | 1.50h | 7 |
| Pavel Svozil | Czech Republic | 1.41h | 2 |
| Adam Szabo | Hungary | 1.34h | 2 |
| Richard Taibi | United States | 2.98h | 1 |
| Hanjie Tan | China | 1.6h | 2 |
| Csilla Tepliczky | Hungary | 7.37h | 4 |
| Christoph Gerber | Germany | 11.81h | 4 |
| Branislav Savic | Serbia | 18.33h | 28 |
| Terrence Ross | United States | 17.06h | 11 |
| Jurgen Rendtel | Germany | 18.03h | 28 |
| Michel Vandeputte | Belgium | 21.27h | 18 |
| Vilem Heblik | Czech Republic | 14.05h | 13 |
| Salvador Aguirre | Mexico | 3.80h | 2 |
| Koen Miskotte | Netherlands | 8.35h | 12 |
| Jakub Koukal | Czech Republic | 5.00h | 7 |
| Nela Todorovic | Serbia | 3.83h | 3 |
| Raul Truta | Romania | 2.92h | 1 |
| Sperberg Ulrich | Germany | 2.05h | 4 |
| Alexandra Vancea | Romania | 2.09h | 5 |
| Erwin Van Ballegoij | Netherlands | 1.27h | 0 |
| Peter Van Leuteren | Netherlands | 8.18h | 6 |
| Betina Vasileva | Bulgaria | 4.00h | 2 |
| Valentin Velkov | Bulgaria | 4.42h | 8 |
| Jan Verbert | Belgium | 2.22h | 3 |
| Benjámin Vigh | Hungary | 1.92h | 2 |
| Myriam Vingerhoets | Belgium | 3.13h | 2 |
| Sabine Waechter | Germany | 1.23h | 2 |
| Ewa Wala | Poland | 5.68h | 5 |
| William Watson | United States | 16.58h | 10 |
| Oliver Wusk | Germany | 3.62h | 1 |
| Yulia Yancheva | Bulgaria | 2.77h | 1 |
| Raziyeh Zahedi | Iran | 1.50h | 0 |
| Przemyslaw Zoladek | Poland | 10.6h | 13 |
Create your own analysis. The files below can be opened using Excel:
kcg2012_rate.csv (number of meteors per interval per observer)
kcg2012_magn.csv (number of meteors per magnitude bin per observer)
The information on this page may be distributed freely provided credit is given to the International Meteor Organization (IMO) and, when possible, to the individual observers. The computer facilities to generate this page are provided by ESA/RSSD and Armagh Observatory.
References:


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§3076. Financial institution; compliance
A financial institution that is subject to and in compliance with the Federal Interagency Guidance on Response Programs for Unauthorized Access to Customer Information and Customer Notice, issued on March 7, 2005, by the Board of Governors of the Federal Reserve System, the Federal Deposit Insurance Corporation, the office of the comptroller of the currency and the office of thrift supervision, and any revisions, additions, or substitutions relating to said interagency guidance, shall be deemed to be in compliance with this Chapter.
Acts 2005, No. 499, §1, eff. Jan. 1, 2006.


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a
Experimental frequencies refer to the spectra displayed in Figure 3 b. The TSL period in both theory and experiment is 9 nm. The scattering configuration used both for experiments and calculations is the x̅( yy) x. The error on the experimental values is ±1.5 cm –1.


| Network Working Group | J. Doe |
| Request for Comments: 5299 | August 2008 |
| Category: Informational |
Default RFC IPR as of August 2008
This memo provides information for the Internet community. It does not specify an Internet standard of any kind. Distribution of this memo is unlimited.
This is a test case document, it is not RFC 5299 (which was never issued by the RFC-Editor).
Dummy Section.
Copyright © The IETF Trust (2008).
This document is subject to the rights, licenses and restrictions contained in BCP 78, and except as set forth therein, the authors retain all their rights.

The IETF takes no position regarding the validity or scope of any Intellectual Property Rights or other rights that might be claimed to pertain to the implementation or use of the technology described in this document or the extent to which any license under such rights might or might not be available; nor does it represent that it has made any independent effort to identify any such rights. Information on the procedures with respect to rights in RFC documents can be found in BCP 78 and BCP 79.
Copies of IPR disclosures made to the IETF Secretariat and any assurances of licenses to be made available, or the result of an attempt made to obtain a general license or permission for the use of such proprietary rights by implementers or users of this specification can be obtained from the IETF on-line IPR repository at <http://www.ietf.org/ipr>.
The IETF invites any interested party to bring to its attention any copyrights, patents or patent applications, or other proprietary rights that may cover technology that may be required to implement this standard. Please address the information to the IETF at ietf-ipr@ietf.org.


Streaming to a Theater Near You
Expanding the on-demand business model
January 31, 2016
I recently read Fortune’s “How to Make a Profit in the New Hollywood,” which interestingly explored several trends in the movie industry, including the entrance of streaming services such as Netflix and Amazon into the world of original feature film content.
Netflix and Amazon are no strangers to original content. Their ballooning subscriber numbers and collective Emmy and Golden Globe nomination tallies over the last several years can attest to that fact. But up to this point, their expertise has been in the realm of television — an industry structured vastly different from that of feature films, especially in terms of distribution.
Keeping this in mind, one statement in the Fortune article really stuck out to me. In the closing paragraph of the piece, Fortune mentions that “simultaneous theater and home release has long been a no-no in Hollywood, with theater chains denouncing it and studios fearing it will cannibalize revenue,” adding that, “neither Netflix nor Amazon has figured out how to make the new economics work.”
To put this in perspective, Netflix’s first attempt to crack the feature film distribution model was to simultaneously release its first film, Beasts of No Nation, both online and in theaters. Ultimately, the film showed in 31 theaters and brought in less $91,000 in ticket sales — enough to make it eligible for Oscar nominations (though it didn’t get any) but not enough to make it a very compelling business model moving forward.
I’m not saying that I know all of Netflix’s motivations behind employing this strategy, but I believe that there is a better way to structure a theater distribution model for streaming services moving forward. One that could benefit both the streaming services (through exposure to new subscribers and awards) and the theaters (through less burdened revenue generation).
The solution: give theaters the content for free.
This is a radically different approach from the way movies are currently distributed. In the traditional studio distribution model, studios work with distributors to lease their movies to theaters in order to recoup the cost of the film’s production. But streaming services don’t have to follow this model because they cover production costs through subscription fees — freeing them up to pursue a new approach.
Ticket sales would then take place one of two ways:
- Current streaming subscribers could claim free tickets to see the film in theaters — the only limit to the number of tickets the subscriber could claim would be the number of screens his or her subscription allows.
- Non-subscribers as well as anyone else could purchase tickets in the traditional sense — that ticket revenue would be split at a pre-negotiated rate between the streaming service and the theater. It’s worth noting that tickets for these films could have the potential to be sold for less than the average ticket price of studio movies, since the money would not have to cover any production costs and would automatically be profit for the streaming services.
It’s not just the mechanics of the model that work, but it also acts as a value add for both parties:
- Theaters will still be able to benefit from the one thing that has kept movie theaters in business throughout years of declining ticket sales — concessions. In the traditional studio model where the distributor leases the film to the theater, tickets are often sold at a loss in order to get people in the door so that theaters can convert that traffic into profit through high margin concession sales. In the proposed model, a free movie or reduced ticket price would get more people in the door and allow the theaters to convert on concession sales without having to take the customary losses on ticket sales (and even giving them a cut of the revenue for non-subscriber ticket sales).
- On the streaming service side, theaters would be more likely to show the film (since the content would be a free way to get people in the door and ticket sales to non-subscribers would generate revenue not previously seen in the studio model) giving both the film and the streaming service’s ability to create original content more exposure to a wider audience. Looking past the additional revenue from non-subscriber ticket sales, the exposure could lead to more full-time subscribers or even that elusive Academy Award.
I’ll admit, there are several core assumptions to this model that, if proven false, cause the entire model to collapse on itself. The biggest assumption of all: people love going to the movies. I’m writing this from my perspective and I personally love the experience of going to a theater. But unlike the people who are keeping theaters in business by buying a $10 bag of popcorn once they’ve already bought their ticket, I have a hard time shelling out money for concessions when I just paid $13-$18 just to get myself in the door. Change that equation around to where I am getting in the door for free, and that $13-$18 that I just saved might not stay in my pocket for long.
Additionally, it would strike a nice balance between dropping $30+ on a movie night out and doing a yet another movie night in. Who knows, maybe I could finally spring for those sour patch kids that I always see her eyeing.
Disclaimer: I have simplified several areas of the film distribution model for illustrative purposes. Each lease agreement between the theater and the distributor is unique and is likely to have different terms that have varying effect on the financial impact in each unique situation.


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Use the following code to create a basic inputEx MultiSelectField. The first value of "options" is used as the invite text to select an option.
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Ithad
Help Me Pick New Logo Through 3 April 2016!
I am in the process of running a logo design contest on 99designs and have created a poll with 6 of the best logo designs I've received. I would love for you to vote on the logo design. It only takes a minute.
Like Sci-Fi? Read My New Online Fiction Series.
Do you like Sci-Fi? While I finish up my next novel, I have started an online fiction series called Forbearance. Picking up from the canteen scene in Bellicose, we meet Keius Minjen, a postal marine, as he tries to survive the battle planet Guna to exact revenge and one day liberate his homeland.
Sign-up if you want me to send you news about upcoming installments of Forbearance or my other writings.
Overview
Ithad orbits Ono-ithad, a white dwarf (F class star). Ono-ithad is the only star in the system.
Stellar Data
Ono-ithad is a white dwarf (F-VI) star. It is somewhat unusual in that its solar output is approximately 25%25 lower than other F class stars of its age and size.
Planets
Kodur
- Gravity%25dlstar%25
- Poor
- Habitat
- Terrible
- Colony
- Terrible
- Resources
- Fair
A Mars-sized world with a thick, corrosive atmosphere that traps enough solar energy to make it classified as a hot house planet (a planet with a runaway greenhouse effect). There have been no recorded manned landings, but there are a number of automated research stations scattered on its surface.
Ithad
- Gravity%25dlstar%25
- Fair
- Habitat
- Fair
- Colony
- Good
- Resources
- Fair
Ithad is the only habitable world in the system. It has no moons.
Shatnain
- Gravity%25dlstar%25
- Superb
- Habitat
- Terrible
- Colony
- Terrible
- Resources
- Terrible
A gas giant about 1.5 Jupiter masses. It has a large number of satellites, two of which (Ekretar and Tawmerik) are nearly Ithad’s size. Due to the distance from the primary, none of these moons is habitable, although Ekretar, due to a large number of metal deposits, was even during the Emergence Era the object of full-scale mining, and still is to this day.
Rogat
- Gravity%25dlstar%25
- Mediocre
- Habitat
- Terrible
- Colony
- Terrible
- Resources
- Poor
A distant, icy world about half Ithad’s size. It is currently uninhabited, but during the Tawmerik dynasty was used as a naval base. The naval base was abandoned, and it was long ago stripped by scavengers, leaving only the shells of old buildings.
Description
Ithad is an Earth-like world, slightly smaller and with a lower density, leading to a lower surface gravity (approximately .85g). While it’s low density would indicate it is poor in heavier elements, there are significant iron, gold and nickel deposits, largely the product of a period early in the planet’s history of heavy meteor bombardments.
It’s ice caps dominate its surface, and paleoclimatological research indicates that it has been in the throes of an ice age for nearly 250 million years, likely due to the decreased solar output of its primary. Still, it has several sizable bodies of water, the largest, the Sea of Kos, about half the size of the Indian Ocean. All of the bodies of water lay in a wide band around the equator, with the northernmost and southernmost seas being directly fed by the huge ice sheets.
The climate of Ithad is quite varied, from the frigid wastes in the north and south, through the deserts that dominate the land not covered in ice. The equatorial regions have a few large arboreal forests, and in the Tiasing Valley is the sole descendant of ancient rainforests. There are also areas of vast plains of grass, which can best be classified as temperate savannahs.
Despite the cold climate, Ithad sports some large fauna; including the Miaset (an elephant-sized pack herbivore that resembles a cow with rabbit’s ears), the Kuomo (a feline-like predator the size of a cow) and the Selet (which resembles in size and habit a crocodilian, save for a thick pelt of hair). Several animals of Terran origin, including cattle, sheep and dogs, can be found. There are no native avian species (save for a number of flying arthropods), but aquatic life is rich, though there are no aquatic animals larger than the Zasuma (an aquatic reptile about the size of an otter).
All life on Ithad uses the same amino acids as Terrestial life does, and though there are some minor incompatibilities, life of Terrestial descent can survive. The few nutrients lacking are made up for by Terrestial animals imported during the Emergence Era.


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(a) XRD patterns of freshly made and aged pristine perovskit ... |
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Proposed mechanism for additive-assisted film formation. Dec ... |
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(a) XRD patterns of freshly made and aged perovskite contain ... |
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(a) XRD pattern magnification for the (100) and (200) of the ... |
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March 2023 Hacker News Hiring Trends
The Software Developer job industry is facing many changing dynamics, and the data from the "Ask HN: Who is hiring?" thread on Hacker News is a great way to track the changes. From the overall drop in job postings, the return of work to the office, to the rise in AI technogies poised to cause disruption to the way we work.
First, there is the total number of job postings, at the lowest levels in years. For March, there are 440 (as of this writing) top level comments on the thread, which represent individual job postings. This is up a bit from last month's count of 394, but prior to Feburary, there wasn't a month with less than 480 postings since December, 2015. This analysis was also confirmed/cited earlier this week over at The Pragmatic Engineer.
For March, total postings are down 49% year-over-year from March 2022. This trend has been going on for a few months now with consistent big YOY drops. The last time a month's postings approached their previous year's was in May, 2022.
Now, in Spring of 2023, not only is the total software developer job market down, but remote job postings are also down to the lowest level seend since COVID-19 sent so many developers home 3 years ago. There was a peak of 76% of postings, now down to 64%. Fully Onsite jobs aren't quite back to pre-covid levels, which shows that many compaonies are trying out hybrid approaches.
Along with the number of jobs and where those jobs are performed, the technologies we see and use everyday are experiencing big waves. In 2021, we couldn't escape Web3 hype. Now, AI and ChatGPT have taken over our feeds. But, job data doesn't necessarily always reflect the hype.
Here it begins, the first month of really focusing on where AI is in the job market. In March, Machine Learning is over 13% of postings and AI is mentioned in over 10%. Neither surpass their recent record highs, but this will be a trend to watch in the coming months.
Compare Machine Learning, AI, ChatGPT, and GPT-3
Web3, Blockchain, Bitcoin, and Ethereum are all still mentioned, but well off their highest levels.
Compare Web3, Blockchain, Bitcoin and Ethereum
Django and Rails are neck-and-neck in the number of job postings! Though Node.js is still the most popular server-side framework.
Compare node.js, Rails, PHP and Django
Compare React, Angular, Vue, and Ember
Compare Postgresql, MySQL and SQL Server
Compare Mongodb, Elasticsearch, Cassandra and DynamoDB
Compare API, REST, GraphQL, and gRPC
Specialization trends are still steady.
Compare Full Stack, Frontend, and Backend
Engineering levels are pretty stable, with Senior being the most common, by far.
Compare Principal, Staff, Senior, and, Junior
Finally, some stability! Programming language rankings are more stable than much of the rest of the industry.
Compare Top 10 Programming Languages
| Tech | Rank | Last Month | Change | Last Year | Change |
|---|---|---|---|---|---|
| Remote | 1 | 1 | 0 | 1 | 0 |
| Senior | 2 | 2 | 0 | 2 | 0 |
| Full Stack | 3 | 3 | 0 | 4 | +1 |
| Back End | 4 | 5 | +1 | 5 | +1 |
| React | 5 | 4 | -1 | 3 | -2 |
| Python | 6 | 6 | 0 | 7 | +1 |
| Front End | 7 | 10 | +3 | 6 | -1 |
| Onsite | 8 | 7 | -1 | 10 | +2 |
| TypeScript | 9 | 8 | -1 | 8 | -1 |
| Machine Learning | 10 | 9 | -1 | 14 | +4 |
| AWS | 11 | 12 | +1 | 9 | -2 |
| Next.js | 12 | 17 | +5 | 18 | +6 |
| Cloud | 13 | 11 | -2 | 12 | -1 |
| AI | 14 | 14 | 0 | 24 | +10 |
| Hybrid | 15 | 15 | 0 | 28 | +13 |
| Open Source | 16 | 16 | 0 | 20 | +4 |
| Postgresql | 17 | 13 | -4 | 11 | -6 |
| golang | 18 | 19 | +1 | 13 | -5 |
| DevOps | 19 | 20 | +1 | 17 | -2 |
| Security | 20 | 18 | -2 | 15 | -5 |
| Tech | Mentions | Rank | Last Year Mentions | Last Year Rank | Change |
|---|---|---|---|---|---|
| AR | 6 | 69 | 3 | 149 | +80 |
| Prometheus | 6 | 67 | 6 | 106 | +39 |
| Git | 10 | 47 | 8 | 86 | +39 |
| Snowflake | 7 | 61 | 6 | 99 | +38 |
| gRPC | 6 | 65 | 6 | 103 | +38 |
| Grafana | 5 | 72 | 6 | 102 | +30 |
| Redux | 10 | 46 | 14 | 69 | +23 |
| Distributed Systems | 11 | 44 | 15 | 67 | +23 |
| Computer Vision | 7 | 58 | 10 | 76 | +18 |
| Tailwind | 7 | 62 | 10 | 78 | +16 |


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Klassy Cafe is one of the best restaurant HTML templates with Bootstrap v4.5.2 CSS framework. You can download and feel free to use this website template layout for your restaurant business. You are allowed to use this template for commercial purposes.
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WHITE MAN'S BURDEN A film review by Ben Hoffman Copyright 1995 Ben Hoffman
About twenty minutes into the movie it became clear what point writer/director Desmond Nakano wished to make: What if black people changed places with white?  What if all the indignities blacks frequently suffer at the hands of many whites were reversed?
Once having gotten that understanding and, because I have always been a fighter for racial and religious equality, I did not need a movie to bring it into focus for me.  I'm inclined to think that would be the case ... which is a pity.
Director Nakano says that if "white Man's Burden" can jar viewers out of their usual polarized complacency and provoke genuine dialogue on race, then it will have succeeded in its intent. This film is very unlikely to accomplish that, however honorable and worthy its intentions.
Louis (John Travolta) works in a factory where all the employees are white, the one exception being the executive who runs the place. Louis is a hard worker; he does more than is expected. When a package has to be delivered to the factory's owner, Thaddeus Thomas (Harry Belafonte), he volunteers to do it. Arriving at the gated entrance to the estate, the maid, via phone, tells him to bring the package around to the side of the house.
Inside the house, the family and friends, all elegantly attired, and served by a white maid, are departing after dinner. This is one very rich, high society family. As Louis is standing, package in hand, waiting for someone to come and accept it, Thomas' wife has just finished with her shower and is taking off her towel while standing at an open window, at which point Thomas sees Louis and assumes he is a Peeping Tom. When the maid had told Louis to go to the side of the house, she meant the other side.
The package is accepted by the maid. Louis, next day, approaches his black manager and asks if he could become a foreman as the current foreman is leaving, and "as you know, I have been a hard worker for nine years here." Instead, he is fired. The explanation which Louis ekes out is that the boss does not want Peeping Toms employed at his plant.
Louis is desperate. He has not ever earned enough to support his wife and two children and now he is being canned. In the evening, in despair, he goes for a walk. He sits at the curb.   (A robbery had recently occurred and the description of the robber fit Louis.) [All whites look alike?] When the police discover he is not the robber, they say "Sorry about that" and take off in their patrol car.
Attempts by Louis to meet with Mr. Thomas and explain meets with rejection. Mr. Thomas does not want to talk with him. At this point, the desperate Louis points a gun at Mr. Thomas in order to force him to listen and get his job back. What follows is a kidnapping.
It is quite obvious that the movie has a real, and important story to tell but I do not think this film is the one to do it.
Tom Bower plays Louis' homeless friend who does not want to get involved with the kidnaping. Kelly Lynch has the role of Louis' wife trying to make ends meet.
2.5 Bytes 4 Bytes = Superb 3 Bytes = Too good to be missed. 2 Bytes = So so. 1 Byte = Save your money.
-- Ben Hoffman
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